The Conflict Between Explainable and Accountable Decision-Making Algorithms

TL;DR

This paper critically examines the tension between explainability and accountability in decision-making algorithms, highlighting potential pitfalls of post-hoc explanations and advocating for stronger regulation to ensure responsibility.

Contribution

It challenges the effectiveness of explainable AI in ensuring accountability and proposes regulatory measures to address responsibility issues in high-stakes AI systems.

Findings

Post-hoc explanations may obscure developer responsibility.

Explainability can lead to misattribution of blame to stakeholders.

Regulation is necessary to enforce accountability in AI decision-making.

Abstract

Decision-making algorithms are being used in important decisions, such as who should be enrolled in health care programs and be hired. Even though these systems are currently deployed in high-stakes scenarios, many of them cannot explain their decisions. This limitation has prompted the Explainable Artificial Intelligence (XAI) initiative, which aims to make algorithms explainable to comply with legal requirements, promote trust, and maintain accountability. This paper questions whether and to what extent explainability can help solve the responsibility issues posed by autonomous AI systems. We suggest that XAI systems that provide post-hoc explanations could be seen as blameworthy agents, obscuring the responsibility of developers in the decision-making process. Furthermore, we argue that XAI could result in incorrect attributions of responsibility to vulnerable stakeholders, such as those who are subjected to algorithmic decisions (i.e., patients), due to a misguided perception that they have control over explainable algorithms. This conflict between explainability and accountability can be exacerbated if designers choose to use algorithms and patients as moral and legal scapegoats. We conclude with a set of recommendations for how to approach this tension in the socio-technical process of algorithmic decision-making and a defense of hard regulation to prevent designers from escaping responsibility.