The optimisation of sales practices in consumer markets through machine learning not only harbours the potential to better match consumer preferences with products, but also risks to facilitate the exploitation of consumer weaknesses discovered via data analysis. More specifically, recent technological advances have brought us to the edge of mind-reading technologies, which automatically analyse mental states and adapt offers accordingly, in potentially manipulative ways. This article shows that, in market contexts, the challenges of manipulation by algorithm necessitate an integrated understanding of unfair commercial practice, data protection, and privacy law. It maps the interactions between these contiguous yet distinct fields of law, and draws on economics and computer science to develop a novel framework to deal with algorithmic influence. Furthermore, it critically discusses the Commission proposals for the Digital Services Act and the Artificial Intelligence Act, and suggests to complement them with more broadly applicable measures to mitigate algorithmic manipulation.

中文翻译：

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通过算法进行操纵。探索不公平商业行为、数据保护和隐私法的三角关系

通过机器学习优化消费者市场的销售实践，不仅有可能更好地将消费者偏好与产品相匹配，而且还存在促进利用数据分析发现的消费者弱点的风险。更具体地说，最近的技术进步将我们带到了读心技术的边缘，这种技术可以自动分析心理状态并以潜在的操纵方式相应地调整报价。本文表明，在市场背景下，算法操纵的挑战需要对不公平商业实践、数据保护和隐私法的综合理解。它描绘了这些连续但不同的法律领域之间的相互作用，并利用经济学和计算机科学来开发一个新的框架来处理算法的影响。此外，它批判性地讨论了委员会关于《数字服务法》和《人工智能法》的提案，并建议用更广泛适用的措施来补充它们，以减轻算法操纵。