The use of computational systems to make decisions with or without human involvement. These systems will take data as an input and produce a decision or recommendation. Where automated decision making is embodied in an actuated system or device (such as a driverless car) then the decisions are translated directly into automatic actions.
The EU’s GDPR has specific provisions for solely automated decision-making. This has been defined by the Article 29 Working Party as ‘the ability to make decisions by technological means without human involvement’. Human involvement in the decision-making is sufficient to prevent the application of Article 22 GDPR rights to information about the logic of the automated processing involved. However, the guidance quoted emphasises that such involvement must be meaningful, from a person with sufficient expertise and authority to overrule the algorithm if necessary.
Automated decision-making is also notable for providing a context for the much-contested right to an explanation under the GDPR, which has opened wider debates about explainable AI and whether such explanations help individuals safeguard their rights, or whether a more systemic approach towards accountability is required.
Further reading:
See also: RIGHT TO PRIVACY, TRANSPARENCY, US PRIVACY LAWS
Marabelli, M., Newell, S. and Handunge, V., 2021. The lifecycle of algorithmic decision-making systems: organizational choices and ethical challenges. The Journal of Strategic Information Systems, 30(3), 101683, https://doi.org/10.1016/j.jsis.2021.101683.
Selbst, A.D. and Powles, J. 2017. Meaningful information and the right to explanation. International Data Privacy Law, 7(4), 233–42, https://par.nsf.gov/servlets/purl/10074338.
Kaminski, M.E., Malgieri, G.,2021. Algorithmic impact assessments under the GDPR: producing multi-layered explanations. International Data Privacy Law, 11(2), 125–44, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3456224.
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Marabelli, M., Newell, S. and Handunge, V., 2021. The lifecycle of algorithmic decision-making systems: organizational choices and ethical challenges. The Journal of Strategic Information Systems, 30(3), 101683, https://doi.org/10.1016/j.jsis.2021.101683.
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Selbst, A.D. and Powles, J. 2017. Meaningful information and the right to explanation. International Data Privacy Law, 7(4), 233–42, https://par.nsf.gov/servlets/purl/10074338.
-
Kaminski, M.E., Malgieri, G.,2021. Algorithmic impact assessments under the GDPR: producing multi-layered explanations. International Data Privacy Law, 11(2), 125–44, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3456224.
