The UK Competition and Markets Authority (CMA) recently published its initial Report on AI Foundation Models (the FM Report), which sets out the CMA’s early views on how foundation models (FMs) are developed and deployed as well as potential future regulatory interventions.
FMs are systems that are trained on vast amounts of data and are then applied to generate an output such as text, images, video, audio, or even physical output through robotics.
The FM Report identifies the following potential concerns, among others: (1) FM developers with market power dominating downstream markets and preventing downstream businesses without FMs from adequately integrating with and benefiting from FMs; and (2) FM developers being denied key resources needed to compete (e.g., computational resources). Increased UK merger control and antitrust enforcement in markets involving FMs is more likely following the FM Report.
For more information on artificial intelligence (AI) regulation in the United Kingdom and on the UK Digital Markets, Competition and Consumers (DMCC) Bill, which will further empower the CMA in this space, please refer to our previous publications.
In the European Union (EU), draft regulation of AI, including certain compliance and risk management measures, is currently going through the legislative process (the EU AI Act). For more information on the EU AI Act, please refer to our previous publications.
FMs are machine learning models, i.e., systems or combinations of systems that are trained on vast amounts of data and can be adapted to operate on a wide range of tasks and operations, including conversational and text processing, creating realistic images from natural language descriptions, summarizing information, and answering complex questions, among other features.
FMs are deployed in user-facing applications across a variety of industries including social media, productivity software, search functions, legal, healthcare, and robotics.
Approximately 160 FMs have been developed by firms ranging from established technology firms to new AI companies.
The FM Report discusses the following key features of competition in FMs and the related concerns:
Entrenched Market Power and Downstream Availability of FMs
The CMA is concerned that FMs may be used to entrench market power in downstream or adjacent markets, potentially allowing firms to leverage that market power to unfairly disadvantage rivals and reduce competition in those markets or related markets, e.g., through anticompetitive tying or bundling of FM products and services.
Access to Proprietary Data
The increased use of proprietary data to develop FMs could disadvantage smaller firms seeking to launch or expand their FMs. Currently, developers have two options for sourcing data to develop FMs: (1) utilize data that they already own or (2) purchase data from third-party providers. One potential future challenge for FM developers that do not already have access to relevant proprietary data is added costs should proprietary data become a requirement for improving FM performance.
The FM Report noted that ensuring reasonable access to such data is likely to be essential for preventing established tech companies from blocking new entrants from launching their FMs or expanding their FM capabilities and presence.
Access to Computing Power
Access to computing power is integral for FM development as there is a correlation between scale and performance of FMs. Smaller developers may be negatively impacted should they not have sufficient resources or partnerships to increase FM model scale, while larger players stand to gain from this aspect of FMs. The CMA has stated that ensuring access to computing power on fair commercial terms will likely be important to ensuring effective competition.
First- and Early-Mover Advantages
First-mover or early-mover advantages might negatively impact the development of certain FMs. For example, the FM Report notes that competition may be restricted if established tech companies are the only ones that can access sufficient funding, technical expertise, resources, economics of scope and scale, and feedback data. Furthermore, established tech companies are likely to benefit from existing customer bases, which could prevent new competitors from launching FMs.
Open-Source FMs
Open-source FMs are FMs that are freely shared and can be used at no cost, subject to their licenses (which may prohibit commercial use). The FM Report takes the position that open-source models promote innovation, enabling more developers to improve existing FMs and develop new ones.
The CMA cautioned that incentives to maintain open-source FMs are likely to be affected by monetization and increased costs associated with computing power. Restricted access to key inputs could therefore promote the more widespread use of closed-source FMs of larger technology companies, which may ultimately harm competition.
Economies of Scope
The FM Report suggests that economies of scope related to costs could present a significant advantage to incumbents that may benefit from the ability to spread high development costs across a more expansive range of FM services. This could negatively impact new entrants that may only be active initially in providing a smaller number of FM services.
Barriers to Switching
The CMA highlights that switching between different FMs could prove difficult for consumers if individual preferences (e.g., an FM virtual assistant that can mimic a consumer’s writing style) were lost should they switch. The CMA may be particularly concerned if there were “artificial” switching costs that arise purely due to product design decisions taken by providers primarily for the purpose of weakening competition, and may focus its enforcement on such “artificial” barriers to switching.
To ensure competition in the development and deployment of FMs, the CMA proposes several principles to assist FM development and deployment:
The CMA notes that these principles are not exhaustive and will be updated as its consultation continues. The FM Report highlights several nonexhaustive factors that could undermine the proposed principles such as anticompetitive behavior by large players, mergers and acquisitions (M&A) activity triggering a substantial lessening of competition, switching restrictions on business users between FM providers, and consumer misinformation. Future UK AI regulation and enforcement will likely seek to implement these principles.
The CMA states that there is likely to be increased M&A enforcement within the markets involving FMs as certain transactions could undermine the principles proposed by the CMA. The FM Report flagged that, while efficiencies can arise from certain transactions, the CMA is encouraging businesses in this space to notify transactions that may meet the CMA’s jurisdictional thresholds.
The CMA has wide discretion to review transactions under the “share of supply test,” pursuant to which the CMA may review transactions wherein the merging parties overlap in the supply of a good or service of any reasonable description in the UK and where their combined share of supply exceeds 25%. Importantly, the CMA can use a wide range of metrics in applying this test, and has even reviewed transactions in which the target had no UK turnover.
Following the FM Report, the risk of the CMA reviewing FM mergers, imposing remedies, and even blocking such transactions is heightened.
CMA merger control enforcement is distinct from and in addition to national security reviews by the UK government of transactions involving UK AI companies under the National Security and Investment Act 2021.
Following the FM Report, increased competition enforcement in markets involving FMs is probable. FM developers with strong market positions should regularly review their business practices to ensure that they comply with the rules prohibiting abuses of market power.
Examples of potentially problematic conduct could include (1) FM developers self-preferencing (e.g., generating responses that promote other products or services offered by the developer); (2) large, vertically integrated technology companies that develop FMs denying “key inputs” to smaller developers (such as computing power or data) with a view to excluding them from the market; and (3) any tying and bundling strategies.
The CMA may also focus on barriers to switching and questions of data portability and transparency in reviewing markets that involve FMs.
The CMA announced that it has commenced a “significant programme of engagement” that will take place across the United Kingdom, United States, and elsewhere in the coming months. The CMA will seek a range of views from consumer groups and civil society representatives, leading FM developers, and major deployers of FMs, among other stakeholders. The CMA intends to publish an update on its thinking and proposed principles in early 2024.
Such next steps for the CMA align with the current drive in the UK for an AI regulation roadmap, which was recently cited in the White Paper published earlier in 2023. Under the White Paper, the UK government will remain engaged in ongoing AI market research over the coming year and beyond. This will see regulators encouraged to publish guidance in this space, an additional CMA report on FMs, and the impact of AI is anticipated in this regard.
Morgan Lewis remains committed to staying abreast of these developments and supporting our clients in navigating the evolving legal landscape surrounding AI foundation models. Morgan Lewis will continue to provide legal advice, risk assessment, compliance support, representation in investigations, and strategic guidance in response to opportunities, risks, and challenges posed by AI.
If you have any questions or would like more information on the issues discussed in this LawFlash, please contact any of the following: