Automated decision-making

Automated decision-making (ADM) involves the use of data, machines and algorithms to make decisions in a range of contexts, including public administration, business, health, education, law, employment, transport, media and entertainment, with varying degrees of human oversight or intervention. ADM involves large-scale data from a range of sources, such as databases, text, social media, sensors, images or speech, that is processed using various technologies including computer software, algorithms, machine learning, natural language processing, artificial intelligence, augmented intelligence and robotics. The increasing use of automated decision-making systems (ADMS) across a range of contexts presents many benefits and challenges to human society requiring consideration of the technical, legal, ethical, societal, educational, economic and health consequences.[1][2][3]

  1. ^ Marabelli, Marco; Newell, Sue; Handunge, Valerie (2021). "The lifecycle of algorithmic decision-making systems: Organizational choices and ethical challenges". Journal of Strategic Information Systems. 30 (1): 101683. doi:10.1016/j.jsis.2021.101683. Retrieved November 1, 2022.
  2. ^ Larus, James; Hankin, Chris; Carson, Siri Granum; Christen, Markus; Crafa, Silvia; Grau, Oliver; Kirchner, Claude; Knowles, Bran; McGettrick, Andrew; Tamburri, Damian Andrew; Werthner, Hannes (2018). When Computers Decide: European Recommendations on Machine-Learned Automated Decision Making. New York: Association for Computing Machinery. doi:10.1145/3185595.
  3. ^ Mökander, Jakob; Morley, Jessica; Taddeo, Mariarosaria; Floridi, Luciano (2021-07-06). "Ethics-Based Auditing of Automated Decision-Making Systems: Nature, Scope, and Limitations". Science and Engineering Ethics. 27 (4): 44. arXiv:2110.10980. doi:10.1007/s11948-021-00319-4. ISSN 1471-5546. PMC 8260507. PMID 34231029.