Reasonable Machines: A Research Manifesto

TL;DR

This paper advocates for developing 'Reasonable Machines' capable of autonomous moral and legal justification, integrating social reasoning, ontologies, and argumentation to foster trust and transparency in AI systems.

Contribution

It introduces a novel framework combining social reasoning models, ethico-legal ontologies, and argumentation technology for autonomous moral justification in AI.

Findings

Proposes a hybrid reasoning approach for moral decision-making.

Highlights the importance of ethico-legal ontologies for trust.

Suggests new dimensions for human-machine interaction.

Abstract

Future intelligent autonomous systems (IAS) are inevitably deciding on moral and legal questions, e.g. in self-driving cars, health care or human-machine collaboration. As decision processes in most modern sub-symbolic IAS are hidden, the simple political plea for transparency, accountability and governance falls short. A sound ecosystem of trust requires ways for IAS to autonomously justify their actions, that is, to learn giving and taking reasons for their decisions. Building on social reasoning models in moral psychology and legal philosophy such an idea of >>Reasonable Machines<< requires novel, hybrid reasoning tools, ethico-legal ontologies and associated argumentation technology. Enabling machines to normative communication creates trust and opens new dimensions of AI application and human-machine interaction. Keywords: Trusthworthy and Explainable AI, Ethico-Legal Governors, Social Reasoning Model, Pluralistic and Expressive Normative Reasoning