Record summary
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Risk profile
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"Fig 3 shows that technological, data, and analytical AI risks are characterised by the loss of control over AI systems, whereby in particular the autonomous decision and its consequences are classified as risk factors since they are not subject to human influence (Boyd & Wilson, 2017; Scherer, 2016; Wirtz et al., 2019). Programming errors in algorithms due to the lack of expert knowledge or to the increasing complexity and black-box character of AI systems may also lead to undesired AI results (Boyd & Wilson, 2017; Danaher et al., 2017). In addition, a lack of data, poor data quality, and biases in training data are another source of malfunction and negative consequences of AI (Dwivedi et al., 2019; Wirtz et al., 2019)."
Suggested mitigations
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Source
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Included resource
Governance of artificial intelligence: A risk and guideline-based integrative framework
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.