984 research outputs found
Designing Normative Theories for Ethical and Legal Reasoning: LogiKEy Framework, Methodology, and Tool Support
A framework and methodology---termed LogiKEy---for the design and engineering
of ethical reasoners, normative theories and deontic logics is presented. The
overall motivation is the development of suitable means for the control and
governance of intelligent autonomous systems. LogiKEy's unifying formal
framework is based on semantical embeddings of deontic logics, logic
combinations and ethico-legal domain theories in expressive classic
higher-order logic (HOL). This meta-logical approach enables the provision of
powerful tool support in LogiKEy: off-the-shelf theorem provers and model
finders for HOL are assisting the LogiKEy designer of ethical intelligent
agents to flexibly experiment with underlying logics and their combinations,
with ethico-legal domain theories, and with concrete examples---all at the same
time. Continuous improvements of these off-the-shelf provers, without further
ado, leverage the reasoning performance in LogiKEy. Case studies, in which the
LogiKEy framework and methodology has been applied and tested, give evidence
that HOL's undecidability often does not hinder efficient experimentation.Comment: 50 pages; 10 figure
Machine ethics via logic programming
Machine ethics is an interdisciplinary field of inquiry that emerges from the need of
imbuing autonomous agents with the capacity of moral decision-making. While some
approaches provide implementations in Logic Programming (LP) systems, they have not
exploited LP-based reasoning features that appear essential for moral reasoning.
This PhD thesis aims at investigating further the appropriateness of LP, notably a
combination of LP-based reasoning features, including techniques available in LP systems,
to machine ethics. Moral facets, as studied in moral philosophy and psychology, that
are amenable to computational modeling are identified, and mapped to appropriate LP
concepts for representing and reasoning about them.
The main contributions of the thesis are twofold.
First, novel approaches are proposed for employing tabling in contextual abduction
and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets.
Second, a variety of LP-based reasoning features are applied to model the identified
moral facets, through moral examples taken off-the-shelf from the morality literature.
These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.Fundação para a Ciência e a Tecnologia (FCT)-grant SFRH/BD/72795/2010 ; CENTRIA
and DI/FCT/UNL for the supplementary fundin
Logic Programming and Machine Ethics
Transparency is a key requirement for ethical machines. Verified ethical
behavior is not enough to establish justified trust in autonomous intelligent
agents: it needs to be supported by the ability to explain decisions. Logic
Programming (LP) has a great potential for developing such perspective ethical
systems, as in fact logic rules are easily comprehensible by humans.
Furthermore, LP is able to model causality, which is crucial for ethical
decision making.Comment: In Proceedings ICLP 2020, arXiv:2009.09158. Invited paper for the
ICLP2020 Panel on "Machine Ethics". arXiv admin note: text overlap with
arXiv:1909.0825
Computational ethics
Technological advances are enabling roles for machines that present novel ethical challenges. The study of 'AI ethics' has emerged to confront these challenges, and connects perspectives from philosophy, computer science, law, and economics. Less represented in these interdisciplinary efforts is the perspective of cognitive science. We propose a framework – computational ethics – that specifies how the ethical challenges of AI can be partially addressed by incorporating the study of human moral decision-making. The driver of this framework is a computational version of reflective equilibrium (RE), an approach that seeks coherence between considered judgments and governing principles. The framework has two goals: (i) to inform the engineering of ethical AI systems, and (ii) to characterize human moral judgment and decision-making in computational terms. Working jointly towards these two goals will create the opportunity to integrate diverse research questions, bring together multiple academic communities, uncover new interdisciplinary research topics, and shed light on centuries-old philosophical questions.publishedVersio
Artificial consciousness and the consciousness-attention dissociation
Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. This becomes clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems—these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness
Real Islamic Logic
Four options for assigning a meaning to Islamic Logic are surveyed including
a new proposal for an option named "Real Islamic Logic" (RIL). That approach to
Islamic Logic should serve modern Islamic objectives in a way comparable to the
functionality of Islamic Finance. The prospective role of RIL is analyzed from
several perspectives: (i) parallel distributed systems design, (ii) reception
by a community structured audience, (iii) informal logic and applied
non-classical logics, and (iv) (in)tractability and artificial intelligence
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