The increasing prevalence of artificial intelligence in competition law presents numerous new challenges that the current legislative framework seems not to address effectively. Traditional practices are evolving, bringing potential risks of new violations. One major issue is the use of pricing algorithms, which can lead to tacit collusion by allowing coordination without formal agreements, while also facilitating platforms in favoring their own products. The biggest problem with applying antitrust legislation to algorithms is that it can only be applied if it can be proven that the algorithms are capable of achieving and enforcing a joint policy through a certain form of "consent of wills". A greater difficulty arises with self-learning algorithms, which allow business decisions to be made by a computer program rather than a human, enabling companies to avoid creating any structure that a regulator might consider collusion. The use of pricing algorithms also presents numerous complex challenges in terms of corporate responsibility for the anticompetitive behavior of algorithms. Therefore, regulating pricing algorithms is crucial for ensuring transparency and sanctioning violations. However, the positive effects of algorithm use must not be overlooked in its design and implementation. Given the potential dangers and the many concerns that are rightly raised in the case of excessive regulation of pricing algorithms, it will therefore be crucial in the future to examine the problem comprehensively and to find an optimal solution that takes into account both the dangers and the competition law benefits of using pricing algorithms.
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