Definitions of intent suitable for algorithms

IF 3.1 2区 社会学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence and Law Pub Date : 2022-07-25 DOI:10.1007/s10506-022-09322-x
Hal Ashton
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引用次数: 12

Abstract

This article introduces definitions for direct, means-end, oblique (or indirect) and ulterior intent which can be used to test for intent in an algorithmic actor. These definitions of intent are informed by legal theory from common law jurisdictions. Certain crimes exist where the harm caused is dependent on the reason it was done so. Here the actus reus or performative element of the crime is dependent on the mental state or mens rea of the actor. The ability to prosecute these crimes is dependent on the ability to identify and diagnose intentional states in the accused. A certain class of auto didactic algorithmic actor can be given broad objectives without being told how to meet them. Without a definition of intent, they cannot be told not to engage in certain law breaking behaviour nor can they ever be identified as having done it. This ambiguity is neither positive for the owner of the algorithm or for society. The problem exists over and above more familiar debates concerning the eligibility of algorithms for culpability judgements that mens rea is usually associated with. Aside from inchoate offences, many economic crimes with elements of fraud or deceit fall into this category of crime. Algorithms operate in areas where these crimes could be plausibly undertaken depending on whether the intent existed in the algorithm or not.

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适用于算法的意图定义
本文介绍了直接意图、手段目的、间接意图和不可告人意图的定义,这些定义可用于测试算法参与者的意图。这些意图的定义是由普通法管辖区的法律理论提供的。在某些犯罪中,造成的伤害取决于造成伤害的原因。在这里,犯罪的行为或表现要素取决于行为人的精神状态或犯罪意图。起诉这些罪行的能力取决于识别和诊断被告故意状态的能力。某一类自学成才的算法行动者可以被赋予广泛的目标,而无需被告知如何实现这些目标。如果没有意图的定义,他们就不能被告知不要从事某些违法行为,也永远不能被认定为有违法行为。这种模糊性对算法所有者或社会都不是积极的。这个问题存在于人们更熟悉的关于犯罪意图通常与之相关的有罪判决算法的资格的辩论之上。除了早期犯罪外,许多带有欺诈或欺骗成分的经济犯罪都属于这类犯罪。算法在可能合理实施这些犯罪的领域运行,这取决于算法中是否存在意图。
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来源期刊
CiteScore
9.50
自引率
26.80%
发文量
33
期刊介绍: Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. Topics of interest include, but are not limited to, the following: Computational models of legal reasoning and decision making; judgmental reasoning, adversarial reasoning, case-based reasoning, deontic reasoning, and normative reasoning. Formal representation of legal knowledge: deontic notions, normative modalities, rights, factors, values, rules. Jurisprudential theories of legal reasoning. Specialized logics for law. Psychological and linguistic studies concerning legal reasoning. Legal expert systems; statutory systems, legal practice systems, predictive systems, and normative systems. AI and law support for legislative drafting, judicial decision-making, and public administration. Intelligent processing of legal documents; conceptual retrieval of cases and statutes, automatic text understanding, intelligent document assembly systems, hypertext, and semantic markup of legal documents. Intelligent processing of legal information on the World Wide Web, legal ontologies, automated intelligent legal agents, electronic legal institutions, computational models of legal texts. Ramifications for AI and Law in e-Commerce, automatic contracting and negotiation, digital rights management, and automated dispute resolution. Ramifications for AI and Law in e-governance, e-government, e-Democracy, and knowledge-based systems supporting public services, public dialogue and mediation. Intelligent computer-assisted instructional systems in law or ethics. Evaluation and auditing techniques for legal AI systems. Systemic problems in the construction and delivery of legal AI systems. Impact of AI on the law and legal institutions. Ethical issues concerning legal AI systems. In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law.
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