Despite the reality that self-learning artificial intelligence systems (SLAIS) are gaining in sophistication, humanity’s focus regarding SLAIS-human interactions are unnervingly centred upon transnational commercial sectors and, most generally, around issues of intellectual property law. But as SLAIS gain greater environmental interaction capabilities in digital spaces, or the ability to self-author code to drive their development as algorithmic models, a concern arises as to whether a system that displays a “deceptive” level of human-like engagement with users in our physical world ought (...) to be uniquely protected. Although many voices in the legal and technology realms have continued to argue against unique protections for digital entities, the fact at hand is that SLAIS design is becoming increasingly anthropomorphic so as to make these systems more capable of interacting with a wide range of (potentially) vulnerable populations—generally as a means to enhance these populations’ overall well-being. To frame this concern in a different way, the specific question at hand is whether a human’s “ownership” of such an advanced SLAIS is legal, considering that it (or they) may possess intelligence on par with a human or a convincing-enough display of such behaviour. Given that “ownership” over entities with (seemingly) intelligent behaviours consistent with human populations has been effectively banned by the international community, an examination into this subject and its implications is wholly necessary given humanity’s quest to exist solely in digital environments through whatever means possible. (shrink)

In this paper, we use a pseudo-algorithmic procedure for assessing an AI-generated text. We apply the Comprehensive Assessment Procedure for Natural Argumentation (CAPNA) in evaluating the arguments produced by an Artificial Intelligence text generator, GPT-3, in an opinion piece written for the Guardian newspaper. The CAPNA examines instances of argumentation in three aspects: their Process, Reasoning and Expression. Initial Analysis is conducted using the Argument Type Identification Procedure (ATIP) to establish, firstly, that an argument is present and, secondly, its specific (...) type in terms of the argument classification framework of the Periodic Table of Arguments (PTA). Procedural Questions are then used to test the acceptability of the argument in each of the three aspects. The analysis shows that while the arguments put forward by the AI text generator are varied in terms of their type and follow familiar patterns of human reasoning, they contain obvious weaknesses. From this we can conclude that the automated generation of persuasive, well-reasoned argumentation is a far more difficult task than the generation of meaningful language, and that if AI systems producing arguments are to be persuasive, they require a method of checking the plausibility of their own output. (shrink)

We are sometimes unsure of the moral status of our relationships with other entities. Recent case studies in this uncertainty include our relationships with artificial agents (robots, assistant AI, etc.), animals, and patients with “locked-in” syndrome. Do these entities have basic moral standing? Could they count as true friends or lovers? What should we do when we do not know the answer to these questions? An influential line of reasoning suggests that, in such cases of moral uncertainty, we need meta-moral (...) decision rules that allow us to either minimize the risks of moral wrongdoing or improve the choice-worthiness of our actions. One particular argument adopted in this literature is the “risk asymmetry argument,” which claims that the risks associated with accepting or rejecting some moral facts may be sufficiently asymmetrical as to warrant favoring a particular practical resolution of this uncertainty. Focusing on the case study of artificial beings, this article argues that this is best understood as an ethical-epistemic challenge. The article argues that taking potential risk asymmetries seriously can help resolve disputes about the status of human–AI relationships, at least in practical terms (philosophical debates will, no doubt, continue); however, the resolution depends on a proper, empirically grounded assessment of the risks involved. Being skeptical about basic moral status, but more open to the possibility of meaningful relationships with such entities, may be the most sensible approach to take. (shrink)

Ambitious value learning proposals to solve the AI alignment problem and avoid catastrophic outcomes from a possible future misaligned artificial superintelligence (such as Coherent Extrapolated Volition [CEV]) have focused on ensuring that an artificial superintelligence (ASI) would try to do what humans would want it to do. However, present and future sentient non-humans, such as non-human animals and possible future digital minds could also be affected by the ASI’s behaviour in morally relevant ways. This paper puts forward Sentientist Coherent Extrapolated (...) Volition, an alternative to CEV, that directly takes into account the interests of all sentient beings. This ambitious value learning proposal would significantly reduce the likelihood of risks of astronomical suffering from the ASI’s behaviour, and thus we have very strong pro-tanto moral reasons in favour of implementing it instead of CEV. This fact is crucial in conducting an adequate cost-benefit analysis between different ambitious value learning proposals. (shrink)