People's Councils for Ethical Machine Learning. (April 2018)

• Record Type: Journal Article
• Authors: McQuillan, Dan
• Is Part Of: Social media + society. Volume 4:Number 2(2018:Apr./Jun.)
• Publication Date: 2018-04
• Subjects: big data -- ethics -- Hannah Arendt -- machine learning; Social media -- Periodicals; Social media -- Social aspects -- Periodicals; 302.231
• DOI: 10.1177/2056305118768303
• Languages: English
• ISSNs: 2056-3051

Abstract

Machine learning is a form of knowledge production native to the era of big data. It is at the core of social media platforms and everyday interactions. It is also being rapidly adopted for research and discovery across academia, business, and government. This article will explores the way the affordances of machine learning itself, and the forms of social apparatus that it becomes a part of, will potentially erode ethics and draw us in to a drone-like perspective. Unconstrained machine learning enables and delimits our knowledge of the world in particular ways: the abstractions and operations of machine learning produce a "view from above" whose consequences for both ethics and legality parallel the dilemmas of drone warfare. The family of machine learning methods is not somehow inherently bad or dangerous, nor does implementing them signal any intent to cause harm. Nevertheless, the machine learning assemblage produces a targeting gaze whose algorithms obfuscate the legality of its judgments, and whose iterations threaten to create both specific injustices and broader states of exception. Given the urgent need to provide some kind of balance before machine learning becomes embedded everywhere, this article proposes people's councils as a way to contest machinic judgments and reassert openness and discourse.