Toward accountable human-centered AI: rationale and promising directions

独创性 计算机科学 人工智能 对抗制 价值(数学) 政治 脆弱性(计算) 数据科学 工程伦理学 管理科学 政治学 计算机安全 工程类 法学 机器学习 创造力
作者
Junaid Qadir,Mohammad Qamar Islam,Ala Al‐Fuqaha
出处
期刊:Journal of Information, Communication and Ethics in Society [Emerald Publishing Limited]
卷期号:20 (2): 329-342 被引量:35
标识
DOI:10.1108/jices-06-2021-0059
摘要

Purpose Along with the various beneficial uses of artificial intelligence (AI), there are various unsavory concomitants including the inscrutability of AI tools (and the opaqueness of their mechanisms), the fragility of AI models under adversarial settings, the vulnerability of AI models to bias throughout their pipeline, the high planetary cost of running large AI models and the emergence of exploitative surveillance capitalism-based economic logic built on AI technology. This study aims to document these harms of AI technology and study how these technologies and their developers and users can be made more accountable. Design/methodology/approach Due to the nature of the problem, a holistic, multi-pronged approach is required to understand and counter these potential harms. This paper identifies the rationale for urgently focusing on human-centered AI and provide an outlook of promising directions including technical proposals. Findings AI has the potential to benefit the entire society, but there remains an increased risk for vulnerable segments of society. This paper provides a general survey of the various approaches proposed in the literature to make AI technology more accountable. This paper reports that the development of ethical accountable AI design requires the confluence and collaboration of many fields (ethical, philosophical, legal, political and technical) and that lack of diversity is a problem plaguing the state of the art in AI. Originality/value This paper provides a timely synthesis of the various technosocial proposals in the literature spanning technical areas such as interpretable and explainable AI; algorithmic auditability; as well as policy-making challenges and efforts that can operationalize ethical AI and help in making AI accountable. This paper also identifies and shares promising future directions of research.
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