Artificial intelligence and consumer manipulations: from consumer's counter algorithms to firm's self-regulation tools

Abstract

The growing use of artificial intelligence (A.I.) algorithms in businesses raises regulators' concerns about consumer protection. While pricing and recommendation algorithms have undeniable consumer-friendly effects, they can also be detrimental to them through, for instance, the implementation of dark patterns. These correspond to algorithms aiming to alter consumers' freedom of choice or manipulate their decisions. While the latter is hardly new, A.I. offers significant possibilities for enhancing them, altering consumers' freedom of choice and manipulating their decisions. Consumer protection comes up against several pitfalls. Sanctioning manipulation is even more difficult because the damage may be diffuse and not easy to detect. Symmetrically, both ex-ante regulation and requirements for algorithmic transparency may be insufficient, if not counterproductive. On the one hand, possible solutions can be found in counter-algorithms that consumers can use. On the other hand, in the development of a compliance logic and, more particularly, in tools that allow companies to self-assess the risks induced by their algorithms. Such an approach echoes the one developed in corporate social and environmental responsibility. This contribution shows how self-regulatory and compliance schemes used in these areas can inspire regulatory schemes for addressing the ethical risks of restricting and manipulating consumer choice.

Dark sides of artificial intelligence: The dangers of automated decision‐making in search engine advertising

“…de Marcellis‐Warin et al (2022) argue that artificial automated decision‐making reduces the available and viable options. These systems thus bias the way users decide on alternative solutions, leading to unbalanced transaction processing (de Marcellis‐Warin et al, 2022). The same applies to Google's auction process.…”

“…In automated sales contexts, algorithmic decisions could result in special offers that skim off vendors' economic surplus to increase automated platforms' revenue. Naturally, such automated behavior also constrains users' decision space (de Marcellis‐Warin et al, 2022). Furthermore, consumers fear that algorithms manipulate their decisions and increase individual prices based on their personal characteristics (Calo, 2014).…”

Managing the race to the moon: Global policy and governance in Artificial Intelligence regulation—A contemporary overview and an analysis of socioeconomic consequences

“…However, it is important to recognize that while self-regulation is beneficial, it should not be seen as a substitute for comprehensive legal regulations. Instead, it should complement future laws by laying the groundwork for responsible AI development and use, ensuring that when regulations are enacted, they are informed by the practical experiences and ethical considerations of those at the forefront of AI technology [30,45].…”

Research on the Regulation of Algorithmic Price Discrimination Behaviour of E-Commerce Platform Based on Tripartite Evolutionary Game

“…However, e-commerce platforms have the advantage of asymmetric data information [35] and opaque algorithms [36]. Meanwhile, the government's single-party regulatory capacity is limited [37], makes it difficult to effectively monitor and regulate their algorithmic price discrimination behaviours [38]. As actual purchasers of products and services, consumers are more price-sensitive [39], and consumers, as stakeholders, can use their social graph radiation to amplify perceived unfair pricing information and compete with algorithmic price discrimination [40].…”