Ethics of AI: A Systematic Literature Review of Principles and Challenges
Ethics of AI: A Systematic Literature Review of Principles and Challenges
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人工智能伦理：原则和挑战的系统文献综述
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
M. Akbar
中科院分区：
文献类型：
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作者：
A. Khan;Sher Badshah;Peng Liang;Bilal Khan;M. Waseem;Mahmood Niazi;M. Akbar
人工智能的伦理成为政策制定者和学术研究人员感兴趣的全球话题。在过去的几年里，各种研究组织、律师、智囊团和监管机构都参与了制定人工智能伦理准则和原则的工作。然而，对这些原则的含义仍有争议。我们进行了一项系统性文献综述（SLR）研究，以调查对人工智能原则重要性的共识，并确定可能对人工智能伦理原则的采用产生负面影响的挑战性因素。结果表明，全球收敛集包括22个伦理原则和15个挑战。透明度、隐私、问责制和公平被认为是最常见的人工智能道德原则。同样，缺乏道德知识和模糊的原则被认为是考虑人工智能道德的重大挑战。这项研究的结果是提出一个成熟度模型的初步投入，该模型评估人工智能系统的道德能力，并为进一步改进提供最佳实践。
Ethics in AI becomes a global topic of interest for both policymakers and academic researchers. In the last few years, various research organizations, lawyers, think tankers, and regulatory bodies get involved in developing AI ethics guidelines and principles. However, there is still debate about the implications of these principles. We conducted a systematic literature review (SLR) study to investigate the agreement on the significance of AI principles and identify the challenging factors that could negatively impact the adoption of AI ethics principles. The results reveal that the global convergence set consists of 22 ethical principles and 15 challenges. Transparency, privacy, accountability and fairness are identified as the most common AI ethics principles. Similarly, lack of ethical knowledge and vague principles are reported as the significant challenges for considering ethics in AI. The findings of this study are the preliminary inputs for proposing a maturity model that assesses the ethical capabilities of AI systems and provides best practices for further improvements.