Please note: this is a Policy Brief by Anukriti Upadhyay, former Research Intern at the Indian Society of Artificial Intelligence and Law. In a 3-page letter to Satya Nadella, Twitter's company, X Corp. had stated that Microsoft had violated an agreement over its data and had declined to pay for that usage. And in some cases, Microsoft had used more Twitter data than it was supposed to. Microsoft also shared the Twitter data with government agencies without permission, the letter said. To sum up, Twitter is trying to charge Microsoft for its data which has earned huge amount of profit to Microsoft. Mr. Musk, who bought Twitter last year for $44 billion, has said that it is urgent for the company to make money and that it is near bankruptcy. Twitter has since then introduced new subscription products and made other moves to gain more revenue. Also, in March, the company had stated it would charge more for developers to gain access to its stream of tweets. Elon Musk and Microsoft have had a bumpy relationship recently. Among other things, Mr. Musk has concerns with Microsoft over OpenAI. Musk, who helped found OpenAI in 2015, has said Microsoft, which has invested $13 billion in OpenAI, controls the start-up’s business decisions. Of course, Microsoft has disputed that characterisation. Microsoft’s Bing chatbot and OpenAI’s ChatGPT are built from what are called large languages models, or LLMs, which build their skills by analysing vast amounts of data culled from across the internet. The letter to Satya Nadella does not specify if Twitter will take legal action against Microsoft or ask for financial compensation. It demands that Microsoft abide by Twitter’s developer agreement and examine the data use of eight of its apps. Twitter has hired legal services which seeks report by June on how much Twitter data the company possesses, how that data was stored and used, and when government-related organizations gained access to that data. Twitter’s rules prohibit the use of its data by government agencies, unless the company is informed about it first. The letter adds that Twitter’s data was used in Xbox, Microsoft’s gaming system; Bing, its search engine; and several other tools for advertising and cloud computing. “the tech giant should conduct an audit to assess its use of Twitter's content.” Twitter claimed that the contract between the two parties allowed only restricted access to the twitter data but Microsoft has breached this condition and has generated abnormal profits because of using Twitter’s API. Currently, there are many tools available (from Microsoft, Google, etc.) to check the performance of AI systems, but there is no regulatory oversight. And that is why, experts believe that companies, new and old, need to put more thought into self-regulation. This dispute has highlighted the need to keep a check on the utilization of data by companies to develop their AI models and regulate them. Data Law and Oversight Concerns In this game of tech giants to win the race of AI development, the biggest impact is always bestowed upon the society. Any new development is prone to attract illegal activities that can have a drastic effect on the society. Even though the Personal Data Protection Bill is yet to become law, big tech firms like Google, Meta, Amazon and various e-commerce platforms are liable to be penalised for sharing users’ data with each other if consumers flag such instances. Currently in India, under the Consumer Protection Act, 2019, the department can take action and issue directions to such firms. Since the data belongs to a consumer, if the consumer feels that their data is being shared amongst firms without their express consent, they are free to approach us under the Consumer Protection Act. If we look at the kind of data which is shared between firms, any search on Google by a person leads to the same feeds being shown on Facebook. This means that user data is being shared by big tech firms. In case the data is not shared with the express consent of users concerned, they can approach the Consumer Protection Forums. The same is relevant to the Twitter-Microsoft dispute, wherein the data used by the latter was put up by the Twitter users on their twitter account and the same was getting used by Microsoft without the user’s consent. If we analyse WhatsApp's data sharing policies for example, Meta has stated that it can share business data with Facebook. But at the same time, the Competition Commission of India has objected to this as a monopolistic practice and the matter is in court. Consumers have the right to seek redressal against unfair / restrictive trade practices or unscrupulous exploitation of consumers. Protecting personal data should be an essential imperative of any democratic republic. Once it becomes law, citizens can intimate all digital platforms they deal with to delete their past data. The firms concerned will then need to collect data afresh from users’ and clearly spell out the purpose and usage. They will be booked for data breach if they depart from the purpose for which it was collected. Data minimisation, purpose limitation and storage limitation are the hallmarks which cannot be compromised with. Data minimisation means firms can only collect the absolute minimum required data. Purpose limitation will allow them to use data only for the purpose for which it has been acquired. With storage limitation, once the service is delivered, firms will need to delete the data. With the rapid development of AI, a number of ethical issues have cropped up. These include: the potential of automation technology to give rise to job losses the need to redeploy or retrain employees to keep them in jobs the effect of machine interaction on human behaviour and attention the need to address algorithmic bias originating from human bias in the data the security of AI systems (e.g., autonomous weapons) that can potentially cause damage While one cannot ignore these risks, it is worth keeping in mind that advances in AI can - for the most part - create better business and better lives for everyone. If implemented responsibly, artificial intelligence has immense and beneficial potential. Investment and Commercial Licensing AI has been called the electricity of the 21st century. While the uses and benefits of AI are exponentially increasing, there are challenges for businesses looking to harness this new technological advancement. Chief among the challenges are: The ethical use of AI, Legal compliance regarding AI and the data that fuels AI, Protection of IP rights and the appropriate allocation of ownership and use rights in the components of AI. Businesses also need to determine whether to build AI themselves or license it from others. Several unique issues impact AI license agreements. In particular, it is important to address the following key issues: “IP ownership and use rights, IP infringement, Warranties, specifically performance promises and Legal compliance.” Interestingly, IP treaties simply have not caught up to AI yet. While aspects of AI components may be protectable under patents, copyrights, and trade secrets, IP laws primarily protect human creativity. Because of the focus on human creation, issues may arise under IP laws if the AI output is created by the AI solution instead of a human creator. Since the IP laws do not squarely cover AI, as between an AI provider and user, contractual terms are the best way to attempt to gain the benefits of IP protections in AI license agreements. How Does it Affect the Twitter-Microsoft Relationship Considering this issue, the parties could designate certain AI components as trade secrets. Protect AI components by: limiting use rights; designating AI components as confidential information in the terms and conditions; and restricting use of confidential information. Include assignment rights in AI evolutions from one party or the other. Determine the license and use rights the parties want to establish between the provider and the user for each AI component. Clearly articulate the rights in the terms and conditions. The data sharing agreement must cover which party will provide and own the training data, prepare and own the training instructions, conduct the training, and revise the algorithms during the training process and own the resulting AI evolutions. As for data ownership, the parties should identify the source of the data and ensure that data use complies with applicable laws and any third-party data provider requirements. Ownership and use of production data for developing AI models must be set out in the form of terms and conditions which party provides and which party owns the production data that will be used. If the AI solution is licensed to the user on-premises (the user is running the AI solution in the user’s systems and environment), it is likely that the user will supply and own the production data. However, if the AI solution is cloud-based, the production data may include the data of other users. In a cloud situation, the user should specify whether the provider may use the user’s data for the benefit of the entire AI user group or solely for the user’s particular purposes. It is important to note that limiting the use of production data to one user with an AI solution may have unintended results. In some AI applications, the use of a broader set of data from multiple users may increase the AI solution’s accuracy and proficiency. However, counsel must weigh the benefits of permitting a broader use of data against the legal, compliance, and business considerations a user may have for limiting use of its production data. When two or more parties are each contributing to the AI evolutions, the license agreement should appoint a contractual owner. The parties must then determine who will own AI evolutions or whether AI evolutions will be jointly owned, which presents additional practical challenges. The use of AI presents ethical issues and the organizations must consider how they will use AI and define principles and implement policies regarding the ethical use of AI. One portion of the AI ethical use consideration is legal compliance, which is another issue that is more challenging for AI than for traditional software or technology licensing. AI-based decisions must satisfy the same laws and regulations that apply to human decisions. AI is different from many other technologies because AI can produce legal harms against people and some of that legal harm might not only violate ethical norms, but may also be actionable under law. It is important to address legal compliance concerns with the provider before entering into an AI license agreement to determine which party is responsible for compliance. Some best practices that could be adopted, are proposed as follows: To deal with legal compliance issues in investment and licensing, companies can conduct diligence on data sharing to determine if there are any legal or regulatory risk areas that merit further inquiry. Develop policies around data sharing and involve the various stakeholders in the policy-making process to ensure that thoughtful consideration is given about when it is appropriate to use the data and in what contexts. Implement a risk management framework that includes a system of ongoing monitoring and controls around the use of AI. Consider which party should obtain third-party consents for data use due to potential privacy and data security issues. AI is transforming our world rapidly and without much oversight. Developers are free to innovate, as well as to create tremendous risk. Very soon leading nations will need to establish treaties and global standards around the use of AI, not unlike current discussions about climate change. Governments will need to both: Establish laws and regulations that protect ethical and productive uses of AI. Prohibit unethical, immoral, harmful, and unacceptable uses. These laws and regulations will need to address some of the IP ownership, use rights, and protection issues discussed in this article. However, these commercial considerations are secondary to the overarching issues concerning the ethical and moral use of AI. In line with the increased attention on corporate responsibility and issues like diversity, sustainability, and responsibility to more than just investors, businesses that develop and use AI will need policies and guidance against which the use of AI should be assessed and utilised. These policies and guidance are worthy of board-level attention. Technology lawyers who in these early days assist clients with AI issues must monitor developments in these areas and, wherever possible, act as facilitators and leaders of thoughtful discussions regarding AI. Also, adapting the precautionary measures will save a lot of legal cost for the companies and will ensure that the data is not misused or oversued.

Artificial intelligence is booming the industry, but the question remains about the regulation as this is only a precaution that can put constraints on innovation. For example, a government report in Singapore highlighted the risks posed by AI but concluded that ‘it is telling that no country has introduced specific rules on criminal liability for artificial intelligence systems. Being the global first-mover on such rules may impair Singapore’s ability to attract top industry players in the field of AI[1].’ These concerns are well-founded. As in other areas of research, overly restrictive laws can stifle innovation or drive it elsewhere. Yet the failure to develop appropriate legal tools risks allowing profit-motivated actors to shape large sections of the economy around their interests to the point that regulators will struggle to catch up. This has been particularly true in the field of information technology. For example, social media giants like Facebook monetized users’ personal data while data protection laws were still in their infancy[2]. Similarly, Uber and other first-movers in what is now termed the sharing or ‘gig’ economy exploited platform technology before rules were in place to protect workers or maintain standards. As Pedro Domingo once observed, people worry that computers will get too smart and take over the world; the real problem is that computers are too stupid and have already taken over[3]. Much of the literature on AI and the law focuses on a horizon that is either so distant that it blurs the line with science fiction or so near that it plays catch-up with the technologies of today. That tension between presentism and hyperbole is reflected in the history of AI itself, with the term ‘AI winter[4]’ coined to describe the mismatch between the promise of AI and its reality. Indeed, it was evident back in 1956 at Dartmouth when the discipline was born. To fund the workshop, John McCarthy and three colleagues wrote to the Rockefeller Foundation with the following modest proposal: [W]e propose for 2 months and 10 men needed for the study of artificial intelligence will be carried out in the summer of 1956 ……… The study was on the conjecture nature of learning where the machines should be made intelligent to stimulate it. In this study, an attempt will be made to find out how machines use language for the concept to solve problems, reserved for humans. We think that significant advancement can be made and only a selected group of people will work on the summer project.” The innovation in the field of AI was started a long time ago but there were no precautions and regulations to put the use of AI in control. Every entity on the planet Earth can agree to the term that AI can be more fearful than one’s thought. Just as the statement by the AI robot Sofia “she plans to take over the human being and their existence. Moreover, the website run by AI shows the last picture of humans as very degraded beings. As said in the statement by Pablo Picasso[5] “the new mechanical brains are useless, they only provide an answer that was taught to them” As countries around the world struggle to capitalize on the economic potential of AI while minimizing avoidable harm, a paper like this cannot hope to be the last word on the topic of regulation. But by examining the nature of the challenges, the limitations of existing tools, and some possible solutions, it hopes to ensure that we are at least asking the right questions. As it is said every space in nature and physics needs to be fulfilled otherwise it would create a hole -a black hole. The paper "Neurons Spike Back: A Generative Communication Channel for Backpropagation" presents a new approach to training artificial neural networks that is based on an alternative communication channel for backpropagation. Backpropagation is the most widely used method for training neural networks, and it involves the use of gradients to adjust the weights of the network. The authors propose a novel approach that uses spikes as a communication channel to carry these gradients. The paper begins by introducing the concept of spiking neural networks (SNNs) and how they differ from traditional neural networks. SNNs are modelled after the way that biological neurons communicate with each other through spikes or action potentials. The authors propose using this communication mechanism to transmit the gradients during backpropagation. But before that we need to understand what is deep learning and the neural networks and deep neural networks. Inductive & Deductive Machines in Neural Spiking Inductive machines are also known as unsupervised learning machines. They are used to identify patterns in data without prior knowledge of the output. Inductive machines make use of a clustering algorithm to group similar data together. An example of an inductive machine is the self-organizing map (SOM). SOMs are used to create a two-dimensional representation of high-dimensional data. For example, if you have a dataset consisting of several features such as age, gender, income, and occupation, an SOM can be used to create a map of this data where similar individuals are placed close together. On the other hand, deductive machines are also known as supervised learning machines. They are used to learn from labeled data and can be used to make predictions on new data. An example of a deductive machine is the multi-layer perceptron (MLP). MLPs consist of multiple layers of interconnected nodes that are used to classify data. For example, if you have a dataset consisting of images of cats and dogs, an MLP can be trained on this data to classify new images as either a cat or a dog. Neural spiking is the process of representing information using patterns of electrical activity in the neurons of the brain. Inductive and deductive machines can both be used to model neural spiking, but they differ in their approach. Inductive machines can be used to identify patterns in the spiking activity of neurons without prior knowledge of the output. Deductive machines, on the other hand, can be used to predict the spiking activity of neurons based on labeled data. How Deep Learning + Neural Networks Work Deep learning is a subset of machine learning that utilizes artificial neural networks to learn from large amounts of data. Neural networks, in turn, are models that are inspired by the structure and function of the human brain. They are capable of learning and recognizing patterns in data, and can be trained to perform a wide range of tasks, from image recognition to natural language processing. At the heart of a neural network are nodes, also known as neurons, which are connected by edges or links. Each node receives input from other nodes and computes a weighted sum of those inputs, which is then passed through an activation function to produce an output. The weights of the edges between nodes are adjusted during training to optimize the performance of the network.[6] In a deep neural network, there are typically many layers of nodes, allowing the network to learn increasingly complex representations of the data. This depth is what sets deep learning apart from traditional machine learning approaches, which typically rely on shallow networks with only one or two layers. Deep learning has been applied successfully to a wide range of tasks, including computer vision, natural language processing, and speech recognition. One of the most well-known applications of deep learning is image recognition, where deep neural networks have achieved state-of-the-art performance on benchmark datasets such as ImageNet. However, deep learning also has some limitations. One of the main challenges is the need for large amounts of labeled data to train the networks effectively. This can be a significant barrier in areas where data is scarce or difficult to label, such as medical imaging or scientific research. Another limitation of deep learning is its tendency to be overfitted to the training data. This means that the network can become too specialized to the specific dataset it was trained on and may not generalize well to new data. To address this, techniques such as regularization and dropout have been developed to help prevent overfitting. Despite these limitations, deep learning has had a significant impact on many areas of research and industry. In addition to its successes in computer vision and natural language processing, deep learning has also been used to make advances in drug discovery, financial forecasting, and autonomous vehicles, to name a few examples. One of the reasons for the success of deep learning is the availability of powerful hardware, such as GPUs, that can accelerate the training of neural networks. This has allowed researchers and engineers to train larger and more complex networks than ever before, and to explore new applications of deep learning. Another important factor in the success of deep learning is the availability of open-source software frameworks such as TensorFlow and PyTorch. These frameworks provide a high-level interface for building and training neural networks and have made it much easier for researchers and engineers to experiment with deep learning. Spiking Neural Networks A spiking neural network (SNN) is a type of computer program that tries to work like the human brain. The human brain uses tiny electrical signals called "spikes" to send information between different parts of the brain. SNNs try to do the same thing by using these spikes to send information between different parts of the network. SNNs work by having lots of small "neurons" that are connected together. These neurons can receive input from other neurons, and they send out spikes when they receive enough input. The spikes are then sent to other neurons, which can cause them to send out their own spikes. SNNs can be used to do things like recognize images, control robots, and even help people control computers with their thoughts. They can also be used to study how the brain works and to build computers that work more like the brain[7]. The basic structure of an SNN consists of a set of nodes, or neurons, that are interconnected by synapses. When a neuron receives input from other neurons, it integrates that input over time and produces a spike when its activation potential reaches a certain threshold. This spike is then transmitted to other neurons in the network via the synapses. There are several ways to implement SNNs in practice. One common approach is to use rate-based encoding, where information is represented by the firing rate of a neuron over a certain time period. In this approach, the input to the network is first converted into a series of spikes, which are then transmitted through the network and processed by the neurons.[8] One example of an application of SNNs is in image recognition. In a traditional neural network, an image is typically represented as a set of pixel values that are fed into the network as input. In an SNN, however, the image can be represented as a series of spikes that are transmitted through the network. This can make the network more efficient and reduce the amount of data that needs to be processed. Another example of an application of SNNs is in robotics. SNNs can be used to control the movement of robots, allowing them to navigate complex environments and perform tasks such as object recognition and manipulation. By using SNNs, robots can operate more efficiently and with greater accuracy than traditional control systems. SNNs are also being explored for their potential use in brain-computer interfaces (BCIs). BCIs allow individuals to control computers or other devices using their brain signals, and SNNs could help improve the accuracy and speed of these systems. One challenge in implementing SNNs is the need for specialized hardware that can efficiently process and transmit spikes. This has led to the development of neuromorphic hardware, which is designed to mimic the structure and function of the brain more closely than traditional digital computers. Despite these challenges, SNNs are a promising area of research that has the potential to improve the efficiency and accuracy of a wide range of applications, from image recognition to robotics to brain-computer interfaces. As researchers continue to explore the capabilities of SNNs, we can expect to see new and innovative applications of this technology emerge in the years to come. The authors then present the results of experiments that compare their approach to traditional backpropagation methods. They demonstrate that their method achieves comparable results in terms of accuracy but with significantly lower computational cost. They also show that their method is robust to noise and can work effectively with different types of neural networks. Overall, the paper presents a compelling argument for the use of spiking neural networks as a communication channel for backpropagation. The proposed method offers potential advantages in terms of computational efficiency and noise robustness. The experiments provide evidence that the approach can be successfully applied to a range of neural network architectures. References [1] Penal Code Review Committee (Ministry of Home Affairs and Ministry of Law, August 2018) 29. China, for its part, included in the State Council’s AI development [2] Shoshana Zuboff, The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power [3] Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World [4] AI is whatever hasn’t been done yet.’ See Douglas R Hofstadter, Gödel, Escher, Bach: An Eternal Golden Braid (Basic Books 1979) 601. [5] William Fifield, ‘Pablo Picasso: A CompInterviewrview’ (1964) [6]NeuronsSpikeBack.pdf (mazieres.gitlab.io) [7] https://analyticsindiamag.com/a-tutorial-on-spiking-neural-networks-for-beginners/ [8] https://cnvrg.io/spiking-neural-networks/

Generative AI has become an industry topic of utmost vogue, that perhaps we see a period of intellectual trespassing on this piece of technology. There is nothing surprising about it, since the technology itself has huge computational capabilities and represents a new form of technology portability, in the age of artificial intelligence. While some investors and start-up entrepreneurs may claim the rise of generative AI as a measure to develop early-stage AGI (artificial general intelligence), we believe the real picture is too complex to be side-lined or presumed. In this report, all of the authors have provided a wider picture of the generative AI landscape in the context of the global economy. We have adopted a classification-based approach, where we have sorted out some of the most mainstream use cases of generative AI tools, and provided ontological categories to such applications. Yashudev Bansal, Research Intern, Indian Society of Artificial Intelligence and Law, has contributed to the overview of the generative AI landscape and offered amazing insights on the use cases of large language models for use cases such as legal management and drafting. Kapil Naresh, Founder, Juriaide, has offered profound insights and a proper dissection of various legal issues related to (1) Proprietary Issues related to Intellectual Property Law, (2) Data Quality, Privacy & Content Issues, (3) Pseudonymous Disruption and (4) Digital Public Infrastructure. It has been an honour to provide insights and exploration of legal issues such as (1) Artificial Intelligence Hype, (2) Product-Service Classifications, (3) Unclear Derivatives & Derivatives of Derivatives, (4) Proprietary Issues related to Intellectual Property Law and (5) Digital Public Infrastructure. To conclude, it has been my pleasure to develop this report after weeks of deliberation among the authors of this report, and my VLiGTA Research Team. I express my special regards to Sanad Arora, Junior Research Associate at VLiGTA and Vagish Yadav, Advocate, the High Court of Allahabad, for their moral support. You can read an overview of the report here. We are grateful to Rodney D Ryder, Founding Partner, Scriboard for authoring a Foreword to this technical report. Anyone who is interested to discuss about the nuances of the report, can contact us at vligta@indicpacific.com. The report is now available on the VLiGTA.App: https://vligta.app/product/deciphering-regulative-methods-for-generative-ai-vligta-tr-002/

Lawyering is not limited to litigation. The diversity of professional opportunities for legal professionals exist in various forms and it will only increase in the information age. Now, in this article, let us understand the concept of a multi-polar world order (in International Relations (IR)), and what implications does a multipolar world, have on the legal profession as well as the field of law. We are already seeing some trends in the modern world, which will be discussed in this article. What is a Multi-polar World Order? In international relations, scholars consider a multi-polar world as the most raw and exhaustive form of the realpolitik as we know. In international politics, a realpolitik refers to the political realities which shape existing domestic, intergovernmental and global institutions, be it state actors or non-state actors. Decades ago, we could not anticipate that several actors involved in money laundering can use cryptocurrencies to further their hawala transactions. If it were not for the COVID pandemic, the world could not have sought the purpose of a digital cyberspace and the necessity of force majeure clauses in contracts. As the world is still healing from the after-effects of the pandemic, the trade impact of the US-China trade war in 2018, followed by this pandemic and the Ukraine-Russia conflict in Eastern Europe has been scathing, without any doubt. Does it affect the way legal professions work? Indeed it does. However, it is necessary to have a deeper enquiry on how the multi-polar world affects the legal field. As we understand the theories of power and influence, we must have heard terms like - a unipolar world, a bi-polar world and so on. Well, a multipolar world is quite interesting, because many notions of international relations, especially those dominated by the scholars of US Foreign Policy have been challenged by the emergence of this concept. As per the diagram above, in the information age, we see the following trends clearly showing the emergence of a multipolar world: Legal systems across the world adapt with the disruption of different industry sectors and their all-time impact on human lives, at both domestic and transnational levels. The concept of alliances and ententes does not materialise in a proper fashion because the power dynamics of a multipolar world empowers the smaller allies of a larger power to take distinctive (if not hostile) paths of economic, political and diplomatic engagement. This leads countries to form their own sovereign decisions and concerns, based on their own understanding and acceptance of legal systems and principles; Many settled questions of law in various legal systems are subject to cleavage because of the case-by-case, industry-by-industry impact of digital technologies (especially Web2 technologies). In the Global South countries, however, where many legal questions are not properly settled, newer questions of law emerge which further complicate or integrate the situation (depends on how the regulators, judges and legislators address the problem); Countries either align with some major powers (for example the US or China), become non-aligned or become multi-aligned. Two key phenomenon come into being - justifying strategic autonomy and interplaying strategic hedging. The categorisation is furthered as follows: If they have been aligned and stay aligned - the legal systems already influenced by the major geopolitical players in that alliance are in vogue with the major powers’ legal systems, norms and principles. Even in contentious areas such as commerce and trade (for example), some parity can be observed. If they have been aligned and have a distinctive approach - their legal systems start becoming compatible to those of the major powers’ legal systems. If they have been non-aligned - their legal systems stay largely neutral and unchanged by the emerging legal norms and methods across the globe (which is a rather unrealistic or unsustainable situation). If they have become multi-aligned - their legal systems optimise the risks attached to the sovereign decisions and approaches they agree with. In the language of international law, their state practices do not bear a hostile character, yet hedge the risks associated with the distinctive legal and policy positions they strive to take. The question of bearing hostility and abruptness on legal and public policy points of view for governments, is hard to address, despite the fact that most of such questions can be addressed within the language of international law. Yet, political power guides the realpolitik, especially how sovereignty is defined, which is why it could become a political question as to how legal systems conflicting with one another resolve the situation. Multilateral institutions are subject to question and review, where the following trends are visible: They adapt with time and bear institutional cum policy transformation; or They do not adapt and render their components and subsidiaries toothless without any potential or scope of action; or They are used by countries in groups to negotiate and establish backdoor negotiations to make incremental use of the existent systems by making small changes to (if not restore but) maintain the political purpose of the institution. Since many (if not most) legal systems are subject to policy disruption, leading to a rise in grey areas of legal importance, hard laws and their notion in jurisprudence remains incomplete due to their being inflexible. The role of Soft Law becomes important as legal and policy prescriptions provided through help out and encourage legal innovation. Now, in the next section, it is discussed how lawyering and legal practice has shaped itself in the wake of the multi-polar nature of the realpolitik, strictly, in the legal profession. Unsettled Notions, Emerging Lawyers For sure, when pandemics or any natural disaster come, it is presumed that huge disruptions happen. However, the change must stick with time and ensure its own worth. In the legal profession, the multi-polar nature of the realpolitik had already become mainstream since 2008. However, the significant changes in this realm takes years to settle. One of the biggest achievement of the multi-polar world, which is still US-dominated, has been the emergence of new legal opportunities. The transformation of technology law as a field for example, furthered into creating a set of requirements in the legal domain, especially in the developed countries. In India, however, the change has not been quite rapid at a macro level, except maybe in the Tier-1 cities to a limited extent. Another trend which has become quite apparent is the role of information economy. Due to the disruptions brought by the pandemic, many law professionals who were accustomed with the “traditional” forms of work, are now harnessing the potential of the digital world. Content creation may be considered an obvious answer to this point, but it does not end there. In-house legal work, knowledge management, product development (especially through agile management, for e.g., scrum master) and others. Due to the increasing and quite newfound importance of soft law, i.e., self-regulatory initiatives that a company undergoes, it is apparent that in certain ways, the notion that law is top-down has been affably challenged. The new set of legal opportunities have a consultative and exhorting characteristic, which may saturate the importance of courts and tribunals. It does not however mean that every form of alternative dispute resolution gains maximal importance. Every tool of ADR has its own sector-specific, stakeholder-specific importance, which if utilised at best, would help governments and other stakeholders across the world to bear the tremors that the multi-polar world order bring upon municipal legal systems, across the world. In short, there is no doubt that legal systems across the world are trying to adapt with the geopolitical conditions which shape the socio-economic, logistic and even administrative factors that affect polities globally. However, there is a limit to adapt with the systems, and without understanding how international relations in conceptual aspect has transformed so much, the adaptation of the surroundings would render the systems and legal instruments weak and dysfunctional, in many ways and cases. In the next section, this problem is discussed. The IR Perspective on Legal Systems: Limits of Adaptation Legal systems represent the actuality of political thinking germinated in proper legal concepts and principles agreed upon in countries across the world, democratic or not. Now, from a scholarly perspective, the multi-polar world order as it exists also represents the state of the “modern world” as we know. This world order resembles the world like a pandora box, which means that uncertainties rise with time. For example, a flawed assumption which many people have about the turbulent times in Europe due to the ongoing Ukraine-Russia conflict is that the modern world, which created norms, institutions and principled regulation (at least on paper) is subject to some irreparable damage. They however forget to realise that Europe’s history repeats in many ways, every century. The way the European Union (not continental Europe) has handled the situation in Eastern Europe has been emblematic of how political leaders in Europe make decisions. For example, it could be a moral argument that a set of countries can be anyhow ejected out of SWIFT to isolate them from the “global” financial system. However, countries in Asia, Latin America and Africa would not find this approach comfortable. Nevertheless, political visions generally have to be constructive and self-explanatory. They shape legal decisions. However, inconsistency in bearing consequences does affect the constructed “rules-based” international order, within the multi-polar world, which should ask questions whether countries are interested in preserving the current world order or not. From a legal angle, a breakdown of trust and norms is inevitable in many domains. A simple example is the Paris Accords of 2015. In line with the 2015 Accords, only India abided by the GHG emission limits so far, so well as a party to the Accords. Yet, the principle of common but differentiated responsibility has been left astray in practice by countries in the Global North. The fragility of the rules-based international order, despite bearing a first-principles approach towards shaping international legal thinking is shaped by asking whether consequences are foreseeable. Laws work when power is distributed and imbibed within them so that they become kinetic. Geography however becomes the playing field, which is where jurisdictions come in. Maybe legal systems across the world should become anti-fragile, where they solidify their policy object and become stable to govern. At a macro level, these subtleties generally do not seem much visible because any change driven by legal systems either can be incremental due to the exigencies or could be too swift. The practical meaning of trust in a legal process, as well as the principles has also changed due to the multipolar order. Yes, the stable way in which trust was easy to transact in legal systems has been affected, and maybe it could not return the old way it used to be. However, the importance of finding multiple legal pathways has for sure increased the chances of addressing peculiar and hard legal disputes (maybe not in every sector/domain of law, but at least in some of the crucial ones) in the most suitable way. Mapping the Possibilities of Legal Innovation Interestingly, there are immense possibilities of legal innovation, which could happen due to the nature of the multi-polar world order. As discussed in the first section of the article, countries adapt with systems in their own suitable ways. This diagram above explains some common and uncommon indicators that may show signs of legal innovation. For example, the conceptual understanding of a legal dispute does not necessarily change. However, in the most unusual ways, sometimes, legal disputes or problems transform the operability of legal tools and instruments. Another example could be where governments do not necessarily preclude the stakeholders from becoming a part of the process but facilitate only those stakeholders, who have some purposive value. India is an impressive example where SEBI has recently joined the account aggregator framework. To conclude, it can be stated that this multipolar world order in the 21st century, unlike other times, is more evolved and despite uncertainties - understandable. The world has become mature and interconnectedness has made engaging with the realpolitik more subtle, secure and sensible.

This article is co-authored by Tara Ollapally, CAMP Arbitration & Mediation Practice. Introduction: Tend and Befriend Responses to Conflict Conflicts are ubiquitous, unavoidable, and almost always uncomfortable. An inevitable consequence of human interaction, conflict, if managed well can be a source of innovation, creativity, growth and meaningful relationships. Any conflict originates from differences. Differences in ideas, values, or perceptions of facts. These differences if not handled well will lead to disagreements, and disagreements if not respectfully managed will lead to disputes which eventually could lead to all-out conflict. If it is escalation of the differences that causes conflicts, it is also inversely true that to resolve conflicts we must de-escalate the situation to resolve them more efficiently. The importance of handling a conflict at the earliest stems from the intrinsic link between cause and consequence.[1] The primary reason for conflicts is the urge to protect something or someone deeply attached to the conflicting parties.[2] Christopher Moore gives a particularly easy understanding of different types of conflicts, since resolving the different types of conflict will require different approaches. He calls it the ‘Circle of Conflict’[3]. As per Moore, conflicts are divided into 5 types, Value Conflicts, Relationship Conflicts, Structural Conflicts, Interest Conflicts, and Data Conflicts. Responses to Conflict Neurobiology research, first understood and described by Walter Cannon in 1932 has understood the human stress response to most commonly be Fight, Flight, Freeze[4] - to get aggressive and fight, to run away from the conflict or to freeze and not take any action hoping for the situation to pass.[5] Recent research from UCLA has shed light on another common response to stress – Tend and Befriend[6]- to build a connection between the conflicting parties, allowing for vulnerability and understanding.[7] This research shows that humans have used social relationship not only as a basic accommodation to the exigencies of life, but also as a primary resource for dealing with stressful circumstances.[8] In this article we share that Mediation as a dispute resolution process promotes the Tend and Befriend response. To holistically address disputes, systems must be designed to evoke this natural human response. A mature legal system that acknowledges building bridges and fostering relationships as a way our species responds to conflict will make mediation a recognised process in its dispute resolution system. Mediation as a way to enhance the Tend and Befriend response Formal legal systems are traditionally an adversarial process wherein conflicting parties are set up as adversaries and a determination of right/ wrong is made by a neutral third person. This process triggers the fight response in conflict. Mediation, as a dispute resolution process, is designed around enhancing collaboration and brings two conflicting parties together to understand, dialogue and reach an amicable solution. It creates a conducive environment whereby the parties are able to form a connection and build on it. It triggers the response under stress to affiliate and connect.[9] The ‘tend and be-friend’ approach is built on this response, where human beings come together to protect themselves. Mediation provides instrumental social support that involves providing tangible assistance as part of a social network of mutual assistance and obligations[10]. Although collaborative processes were ingrained in our traditional social system, 300 years of the formal court system has greatly impacted the collaborative response in conflict. The wise old person in the village who the community turned to and evoked the “tend and befriend’ response was replaced by the powerful village head who incited the response to fight. Formal systems that were built on the Anglo Saxon model completely replaced traditional systems that promoted dialogue, preserved relationships and focussed on win/win outcomes. To nurture and reacquaint ourselves to the tend and befriend response, strong action is needed. The Mediation Bill, 2021 which is currently under consideration at the Parliament proposes mandatory mediation for civil and commercial disputes. We welcome this step and believe that if well implemented, it could provide the impetus to develop a whole new way to resolve disputes – a way that is not only inherently natural but also badly needed in our country today. Mandatory Mediation for India “Constitutional morality is not a natural sentiment. It has to be cultivated." - B.R. Ambedkar, Annihilation of Caste India has consistently used strong laws to drive social change - whether it was the 1843 Indian Slavery Act that abolished slavery and helped changed minds about this abominable practice or The Hindu Child Marriage Restraint Act, 1929 replaced by the prohibition of Child Marriage Act, 2006 that prohibited child marriage and imposed sanctions for the same or the The Child Labour (Prohibition and Regulation) Act 1986[11] that prohibited the employment of children under 14 years or the Protection of Women from Domestic Violence Act, 2005; India has successfully used strong laws to bring about social transformation. To encourage a collaborative mind set, mediation must be strongly encouraged through legislation. A culture of ‘mediation first’ can be effectively promoted through policy. Countries round the world have successfully experimented with mandatory mediation models to not only reduce burden on courts but also encourage behavioural change when responding to conflict. Mandatory Mediation Internationally Italy serves as one of the most leading examples of a successful mandatory mediation law and policy. Voluntary mediation was first introduced as an option to disputants in Italy in 2003 but was hardly used. In 2010 Italian lawmakers introduced mandatory mediation legislation, recognising a clear reluctance by parties to engage in mediation and to address the heavily overburdened courts. Legislative Decree No. 28/2010 required mandatory mediation for certain kinds of disputes.[12] Before a filing in court, parties and lawyers are required to engage in an initial mediation session with an ability, thereafter, to easily opt out of mediation. Tax reliefs were offered to parties who engaged in the mediation process, and it was to be quadrupled if an agreement was achieved. This mandatory initial mediation session model has not only drastically increased the number of cases that attempted and settled in mediation but also recorded a substantial decrease in the number of court filings.[13] In Singapore, Mediation is divided into court-annexed and private. In 2010, the State Courts increased the use of mediation in civil disputes by adopting the 'ADR Form at the Summons for Directions' stage. Both attorneys and clients are required to sign a document certifying that they have explored ADR possibilities and indicating their decision regarding the same. In 2012, a "presumption of ADR" was implemented, which requires all civil cases to be automatically directed to mediation or other types of ADR unless one or more parties opted out. Refusing to employ ADR for reasons considered unacceptable by the registrar results in financial fines under Rules of Court Order[14]. Mediation in the European Union has also had more success when it involves elements of mandatory nature.[15] Turkey introduced mandatory mediation for certain categories of disputes and has recorded a drop of up to 70% in court filings in those categories[16]. Greece, and the UK are also using strong mandatory mediation policies to increase the culture of collaboration and reduce pendency in courts. India is in desperate need of multiple solutions to address the crisis of 4.7 crore cases pending in our courts[17]. An efficient [18] process that promotes a culture of dialogue and respectful understanding must be a choice for every Indian. India attempted mandatory mediation by amending the Commercial Courts Act, 2015, which did not yield desired results. Unfortunately it did not include a strong sanction for non-appearance and provided an exception for cases that needed interim relief. This became the Achilles heel in the law and rendered it practically useless. The draft Mediation Bill 2021 that is currently pending before the Indian Parliament proposes mandatory mediation for all civil and commercial cases before the institution of a suit. If it is drafted in a manner that ensures a strong push towards mediation but also allows for disputants to easily access the courts after a meaningful initial attempt, we are creating the possibility of a mediation first culture that will reduce court filings and promote peace. Needless to say, strong professionals who understand the process and are skilled to facilitate dialogue and resolution is a non-negotiable element in making this policy a success. Conclusion As a human species, we now know that our human brain is capable of evoking a response of tend and befriend under stress. This response stimulates the evolved neocortex part of our brain where rational decisions and creative problem solving is possible[19]. As a legal system we are in desperate need of options and alternatives – our courts, the only option for dispute resolution in India, are facing an impossible case load that is only increasing. As a society, our ability to dialogue, understand each other and collaborate is essential for us to be able to solve our most urgent problems on which our survival depends. Laws play a significant role in influencing behavioural change. A law that encourages dialogue and collaboration of the disputants and promotes an efficient process that finds quick, sustainable resolution seems like a win/win option for India. We welcome India’s move to introduce mandatory mediation. All eyes now, on a well drafted law that will get the disputant to the mediation table but also preserves every Indian’s fundamental right to access to justice. References [1] Sriram Panchu, Mediation: Practice and Law (The Path to Successful Dispute Resolution), 3rd Edition. [2] Beer and Packard, The Mediator’s Handbook, 4th Edition. [3] Christopher Moore, The Mediation Process: Practical Strategies for Resolving Conflict, 3rd., (San Francisco: Jossey-Bass Publishers, 2004) [4] Canon 1932 [5] Shelley E. Taylor, Laura Cousino Klein, Brian P. Lewis, Tara L. Gruenewald, Regan A. R. Gurung, and John A. Updegraff, Biobehavioral Responses to Stress in Females: Tend-and-Befriend, Not Fight-or-Flight, Psychological Review 2000, Vol. 107, No. 3, 411-429 (https://scholar.harvard.edu/marianabockarova/files/tend-and-befriend.pdf) [6] ibid [7] Derba Gerardi, Perspectives on Leadership, The American Journal of Nursing, (September 2015), Vol 115 No 9, 61. [8] Shelley E. Taylor, Tend and Befriend Theory, Handbook of Theories of Social Psychology. Sage Publications, 2011. [9] Shelley E. Taylor, Tend and Befriend: Biobehavioural Bases of Affiliation under Stress, Current Directions under Psychological Science, (December 2006), Vol 15 No 6, 273. [10] Shelley E. Taylor, Tend and Befriend Theory, Handbook of Theories of Social Psychology. Sage Publications, 2011. [12] Disputes related to condominiums, property, division of goods (or partition), family-business covenants and agreements, wills and inheritance, leases, loans, business rents, medical and paramedical malpractice, libel, insurance, and banking and financial contracts. Legislative Decree No. 28 of 4th March 2010, Italy. [13] Leonardo D’ Urso, Italy’s ‘Required Initial Mediation Session’: Bridging The Gap between Mandatory and Voluntary mediation https://www.adrcenterfordevelopment.com/wp-content/uploads/2020/04/Italys-Required-Initial-Mediation-Session-by-Leonardo-DUrso-5.pdf [14] Code of Ethics and Basic Principles of Court Mediation, available at http://www.subccourts.gov.sg, under “Civil Justice Division, Court Dispute Resolution/Mediation”. [15] Giuseppe De Palo; Romina Canessa, Sleeping - Comatose Only Mandatory Consideration of Mediation Can Awake Sleeping Beauty in the European Union, 16 Cardozo J. Conflict Resol. 713 (2014). [16] Tuba Bilecik, Turkish Mandatory Mediation Expands Into Commercial Disputes, http://mediationblog.kluwerarbitration.com/2019/01/30/turkish-mandatory-mediation-expands-into-commercial-disputes/ [17] Over 4.70 crore cases pending in various courts: Govt https://economictimes.indiatimes.com/news/india/over-4-70-crore-cases-pending-in-various-courts-govt/articleshow/90447554.cms?from=mdr [18] In private mediation nearly 70% of cases settle within 3 months. In court mediation programs, specifically at the Bangalore Mediation Centre of the Karnataka High Court the settlement rate is 66% in 90 days (Strengthening Mediation in India: A Report on Court-Connected Mediations, Vidhi Centre for Legal Policy Table 8) [19] Cloke, K., 2013. Bringing Oxytocin into the Room: Notes on the Neurophysiology of Conflict About the Author Mohit Mokal is a Senior Associate, Mediation at CAMP Arbitration & Mediation Practice and Tara Ollapally is the Co-Founder & Mediator at CAMP Arbitration & Mediation Practice. The opinions expressed in this article are those of the authors. They do not purport to reflect the opinions or views of Indic Pacific Legal Research LLP or its members.

Coca Cola’s utility increases on a hot day compared to other days which was noticed as a profit maximization opportunity and in 1999, the company considered the implementation of temperature-sensitive vending machines that would alter the price of the product as per the intensity of heat in its surroundings[1]. This sums up the idea of dynamic pricing, which various corporations have been employing while retaining the demand-supply equilibrium in the nucleus. Algorithms, on the other hand, are just one of the extremely effective means to harness the concept of dynamic pricing which translates to Algorithmic Pricing. It is applied for constantly altering the offer price depending upon the consumers’ personalized data sets, derived mostly by past activities and recent trends[2]. In the most generalist sense, Algorithms can be traced back to the time before the invention of computers. Simply put, it denotes a set of rules that ought to be repeated, in a specified sequence to accomplish the given task. With the overall technological revolution, Algorithms have become more and more sophisticated due to the application and evolution of Big Data, Machine Learning and Artificial Intelligence (AI), which have made it particularly efficient in creating useful data repositories, making predictions, decision making and achieving goals within time. Especially e-commerce websites like Amazon and Flipkart have been able to achieve exponential growth due to this inexpensive piece of technological innovation. The present-day Algorithms are capable of performing complex tasks like predictive analysis which helps a corporation to appraise consumer behaviour, forecast risks, highlight the new competition and estimate demand, all at once and synchronised to capitalise on profits. Governments have also been using it to gauge criminal behavioural patterns, intensities and possible occurrences of the crime, by applying it to different variables like period and location. Due to the expansive nature of Algorithm Pricing, it has been subject to scrutiny in recent years. Domestic regulators, as well as International Organisations, have been conducting research into possibilities of intrusions into privacy, business ethics and competition regulations caused by such Algorithms. This analysis will critically examine the regulatory concerns associated with Algorithm Pricing in isolation while acknowledging that growth of the e-commerce industry on whole has indeed led to innovation, connectivity and overall progress. It is a policy issue: International Trade Law The body of International Trade Law consists of treatise, principles and customs which regulate the transactions of two or more private sector parties belonging to different states. The World Trade Organization (WTO) and the Organization of Economic Cooperation and Development (OECD) have been expressing concerns of violation of privacy rights and competition policies[3]. How the WTO and OECD give teeth to these concerns is yet to be seen since at International level and in private contracts, these organisations can only emphasise States to take action depending on their accessions. For instance, the prices of essential goods are regulated as per the General Agreement on Tariffs and Trade (GATT) which is consensual[4]. Although the silver lining is that these organisations play a vital role in establishing standards for the conduct of business which will be dealt with in detail in further paragraphs. International organisations and technological innovations have always gone hand in hand, as for instance, the United Nations Commission on International Trade Law (UNCITRAL) played an important role during the internet regulation phase wherein its efforts helped recognise electronic contracts and records, in policies of individual states. In 1998, WTO along with the support of other States, granted a moratorium on duties for products of electronic transmissions, thereby facilitating easy trade in digital products[5]. The Algorithm Pricing mechanisms adopted by e-commerce companies gather huge amounts of consumer and competitors’ data which is then sorted out to understand seasonal preferences and then flash appropriate offer prices. The international community is specifically concerned since a major chunk of the population is unaware that such processes are being employed to gather their data and use it contrary to their interests. The European Union (EU) Courts’ technological approach asserts the highest importance to interpret provisions in a way, so as to further the goal of consumer welfare. If such processes cannot be accommodated into a specialised law, then it can be accommodated into general welfare provisions through the channel of interpretation. The functioning of this Algorithm Pricing (AP) goes against consumer welfare as the consumer is subjected to imperfect knowledge about the prices being charged to him. A strong welfare setting would require that a consumer knows, not only what he is being charged but also what other consumers, with identical/similar status, are being charged. One would argue that similar friction prevails in an offline setting as well, but the underlying point here is that consumers lack preliminary knowledge of dynamic pricing on e-commerce platforms. Consumers must be expressly made aware of the variables which determine a personalised price setting for different individuals or just the fact that dynamic pricing exists[6]. It is difficult to prove the illegality of the use of the algorithms itself or the manner in which they are being processed, but it is necessary to investigate the nature of actions like targeted advertisements, collection of consumer data and preferences, disclosures made, responsiveness to price offers and past purchases trajectories. Ultimately, it is for the respective States to decide, as a matter of policy, the extent to which these intrusions should be allowed. It becomes an increasingly important issue since foreign companies’ activities related to data mining in the domestic sphere can lead to remittance of vital information out of the country which, in exceptional circumstances, may lead to strategic concerns for a state. Competition Concerns Simply by selling the same products at different prices to different people is not illegal. Issues arise only when two or more market players expressly agree to raise, reduce or stabilise their prices, in order to defeat natural competition[7]. One would say that in the absence of an express agreement, Algorithmic Pricing could at the most, lead to tacit collusion with the competitor to alter the price, which is outside the purview of Competition law. Regulators here have raised concerns that the sheer vastness of capabilities of Algorithmic Pricing can lead to an understanding, whereby it can teach itself to manipulate prices anti-competitively. Hence, even without an agreement or human intervention, Big Data analytics might supplement reactive pricing in a way which will eventually teach itself to arrive at a cooperative equilibrium with other competitors' algorithms[8]. In effect, this cooperative behaviour leads to conscious and express coordination which at all times, prevents unsatisfied demand and excess supply. Such processes then deprive the consumer of the lower price which it could have gained from the result of the competition despite the e-commerce platform being able to afford a reduction in price below the threshold. The OECD has recognised these activities as potentially illegal and asked to keep a check on developments in AI to determine if it can take business decisions which will finally bring Algorithmic pricing under regulatory scrutiny[9]. Another concern is that due to these Algorithms processing data every second, they act as a watchdog to quickly identify a new entrant or competition in the market. Such identification is then used to offer competitive prices which the entrant can never afford to match. There is no denying the fact that consumers derive huge benefits from competitive pricing but the big picture shows that those benefits are not derived equally by all consumers, which goes to the root of collective justice[10]. Establishment of standards International Organisations are in a better position to establish standards to deal with exploitative aspects of Algorithm Pricing. The following reasons suggest why such Algorithms are unfair which may not necessarily be illegal but surely essential for setting standards. The rationale for establishing standards lies in the fact that Algorithms being used for pricing are neither transparent nor ubiquitous which makes it unfair and highly violative of the well-established social conventions one would follow in an offline retail setting. It is a matter of moral legitimacy that a transaction must not only involve consensus but also informed consent, which is absent in an online transaction where a consumer would not have indulged with the seller if it was aware that the e-commerce platform waived off its willingness to lower the prices by colluding. Data-driven Algorithms assess consumer information at a granular level which in contrast is not available to the consumer leading to plausible exploitation. When one consumer is offered a price for a product, it should act as a threshold for other consumers to determine the value of the product. Consumers could have come to another valuation (lower) for the same product which was denied to them without knowledge of the same. Due to the opaqueness of the Algorithm Pricing strategies, behavioural economics suggests that consumers are being treated unfairly. Privacy concerns related to these activities are huge, as everything from past behavioural activities to location tracking to capacity and willingness to pay is tapped, stored and utilised at the expense of the consumer itself making Algorithm Pricing a fit case for regulation by well-defined standards[11]. Transparency Transparency serves as a separate calling for regulation of Algorithm Pricing as it is this aspect from which all other issues relating to Algorithmic Pricing arise. Generally, transparency for such a technological process can be achieved with an adequate evaluation of the software system, monitoring its activity and subjecting it to self-regulation as a reporting entity. Although the ground reality is not so simple, considering that transparency was to be imposed then even submission of complex and long algorithmic program codes would be extremely challenging to decipher in order to unwrap some real substance of unfairness[12]. Proving illegality will altogether be more difficult as, in a sandbox environment, achieving the result of the desired price to prove guilt will depend on all requisite variables falling perfectly in the right place and time in a sequential and synchronised manner. There is little realisation of the fact that providing source codes will not lead to transparency unless the rationale behind particular codes are made known to the authorities which is an impossible task as companies have a stronger right to secure their trade secrets[13]. Regulators also need to be mindful about the fact that any policy brought does not become too conducive for the existence of the industry itself. Conclusions Some of the possible regulations which can be adopted are restricting volatility of price fluctuation by introducing cap limits, tapping into competitor’s data could be declared to be illegitimate and regulation of the algorithm designs from the inception. Although these restrictive policies can be adopted, the regulators, domestically and internationally, will have to take a cautious approach to avoid excessive regulations and undertaking supervisory burden for an industry which has generated great wealth for the society. An appropriate regulatory structure should involve definite laws which could be information technology law, competition law or intellectual property rights. If several agencies need to be involved then a structure of coordination to avoid overlapping needs to be in place. International Trade Law should fortify its substantive laws to cover situations dealing with foreign companies in other jurisdictions. Ultimately, the regulators do not have concrete proofs of privacy or competition law breaches but have serious concerns about the possibility of illegalities being committed by Algorithmic Pricing. Regulators are ready with cavalry to engage in meaningful regulation of Algorithmic Pricing but which innovation will be the last straw to break the camel’s back is to be seen. References 1[1] Seele P, Dierksmeier, Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing, J Bus Ethics (2019), https://doi.org/10.1007/s10551-019-04371-w [2] Thomas Gehrig, Oz Shy and Rune Stenbacka, 'A Welfare Evaluation of History-Based Price Discrimination' (2012) 12 Journal of Industry, Competition & Trade [3] CPI Talks, Interview with Antonio Gomes of the OECD, May 2017, https://www.competitionpolicyinternational.com/cpi-talks-interview-with-antonio-gomes-of-the-oecd/ [4] WTO, Substance of Accession Negotiations, Handbook on Accession to WTO, https://www.wto.org/english/thewto_e/acc_e/cbt_course_e/c5s2p3_e.htm [5] World Trade Organization, How Do We Prepare for Technology Induced Reshaping of Trade, World Trade Report 2018, https://www.wto.org/english/res_e/publications_e/wtr18_4_e.pdf [6] Christopher Townley, Eric Morrison & Karen Yeung, Big Data and Personalised Price Discrimination in EU Competition Law, King’s College London, Legal Studies Research Paper Series, Paper No, 2017-38, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3048688 [7] Algorithm Pricing and its Effect on Competition Law, Society of International Trade and Competition Law, https://nujssitc.wordpress.com/2018/02/23/algorithm-pricing-and-its-effect-on-competition-law/ [8] Refer Supra Note 5 [9] OECD, Algorithms and Collusion – Background Note by the Secretariat, Directorate for Financial Enterprise Affairs, DAF/COMP(2017), https://one.oecd.org/document/DAF/COMP(2017)4/en/pdf [10] Refer Supra Note 6 [11] Refer Supra Note 5 [12] Deven R Desai and Joshua Kroll, Trust but Verify: A Guide to Algorithms and the Law, Harvard Journal of Law and Technology Vol 31, https://jolt.law.harvard.edu/assets/articlePDFs/v31/31HarvJLTech1.pdf [13] Refer Supra Note 9

Lawyers in the 21st century, are no longer limited to court galleries, nor their acumen and approaches to real-life problems affected by digital technologies can be traditional. Today’s lawyers must act like consistent conflict managers, who would use their clarity of first principles in legal theory to provide real-time, stage-conscious, risk-sensitive solutions. A theory of law and economics, differing from the decades’ old Keynesian and Newtonian economic thought models, now calls for complex adaptivity in lawyering. In fact, when legacy institutions become either dysfunctional or overburdened, lawyering solutions to address legal problems related to digital products and services, would surely go beyond the usual ways of addressing liability and rule of law concerns. Even auditing and compliance, as simplified or complicated it may seem, shapes the regulatory approaches of governments and enables mobility in solving problems. In my previous articles, I have covered the concept of soft law in detail, in which I have discussed how understanding legal concepts and principles is not limited to the general sources of law. There are certain exhorting sources and means of understanding law, which indeed do not establish themselves to be, what we call as hard law. If we try to solidify those understandings and sources in the applied form, then those sources and means do not remain as soft law at all. It is necessary to recognise tools to mobilise legal solutions as the means and not the end. Following this principle, in this article, I will explain about agile management in law, and will cover how can we use this as a tool or a means to enhance lawyering in law & digital technologies. What is Agile Management/Methodology? In 2001, a group of individuals authored the Principles of Agile Methodology in which they proposed much modernised means of software development. The 12 principles are quite simple, described as follows: Deliver customer satisfaction by delivering valuable software continuously Always accept change of requirements matter how early or late in the project Deliver software that works within a shorter timescale Both developers and business professionals must work closely together daily throughout the project Information is best transferred between parties in face-to-face conversations Motivate people to build a project by creating an environment of appreciation, trust, and empowerment Working software is the key measure of progress The agile process promotes sustainable development Continuous attention to excellence and quality in technical development and design boosts the agility Simplicity is a vital part of effective agile management Self-organized teams produce the best architecture, requirements, and design Teams should reflect through inspection and adaption to be more effective When we understand these principles, it is necessary to realise that these principles are more indicative and reflective in creating sustainable legal solutions or at least those legal methodologies which are coherent with the agile development of digital technologies. Lawyers would largely have to ensure that from every possible and legally cognizable stage of technology development, they have to propose and provide handy solutions, which fit in the legal status quo, while the laws and regulations which cover digital technologies, really become handy enough to promote technological and legal innovation. We can also argue that the development of ethical principles for different kinds of digital technologies, may be attributed to the inspiration of these obvious 12 principles of agile management, which somehow reflect upon some crucial areas of technology development, such as: Knowledge Management Corporate Ethics Auditing and Compliance Examples of such technologies could range from artificial intelligence to IoT and even the emergent Web3 technologies, such as metaverse and blockchain. It would be reasonable to understand how to develop the skill of agile management and asking the right questions to develop strategic solutions to address digital transformation. Some General Know-hows of Agile Management There are no exhaustive or rigid approaches towards agile management. When we read those 12 principles of agile methodology in software/digital product development, we can understand that the applicative effect of these principles, does not have to be rigid. If we try to achieve rigid outcomes, then the sustainable essence of the principles has neither been understood, nor been achieved. Let me take a principle, as an example: Continuous attention to excellence and quality in technical development and design boosts the agility The above principle, describes the essence of giving continuous attention to achieve excellence and quality in two important things - technical development and technical design. For a technology lawyer, who has to advise and help the company developers - the principle gives indicates the following to reflect upon: If no regulation or law on a class of digital technology exists in general, then self-regulation backed by market economy concerns drive the ethics of auditing and compliance, naturally. It would be reasonable to help technology companies to do these: Shaping auditing and compliance standards for digital products and services provided Engaging on consultation to promote sensible life cycles of the digital products and services Checking and shaping ethical approaches behind the design and development of the required digital products and services If any law or regulation, which regulates a particular sector, is applicable to that class of digital technologies, then self-regulation and market concerns would have to be sensitive to the the laws and regulations applicable to the sector. It would be reasonable to help technology companies to do these: Adhering with and promoting auditing and compliance standards for digital products and services provided, in lieu of their impact on the particular sector Shaping separate ethical methodologies on the sector-wise impact of the digital products and services, maybe in terms of their usage, their market value, their capacities, their effectiveness or the risks associated The principle is quite obvious is simple, for sure. But its value and applicability differs largely as legal problems often become complicated. In India, many of the legal questions remain unsettled, which makes it probable to have a first principles approach in addressing the ethics, the physique and the jurisprudence behind enabling agile management. Therefore, the know-hows can be used to learn, achieve, generate and improve the practical knowledge required to provide legal, ethical and management solutions. Some of the ways that technology lawyers may adapt with to gather those know-hows are described: Develop the first principles, legal, ethical and even economical behind the scheme of product development Stakeholder consultation is necessary to gather expert opinions Testing, evaluation and improvements in a digital product’s life cycle must be done coherently Apply schematic methods of thinking and understanding the ethical and legal anomalies with respect to the digital product The know-hows learnt and achieved from these general means could contribute towards enabling compliant and even sustainable business practices in general. Knowledge Management Knowledge management, in general relates to regulating the knowledge and information pertaining to business practices of a company. Whatsoever knowledge and information collected, which is learnt and generated in a company would be subject to regulation by a company’s management. Agile management could help in improving knowledge management in simple ways. Scrum meetings are a good example to regulate knowledge and information, where team members when share insights can indicate the kind of knowledge generation actually happening, and the level of competitiveness in addressing product-related issues. Even Feature-driven Development could be helpful in achieving knowledge management practices. Corporate Ethics Agile practices surely resemble corporate governance practices in a company, exemplifying how key decisions are made, and how the management leadership within the company ensure reasonable HR, development, auditing, risk assessment and other domains of concern. An example of corporate ethics could be observed in the development process of a digital product into several parts so that they are developed in iterations. From Creating Legal Norms to Creating Legal Solutions Sebastian Hartmann in an article on Solution Managers for Professional Service Firms explains how professional service firms approach creating legal solutions. This diagram from the article creates a much clearer picture: Now, norm creation and method creation play an important role in self-regulation in the information age. Yet, the emanation of these concepts come from the traditional understanding of governance and law-making, which has a top-down human element to approach legal problems. In this chart above, if we look at the traditional segments, it is determinable that the focus has now shifted to creating legal solutions, where agile methodologies can be adapted. The human-to-technology semblance shapes the efficacy of digital technologies in providing professional legal solutions. The genesis of legal solutions does not necessarily lie in public policy per se, but in providing all-round collaboration-oriented solutions to generic problems associated with digital products, which includes scale, technology UI/UX, consumer acquisition, deliverability and other factors of importance. Maybe public policy could enable the role of governments and various other stakeholders, such as domain experts, sector experts and consumers. Actions create the imprint of self-regulation, while could also enable regulators to drive markets smoothly, which could be simple in application to happen. It also enables healthy stakeholder consultations, which for sure could have better impact per se. In further articles, the role of agile management would be covered regularly.

In this article, I have discussed about a recent trend being pushed by various marketing firms, law scholars and industry players about the interesting problems surrounding around this similar notion that intellectual property rights, which are granted to humans, governments, companies or any proper legal entity, can be granted to artificial intelligence systems and technologies. There may be some proper arguments in the favour of the proposition, in the fields of technology and jurisprudence. However, my view is that the evolution of the digital technologies such as AI (or even AI-integrated) which we exemplify, have still not been a part of that saturation to promote the possibility of granting such rights. This article can be considered as a counter-propositional article to begin on this question of recognition of IP rights of AI systems and technologies. The CEI and SOTP Classifications of ISAIL: A Quick Recap Let us take a quick recap on the article in which I had discussed about the legal status of artificial intelligence technologies. As per the classifications provided by the Indian Society of Artificial Intelligence and Law on entitative status of artificial intelligence technologies - there are 2 clear ways to do it - CEI and SOTP. As per this diagram, I had also proposed that the any AI technology/system can be manifestly present/available within any other class of technology in the tangible forms, that we understand. So, you might require machine learning tools, in a blockchain-based system, or maybe IOT and RFID tags used require the internal support of AI technologies for execution purposes. Sometimes, maybe even any class or sub-class of AI technology could exist within any class or sub-class of AI technology, if it is possible, in legitimate terms. Now, the idea of being manifestly available changes legal theory perspectives on deciphering what kinds of rights, privileges, liabilities and agencies can be accorded on any AI system/technology, since on a case to case basis, it is obvious to consider the situation becoming bleak or uncertain - because it could also lead any law professional to interpret such incidence in reductionist terms, heavily. Sometimes, technologies are embedded in certain ways as industrial trends shape up that disputes can still be addressed (keeping other factors aside for a while, if) in an ordinary fashion. Yet, in the field of judicial governance and alternate dispute resolution, especially in the technology law domain, it would be rather prudent to assume that complications may genuinely or obviously arise on the agency of any technology being put to use. This at least shows a simple phenomenon that unless proper trends are adapted with, sweeping generalisations on the status of AI technologies being recognised in legal systems, cannot be made. Dr Jeffrey Funk, a technology consultant (formerly at NUS Singapore) recently gave an intriguing example via a LinkedIn post, which is related to a prediction made by the University of Chicago that data and social scientists have developed an algorithm that forecasts crime by learning patterns in time and geographic locations from public data on violent and property crimes. However, the model predicts using historical data and does not predict specific events. Gary Smith writes for Mind Matters an article on the same issue, where he provides an informed critique on algorithmic criminology. An excerpt from the article is provided below: Algorithmic criminology is now widely used to set bail for people who are arrested, determine prison sentences for people who are convicted, and decide on parole for people who are in prison. Richard Berk is a professor of criminology and statistics at the University of Pennsylvania. One of his specialties is algorithmic criminology: “forecasts of criminal behavior and/or victimization using statistical/machine learning procedures.” He wrote that, “The approach is ‘black box’, for which no apologies are made,” and gives an alarming example: “If I could use sun spots or shoe size or the size of the wristband on their wrist, I would. If I give the algorithm enough predictors to get it started, it finds things that you wouldn’t anticipate.” Things we don’t anticipate are mostly things that don’t make sense, but happen to be coincidentally correlated. Now, in the field of AI Ethics, discussions have already shifted from attaining responsible AI (according imagined responsibilities on the AI system/technology and their creators) to explainable AI, where the questions revolve around the classic black box problem where algorithms lack explainability to human data subjects (if we take the GDPR lexicon, for example). This infographic clearly shows that in general, with exceptions, the responsible AI condition for any AI technology/system could be pre-emptive or ex-ante, to prevent any harm/damage to human data subjects (for example). In general, the explainability of AI technologies comes into question when it is a routined necessity to check them or when impact assessment has to be done. There are nuances in both the concepts’ materialisation, without any doubt. Let us now understand the problem behind even granting IP rights to AI technologies. The “Rights” of AI Technologies/Systems within IP Law It is a basic understanding that rights, duties, liabilities, facets of accountability and even agency of any tangible legal entity has to be decided on a clear and factual basis. Jurisprudence may be old, and it could be possible in the case of digital technologies that precedents might not even exist in many Global North and Global South countries. Nevertheless, sometimes the regulators intervene (AI policies, for example, India’s NITI Aayog’s Responsible AI Reports of 2020), legislative competence and approaches are sharpened (for example, European Commission’s draft proposal of the Artificial Intelligence Act) or the judicial bodies intervene and define some new principles or norms (for example, Commissioner of Patents v Thaler [2022] FCAFC 62, which is overturned as of now). Now, there are many general reasons why such soft or hard interventions are undertaken. Some of the reasons are outlined as follows: Some scholarly opinions by any judge or member of a regulatory/executive/legislative body could have contemporary relevance, and their groupthink could be taken into account to mobilise the process of policy formulation, acceptance and democratisation, from an industry point of view. In the field of law, it becomes necessary to start defining at least some basic aspects of a technology taken into scrutiny. Without any first principles, there is no possible to ensure accountability of the companies and creators who are benefiting the use of the technology as a subject matter. The European Union’s Artificial Intelligence Act (draft) in its Annex 1 provides a narrow definition of what constitutes artificial intelligence, for example. All states and their judicial and executive functionaries are the closest means to ensure that some relevant intervention or action is sought. For example, in India, the Delhi High Court has come up with important judgments on Twitter not adhering to The Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, which then (along with public comments) contributed discussions to review the 2021 Rules and notify amendments in the same. A general problem which emerges in the case of intellectual property law is that be it copyrights, trademarks, patents, industrial designs or even integrated circuits, it is duly important to signify at least some corollaries of what rights or duties or agency do we have to even accord to any artificial intelligence technology. The challenges are immense since much formalisation is not possible to happen unless the technology trends in the industry, globally and nationally, are stable. If companies are manufacturing AI technologies and systems which are weak on their explainability and during their cycle of making - their efficiency has even not been tested properly - there is no reason to provide any special legal faculties to AI technologies under IP law. For example, people can claim granting the rights of an inventor to an AI system, or claim that some AI software must be granted copyright for “making” some artistic work. The problem however is that the human touch to any creation, is something, which cannot be - replaced with algorithms-based anthropomorphism. This is similar to the case of the predictions made by researchers at the University of Chicago about an AI system predicting a crime even before its happening. AI hype is a serious problem because it shields the Black Box problem of AI systems and technologies. It also ensures in the market that the regulators fail to develop informed and sustainable rules and approaches to address the relevance and use of AI technologies, sector-wise. Cindy M Grimm provides an interesting example in an article published by Brookings Institution. We can illustrate this failure with a simple example. Let’s say the program manager requests a robot system that can see an apple and pick it up. The actual implementation is a camera that detects red pixels that form a rough circle. The robot uses two consecutive images to estimate the location of the apple, executes a path that moves the gripper to the apple, then closes the gripper fingers and lifts. When deployed, the robot mistakes the picture of a hot air balloon on a shirt and tries to drive the gripper through the person in an attempt to pick it up. This failure is not at all a surprise given the implementation description but would come as a shock to the person who was only told that the robot could “see apples and pick them up.” Many of the failures that seem to plague robots and AI systems are perfectly clear when described in terms of implementation details but seem inconceivably stupid when described using anthropomorphic language. The same case could easily apply to Creative Adversarial Networks (CANs), a subset of Generative Adversarial Networks. S Will Chambers, for Towards Data Science explains how CANs work: In the GAN, which the authors call a Creative Adversarial Network (CAN), a generator network creates images and a discriminator network, which is trained on 81,500 paintings, critiques the generated images based on aesthetics. Interestingly, when the CAN images were placed beside contemporary human artworks, human evaluators could not tell which images were artificially-generated. In many cases, the CAN images were rated aesthetically higher than the human artwork. Now, aesthetics has its own value, in philosophical and real terms. The reality however is that critiquing aesthetics does not ever mean possessing the tendency of creating something better. From a propositional aspect, using CANs to use generated images and develop aesthetically advanced or sophisticated “artwork”, might seem to be lucrative. However, mastering two skills - aestheticisation and critiquing human-made aesthetics can only have a human touch when humans are aware and doing it voluntarily. In the case of CANs, it seems that when algorithms anthropomorphise - there is no human touch or involvement. Human-made works, with their own mores, imagination, rules, biases and realities are left to algorithmic scrutiny, which again is not human-centric. Maybe, in certain aspects of artistic evaluations or creativity, those who are trained in CANs and GANs might use these algorithms as a project, or for any commercial and other use. However, granting any specific rights to an AI systems does not make sense. The right to critique even under a basic understanding of international human rights law, especially, Art. 19 of the International Convention of Civil and Political Rights (read with the UDHR of 1948) - is a freedom of expression right. Freedom of expression, be it under a libertarian understanding of rights - needs to have a human touch, because that system of understanding is definitive to protect human freedom of speech and expression against the excesses of a state. Let us assume that an AI system generates images using CANs, then why should it be even granted any IP rights? The Council of Europe, a premier multilateral body embracing global governance on issues of international human rights, under its former Ad Hoc Committee on Artificial Intelligence, recognised the human rights-centric aspect of artificial intelligence ethics. Emanating rights to human beings is sacred and fundamental, because human creativity, is truly, human. Algorithmic creativity is anthropomorphic and does not account to clear solutions and precedents. Here is a discussion I had with Gregor Strojin, the former Chair of the Ad hoc Committee on Artificial Intelligence for the Council of Europe months ago. For reference, I recommend readers to watch this discussion with Maksim Karliuk, at 14:31, on Human-centered Artificial Intelligence. Dr Richard Self has also provided strong arguments against the recognition of IP rights to AI systems and technologies. The arguments are provided as follows, with some elaborations: 1) As far as we know, AI systems do not have the ability to reason. All current LLM systems are pure stochastic parrots and even lack the ability to understand their "knowledge". It means that AI systems and technologies beyond even the questions of responsibility and explainability, have in general - not reached the ability to understand knowledge. Philosophically, it could be argued that the understanding has to be human-centric or maybe it could be anthropomorphised. The former seems to be a legitimate criterion and not the latter considering the harms of algorithmic anthropomorphism. If the latter option is chosen, for convenience reasons, then its life cycles must be regulated and tested with due dilligence. Knowledge management is delicate and within the domains of law and management, must be addressed reasonably, especially when technologies like artificial intelligence are the subject-matter. The Annex 1 of the EU’s Artificial Intelligence Act, is one of the most controversial and significant examples to look out for. 2) Any current form of "AI invention" is normally shown in systems that try many different solutions, such as genetic algorithms. This is not creativity, nor is it usually any form of reasoning. This argument makes sense because invention and creativity are not the same. There could be, in the human case, creative efforts behind generating or discovering something. Yet, it does not make a case for AI technologies and systems. 3) All current forms of AI are very narrow and cannot transfer knowledge between different domains. 4) Non-human entities, such as a software system also do not have any rights to real property and are owned by humans or institutions and businesses. As such, an AI system is just a tool that humans use to rapidly analyse different options. The resultant IP then rests with the natural human who posed the question and guided the tool towards a solution, or possibly, the IP is retained by the organisation for whom the person works. On point 3: AI can be categorised as Narrow, Weak and Strong AI as well. Measuring the “narrowness” of AI technologies can be done through many relevant methods - including quality and life cycle assessment, impact assessment, auditing, data quality, algorithmic explainability (the black box dilemma), due dilligence, etc. There has not been any AI technology ever found which can transfer knowledge from an X domain to a Y domain. This is a human skill, with human orientation, which again, has been formalised for years and centuries. This point surely is sensible. On point 4: Dr Self has pointed out the most complicated aspect of even granting IP rights to AI technologies: corporate governance & ethics. IP rights are used by legal entities and when companies (be it MSMEs, large corporations, start-ups) or any other possible legal entity owns the IP, can develop strategic knowledge resources for their internal and/or knowledge uses. Whether it becomes legally relevant for a regulator to intervene is a subjective question, as for different classes of AI technologies/systems, there are different multi and cross-industrial requirements. Specific cases, perhaps can be taken into regard to further unfold and study the phenomenon. Conclusion It is pertinent to note that the classes of AI technologies, and their manifest availability makes them further complex and uncertain (unless properly tested and documented) in terms of their legal/juristic status. If and only if IP rights are to be even granted to any such technologies, it should be the primary requirement of a State to define the legal and juristic entitative status of the class of AI technologies. The European Union’s approach to begin with the process is quite promising. How much sectorial that approach is, remains to be seen. Instead of asking hyped pop culture-inspired questions on the legal status of AI, it is necessary to study the contours of regulating AI technologies (their development, production, usage, auditing and impact assessment) and how corporate governance & knowledge management affects the strategic role and inclusion of AI technologies.

DISCLAIMER: The contents of this blog article reflect the personal views of the author alone and do not constitute the views of any of the author’s affiliated organizations. The contents of the blog article cannot be treated as legal advice under any circumstances. The use of smart contracts as opposed to paper based traditional contracts continues to increase in commercial activity and practice. With the advent of Web 3.0 technologies, smart contracts may become a standard form of contract since the characteristics of automated self- execution, operability on a decentralized blockchain and speedy execution of contractual obligations are more suitable to the needs of commercial transactions, and as well as for eliminating breaches in day- to day commercial transactions. However, the possibility of disputes exist in every contractual transaction and smart contracts are no exception to it. Considering that the regulation of smart contracts is at a nascent stage across jurisdictions, with India, having no legal framework at place, the idea of resolving smart contract disputes in a Civil Court is still implausible. But, at the same time, the possibility of solving smart contract disputes through arbitration is feasible due to the possibility of party autonomy in several crucial aspects such as choice in law, choice of forum, choice of procedure and the like, to be applied in the arbitration proceedings. Therefore, this blog attempts to examine the arbitrability of smart contract disputes in India with an aim to expose challenges and provide solutions in the current legal framework that may pave a path to better arbitrability of smart contract disputes in India. Understanding Smart Contracts A smart contract is an agreement between two or more parties in the form of computer codes which automatically executes either a portion or the entire contract between parties on the fulfilment of pre- determined parameters that have been added to the code. The execution of smart contracts happen on a blockchain network for which transaction fees referred to as “gas fees” are paid by the executing party. Since the idea of having smart contracts was to alleviate breach of contract, smart contracts are irreversible. In order to illustrate in a better way, a diagram with an example is being provided below: The diagram above showcases an example of a transaction of sale of goods by the manufacturer to the wholesaler using a smart contract. However, smart contracts in the practical sense tend to be more complex involving pre- determined parameters for aspects such as non- acceptance of delivery, delay in transportation, termination of contract and the like. Nature of Smart Contract Disputes Now that a basic idea of smart contract transactions along with an example has been discussed, it is important to discuss the nature and manner in which smart contract disputes may arise. Contrary to the general perception, although smart contracts self- execute on pre- determined parameters, the scope of breach of contract is quite high. Disputes may arise on account of error in the code leading to non- execution, change in law resulting in illegality of contract, defect in goods or deficiency in service and many more similar reasons. Due to this, it is necessary for an adequate dispute resolution mechanism to be used for resolving smart contract disputes. Arbitration is the most-suited dispute resolution method for smart contract disputes since blockchain arbitration as well as standard arbitration methods already exist and are being used in few jurisdictions to solve disputes arising out of smart contracts. On perusal of Diagram 2 above, it is easily inferable that blockchain arbitrations are conducted on the blockchain itself where adjudicators referred to as “jurors” arrive at a decision on the basis of majority voting and where the enforcement of the award takes place on the blockchain itself. The enforcement of the award on the blockchain itself is achieved by ensuring that the parties deposit an escrow amount on- chain. Blockchain arbitrations may not be legally recognized in several jurisdictions and are often viewed as reducing party autonomy and snatching the expert element away from arbitrations since majority voting by jurors is the criteria for reaching at a decision. Standard off- chain arbitration is the traditional arbitration process where the dispute is resolved before an Arbitration Tribunal (which can either be a physical or a virtual Arbitral Tribunal) by Arbitrator(s) appointed by the parties and the enforcement of the Arbitral Award is made by a Civil Court having jurisdiction. However, when it comes to smart contract disputes, even standard arbitration has its own set of issues such as the non- recognition of smart contracts as a valid contract in many jurisdictions and problems related to enforceability of an Arbitral Award solving a smart contract dispute. Identifying Legal Challenges from the Indian Perspective Essentials of Contract and the Consideration Conundrum In the Indian context, to determine the arbitrability of smart contract disputes, it is primarily necessary to examine if smart contracts can be treated as valid contracts. Section 10 of the Indian Contract Act, 1872 stipulates the essentials of a valid contract. On perusal of the Diagram above, it is easily understandable that the essentials of a valid contract under the Indian Contract Act, 1872 is that there must be parties competent to contract, a legitimate offer and acceptance, free consent of parties entering into the contract, lawful consideration, lawful object and the contract must not expressly be declared as void. In the Indian context, smart contracts can certainly have competent parties to contract, legitimate offer and acceptance, free consent of parties, lawful object and the contract would also not expressly be declared as void, but the challenge arises in the portion of meeting the requirement of lawful consideration. The colossal reason for the consideration involved in smart contract transactions not being treated as lawful is because of the use of cryptocurrency as consideration in smart contract transactions. Initially, the Reserve Bank of India had banned banks and financial institutions from dealing in cryptocurrencies, but this was subsequently reversed by the Supreme Court of India. Vide the Finance Act, 2022 direct tax on transfer of cryptocurrencies were introduced. However, this is more or less a temporary arrangement up till the introduction of the Central Bank Digital Currency which will impose a blanket ban on all other forms of cryptocurrencies and only legalize the Central Bank Digital Currency introduced by the Reserve Bank of India. For the present moment lack of express legalization of cryptocurrency in India exists but once the Central Bank Digital Currency is introduced, its use as consideration in smart contract transactions will be treated as “lawful consideration”. Until then, the consideration conundrum may continue because of manifold interpretations and lack of clarity. Impossibility of Stamping of Smart Contracts Under Indian law, there is an express requirement of every contract to be stamped as per the provisions of the Indian Stamp Act, 1899 read with the provisions of the State law for stamping enacted. Even though the Supreme Court of India has emphasized that although unstamped contracts are curable, but in the occasion of Arbitral Tribunals and Civil Courts coming across unstamped contracts, they have to impound such unstamped contracts and require parties to pay Stamp Duty. This may entirely be impossible in terms of smart contracts since smart contracts are executed on the blockchain itself and are intrinsically irreplicable, making them impossible for stamping as per the Indian Stamp Act, 1899 or as per the State stamping laws. Non-Recognition of Blockchain Arbitration Indian law does not recognize blockchain arbitrations because of the entire legal system having been created for accommodating dispute resolution of paper- based and written contracts. Furthermore, blockchain arbitrations may not involve oral hearings and may also not permit additional pleadings to be made, resulting in the violation of principles of natural justice. This is why, for the moment, the possibility of blockchain arbitration in the Indian context may be a far- fetched idea. Governing Law, Choice of Procedural Rules, Venue, Seat of Arbitration, Appointment and Qualifications of Arbitrators Traditional paper-based contracts and electronic contracts commonly have governing law, choice of procedural rules, venue of arbitration, legal seat of arbitration, appointment and qualification of arbitrators incorporated as a part of the contract itself. However, this may not be the case when it comes to smart contracts since parties may often opt for blockchain arbitration wherein the dispute is solved as well as enforced on the blockchain itself with the help of escrow deposit made at the time of initiation of the dispute and a voting “jury” system. In the Indian context, this may prove to be challenging since the entire mechanism of blockchain arbitration is not legally recognized. Power of Judicial Authority to Refer Parties to Arbitration Defeated on Procedural Ground Section 8 of the Arbitration and Conciliation Act, 1996 confers a judicial authority (including a Civil Court) to refer parties to arbitration where an application is made. However, a mandatory procedural condition imposed is that an original or duly certified copy of the arbitration agreement has to be furnished along with such application. This can prove to be an impediment when it comes to smart contracts since smart contracts are executed on the blockchain and intrinsically irreplicable and therefore, to be able to provide an original or duly certified copy of the arbitration agreement may not be possible unless and until an arbitration agreement was signed off-chain. Issues in Enforcement of Arbitration Award The above Diagram explicates the issues which currently exist in the enforcement of arbitration awards solving smart contract disputes in India. The first extant issue is that Article II of the New York Convention requires that a valid arbitration agreement needs to be in writing. Smart contracts can be in code as well as natural language form, but in case the smart contract is entirely in code, then it may not be treated as a valid arbitration agreement under the New York Convention. The second extant issue is that similarly, Section 7 of the Arbitration and Conciliation Act, 1996 also requires that an arbitration agreement needs to be in writing which may lead to non- recognition of smart contracts entirely in code. The third extant issue is that Section 47 of the Arbitration and Conciliation Act, 1996 requires that during enforcement of a foreign award, the original arbitration agreement or a duly certified copy of the original arbitration agreement has to be presented before the Civil Court. As pointed out, this is not possible in relation to smart contracts unless and until an arbitration agreement is entered into between the parties separately off- chain. The fourth extant issue is that in case an Arbitral Tribunal passes an Award directing certain remedial action to be taken on the blockchain itself, it is unclear if the Civil Court enforcing the Award has the power to order such remedial action to be undertaken on the blockchain to the blockchain network provider since the blockchain network provider is neither obligated by Indian law to do so, nor is the blockchain network provider a party to the smart contract. It is indeed true that the parties have to accept the terms and conditions (in the form of an electronic contract) of the blockchain network provider while availing their services, but that in itself would constitute a separate contract. Furthermore, Section 36 of the Arbitration and Conciliation Act, 1996 also stipulates that enforcement of Award has to be done as per the Code of Civil Procedure, 1908 as if it was a Decree passed by a Civil Court. For foreign awards, similar provisions exist under Sections 48 and 49 of the Arbitration and Conciliation Act, 1996. Due to these provisions, immense difficulty may arise for the portion of the Arbitration Award to be executed on- chain (on the blockchain) since there exists no mechanism permitting the enforcement of Award on the blockchain itself. Solving Legal Challenges in the Arbitrability of Smart Contract Disputes in India Now that several extant issues in the arbitrability of smart contract disputes have been discussed, it is necessary to solve such legal challenges under Indian law which are hampering the arbitrability of smart contract disputes in India. Due to the inherent nature and development of Indian jurisprudence, it may not be possible to legalize blockchain arbitration for the moment. However, this does not mean that parties in smart contract disputes should be left remediless. Therefore, this part of the article is dedicated towards explicating solutions and suggestions that can permit smart contract disputes to be solved under the current law of arbitration in India. Dealing with the Consideration Conundrum Section 23 of the Indian Contract Act, 1872 stipulates what considerations are lawful. In case a form of consideration is forbidden by law, by its nature defeats the provisions of any law, is fraudulent in nature, involves or implies injury to property or person of another or if it is deemed as immoral or opposed to public policy by a Court, then such form of consideration would be treated as unlawful. Cryptocurrency does not defeat the provisions of any existent Indian law, is not fraudulent in nature, does not imply injury to property or person of another and has not been deemed as immoral or opposed to public policy by a Court. Furthermore, for the moment, cryptocurrency is not expressly forbidden by law either, but it seems that Indian law is certainly heading towards that direction with the idea of the Central Bank Digital Currency. This would mean that in case parties enter into smart contracts with a choice of governing law as India, and the change in law forbidding cryptocurrencies except the Central Bank Digital Currency occurs, then parties would not be able to initiate arbitration since such contract would become void on account of illegal consideration under Section 23 read with Section 24 of the Indian Contract Act, 1872. Even if an arbitration is initiated and the change in law occurs after that, parties would still face tremendous difficulties in enforcing such arbitral awards since it would be challenged and may even be set- aside by Indian Courts for being in contravention to fundamental public policy of India under the Arbitration and Conciliation Act, 1996. Therefore, up till the introduction of the Central Bank Digital Currency (since the legalization of other forms of cryptocurrency seems to be highly unlikely) it would be on the more commercially viable side, for two Indian parties or even foreign parties with disputes in India arising out of smart contracts to choose a foreign seat of arbitration and a foreign governing law with a venue of arbitration as India in order to avoid any form of difficulties to initiating arbitrations or enforcing awards made for smart contract disputes. Solving the Issue of Stamping of Smart Contracts Since the provisions of the Indian Stamp Act, 1899 are based completely for traditional paper- based contracts, they are redundant when applied in the context of smart contracts. The need for solving the issue of stamping of smart contracts arises out of the fact that stamping entails the collection of Stamp Duty for the Government and would lead to Revenue loss in case robust provisions for stamping of smart contracts are not introduced. Furthermore, as pointed out above, the Supreme Court of India has laid down that Arbitral Tribunals and Civil Courts (during enforcement) are required to ensure that parties cure any defects of unstamped agreements by the payment of Stamp Duty and therefore, in spirit has affirmed the mandatory nature of stamping of contracts. Although the long-term goal should be to introduce a blockchain based stamping system, looking at the current ground realities, the Indian Government may be few years away from developing such a system. In order to ensure that stamping does not become an incurable defect for smart contracts, the e- stamping facility could come to the rescue. The buyer in the smart contract transaction or the seller (only if expressly agreed upon in the smart contract) can pay the necessary Stamp Duty using the e- stamping facility. However, in order for this to happen, the Indian Stamp Act, 1899 and its corresponding State stamping laws will have to specifically confer recognition of “instrument chargeable with duty” to smart contracts and also include them in the Schedule prescribing the Stamp Duty payable. Once this is done, the buyer or the seller (if specifically agreed upon in the contract) can pay the applicable Stamp Duty prescribed through the e- stamping facility. This way, even if it is found during arbitration proceedings or enforcement of award proceedings that Stamp Duty has not been paid, it will remain as a curable defect which can be rectified by the concerned parties. Solving Issues Pertaining to Governing Law, Choice of Procedural Rules, Venue, Seat of Arbitration, Appointment, Qualification of Arbitrators and Enforcement of Arbitration Awards As opposed to traditional paper- based contracts or even electronic contracts for that matter, aspects such as governing law, choice of procedural rules, venue, seat of arbitration, appointment of arbitrators and qualification of arbitrators may not be included in smart contracts as a matter of standard practice due to its reliance on blockchain arbitration that is not legally recognized in India. Considering that these aspects play a vital role in standard off- chain arbitrations, there are two ways in which parties to smart contracts can deal with the issue. The parties could opt to implement only the transactional portion through a smart contract code and have a natural language electronic contract or a natural language paper contract as an arbitration contract that will contain governing law, choice of procedural rules, venue of arbitration, seat of arbitration, appointment and qualification of arbitrators. This will enable parties to initiate arbitrations and enforce the arbitration award without any difficulty and parties can even freely choose between ad- hoc arbitrations or institutional arbitrations as per their requirements. Alternatively, the parties could include governing law, choice of procedural rules, venue of arbitration, seat of arbitration, appointment and qualification of arbitrators in the smart contract itself and permit the intervention of an Arbitral Tribunal acting as a blockchain oracle when a dispute arises. A blockchain oracle is an entity that connects the blockchain with external data sources allowing inputs and outputs from external sources to the blockchain as well as vice versa. In other words, it is the mechanism through which a blockchain can interact with external data sources. In order to explicate as to how an off- chain Arbitral Tribunal can act as a blockchain oracle, a diagram has been provided below: On perusal of the diagram above, the first step in the process of Arbitral Tribunal as a blockchain oracle is that the smart contract needs to be coded with predetermined parameters that would constitute a breach of contract. Without this, the possibility of automated initiation of arbitration would not be possible. This means the parties would have to agree in advance in respect of the factors that would constitute as a breach of contract. In case the breach of contract arises out of a technical issue in the blockchain itself or the smart contract, then the respective contracts of the parties with the blockchain network provider will have relevance and separate legal action will have to be taken by the aggrieved party against the blockchain network provider. The second step is that the notice for commencement of arbitration will have to be sent manually by the party initiating arbitration and this is extremely crucial since Section 21 of the Arbitration and Conciliation Act, 1996 stipulates that the commencement of arbitration would be deemed to be the date on which a Notice or request for arbitration is received by the responding party. However, since the provision begins with “unless otherwise agreed by the parties”, the parties can specifically agree that the date of commencement of arbitration should be the date on which the smart contract sends an automated email communication to the Arbitral institution or Arbitrators, as the case may be for appointment of an Arbitral Tribunal. Once the smart contract sends an automated email communication for constitution of the Arbitral Tribunal as per the number and qualifications of Arbitrators as agreed upon by the parties, the third step would be to conduct the arbitration proceedings off- chain as per the governing law, procedural rules at the seat and venue of arbitration agreed upon by the parties. Now, the pertinent question which would arise is what would be the ideal governing law, procedural rules, legal seat and venue of arbitration. Although there are no issues for parties to agree for the venue of arbitration in India, since Indian law is not completely equipped for arbitrating smart contract disputes, issues may arise for parties if they decide to choose Indian law as the governing law and India as the legal seat. More suitable governing laws and legal seats would be jurisdictions, who have at least some forms of legal recognition conferred to smart contracts. The United States of America, United Kingdom and Italy are jurisdictions which have laws in place for smart contracts and blockchain whereas jurisdictions such as Estonia and the United Arab Emirates seem to be moving towards such legal recognition. Parties could opt for the respective governing laws and legal seat based on their requirements and the intricacies of the impugned transactions. As far as procedural rules are concerned, the JAMS Rules Governing Disputes Arising Out of Smart Contracts and the United Kingdom Jurisdiction Taskforce Digital Dispute Resolution Rules are two of the most commonly known procedural rules for smart contract arbitrations. However, since the idea is to make Indian law a preferred legal seat and choice of law for parties to smart contract disputes, it is necessary that primarily, insertions in clause (3) of Section 7 of the Arbitration and Conciliation Act, 1996 have to be made. Under Section 7(3), a proviso could be added to state that natural language or even fully coded smart contracts should be treated as “agreements in writing” for better clarity. Furthermore, it is of utmost necessity that specific principal legislation on smart contracts is also legislated. A specific enactment for smart contracts is mainly necessary to ensure that Government authorities, Courts, Arbitral Tribunals and statutory auditors are able to seamlessly interact with the smart contracts on the blockchain network as oracles in order to carry out the verification of existence of smart contracts, to reduce the insurmountable difficulties to furnish smart contracts as evidence and also, to ensure that outcomes of disputes expressed in the form of Judgments, Decrees or Awards are reflected in the smart contract. Such principal legislation would also be necessary to assign legal definitions to terms such as “smart contract”, “blockchain” and the like. Introducing specific legislation for smart contracts would also help in solving the dilemma under Section 8 of the Arbitration and Conciliation Act, 1996 which mandatorily requires parties to furnish an original arbitration agreement or a duly certified copy of the arbitration agreement since then, a mechanism for Civil Courts to verify the existence of the smart contract would be made possible. Principal legislation on smart contracts would also have legislative competency since Entry 7 of the Concurrent List (List III) of Schedule VII of the Constitution of India stipulates concurrent powers of the Union of India as well as the States to legislate on matters pertaining to contracts including special form of contracts. Coming back to Diagram 5, the last part is where the Arbitration Award is passed by the Arbitral Tribunal and the portion of the outcome which cannot be enforced on the blockchain is enforced by a Civil Court as per Section 36 of the Arbitration and Conciliation Act, 1996 read with the provisions of the Code of Civil Procedure, 1908 and Sections 48 and 49 of the Arbitration and Conciliation Act, 1996 for foreign Awards. However, when a certain portion or the entire Award has to be executed on the blockchain itself through an inbound oracle, then the same Sections 36, 48 and 49 would create impediments since the express requirement is for enforcement to be done by a Civil Court. Therefore, in order to make Indian arbitration law compatible for smart contract disputes, it is necessary that provisions are introduced in the Arbitration and Conciliation Act, 1996 explicating enforcement of Awards on the blockchain alongside the standard route of enforcement through Civil Courts. Additionally, the requirements of furnishing the original arbitration agreement under Section 47 of the Arbitration and Conciliation Act, 1996 for enforcing a foreign award can also be solved by the principal legislation on smart contracts discussed earlier, coupled with necessary amendments to Sections 47 which will permit the Civil Court (in case of off- chain enforcement) to verify the existence of smart contract. Conclusion From the discussions made in the preceding paragraphs, it is manifestly clear that several qualms do exist in the arbitrability of smart contract disputes in India which can be eliminated by way of necessary insertions and amendments and as well as through introduction of specific principal legislation on smart contracts. However, till that time, in order for parties in smart contract disputes to not be rendered remediless, parties may choose to solve their disputes through arbitration choosing a legal seat and governing law of a jurisdiction with a recognized legal framework for smart contracts as discussed above, up till the time relevant changes are brought under Indian law to make smart contract disputes arbitrable in India.

Some legal concepts are general, while many are not general. The latter of the concepts are designed to shape the economic, administrative and sometimes, political priorities of the systems we live with. In this article, let us deconstruct the idea of “Soft law” to understand in basic terms, the ideation behind creating hybrid legal concepts and regulatory systems in the contemporary times we live in. The “Law” as Known Instead of getting on the usual understanding of legal theory, and its basics, from the positive law theory to other schools of thought, let us adopt a different method to look at “Law” as something different. When ideas are synthesised, solutions are manifested. In general, the process is not as oversimplified, self-explanatory and charted out as we assume it to be. Often it happens that legalising, in a positive or negative sense or maybe with an active/omissive intent, a plane of reference and incidence proliferates, multiplies and complicates/recalibrates with time. For example, the fundamental rules of contract jurisprudence, never change. Yet, as times have changed, the way contracts are understood, surely are not the same, even within a specific legal conundrum. Often the loopholes present and the binding value impugned upon the legal boundaries and extent defined in the documents, reflect the operability of such documents. This can even extend to key legal documents such as constitutions, statutes, rules, regulations, circulars, guidelines and ordinances. According to Prof. Roger Brownsword’s book “Law 3.0: Rules, Regulation and Technology“, the development of Law per se can be assessed, in a modern scheme of things, in 3 stages. An excerpt has been shared above to make a simple reflection. Law 1.0 (Coherentism): This generally implies the era of positive law where top-down approaches to law enforcement, administration and interpretation were existent. We can refer to the post-Industrial revolution times as well for a better context. Law 2.0(Regulatory-instrumentalist): The stage when Law 1.0 as we know, in fundamental terms, is disrupted due to technological interventions. Yet we see, that technology itself becomes a solution and we go into the times of regulatory-instrumentalism (in a generic sense). Although I can refer to the AI “age”, I would limit here by stating that the sophistication of technology development itself could shape our legal and administrative status quo, in as many effective ways possible. This is also the stage when the emergence of regulatory theory is clearly visible, in as many legal fields as possible. Law 3.0(Technocratic): This is the current stage, as of now, where public-private partnerships too shape the way regulators would act, and how laws would affect our day-to-day stakeholders. The potential of technology, regulators and the stakeholders creates the case of regulation, self-regulation, technology-oriented regulation and collaborative governance, together (there could be more or less similar means). Contrary to popular assertions that the US is a free market economy, the most sophisticated and important programmes, which were utilised by several MNCs and companies, are the gift of the United States Government’s agencies (internet for example). What is common to observe are the following: The significance of primary and secondary legal documents, which shape a polity per se, in terms of it being subject to constant change, is largely reduced by delegating their authoritative aspect, operationally, to rules, regulations, circulars and other kinds of by-laws. The role of regulatory theory becomes quite worth engaging and their proximity cum sensitivity to the incidents and circumstances related to the legal disputes or lacunae, is obviously going to be more. A new phenomenon becomes mainstream, which in the information age, has its own colors and forms: stakeholder-ism. It means that various non-state actors become important stakeholders with time in subtle ways, which include citizens, civil society, companies, start-ups and other relevant actors, for local, provincial, national, transnational, international and global settings as we know. These stakeholders have some subtle role in at least vouching to utilise the potential the proximate and sensitive purpose of regulators at the first place. The relevancy of such stakeholders, of course, has to hold some water, which is a long-term issue in the timeline of regulatory and collaborative governance. Even certain non-regulatory state actors gain relevance, and their approach and methods towards “public interest” are renewed with time, to seek clarity and optimisation towards achieving certain goals and maintaining the status quo, as we see. It depends if they affect the regulatory landscape. Yet, their role in shaping the economics behind the legal and administrative machineries, is intriguing. Let us imagine a few examples from the real world, in graphical terms to further understand the phenomenon. #1: RBI: Regulation & Accountability Bhargavi Zaveri discusses an important question on the Indian scenario, whether regulators require constitutional status in India or not. An excerpt from her article published in Business Standard explains quite much about regulatory theory per se. Securing the de jure and de facto is better achieved by asking for “fair contract terms” for these agencies under their governing law, aligning the incentives of the persons heading the regulatory agencies with public interest and requiring them to consistently explain their actions to the public. When an agency is required to explain its actions to the public or its representatives, it may seem like its independence is being compromised. On the contrary, transparency of conduct is one of the most effective ways of incentivising the agency to act in public interest. A classic example is that of the provisions built into the Reserve Bank of India Act in 2015, requiring the regular publication of the minutes of the monetary policy committee’s meetings, individual votes of each member and the requirement to explain to the government the failures in maintaining the inflation target. This is a powerful provision that simultaneously secures independence and accountability, as it would be hard to explain decisions and votes that do not align with public interest. #2: The EU Artificial Intelligence Act Thibault Schrepel weighs down on the EU Artificial Intelligence Act and explains the risk-related considerations involved for companies in the realm of regulation for Network Law Review. Like GDPR, the AI Act will apply to a large number of companies in Europe. There are two overinclusive conditions to fall within the scope of the regulation. First, the company must use an AI system such as defined by the European Commission. The definition of AI is very, very broad. AI includes machine learning systems, but also expert systems, “logic and knowledge-based approaches” and statistical calculations. Two, the company must operate in a risky sector such as defined in the regulation. The riskier the sector, the heavier the regulation. For example, companies operating in “high risk” areas such as health or education will have to submit their AI system to a national agency for validation, before the system is released, whenever it is modified, and every five years. #3: The Amendments to the IHR 2005 on Health Emergencies India, among a group of countries had supported the US-proposed amendments to the International Health Regulations, 2005 (especially Article 6 of the Regulations), with the condition that the right to reservation by states is accepted as an amendment as well. In the Committee A of the World Health Assembly, on the application of Article 6, the Article 62 of the regulations were amended. The objections by certain countries however to the US-proposed amendments stem from reshaping the World Health Organisation’s regulatory capacity per se, over the question of whether the over-centralisation of the WHO is a necessity or not. Dr Silvia Behrendt and Dr Amrei Müller review the amendments proposed by the United States of the International Health Regulations, 2005 for EJIL Talk!. This short review of the US proposals to amend the IHR would like to end with a call on members of the WHA to discuss and carefully consider the implications of the proposed amendments before endorsing and adopting them. Have technocratic, biomedical approaches, developed and implemented from the top down primarily through executive action, worked well in response to Covid-19, justifying a further extension and centralisation of global emergency powers at WHO? And, if WHO’s powers are extended in this way, is there a need to also answer the question quis custodiet ipsos custodes (who guards the guards?), and to thus set up mechanisms ensuring that WHO complies with its obligations under the IHR and its Constitution, as well as its responsibilities for human rights deriving from customary international human rights law? In these 3 different cases, of different magnitude, purpose and scope, we can observe how the subtleties of regulatory theory are tried and tested. Approaches and methods could be rigid, flexible or loose. Nevertheless, tried-and-tested subtleties sometimes might fail, or could work, practically. The transformation of regulatory theory globally, as a concept, is not to just pile up another set of bodies, but to rather innovate in shaping the legal and administrative apparatuses which affect our lives, in any way possible. There can be consequences not without context, of the laws and regulations we adopt and shape with time. Hence, as Hard Law (Law 1.0), the corpus of laws and regulations, shapes, the role of Soft Law becomes much important. The Technocracy of Soft Law Andrew T. Guzman and Timothy L. Meyer explain what Soft Law is in an article for Journal of Legal Analysis, Volume 2(1) [2010]: But to say that soft law rules are quasi-legal is simply to beg the question of what separates the quasi-legal from the nonlegal, on the one hand, and the legal, on the other hand. The discomfort of legal commentators with soft law stems in significant part from this ambiguity. Soft law is a residual category, defined in opposition to clearer categories rather than on its own terms. Thus, soft law is most commonly defined to include hortatory, rather than legally binding, obligations. The focus of this definition is usually on whether or not something that looks like a legal obligation in some ways (e.g., it is a written exchange of promises between states) nevertheless falls short of what is required to formally bind states. This definition, then, is a doctrinal one—things that fall short of international law are called soft law. […] In our view, for reasons that are explained more clearly later, soft law is best understood as a continuum, or spectrum, running between fully binding treaties and fully political positions. Viewed in this way, soft law is something that dims in importance as the commitments of states get weaker, eventually disappearing altogether. […] There are so many different forms of soft law that it is often more fruitful to think of it as a group of subjects, rather than a single one. Let us look at this reflection on Soft Law by Guzman and Meyer in graphical terms. Soft Law, according to this mind map representation, is a corpus of law, which is not so performative like laws. It does have a multi-disciplinary route of impact, and yet we can inspire from the same to shape our legal and administrative solutions, in any area, be it Alternative Dispute Resolution, International Law, and even Constitutional Policy. Soft Law has the potential to bring fields like economy, policy, environment sciences, technology, victimology, finance, data science and many other unbeknownst fields together with the legal field. It behaves like a Schrödinger’s Cat. To make things simple - In quantum mechanics, Schrödinger's cat is a “thought experiment that illustrates a paradox of quantum superposition. In the thought experiment, a hypothetical cat may be considered simultaneously both alive and dead as a result of its fate being linked to a random subatomic event that may or may not occur”. Similarly, Soft Law in reality, does not vanish or exist in absolute terms. It is a phenomenon where the repositories of legal thinking can always learn the best from the policy phenomenon, which are uncertain, unclear and hortatory. Lawmakers and courts can try to make Soft Law rigid, but the nuance always lies in the details. It is impossible to keep up with the rigidity, as Soft Law has to be fungible. Otherwise, the instrumentation which we call as “the” Soft Law, will automatically become a relic or existing part of the Hard Law conundrum, in the form of regulation mechanisms, laws, judgments or any other possible form. I will come up with more insights and analyses in future on various “kinds and forms” of Soft Law to further unpack the phenomenon in the language of graphics.

This is the first blog dedicated to the ideas my team and I developed at the Indian Society of Artificial Intelligence and Law in the last 2 years. Whenever we read “AI”, usually, this makes us think about sci-fi movies and robotics, and then the term artificial intelligence comes in the fray. Interestingly, we all know that artificial intelligence is not 1 technology but a family of technologies. What does this even mean? Now, let me show you a chart made by our team at ISAIL to understand, how to classify AI in its legal and industrial sense: You can view this chart, and find how scientific, legal and industrial classifications differ. Classification Of Artificial Intelligence For example, maybe, some legal aspects of facial recognition technology and unmanned aerial vehicles could be similar. I am not claiming there is a perfect alignment out there. Yet, these technologies in view of their purpose are completely different. So, even if they are like AI, in that pop culture sense, they still are different “species” of artificial intelligence. This is exactly how the idea came into being when my team at ISAIL and I were brainstorming on this issue. This can happen even with general technology systems, such as robots and analytics services. They might be considered like artificial intelligence, but their operational and manifesting value and purpose are completely different. Work robots in a factory which make things easier are not delivering real-time analytics insight and vice versa. Obviously you can mix or merge the features and have 1 system that might try to deliver both of these things. Still, that is very subjective and depends on each and every case, to decide. The ISAIL Classifications When the 2020 Handbook on AI and International Law came into being, I had proposed a 2-tier model on classifying artificial intelligence. I will now discuss the basis of the classification in brief and then explain how this classification can help us refine our legal understanding of not just AI technologies, but also other kinds of disruptive technologies. As the chart explains, there are two kinds of classifications: Concept, Entity and Industry (CEI) Subject, Object and Third Party (SOTP) The first classification has been depicted above, as how they work. As the word Concept is, many argue that AI is an abstract concept, and so it is important to keep ground open for subtle and important positions of policy intervention to redefine the legal understanding of technologies like artificial intelligence, since, like all disruptive technologies, AI is an ever-shaping technology. The word Entity has a special value in legal literature around the world. In legal terms, an entity may be implied to be a company, a natural person, an NGO or any other corpus, whose rights, duties, liabilities and responsibilities are possible to be defined, not just in principle, but also in the spirit of implementation. Generally, polities across the world provide two kinds of statuses - LEGAL and JURISTIC. Legal means that a law has been framed or a set of regulations have been adopted, which have given a clear-cut picture of how that thing will be reckoned in the legal system, and how will the State address that thing. Juristic means that the status is based on some un-codified intervention, maybe via a court order/judgment or the manner in which that thing has been interpreted by the administrative component of governments (bureaucrats). Here, any technology within the family of AI technologies, can be recognised legally, or given some ad hoc (specific) status. Sometimes, giving status not even equivalent to that of a human, a company or any other entity in that generic sense, is also considered giving some juristic status. Considering that AI technologies require proper auditing and policy interventions, the juristic status works sensibly well here. The Industry thing is quite simple. AI technologies differ for every industry’s needs, and as those needs are catered, the technology class becomes valuable for that industry. For example, algorithmic trading services cannot be used by a content creator to make AI-based animations. Similarly, facial recognition software, cannot do the work of voice recognition software literally. That itself is based on how classifications are made. Similarly, what facial recognition software can do for Instagram Reels or Tiktok, is not what the latter would do that exact way. Hence, based on a case-to-case use, this is a first principle understanding that industrial needs differentiate the classes of technologies within the artificial intelligence family. The second classification is also simple. That kind of classification is context-oriented. As per this excerpt, assume that X is a human being, Y is the “AI” system. Subject means that X, the human is being subjected to the environment of the AI system, in which it is sharing its data. Object means that the roles are reversed as Y, the AI system itself is subjected to the human environment, since the circumstances in which Y is being used, must be taken into fair account. Third Party is a case where Y acquires special features, which show that it has a sense of explainability and foresight as an AI system. Generally this is not a perfect scenario, but as an ideal case, we have kept it to analyse more developments in the world of technologies. This is a short graphic explainer of how AI can be classified. Now, there is a principle, which we use to classify. Feel free to read the 2020 Handbook on AI and International Law to know about that principle, in its Chapter 1.

In this article, I review a quite thought-provoking book authored by Balaji Srinivasan, the former CTO of Coinbase. This book, as proposes - is named as “The Network State”. Interested people can purchase or read the book for free. Now, I must say that the book is a propositional masterpiece, since it elucidates a wave of futurist thinking in pursuing international technology law, and the idea of sovereignty under this proposed construct of what Balaji calls a Network State. Let us decipher it by defining some ground rules. I will be deconstructing the basic, and not all advanced ideas, propositions and concepts of this book (I might do analyse those ideas in articles written later in time). I have used the method of testing the potential of the arguments and ideas discussed in the book, in the realms of law, international affairs and governance. This book review is a constructive cum imaginative take on the idea of what a Network State seems to be. I would like to express my hearty gratitude to Balaji’s revering of the Ramanujan Number. This excerpt from the first chapter, the Preamble, is rather powerful in its tone, and serene in its sensibilities: Why 1729? That’s the publisher of this work. It’s named after the Ramanujan number, which symbolizes for us the dark talent: all those people from the middle of nowhere, passed over by the establishment, with crazy-but-correct ideas, who could do great things if only given the opportunity. These are exactly the kinds of people who we expect will found startup societies and network states. The Idea: From a Nation-State to a Network State Now, anyone who has read pure international law or even jurisprudence could be aware of the idea of sovereignty. The word nation generally, in politics and law, refers to the idea of nationality, attributable to a human population. That national identity generally spans differently across places. In certain states, any one identity defines the nation, while in certain states, composite cultures and the conglomeration of various human identities shape the concept of a nation. Sometimes, a national identity is beyond all identities assumed or inherited by an individual/community. Even the concept of self-determination in international law, was produced considering the trends in the so-called rules-based international order as we know. Now, Balaji explains what is a nation-state, which anyone would be referring to the common and obvious features of a nation-state. If we remember the idea of a social contract, we know that a nation state is comprised of - (a) people; (b) territory; (c) government; and (d) sovereignty (or sovereign will). A country may state that it has all the first 3 components, and yet, in practical terms if it cannot exercise its so-called sovereignty, even under the Purposes and Principles of the Charter of the United Nations (assuming they aim a UN state membership) - perhaps it is not sovereign (in an ideal scenario). Although scholars and professionals of international law are aware that sovereignty has to be agreed upon by a set of countries. In some cases, maybe a single country’s recognition could have some value, if not absolute merit in the international legal system. This quite explains how we look at the international rules-based system. Now, Balaji explains the idea of a Network State by two definitions - one being simple, and the other being more descriptive, rather cryptic a little. Let us address both of the definitions. #1: The Simple Definition A network state is a highly aligned online community with a capacity for collective action that crowdfunds territory around the world and eventually gains diplomatic recognition from pre-existing states. #2: The Complicated Definition A network state is a social network with a moral innovation, a sense of national consciousness, a recognized founder, a capacity for collective action, an in-person level of civility, an integrated cryptocurrency, a consensual government limited by a social smart contract, an archipelago of crowdfunded physical territories, a virtual capital, and an on-chain census that proves a large enough population, income, and real-estate footprint to attain a measure of diplomatic recognition. The first definition (#1) is a simple explanation that an online community which mobilises for collective efforts, crowdfunding the territorial dispositions attached to the online community - across the world - is a network state. If we however look at the second definition (#2) - we get a larger and interesting picture of the idea, where Balaji tries to propose that this “online community” becomes a network having 2 important characteristics - a sense of moral innovation (which reminds me of the theological and epistemological roots of liberalism) and assuming some sort of consciousness, which is national (as we know, nation=people in obvious ways). The idea of in-person civility, from a management perspective, fascinates me a lot, because it could be related to the ethics that drives a network state. Now, if I try to relate this with my ideas on Soft Law, I can say that the idea of self-regulation and introspecting into the ethics and values which shape a Network State, has been given enough focus in the definition. Start-up Societies as Network States We are aware of the generic, neoliberal understanding of the moral and ethical basics behind the genesis of the culture of entrepreneurship. In fact, as the book suggests, a network state is a startup society, with a sense of moral innovation, national consciousness and in-person civility, driving a consensual government, which automatically, does not get the diplomatic recognition of a Network State. Balaji also introduces readers with the idea of network unions and archipelagos. He proposes that like startups take time, to become unicorns and then public companies, even startup societies will take time become a network state. On trust, national consciousness and in-person civility, this statement by Balaji is worth noticing: High trust in turn comes from alignment towards a collective purpose and a sense of national consciousness. In the next sections, I analyse the book’s basic ideas, esp. from Chapter 5 - from law, international affairs and governance perspectives. On International Law: Return of Terra Nullius and Terra Incognita This is an excerpt from the Chapter 5 of the book explaining how terra incognita and terra nullius return. Balaji gives a simple proposition that a Network State System assumes many things present on the internet, will eventually become invisible to other subnetworks. It means that the any subordinate component or thing, within the network itself, becomes invisible, eventually. That may be an ordinary tendency to see things, so it does makes real sense why terra incognita could return. The return of terra nullius is nevertheless, more interesting to look forward. Like in public international law, we assume unclaimed physical territories as terra nullius, in the case of even a network state, we can assume that there are so many unclaimed assets, items, identities and indicators, which he covers under the term called the “unclaimed digital territory”. My view is that terra incognita will only increase as more sophisticated technology infrastructure is built with time, which is not just protectionist, but also interventionist. In both of these strands of technology design thinking, if the idea of a Network State becomes a reality, it could be possible that this could go further deeper, in a spiral. As far as terra nullius is concerned, I have some doubts as to why should it work, because what assets become important, may or may not dilute as the internet and the cyberspace transforms with me. Discoveries and innovation has emerged from mere telecommunication devices to the unusual emergence of the internet of bodies (derived from the internet of things), for example. In both the cases, we will see how things are considered horizontal and vertical, subordinately, or insubordinately. The book covers some interesting aspects of economy, governance and control. For example, Balaji rightly points out how real-time national governments can sometimes act as digital governments. Examples range from censorship to geoblocking and access controls of applications like Google, Twitter and others as well, in some cases. As we anticipate the discussion of digital territories, let us ponder upon how the process of diplomatic recognition in a postulated fashion has been covered by the author, which fascinates me. Balaji explains what happens if a Network State in proposition does not have any diplomatic recognition. Here is excerpt from Chapter 5: Another excerpt however must be taken into context, from the same chapter, which is provided as follows: It is understandable that Balaji has taken a reasonable example of cryptography to justify and make his case for diplomatic recognition and other forms of crystallisation to a Network State. This seems to expand the potential of distributed ledger by according private keys to users having exclusive access to their private keys. The Network State in a Multipolar World Order Interestingly, the work even if could be assumed to be utopian to be futurist, has some roots in pragmatism and optimism. Balaji has covered interesting examples of global and Western history, and the present conditions. For example, here is an excerpt from the beginning of Chapter 3 where he explains three billion-people led capitals, which are assumed to be quite significant in power and influence: As the excerpt is self-explanatory, this kind of a characterisation, is a quite normal premise for any proponent to make per se. The one central aspect to all of these three groups or centres of power is that capitalism retains itself as the dominant economic ideology, in the matters of governance and human life. The author’s illustration of all the three examples, make genuine sense. The explanation, interestingly is available within the same chapter with 3 reasons stated, in this excerpt: The third reason is a quite generic one meaning that uncertainty always eclipses over realities of the present. The second reason, from a policy aspect, is eventful, based on the assumption that the US is on a decline, and thus, is event-centric, which might be a case to revisit how Network States can be achieved. And yet, the author comes up with a better reason - the first one - in which he relates to the statements given by India’s External Affairs Minister, Dr S Jaishankar. Balaji thus relates to the assumptions that Eurocentrism, the primal force of modernity and technological revolutions in these centuries, would not remain the same - and that those same forces of technology, are not under any state or empire’s monopoly, which is practically true. The author is trying to explain that while big powers, like China and the United States (earlier it was the Soviet Union and the US), aim to create the situation of bipolarity/unipolarity in the realpolitik, thereby affecting the system of international law and the rules-based order, multi-polarity is what countries, individuals and groups demand for, because they too, like the supporters of Pax Bitcoinica reasonably wish for. It helps various actors to assume their own volition to steer their world, in specifics and general, wherever they go, howsoever flawed it might be. I have also covered Balaji’s proposition of a non-aligned India-Israel partnership, which is cryptocurrency-centric, based on a Twitter thread from his account in the final section of this review. From a perspective of structural and liberal thinking, it seems that Balaji’s understanding of a Network State, is way refined that the ideals of the Westphalian era, and even of the times, when the United Nations was formed. As international law becomes digital, the perspective this book offers, is a treat to read, for law students & professionals and even the scholars of public policy. Here is an excerpt on the multipolar nature of the global order, explained by Dr S Jaishankar from his recent book, The India Way: Strategies for an Uncertain World (2021), Chapter 3: Final Comments and Some Ideas My final comments begin with analysing a Twitter Thread in which Balaji proposes a non-aligned way integrating BTC/Web3. This is the opening tweet for reference. Although, the non-aligned movement has largely shaped India’s international legal perspectives, we can see that Balaji explains why should India lead a decentralised approach to technology autonomy and sovereignty. Here is an excerpt from the thread to refer: Looking at the main components of this book (as I will be covering more perspectives in future articles), I must state that the book, is particularly, strong in its understanding, and has a much clear approach towards technology governance, and I wish that this work, and its legal ideas are scrutinised effectively. Ideas like integrating Linux with the Law of the Sea, itself, has its own waters to be tested in. They seem to be more adaptive, and cyclic, than being reductionist, which could, in reality, enrich the international law scholarship, beyond postmodern analyses. It would also help multilateral institutions gain some relevance, if we take the epistemic undertaking of the technology law theories related to startup societies and network states, in general.