Data & Society > our work > academic journal > Undoing the neutrality of big data

Florida Law Review Forum | 08.16.11

Undoing the neutrality of big data

danah boyd

The mythology surrounding “big data” rests on the notion that technical systems can increase efficiency and decrease bias. Such “neutral” systems are supposedly good for implementing legal logic because, like these systems, law relies on binaries in decision-making, removing the gray and fuzzy from the equation. The problem with this formulation is that efficiency is not necessarily desirable, bias is baked into the data sets and reified technically as well as through interpretation, and legal binaries are neither socially productive nor logically sound.

D&S founder danah boyd responds to Margaret Hu’s work in Big Data Blacklisting with supportive arguments that further Hu’s assertions. boyd discusses how procedure and efficiency make algorithmic decision-making so attractive to policymakers and bureaucrats yet flawed systems in place do not make data neutral and in fact ‘blacklists purposefully distance decision-makers from the humanity of those who are being labeled’.

Subscribe to the Data & Society newsletter

Support us

Donate
Data & Society Research Institute 36 West 20th Street, 11th Floor
New York, NY 10011, Tel: 646.832.2038

Reporters and media:
[email protected]

General inquiries:
[email protected]

Unless otherwise noted this site and its contents are licensed under a Creative Commons Attribution 3.0 Unported license.