The ethics of algorithms: key problems and solutions
By Andreas Tsamados, Nikita Aggarwal, Josh Cowls, Jessica Morley, Huw Roberts, Mariarosaria Taddeo, Luciano Floridi. Ai & Society, 2020
356 citations recorded by the source corpus.
Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016 (Mittelstadt et al. Big Data Soc 3(2), 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative concerns, and to offer actionable guidance for the governance of the design, development and deployment of algorithms.
Subfields: Artificial Intelligence, Health Informatics, Safety Research
View Paper: https://www.semanticscholar.org/paper/ae975dea712cf1c5b2c3fea72ba73ab76780060c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Josh Cowls
- Luciano Floridi
- Mariarosaria Taddeo
- Andreas Tsamados
- Jessica Morley
- Anat Elhalal
- Libby Kinsey
- Anastasia Chan
In Health Informatics
In Safety Research
- Luciano Floridi
- Josh Cowls
- Mariarosaria Taddeo
- Andreas Tsamados
- Jessica Morley
- Daniel S. Schiff
- Anat Elhalal
- Libby Kinsey
Citations in the corpus
- Accountability in artificial intelligence: what it is and how it works (2023, unknown): “However, AIs are neither mere artifacts nor traditional social systems: technological properties often make the outcome of AIs opaque and unpredictable, hindering the detection of causes and reasons for unintended outcomes (Tsamados et al. 2022).”
- The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations (2021, background): “In recent years, this “ Green & Blue ” formula (Floridi and Nobre 2020; Floridi 2020) has become apparent, at least on paper, in European policymaking.”
- Fairness of artificial intelligence in healthcare: review and recommendations (2023, background): “Establish a dedicated system within hospitals for algorithm quality control to continuously monitor AI performance, identify potential biases, and update algorithms accord‑ ingly 3.”