An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020)

TL;DR

This paper develops a comprehensive, interdisciplinary matrix to help qualify AI systems for benefit-risk assessment, integrating concepts from psychology, engineering, ethics, and law to support responsible AI development.

Contribution

It introduces a novel, risk-based qualification matrix that synthesizes interdisciplinary AI concepts for practical assessment and regulation of AI technologies.

Findings

Proposes a flexible, scalable qualification matrix for AI systems.

Integrates interdisciplinary notions into a unified assessment framework.

Supports stakeholders in responsible AI research and regulation.

Abstract

This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence, namely psychology and engineering, and from disciplines aiming to regulate AI innovations, namely AI ethics and law. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems. Relevant concepts are integrated into a matrix intended to help defining more precisely when and how computing tools (programs or devices) may be qualified as AI while highlighting critical features to serve a specific technical, ethical and legal assessment of challenges in AI development. Some adaptations of existing notions of AI characteristics are proposed. The matrix is a risk-based conceptual model designed to allow an empirical, flexible and scalable qualification of AI technologies in the perspective of benefit-risk assessment practices, technological monitoring and regulatory compliance: it offers a structured reflection tool for stakeholders in AI development that are engaged in responsible research and innovation.Pre-print version (achieved on May 2020)