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Rethinking Competition Policy to integrate AI

Artificial intelligence (AI) or commercial operations incorporating AI are upending worldwide industry norms and competition laws. Big data and artificial intelligence have helped propel Internet titans like Amazon, Google, and Meta to previously unheard-of heights of success. Algorithms are used in all of these businesses to deliver value to the end user. Although it's possible that engineers and developers build the AI's software engine to put the algorithms into practise, in the end, value is created through digital automation.

It is difficult to forecast how the recent wave of the AI growth has altered competitive dynamics. The incorporation of AI has created issues that need to be resolved as Indian politicians consider updating the country's current framework for competition law. Committee on Digital Competition Law (CDCL) has just commenced internally discussing the contours of the proposed framework to tackle the anti-competitive conduct of Big Tech. The panel is tasked with submitting a report on the need for an ex-ante regulatory mechanism for digital markets and suggesting a draft Digital Competition Act for India.

This makes it an appropriate time to also asses the adverse implications of AI in terms of competition law. These implications can be divided into three categories: using AI to carry out anti-competitive agreements or strategies; implementing specific anti-competitive strategies by AI without explicit human guidance; and using AI at the same time as a decline in competitive intensity without explicit evidence of anti-competitive agreements or strategies. Anti-competitive behaviour, or collusion, is when competing companies cooperate or reach an agreement to raise profits above the non-cooperative equilibrium.

Pricing Power: The widespread application of AI can foster circumstances that make collusive outcomes more predictable or profitable. For instance, freely accessible metrics that might be employed in AI applications include consumer data, competing offers, and market transactions. When there is a high degree of market transparency, collusion is more likely to occur since knowledge about competitor prices or transactions is easily accessible. In addition to these concerns, AI may increase competition in some markets.

In terms of how quickly organisations respond to market changes, how precisely they foresee and comprehend data, and how they use AI to develop better, more cheap products, for instance, AI may start to play a significant differentiating role amongst businesses. Profit-maximization algorithms might even stop collusive market behaviour depending on how they are constructed. This hypothetical instance of AI creating rivalry demonstrates how AI might also generate competition. The boundary between a company being competitive and abusing its market dominance is, however, very narrow. Powerful corporations may find it easier to utilise anti-competitive strategies such price discrimination or predatory pricing, which can drive out smaller competitors.

Businesses may use AI to assess the increasing amounts of demographic and consumer data, allowing them to set prices based not only on generic consumer groupings but, in some cases, also on a consumer's anticipated willingness to pay. This is referred to as tailored pricing.

Consumer Protection: It may be challenging to detect whether a corporation is engaging in abusive behaviour due to the intricacy of AI algorithms, which may make it challenging to enforce current competition rules. Globally, the evaluation of how AI will affect competitive dynamics by policymakers is still in its infancy and largely theoretical. By enabling new goods and services, more effective decision-making, and possibly even weakening collusive outcomes, AI has a strong pro-competitive potential. However, if AI causes markets to become predictable, transparent, or stagnant or if it promotes the use of strategies that eliminate rivals, there may be risks to competition.

In a broader sense, AI raises forth challenges that are difficult to resolve under competition law and will call on politicians and consumer protection agencies to take corrective action. Through careful merger control, market research to identify pro-competitive policies (particularly those helping consumer information and decision-making), advocacy, and collaboration with other regulators, the risks of anti-competitive behaviour can be minimised. The government will require technical resources and experience to appreciate how AI functions in markets and further legal measures may be required to handle the whole range of competition challenges.

In essence, it remains far too soon to tell if AI can deliver on its promise of enabling pro-competitive consumer advantages or harm competition. Undoubtedly, competition regulation will be crucial in managing the potential negative consequences of AI technology on consumers, smaller businesses, and the economy as a whole. Coordination between regulatory and policy disciplines will be necessary for this, as well as ensuring that regulators have the tools necessary to enforce competition law and that regulatory frameworks support innovative and competitive AI applications.




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