The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism

TL;DR

This paper examines how computer vision systems are increasingly used for profiling individuals by measuring real-world traits, explores the epistemic claims they make, and questions the implications for human subjectivity and legal contestation.

Contribution

It analyzes the measurement and representation practices in computer vision, introduces the concept of computational empiricism, and discusses its societal and legal implications.

Findings

Computer vision systems claim to reveal truths about individuals.

A new form of computational empiricism is being operationalized.

Legal mechanisms can challenge the dominance of computational knowledge.

Abstract

Computer vision and other biometrics data science applications have commenced a new project of profiling people. Rather than using 'transaction generated information', these systems measure the 'real world' and produce an assessment of the 'world state' - in this case an assessment of some individual trait. Instead of using proxies or scores to evaluate people, they increasingly deploy a logic of revealing the truth about reality and the people within it. While these profiling knowledge claims are sometimes tentative, they increasingly suggest that only through computation can these excesses of reality be captured and understood. This article explores the bases of those claims in the systems of measurement, representation, and classification deployed in computer vision. It asks if there is something new in this type of knowledge claim, sketches an account of a new form of computational empiricism being operationalised, and questions what kind of human subject is being constructed by these technological systems and practices. Finally, the article explores legal mechanisms for contesting the emergence of computational empiricism as the dominant knowledge platform for understanding the world and the people within it.