1,893 research outputs found
The Jiminy Advisor: Moral Agreements Among Stakeholders Based on Norms and Argumentation
An autonomous system is constructed by a manufacturer, operates in a society
subject to norms and laws, and is interacting with end users. All of these
actors are stakeholders affected by the behavior of the autonomous system. We
address the challenge of how the ethical views of such stakeholders can be
integrated in the behavior of the autonomous system. We propose an ethical
recommendation component, which we call Jiminy, that uses techniques from
normative systems and formal argumentation to reach moral agreements among
stakeholders. Jiminy represents the ethical views of each stakeholder by using
normative systems, and has three ways of resolving moral dilemmas involving the
opinions of the stakeholders. First, Jiminy considers how the arguments of the
stakeholders relate to one another, which may already resolve the dilemma.
Secondly, Jiminy combines the normative systems of the stakeholders such that
the combined expertise of the stakeholders may resolve the dilemma. Thirdly,
and only if these two other methods have failed, Jiminy uses context-sensitive
rules to decide which of the stakeholders take preference. At the abstract
level, these three methods are characterized by the addition of arguments, the
addition of attacks among arguments, and the removal of attacks among
arguments. We show how Jiminy can be used not only for ethical reasoning and
collaborative decision making, but also for providing explanations about
ethical behavior
Artificial intelligence as law:Presidential address to the seventeenth international conference on artificial intelligence and law
Information technology is so ubiquitous and AI's progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should be good for us. But how to establish proper safeguards for AI? One strong answer readily available is: consider the problems and solutions studied in AI & Law. AI & Law has worked on the design of social, explainable, responsible AI aligned with human values for decades already, AI & Law addresses the hardest problems across the breadth of AI (in reasoning, knowledge, learning and language), and AI & Law inspires new solutions (argumentation, schemes and norms, rules and cases, interpretation). It is argued that the study of AI as Law supports the development of an AI that is good for us, making AI & Law more relevant than ever
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