Thursday 4 February 2021

CMA's paper on algorithms & online platforms: comprehensive report on benefits and perils of AI regulation

The UK Competition and Market’s Authority recently published a report on the consequences of the online platforms’ use of algorithms (‘sequences of instructions to perform a computation or solve a problem’) for consumer protection and for competition (here). This report builds on the CMA’s 2018 paper on pricing algorithms (here). The report starts by highlighting that the increasing sophistication of algorithms usually means decreasing transparency. The CMA’s report acknowledges the benefits of algorithms to consumers, such as the possibility to save consumers’ time by offering them individualized recommendations. Additionally, algorithms benefit consumers by increasing efficiency, effectiveness, innovation and competition. However, the main goal of the report is to list (economic) harms caused to consumers as a result of algorithms.

The report highlights that big data, machine learning, and AI-based algorithms are at the core of major market players such as Google (e.g. their search algorithm) and Facebook (e.g. their news’ feed algorithm). The CMA also acknowledges that many of the harms discussed in this report are not new but were made more relevant by recent technological advances. Finally, the report acknowledges that the dangers brought by algorithmic regulation are even greater where it impacts consumers significantly (such as decisions about jobs, housing or credit).

The harms discussed in the report deal mainly with choice architecture and dark patterns (e.g. misleading scarcity messages on a given product or misleading rankings). Additionally, personalization is depicted as a particularly dangerous harm, since it cannot be easily identified and because it manipulates consumer choice without that being clear to consumers. Personalization is also worrying because it targets vulnerable consumers. In particular, the CMA is worried about possible discrimination as a result of personalization of offers, prices and other aspects.

Personalized pricing implies that firms charge different prices to different consumers according to what the firm (and their algorithms) think that the consumer is willing to pay. While this has some benefits – like lowering search costs for consumers, the CMA warns that consumers might lose trust in the market as a consequence of personalized pricing practices. While some personalized pricing techniques are well-known – such as offering coupons or charging lower prices to new customers, others are more opaque and harder to detect. Non-price related personalization is also described as potentially harmful, such as personalized search results rankings or personalized recommendation systems (e.g. what videos to show next). In particular, the CMA warns that these systems may lead to unhealthy overuse or addiction of certain services by consumers and to a fragmented understanding of reality and public discourse.

Additionally, the use of algorithms harms competition since it can exclude competitors (e.g. through platform preferencing, via ranking, of their own products). Through exclusionary practices, dominant firms can stop competitors from challenging their market position. A prominent example of this is that of Google displaying its own Google Shopping service in the general search results page more favorably than competitors that offer similar services. Finally, the CMA report zooms in on algorithmic collusion, or the use of algorithmic systems to sustain higher prices.

The report also highlights the obstacles brought by lack of transparency, particularly when it comes to platform oversight. The CMA warns that this lack of transparency and the misuse of algorithms may lead consumers to stop participating in digital markets (e.g. deleting social media apps). This justifies, in the CMA’s opinion, the regulators’ intervention. In particular, the CMA considers that regulators can provide guidance to businesses as to how to comply with the law or to elaborate standards for good practices. Overall, the report brings attention to the fact that many laws in place do not apply to algorithmic regulation, such as to discrimination in AI systems. Moreover, the CMA highlights that the application of consumer law to protect consumers against algorithmic discrimination is still an unexplored area.

The report ends with a call for further research on the harms caused by algorithmic regulation. The CMA suggests techniques to investigate these harms that do not depend on access to companies’ data and algorithms, such as enlisting consumers to act as ‘mystery shoppers’ or through crawling or scraping data from websites. The CMA also suggests specific investigation techniques when there is access to the code.

Overall, this is an extremely comprehensive report that not only explains the biggest consumer harms brought by AI regulation but also contains several practical examples, as well as concrete methodological suggestions for further research and for better enforcement. Definitely a recommended read for both academics and practionners alike.