We propose that the prevalent moral aversion to AWS is supported by a pair of compelling objections. First, we argue that even a sophisticated robot is not the kind of thing that is capable of replicating human moral judgment. This conclusion follows if human moral judgment is not codifiable, i.e., it cannot be captured by a list of rules. Moral judgment requires either the ability to engage in wide reflective equilibrium, the ability to perceive certain facts as moral considerations, moral (...) imagination, or the ability to have moral experiences with a particular phenomenological character. Robots cannot in principle possess these abilities, so robots cannot in principle replicate human moral judgment. If robots cannot in principle replicate human moral judgment then it is morally problematic to deploy AWS with that aim in mind. Second, we then argue that even if it is possible for a sufficiently sophisticated robot to make ‘moral decisions’ that are extensionally indistinguishable from (or better than) human moral decisions, these ‘decisions’ could not be made for the right reasons. This means that the ‘moral decisions’ made by AWS are bound to be morally deficient in at least one respect even if they are extensionally indistinguishable from human ones. Our objections to AWS support the prevalent aversion to the employment of AWS in war. They also enjoy several significant advantages over the most common objections to AWS in the literature. (shrink)

Abstract: In the course of seeking an answer to the question "How do you know you are not a zombie?" Floridi (2005) issues an ingenious, philosophically rich challenge to artificial intelligence (AI) in the form of an extremely demanding version of the so-called knowledge game (or "wise-man puzzle," or "muddy-children puzzle")—one that purportedly ensures that those who pass it are self-conscious. In this article, on behalf of (at least the logic-based variety of) AI, I take up the challenge—which is to (...) say, I try to show that this challenge can in fact be met by AI in the foreseeable future. (shrink)

Our chronically impoverished explanatory capacity in respect of P-consciousness is highly suggestive of a problem with science itself, rather than its lack of acquisition of some particular knowledge. The hidden assumption built into science is that science itself is a completed human behaviour. Removal of this assumption is achieved through a simple revision to our science model which is constructed, outlined and named ‘dual aspect science’ (DAS). It is constructed with reference to existing science being ‘single aspect science’. DAS is (...) consistent with and predictive of the very explanatory poverty that generated it and is simultaneously a seamless upgrade; no existing law of nature is altered or lost. The framework is completely empirically self-consistent and is validated empirically. DAS eliminates the behavioural inconsistencies currently inhabiting a world in which single aspect science has been inherited rather than chosen and in which its presuppositions are implemented through habit rather than by scientific examination of options by the scientists actually carrying out science. The proposed DAS framework provides a working vantage point from which an explanation of P-consciousness becomes expected and meaningful. The framework requires that we rediscover what we scientists do and then discover something new about ourselves: that how we have been doing science is not the entire story. Dual aspect science shows us what we have not been doing. (shrink)