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

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)