Technological Due Process

By D. Citron. 2007

305 citations recorded by the source corpus.

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Citations in the corpus

Fairness and Abstraction in Sociotechnical Systems (2019, background): “Different judges might exhibit automation bias [16, 62], deviate from recommendations in biased ways, or ignore them entirely.”
Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse (2019, background): “In the United States, the Obama White House ‒ presaged by key early scholarship (e.g., Citron, 2007; Sweeney, 2013) and developments overseas (e.g., European Commission, 2012) ‒ confronted the challenges of so-called ‘ big data ’ through the lens of discrimination and civil rights (Podesta,…”
Ethical Implications and Accountability of Algorithms (2018, background): “6 Danielle Citron refers to this issue as technological due process (Citron 2007), arguing that “[t]his century’s automated decision making systems combine individual adjudications with rulemaking while adhering to the procedural safeguards of neither.”
On the apparent conflict between individual and group fairness (2019, background): “In contexts in which public administration and private decision-making are being automated or augmented with algorithms, the need for occasional individualised consideration is one of the reasons for keeping a human-in-the-loop, or ‘screen-level bureaucrat’ on hand [1, 8, 12, 48].”
The fallacy of inscrutability (2018, background): “a component of a solution to problems of governing computer systems [1,16,45,46].”
The Threat of Algocracy: Reality, Resistance and Accommodation (2016, background): “…themselves out of this right and for governments to override it so long as other measures are taken for protecting the individual’s ‘legitimate interests’.26 Similar solutions have been proposed in recent papers from Citron and Pasquale (2014; and Citron 2010) and Crawford and Schultz (2014).”
Surveillance, Snowden, and Big Data: Capacities, consequences, critique (2014, background): “For example, computers can terminate individuals’ Medicaid beneﬁts, impairing a statutorily-granted property interest (see Citron, 2008).”
The Society of Algorithms (2021, background): “In a narrow sense, the interpretive work that computer scientists must perform in order to translate social norms and legal rules from human language into computer code inevitably introduces distortions and simplifications (Citron 2007).”
Algorithmic Accountability Reporting: On the Investigation of Black Boxes (2014, background): “48 Journalists might productively offer themselves as a check and balance on algorithmic power while the legislative regulation of algorithms takes shape over a longer time horizon.”
Accountable Artificial Intelligence: Holding Algorithms to Account (2020, background): “…actors—that drive innovation in this area—but are also widely relied upon by governments and public (regulatory) bodies (AI Now Institute NYU 2018; Citron 2008; Eubanks 2018; European Parliament Study 2019; O’Neil 2016; Richardson, Schultz, and Crawford 2019; Shark 2019; UK Government Office for…”
Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science (2018, background): “In the United States, for example, due process requires that citizens who have been deprived of liberty or property by the government be afforded the opportunity to understand and challenge the government’s decision (Citron, 2008).”