When Trust is Zero Sum: Automation Threat to Epistemic Agency

TL;DR

The paper discusses how automation can undermine human epistemic agency and trust in the workplace, proposing adversarial collaboration as a novel solution to preserve human dignity and decision-making authority.

Contribution

It introduces adversarial collaboration as a new approach to mitigate epistemic harms and trust issues caused by automation in workplaces.

Findings

Automation can diminish human epistemic agency even when jobs are retained.

Current solutions may inadvertently exacerbate epistemic harms.

Adversarial collaboration offers a promising alternative to address trust and agency issues.

Abstract

AI researchers and ethicists have long worried about the threat that automation poses to human dignity, autonomy, and to the sense of personal value that is tied to work. Typically, proposed solutions to this problem focus on ways in which we can reduce the number of job losses which result from automation, ways to retrain those that lose their jobs, or ways to mitigate the social consequences of those job losses. However, even in cases where workers keep their jobs, their agency within them might be severely downgraded. For instance, human employees might work alongside AI but not be allowed to make decisions or not be allowed to make decisions without consulting with or coming to agreement with the AI. This is a kind of epistemic harm (which could be an injustice if it is distributed on the basis of identity prejudice). It diminishes human agency (in constraining people's ability to act independently), and it fails to recognize the workers' epistemic agency as qualified experts. Workers, in this case, aren't given the trust they are entitled to. This means that issues of human dignity remain even in cases where everyone keeps their job. Further, job retention focused solutions, such as designing an algorithm to work alongside the human employee, may only enable these harms. Here, we propose an alternative design solution, adversarial collaboration, which addresses the traditional retention problem of automation, but also addresses the larger underlying problem of epistemic harms and the distribution of trust between AI and humans in the workplace.