Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns

TL;DR

This paper investigates how AI practitioners perceive and implement AI ethics principles, proposing a pattern-based template to operationalize these principles into concrete design guidance for responsible AI development.

Contribution

It introduces an empirical study on practitioners' views and a novel template for transforming high-level AI ethics principles into actionable design patterns.

Findings

Practitioners find current guidelines too abstract.

The proposed template helps operationalize AI ethics.

A list of concrete patterns for responsible AI development.

Abstract

Although artificial intelligence (AI) is solving real-world challenges and transforming industries, there are serious concerns about its ability to behave and make decisions in a responsible way. Many AI ethics principles and guidelines for responsible AI have been recently issued by governments, organisations, and enterprises. However, these AI ethics principles and guidelines are typically high-level and do not provide concrete guidance on how to design and develop responsible AI systems. To address this shortcoming, we first present an empirical study where we interviewed 21 scientists and engineers to understand the practitioners' perceptions on AI ethics principles and their implementation. We then propose a template that enables AI ethics principles to be operationalised in the form of concrete patterns and suggest a list of patterns using the newly created template. These patterns provide concrete, operationalised guidance that facilitate the development of responsible AI systems.