Practical Fairness: Achieving Fair and... A source page for quotes linked to Aileen Nielsen. 0 quotes
Practical Time Series Analysis: Predict... A source page for quotes linked to Aileen Nielsen. 0 quotes
“Our discussion of equity was quite wide-ranging and went far beyond the matter of treating similarly meritorious individuals similarly and into the domain of also treating all individuals with a baseline level of respect and autonomy.” RespectAutonomyEquityTreatMeritoriousBaseline Book:Practical Fairness: Achieving Fair and Secure Data Models Source: Practical Fairness: Achieving Fair and Secure Data Models
“Concerns about technology and fairness go back a long way, even from a legal perspective. For example, as early as the 1970s it was illegal under French law to make any decisions affecting human beings in a purely algorithmic manner—that is, without any human supervision.” TechnologyHumanFairnessFrenchLegal1970sAlgorithmic Book:Practical Fairness: Achieving Fair and Secure Data Models Source: Practical Fairness: Achieving Fair and Secure Data Models
“The idea that society can be made more consistent, more accurate, and more fair by replacing idiosyncratic human judgment with numerical models is hardly a new one. In fact, their use even in criminal justice is nearly a century old.” JusticeSocietyHumanJudgementConsistentAccurateFairNumericalIdiosyncratic Book:Practical Time Series Analysis: Prediction with Statistics and Machine Learning Source: Practical Time Series Analysis: Prediction with Statistics and Machine Learning
“Is it fairer for everyone to have the same opportunities or to have the same outcomes? Equality of opportunity or equality of outcome? Is it fairer for decisions to be uniform or to embody an element of human empathy? Impartial justice or individual allowances? Is it fairer to let people know how decisions are made or to have an opaque system to prevent cheating? Transparency or security?” OpportunityJusticeDecisionEmpathyEqualityCheatingTransparencyOutcomeFairOpaque Book:Practical Fairness: Achieving Fair and Secure Data Models Source: Practical Fairness: Achieving Fair and Secure Data Models
“In this group of issues related to fair play, we consider whether we are putting data subjects in a position that undermines their autonomy or authority about how their personal information is used.” AuthorityAutonomyFairFair PlayPersonal Information Book:Practical Fairness: Achieving Fair and Secure Data Models Source: Practical Fairness: Achieving Fair and Secure Data Models
“Openness in political decision-making matters. It is key to maintaining confidence in public institutions and to achieving fairness and due process.” PoliticalDecisionConfidenceOpennessFairnessDue ProcessInstitution Book:Practical Fairness: Achieving Fair and Secure Data Models Source: Practical Fairness: Achieving Fair and Secure Data Models
“Practical considerations most often come up in the form of three fundamental questions a society needs to answer in order to function: Who gets what? (Rules of allocation) How do we decide who gets what? (Rules of decision) Who decides who decides? (Rules of political authority)” PoliticalDecisionSocietyAuthorityFunctionDecideWhoAllocation Book:Practical Fairness: Achieving Fair and Secure Data Models Source: Practical Fairness: Achieving Fair and Secure Data Models
“Activists successfully challenged inequitable access to public assistance by appealing decisions and demanding access to administrative law procedures known as fair hearings.” DecisionDemandActivistChallengeFairAppeal Book:Practical Fairness: Achieving Fair and Secure Data Models Source: Practical Fairness: Achieving Fair and Secure Data Models