Accountable Artificial intelligence;
Human-centered AI;
AI ethics;
D O I:
10.1108/JICES-06-2021-0059
中图分类号:
B82 [伦理学(道德学)];
学科分类号:
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.
机构:
Univ Nat Resources & Life Sci Vienna, Dept Forest & Soil Sci, Human Ctr AI Lab, A-1190 Vienna, Austria
Univ Nat Resources & Life Sci Vienna, Dept Agrobiotechnol, Human Ctr AI Lab, A-3430 Tulln, Austria
Alberta Machine Intelligence Inst, xAI Lab, Edmonton, AB T6G 2E8, CanadaUniv Nat Resources & Life Sci Vienna, Dept Forest & Soil Sci, Human Ctr AI Lab, A-1190 Vienna, Austria
Holzinger, Andreas
Fister Jr, Iztok
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机构:
Univ Nat Resources & Life Sci Vienna, Dept Forest & Soil Sci, Human Ctr AI Lab, A-1190 Vienna, Austria
Univ Maribor, Fac Elect Engn & Comp Sci, Maribor 2000, SloveniaUniv Nat Resources & Life Sci Vienna, Dept Forest & Soil Sci, Human Ctr AI Lab, A-1190 Vienna, Austria
Fister Jr, Iztok
Fister Sr, Iztok
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机构:
Univ Maribor, Fac Elect Engn & Comp Sci, Maribor 2000, SloveniaUniv Nat Resources & Life Sci Vienna, Dept Forest & Soil Sci, Human Ctr AI Lab, A-1190 Vienna, Austria
Fister Sr, Iztok
Kaul, Hans-Peter
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机构:
Univ Nat Resources & Life Sci Vienna, Dept Crop Sci, A-3430 Tulln, AustriaUniv Nat Resources & Life Sci Vienna, Dept Forest & Soil Sci, Human Ctr AI Lab, A-1190 Vienna, Austria
Kaul, Hans-Peter
Asseng, Senthold
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机构:
Tech Univ Munich, Dept Life Sci Engn Chair Digital Agr, HEF World Agr Syst Ctr, Dept Life Sci Engn,Chair Digital Agr, D-85354 Freising Weihenstephan, GermanyUniv Nat Resources & Life Sci Vienna, Dept Forest & Soil Sci, Human Ctr AI Lab, A-1190 Vienna, Austria