Algorithmic Discrimination and Privacy Protection

E. Falletti
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Abstract

Objective : emergence of digital technologies such as Artificial intelligence became a challenge for states across the world. It brought many risks of the violations of human rights, including right to privacy and the dignity of the person. That is why it is highly relevant to research in this area. That is why this article aims to analyse the role played by algorithms in discriminatory cases. It focuses on how algorithms may implement biased decisions using personal data. This analysis helps assess how the Artificial Intelligence Act proposal can regulate the matter to prevent the discriminatory effects of using algorithms. Methods : the methods used were empirical and comparative analysis. Comparative analysis allowed to compare regulation of and provisions of Artificial Intelligence Act proposal. Empirical analysis allowed to analyse existing cases that demonstrate us algorithmic discrimination. Results : the study’s results show that the Artificial Intelligence Act needs to be revised because it remains on a definitional level and needs to be sufficiently empirical. Author offers the ideas of how to improve it to make more empirical. Scientific novelty : the innovation granted by this contribution concerns the multidisciplinary study between discrimination, data protection and impact on empirical reality in the sphere of algorithmic discrimination and privacy protection. Practical significance : the beneficial impact of the article is to focus on the fact that algorithms obey instructions that are given based on the data that feeds them. Lacking abductive capabilities, algorithms merely act as obedient executors of the orders. Results of the research can be used as a basis for further research in this area as well as in law-making process.
算法歧视与隐私保护
目标:人工智能等数字技术的出现成为世界各国面临的挑战。它带来了侵犯人权的许多风险,包括隐私权和个人尊严。这就是为什么它与该领域的研究高度相关。这就是为什么本文旨在分析算法在歧视案件中所起的作用。它侧重于算法如何使用个人数据实现有偏见的决策。这一分析有助于评估《人工智能法案》提案如何规范这一问题,以防止使用算法的歧视性影响。方法:采用实证分析和比较分析相结合的方法。比较分析允许对人工智能法案提案的监管和规定进行比较。实证分析允许分析现有的案例,证明我们的算法歧视。结果:研究结果表明,人工智能法案需要修改,因为它仍然停留在定义层面,需要足够的经验。作者提出了改进的思路,使其更具经验性。科学新颖性:本贡献所授予的创新涉及歧视,数据保护和对算法歧视和隐私保护领域的经验现实影响之间的多学科研究。实际意义:本文的有益影响在于关注算法服从基于数据提供的指令这一事实。由于缺乏溯因能力,算法仅仅充当服从命令的执行者。研究结果可作为该领域进一步研究和立法过程的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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