The ethics of algorithms
Mapping the debate
Bibliographic Data
| ID | 5260780 |
|---|---|
| Authors | Brent Mittelstadt (0000-0002-4709-6404, University of Oxford, corresponding author), Brent Daniel Mittelstadt, Patrick Allo (0000-0001-8809-2170, University of Oxford), Mariarosaria Taddeo (0000-0002-1181-649X, Turing Institute), Sandra Wachter (0000-0003-3800-0113, Turing Institute), Luciano Floridi (0000-0002-5444-2280, Turing Institute) |
| Year | 2016 |
| Volume | 3 |
| Issue | 2 |
| Publication date | 2016-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Big Data & Society (JOURNAL) |
| Journal identifiers | ISSN: 2053-9517 • E-ISSN: 2053-9517 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/2053951716679679 |
| OpenAlex | W2557671501 |
| Language | EN |
| Citations received | 536 |
| References cited | 100 |
In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms
Algorithm · Data science · Economics · Management science · Mediation · Social science · Sociology · Artificial Intelligence in Healthcare and Education · Computer Science · Ethics and Social Impacts of AI · Ethics in Clinical Research
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Role of fairness, accountability, and transparency in algorithmic affordance
Artificial Intelligence and Management
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Social Data
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Perpetuating Advantage
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Legitimacy of Algorithmic Decision-Making
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Encoding and decoding in the human–machine discourse
Responsible governance of generative AI
AIsmosis and the pas de deux of human-AI interaction
Exploring AI-in-the-making
News Algorithms, Photojournalism and the Assumption of Mechanical Objectivity in Journalism
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Transparency in large language model (LLM)-powered digital human twins
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Soul of a new machine
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An Introduction to Statistical Learning
The Emergence of Probability
Strategic opportunities (and challenges) of algorithmic decision-making
The Parable of Google Flu
Self-Exciting Point Process Modeling of Crime
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Big Data's Disparate Impact
The responsibility gap
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The new profiling
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Big Data and Journalism
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After virtue
Thinking critically about and researching algorithms
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| Unique citing works | 536 |
|---|---|
| Citations per year | 59,56 |
| Citation span | 2017 - 2026 (10) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 490 |