Home / Books / Practical Fairness: Achieving Fair and Secure Data Models

Practical Fairness: Achieving Fair and Secure Data Models

Book by Aileen Nielsen · 7 quotes · Decision, Fair, Authority

Browse quotes from Practical Fairness: Achieving Fair and Secure Data Models.

Book detail: Practical Fairness: Achieving Fair and Secure Data Models is presented as a focused source page for quotations connected with this book, collection, transcript, or source record.

Browse quotes from Practical Fairness: Achieving Fair and Secure Data Models.

The quotes below use the same card format as the rest of the site, including topics, source notes, copy actions, image creation, and sharing controls.

Filter quotes by topic

All Decision Fair Authority Autonomy Fairness Political 1970s Activist Algorithmic Allocation Appeal Baseline Challenge Cheating Confidence Decide Demand Due Process Empathy Equality

Practical Fairness: Achieving Fair and Secure Data Models 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.”

Respect Autonomy Equity Treat Meritorious Baseline

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.”

Technology Human Fairness French Legal 1970s Algorithmic

Book:Practical Fairness: Achieving Fair and Secure Data Models

Source: Practical Fairness: Achieving Fair and Secure Data Models

“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?”

Opportunity Justice Decision Empathy Equality Cheating Transparency Outcome Fair Opaque

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.”

Authority Autonomy Fair Fair Play Personal 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.”

Political Decision Confidence Openness Fairness Due Process Institution

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)”

Political Decision Society Authority Function Decide Who Allocation

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.”

Decision Demand Activist Challenge Fair Appeal

Book:Practical Fairness: Achieving Fair and Secure Data Models

Source: Practical Fairness: Achieving Fair and Secure Data Models