Speculations on Uncertainty and Humane Algorithms

TL;DR

This paper emphasizes the importance of incorporating risk and uncertainty, especially epistemic uncertainty, into AI algorithms to enhance ethical decision-making, trustworthiness, and human-centric outcomes in high-risk scenarios.

Contribution

It advocates for the integration of uncertainty management in AI to improve ethical considerations, transparency, and trustworthiness, highlighting its critical role in humane AI development.

Findings

Uncertainty management enhances ethical decision-making.

Handling epistemic uncertainty prevents unjustified assumptions.

Provenance and trustworthiness are linked to uncertainty awareness.

Abstract

The appreciation and utilisation of risk and uncertainty can play a key role in helping to solve some of the many ethical issues that are posed by AI. Understanding the uncertainties can allow algorithms to make better decisions by providing interrogatable avenues to check the correctness of outputs. Allowing algorithms to deal with variability and ambiguity with their inputs means they do not need to force people into uncomfortable classifications. Provenance enables algorithms to know what they know preventing possible harms. Additionally, uncertainty about provenance highlights the trustworthiness of algorithms. It is essential to compute with what we know rather than make assumptions that may be unjustified or untenable. This paper provides a perspective on the need for the importance of risk and uncertainty in the development of ethical AI, especially in high-risk scenarios. It argues that the handling of uncertainty, especially epistemic uncertainty, is critical to ensuring that algorithms do not cause harm and are trustworthy and ensure that the decisions that they make are humane.