Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.805187
Title: The reasonable robot : artificial intelligence and the law
Author: Abbott, Ryan
ISNI:       0000 0004 8509 9248
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 2020
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Abstract:
This thesis argues in favor of a novel principle for AI regulation: AI legal neutrality. Namely, that the law should not discriminate between activity by people and activity by AI when people and AI are performing the same tasks. This will reduce market distortions and help to ensure that decisions are made on the basis of efficiency. Efficiency is not the only principle that should guide AI regulation, but not discriminating between people and AI will tend to improve human well-being. We do not currently have a neutral legal system as between human and AI activity. An AI that is significantly safer than a person may be the best choice for driving a vehicle, but existing laws may prohibit driverless vehicles. A person may be a better choice for packing boxes at a warehouse, but a business may automate because AI receives preferential tax treatment. AI may be better at generating certain types of innovation, but businesses may not want to use AI if this restricts future intellectual property rights. In all of these instances, neutral legal treatment would ultimately benefit society as a whole. As AI increasingly steps into someone's shoes, it will need to be treated more like a person. Sometimes more importantly, as AI is incorporated into our legal standards, people will need to be treated more like AI. In many areas of the law, standards are set by human behavior—the degree of care expected of a driver, the quantum of creativity required to protect a new invention, even the state of mind required for criminal punishment. As AI takes people out-ofthe-loop and comes to be the normal way that tasks are performed, the AI's behavior should set our benchmarks. AI is not part of our moral community, but it should be part of our legal community.
Supervisor: Sarvarian, Arman ; Taggart, Christopher Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.805187  DOI:
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