We are delighted to present IPLR-IG-003, a Feedback Report to the recently proposed Digital Competition Bill, 2024 & the complete report submitted by the Committee on Digital Competition Law, which was submitted to the Ministry Of Corporate Affairs, Government of India.
This feedback report was also possible, thanks to the support and efforts of Vaishnavi Singh, Shresh Narang and Krati Bhadouriya, Research Interns at the Indian Society of Artificial Intelligence and Law.
We express special thanks to the Distinguished Experts at the ISAIL Advisory Council for their insights, and Akash Manwani for his insights & support.
You can access the complete feedback report at https://vligta.app/product/draft-digital-competition-bill-2024-for-india-feedback-report-iplr-ig-003/
This report offers a feedback to the Digital Competition Bill, 2024, from Page 69 onwards, but also offers a proper breakdown of the whole CDCL Report, from the Stakeholder Consultations, to the DPDPA, Consumer Laws, and even the key international practices that may have inspired the current draft of the Bill.
A general reading suggests that the initial chapters of the Bill have a heavy inspiration from the Digital Markets Act of the European Union, but there is no doubt to concur that the Bill offers unique Indian approaches to digital competition law, especially in Sections 3, 4, 7 and 12-15.
We have also inferred some recommendations based on the aiact.in version 2 on aspects of how use of #artificialintelligence may promote anti-competitive practices on issues related to intellectual property and knowledge management.
Here are all points of feedback, summarised:
General Recommendations
Expand the definition of "non-public data" (Section 12): The current section covers data generated by business users and end-users. However, it should also explicitly include data generated by the platforms themselves through their operations, analytics, and user tracking mechanisms. This would prevent circumvention by claiming platform-generated data is not covered.
Enable data portability for platform-generated data: While Section 12 enables portability of user data, it should also mandate portability of inferred data, user profiles, and analytics generated by the platforms based on user activities. This levels the playing field for new entrants. If that’s not feasible within the mandate of CCI, perhaps the Ministry of Consumer Affairs must incorporate data portability guidelines, since this might become a latent consumer law issue.
Expand anti-steering to cover all marketing channels: Section 14 should prohibit restrictions on business users promoting through any channel (email, in-app notifications, etc.), not just direct communications with end-users.
Tighten the definition of "integral" products/services (Section 15): Clear objective criteria should define what constitutes an "integral" tied/bundled product to prevent over-broad interpretations that could undermine the provision's intent.
Incorporate a principle of Fair, Reasonable and Non-Discriminatory (FRAND) treatment: A general FRAND obligation could prevent discriminatory treatment of business users by dominant platforms across various practices.
Recommendations based on AIACT.IN V2
In this segment, we have offered a set of recommendations based on a draft of the proposed Artificial Intelligence (Development & Regulation) Act, 2023, Version 2 as proposed by the first author of this report.
The recommendations in this segment may be largely associated with any core digital services or SSDEs in which the involvement of AI technologies is deeply integrated or attributable.
Establish AI-specific Merger Control Guidelines: Develop specific guidelines or considerations for evaluating mergers and acquisitions involving companies with significant AI capabilities or data assets. These guidelines could address issues such as data concentration, algorithmic biases, and the potential for leveraging AI to foreclose competition or engage in self-preferencing practices.
Shared Sector-Neutral Standards: The Digital Competition Bill should consider adopting shared sector-neutral standards for AI systems, as mentioned in Section 16 of the AIACT.IN Version 2. This would promote interoperability and fair competition among AI-driven digital services.
Interoperability and Open Standards: The Digital Competition Bill should encourage the adoption of open standards and interoperability in AI systems deployed by Systemically Significant Digital Enterprises (SSDEs). This aligns with Section 16(5) of AIACT.IN v2, which promotes open source and interoperability in AI development. Fostering interoperability can lower entry barriers and promote competition in digital markets.
AI Explainability Obligations: Drawing from the AI Explainability Agreement mentioned in Section 10(1)(d) of AIACT.IN v2, the Digital Competition Bill could mandate SSDEs to provide clear explanations for the outputs of their AI systems. This can enhance transparency and accountability, allowing users to better understand how these systems impact competition.
Algorithmic Transparency: Drawing from the content provenance provisions in Section 17 of AIACT.IN v2, the Digital Competition Bill could require SSDEs to maintain records of the algorithms and data used to train their AI systems. This can aid in detecting algorithmic bias and anti-competitive practices.
Interoperability considerations for IP protections (Section 15): The AIACT.IN draft recognizes the need to balance IP protections for AI systems with promoting interoperability and preventing undue restrictions on access to data and knowledge assets. The Digital Competition Bill could similarly mandate that IP protections for dominant digital platforms should not unduly hinder interoperability or access to key data/knowledge assets needed for competition.
Sharing of AI-related knowledge assets (Section 8(8)): The AIACT.IN draft encourages sharing of datasets, models and algorithms through open source repositories, subject to IP rights. The Digital Competition Bill could similarly promote voluntary sharing of certain non-sensitive datasets and tools by dominant platforms to spur innovation, while respecting their legitimate IP interests.
IP implications of content provenance requirements (Section 17): The AIACT.IN draft's content provenance provisions, including watermarking of AI-generated content, have IP implications that need to be considered. Likewise, any content attribution or transparency measures in the Digital Competition Bill should be designed in a manner compatible with IP laws.
While the AIACT.IN Version 2 draft and the Digital Competition Bill have distinct objectives, selectively drawing upon the AI-specific IP and knowledge management provisions in the former could enrich and future-proof the competition framework for digital markets.
We hope the feedback report would be helpful for the Ministry of Corporate Affairs, Government of India and the Competition Commission of India. We express our heartfelt gratitude for the authors to write such an important paper on digital competition policy, with an Indian standpoint.
Should any considerations arise to discuss any of the feedback points, please feel free to reach out at vligta@indicpacific.com.