Separating facts and evaluation: motivation, account, and learnings from a novel approach to evaluating the human impacts of machine learning

Abstract

In this paper, we outline a new method for evaluating the human impact of machine-learning (ML) applications. In partnership with Underwriters Laboratories Inc., we have developed a framework to evaluate the impacts of a particular use of machine learning that is based on the goals and values of the domain in which that application is deployed. By examining the use of artificial intelligence (AI) in particular domains, such as journalism, criminal justice, or law, we can develop more nuanced and practically relevant understandings of key ethical guidelines for artificial intelligence. By decoupling the extraction of the facts of the matter from the evaluation of the impact of the resulting systems, we create a framework for the process of assessing impact that has two distinctly different phases.

Embedding AI in society: ethics, policy, governance, and impacts

“…He also discusses other potential legal ramifications of personhood like contracts and lawsuits. Similarly, Jenkins et al (2022) lay out a two-phase framework for assessing the consequences, good and bad, of AI systems by examining their use in journalism, criminal justice, and the law. They argue that the legal system is likely to provide much commentary on ethical principles such as justice, fairness, accountability, and responsibility.…”

Assessing Deep Learning: A Work Program for the Humanities in the Age of Artificial Intelligence

“…Such a view has been labeled the 'value neutrality thesis' of technology: denoting the idea that technology is a morally and politically neutral medium and that the only relevant factor with regard to outcomes is what humans do with it [241]. This view is increasingly questioned and challenged by approaches that recognize that values are embedded in technology and that technological artifacts have a kind of agency that needs to be reckoned with, not least because they lastingly affect their 'users' and culture and society more broadly [242][243][244][245]. Technologies do something to us as we do something with them [246] and thus make vital an encompassing analysis of the structure of human-technology systems as well as their 'co-evolution' [235,247,248].…”