Revenge Against Robots

Mulligan, Christina

doi:10.2139/ssrn.3016048

Cited by 9 publications

(14 citation statements)

References 3 publications

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“…So, the question at stake is the following: if “free will” means that “nothing external to the party in question was forcing its actions and that it did what it “intended” to do”, why couldn’t this concept apply «almost equally to humans, many animals, and autonomous robots”? From this perspective, a robot appears to be “just as blameworthy as a human for its actions and just as deserving of consequences for its actions” (Mulligan, 2018 , p. 592). In other words: if a human — just as an artifact — is subject to the principle of causality, 11 why would only the former and not also the latter be responsible?…”

Section: Intentional Agency and Compatibilist Accounts Of Human Moral...mentioning

confidence: 99%

“… 3 See for example Hallevy ( 2015 ) about the possibility of punishment of AI systems; see Mulligan ( 2018 ) for a similar stance. …”

mentioning

confidence: 99%

“…For some overview on liability and culpability without moral guilt , from Nietzsche to 20 th Century criminal law, see Donini ( 2020 ). Instead, Mulligan ( 2018 ) argues for robots’ agency and therefore capacity to be blamed based on a “psychological instinct to blame” in humans.…”

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confidence: 99%

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When Doctors and AI Interact: on Human Responsibility for Artificial Risks

Verdicchio

Perin

2022

Philos. Technol.

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A discussion concerning whether to conceive Artificial Intelligence (AI) systems as responsible moral entities, also known as “artificial moral agents” (AMAs), has been going on for some time. In this regard, we argue that the notion of “moral agency” is to be attributed only to humans based on their autonomy and sentience, which AI systems lack. We analyze human responsibility in the presence of AI systems in terms of meaningful control and due diligence and argue against fully automated systems in medicine. With this perspective in mind, we focus on the use of AI-based diagnostic systems and shed light on the complex networks of persons, organizations and artifacts that come to be when AI systems are designed, developed, and used in medicine. We then discuss relational criteria of judgment in support of the attribution of responsibility to humans when adverse events are caused or induced by errors in AI systems.

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Section: Intentional Agency and Compatibilist Accounts Of Human Moral...mentioning

confidence: 99%

“… 3 See for example Hallevy ( 2015 ) about the possibility of punishment of AI systems; see Mulligan ( 2018 ) for a similar stance. …”

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confidence: 99%

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When Doctors and AI Interact: on Human Responsibility for Artificial Risks

Verdicchio

Perin

2022

Philos. Technol.

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“…Some of the possible benefits, drawbacks, and challenges of extending legal personhood to autonomous systems are unique to civil and criminal law. Granting legal personhood to AI systems may facilitate compensating those harmed under civil law ( Turner, 2018 ), while providing general deterrence ( Abbott, 2020 ) and psychological satisfaction to victims (e.g., through revenge ( Mulligan, 2017 )) if these systems are criminally punished. Extending civil liability to AI systems means these machines should hold assets to compensate those harmed ( Bryson et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

The Conflict Between People’s Urge to Punish AI and Legal Systems

et al. 2021

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Regulating artificial intelligence (AI) has become necessary in light of its deployment in high-risk scenarios. This paper explores the proposal to extend legal personhood to AI and robots, which had not yet been examined through the lens of the general public. We present two studies (N = 3,559) to obtain people’s views of electronic legal personhood vis-à-vis existing liability models. Our study reveals people’s desire to punish automated agents even though these entities are not recognized any mental state. Furthermore, people did not believe automated agents’ punishment would fulfill deterrence nor retribution and were unwilling to grant them legal punishment preconditions, namely physical independence and assets. Collectively, these findings suggest a conflict between the desire to punish automated agents and its perceived impracticability. We conclude by discussing how future design and legal decisions may influence how the public reacts to automated agents’ wrongdoings.

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“…Some of the possible benefits, drawbacks, and challenges of extending legal personhood to autonomous systems are unique to civil and criminal law. Granting legal personhood to AI systems may facilitate compensating those harmed under civil law (Turner, 2018), while providing general deterrence (Abbott, 2020) and psychological satisfaction to victims (e.g., through revenge (Mulligan, 2017)) if these systems are criminally punished. Extending civil liability to AI systems means these machines should hold assets to compensate those harmed (Bryson et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Revenge Against Robots

Cited by 9 publications

References 3 publications

When Doctors and AI Interact: on Human Responsibility for Artificial Risks

When Doctors and AI Interact: on Human Responsibility for Artificial Risks

The Conflict Between People’s Urge to Punish AI and Legal Systems

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