Digital and Computational Aspects of Human and AI Ethical Frameworks

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Hector Zenil

Subject: Arts & Humanities, Philosophy

Keywords: philosophy of information; organised complexity; Kolmogorov complexity; logical depth; ethics of information; computational ethics; in- foethics; machine ethics; computational complexity

I explore previous attempts, including recent ones, to introduce aspects of digital information and computation into the discussion of ethical frameworks. I study some limitations and advantages of previous attempts to produce guiding principles at different scales. In particular, I survey and discuss questions and approaches based on, or related to, simulation, information theory, integrated information, computer simulation, intractability, algorithmic complexity, and measures of computational organisation and sophistication. I discuss and propose a set of desirable features of ethical frameworks that may be considered well-grounded, both in theoretical and methodological terms. I will show that while global ethi- cal frameworks that are uncomputable are desirable because they provide non-teleological directions with open-ended meaning, constrained versions should be able to provide guidelines at more local and immediate time scales. In connection to the ethics of artificial intelligence, one point that must be underscored in relation to computational approaches is that (General) AI should only share and embrace an ethical framework that we humans are willing to adopt, preempting the need for possibly flawed distinctions between human and machine actions, especially in connection to concerns of a much more fundamental nature than the classical issues raised by AI development such as job displacement and legal liability. I think that such framework is possible by following a general and universal (in the sense of computation) framework from first computational principles.

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