Definitions of intent suitable for algorithms

TL;DR

This paper proposes formal definitions of different types of intent—direct, oblique, and ulterior—for algorithms, aiding legal and ethical assessments of autonomous agents' potential for harm.

Contribution

It introduces a structured framework for identifying and testing various intent types in algorithms, bridging legal concepts with computational models.

Findings

Defined formal criteria for direct, oblique, and ulterior intent in algorithms.

Provided a basis for testing intent in autonomous algorithmic agents.

Facilitated legal and ethical evaluation of algorithmic actions.

Abstract

Intent modifies an actor's culpability of many types wrongdoing. Autonomous Algorithmic Agents have the capability of causing harm, and whilst their current lack of legal personhood precludes them from committing crimes, it is useful for a number of parties to understand under what type of intentional mode an algorithm might transgress. From the perspective of the creator or owner they would like ensure that their algorithms never intend to cause harm by doing things that would otherwise be labelled criminal if committed by a legal person. Prosecutors might have an interest in understanding whether the actions of an algorithm were internally intended according to a transparent definition of the concept. The presence or absence of intention in the algorithmic agent might inform the court as to the complicity of its owner. This article introduces definitions for direct, oblique (or indirect) and ulterior intent which can be used to test for intent in an algorithmic actor.