Some take seriously the possibility of artificial intelligence (AI) takeover, where AI systems seize power in a way that leads to human disempowerment. Assessing the likelihood of takeover requires answering empirical questions about the future of AI technologies and the context in which AI will operate. In many cases, philosophers are poorly placed to answer these questions. However, some prior questions are more amenable to philosophical techniques. What does it mean to speak of AI empowerment and human disempowerment? And what (...) empirical claims must hold for the former to lead to the latter? In this paper, I address these questions, providing foundations for further evaluation of the likelihood of takeover. (shrink)

Recent progress in artificial intelligence (AI) has drawn attention to the technology’s transformative potential, including what some see as its prospects for causing large-scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power-Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power-seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek power, that (...) they might obtain it, that this could lead to catastrophe, and that we might build and deploy such systems anyway. The second argument claims that the development of human-level AI will unlock rapid further progress, culminating in AI systems far more capable than any human — this is the Singularity Hypothesis. Power-seeking behavior on the part of such systems might be particularly dangerous. We discuss a variety of objections to both arguments and conclude by assessing the state of the debate. (shrink)

I explain the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems show that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. And (...) patience trades off against shutdownability: the more patient an agent, the greater the costs that agent is willing to incur to manipulate the shutdown button. I end by noting that these theorems can guide our search for solutions. (shrink)

The singularity hypothesis is a radical hypothesis about the future of artificial intelligence on which self-improving artificial agents will quickly become orders of magnitude more intelligent than the average human. Despite the ambitiousness of its claims, the singularity hypothesis has been defended at length by leading philosophers and artificial intelligence researchers. In this paper, I argue that the singularity hypothesis rests on scientifically implausible growth assumptions. I show how leading philosophical defenses of the singularity hypothesis (Chalmers 2010, Bostrom 2014) fail (...) to overcome the case for skepticism. I conclude by drawing out philosophical implications of this discussion for our understanding of consciousness, personal identity, digital minds, existential risk, and ethical longtermism. GPI Working Paper No . 19-2022. (shrink)

Many researchers and intellectuals warn about extreme risks from artificial intelligence. However, these warnings typically came without systematic arguments in support. This paper provides an argument that AI will lead to the permanent disempowerment of humanity, e.g. human extinction, by 2100. It rests on four substantive premises which it motivates and defends: first, the speed of advances in AI capability, as well as the capability level current systems have already reached, suggest that it is practically possible to build AI systems (...) capable of disempowering humanity by 2100. Second, due to incentives and coordination problems, if it is possible to build such AI, it will be built. Third, since it appears to be a hard technical problem to build AI which is aligned with the goals of its designers, and many actors might build powerful AI, misaligned powerful AI will be built. Fourth, because disempowering humanity is useful for a large range of misaligned goals, such AI will try to disempower humanity. If AI is capable of disempowering humanity and tries to disempower humanity by 2100, then humanity will be disempowered by 2100. This conclusion has immense moral and prudential significance. (shrink)

This paper addresses a question about the moral status of Artificial Intelligence (AI): will AIs ever become moral patients? I argue that, while it is in principle possible for an intelligent machine to be a moral patient, there is no good reason to believe this will in fact happen. I start from the plausible assumption that traditional artifacts do not meet a minimal necessary condition of moral patiency: having a good of one's own. I then argue that intelligent machines are (...) no different from traditional artifacts in this respect. To make this argument, I examine the feature of AIs that enables them to improve their intelligence, i.e., machine learning. I argue that there is no reason to believe that future advances in machine learning will take AIs closer to having a good of their own. I thus argue that concerns about the moral status of future AIs are unwarranted. Nothing about the nature of intelligent machines makes them a better candidate for acquiring moral patiency than the traditional artifacts whose moral status does not concern us. (shrink)

Longtermists claim that what we ought to do is mainly determined by how our actions might affect the very long-run future. A natural objection to longtermism is that these effects may be nearly impossible to predict — perhaps so close to impossible that, despite the astronomical importance of the far future, the expected value of our present actions is mainly determined by near-term considerations. This paper aims to precisify and evaluate one version of this epistemic objection to longtermism. To that (...) end, I develop two simple models for comparing ‘longtermist’ and ‘neartermist’ interventions, incorporating the idea that it is harder to make a predictable difference to the further future. These models yield mixed conclusions: if we simply aim to maximize expected value, and don’t mind premising our choices on minuscule probabilities of astronomical payoffs, the case for longtermism looks robust. But on some prima facie plausible empirical worldviews, the expectational superiority of longtermist interventions depends heavily on these ‘Pascalian’ probabilities. So the case for longtermism may depend either on plausible but non-obvious empirical claims or on a tolerance for Pascalian fanaticism. (shrink)

Most engineers Fwork within social structures governing and governed by a set of values that primarily emphasise economic concerns. The majority of innovations derive from these loci. Given the effects of these innovations on various communities, it is imperative that the values they embody are aligned with those societies. Like other transformative technologies, artificial intelligence systems can be designed by a single organisation but be diffused globally, demonstrating impacts over time. This paper argues that in order to design for this (...) broad stakeholder group, engineers must adopt a systems thinking approach that allows them to understand the sociotechnicity of artificial intelligence systems across sociocultural domains. It claims that value sensitive design, and envisioning cards in particular, provides a solid first step towards helping designers harmonise human values, understood across spatiotemporal boundaries, with economic values, rather than the former coming at the opportunity cost of the latter. (shrink)

The standard argument to the conclusion that artificial intelligence (AI) constitutes an existential risk for the human species uses two premises: (1) AI may reach superintelligent levels, at which point we humans lose control (the ‘singularity claim’); (2) Any level of intelligence can go along with any goal (the ‘orthogonality thesis’). We find that the singularity claim requires a notion of ‘general intelligence’, while the orthogonality thesis requires a notion of ‘instrumental intelligence’. If this interpretation is correct, they cannot be (...) joined as premises and the argument for the existential risk of AI turns out invalid. If the interpretation is incorrect and both premises use the same notion of intelligence, then at least one of the premises is false and the orthogonality thesis remains itself orthogonal to the argument to existential risk from AI. In either case, the standard argument for existential risk from AI is not sound.—Having said that, there remains a risk of instrumental AI to cause very significant damage if designed or used badly, though this is not due to superintelligence or a singularity. (shrink)

Some authors have recently suggested that it is time to consider rights for robots. These suggestions are based on the claim that the question of robot rights should not depend on a standard set of conditions for ‘moral status’; but instead, the question is to be framed in a new way, by rejecting the is/ought distinction, making a relational turn, or assuming a methodological behaviourism. We try to clarify these suggestions and to show their highly problematic consequences. While we find (...) the suggestions ultimately unmotivated, the discussion shows that our epistemic condition with respect to the moral status of others does raise problems, and that the human tendency to empathise with things that do not have moral status should be taken seriously—we suggest that it produces a “derived moral status”. Finally, it turns out that there is typically no individual in real AI that could even be said to be the bearer of moral status. Overall, there is no reason to think that robot rights are an issue now. (shrink)

In philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such that thinking (...) about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

An artificial general intelligence (AGI) might have an instrumental drive to modify its utility function to improve its ability to cooperate, bargain, promise, threaten, and resist and engage in blackmail. Such an AGI would necessarily have a utility function that was at least partially observable and that was influenced by how other agents chose to interact with it. This instrumental drive would conflict with the strong orthogonality thesis since the modifications would be influenced by the AGI’s intelligence. AGIs in highly (...) competitive environments might converge to having nearly the same utility function, one optimized to favorably influencing other agents through game theory. Nothing in our analysis weakens arguments concerning the risks of AGI. (shrink)

Two interconnected surveys are presented, one of artifacts and one of designometry. Artifacts are objects, which have an originator and do not exist in nature. Designometry is a new field of study, which aims to identify the originators of artifacts. The space of artifacts is described and also domains, which pursue designometry, yet currently doing so without collaboration or common methodologies. On this basis, synergies as well as a generic axiom and heuristics for the quest of the creators of artifacts (...) are introduced. While designometry has various areas of applications, the research of methods to detect originators of artificial minds, which constitute a subgroup of artifacts, can be seen as particularly relevant and, in the case of malevolent artificial minds, as contribution to AI safety. (shrink)

The aim of this thesis is to advance a philosophically justifiable account of Artificial Moral Agency (AMA). Concerns about the moral status of Artificial Intelligence (AI) traditionally turn on questions of whether these systems are deserving of moral concern (i.e. if they are moral patients) or whether they can be sources of moral action (i.e. if they are moral agents). On the Organic View of Ethical Status, being a moral patient is a necessary condition for an entity to qualify as (...) a moral agent. This view claims that because artificial agents (AAs) lack sentience, they cannot be proper subjects of moral concern and hence cannot be considered to be moral agents. I raise conceptual and epistemic issues with regards to the sense of sentience employed on this view, and I argue that the Organic View does not succeed in showing that machines cannot be moral patients. Nevertheless, irrespective of this failure, I also argue that the entire project is misdirected in that moral patiency need not be a necessary condition for moral agency. Moreover, I claim that whereas machines may conceivably be moral patients in the future, there is a strong case to be made that they are (or will very soon be) moral agents. Whereas it is often argued that machines cannot be agents simpliciter, let alone moral agents, I claim that this argument is predicated on a conception of agency that makes unwarranted metaphysical assumptions even in the case of human agents. Once I have established the shortcomings of this “standard account”, I move to elaborate on other, more plausible, conceptions of agency, on which some machines clearly qualify as agents. Nevertheless, the argument is still often made that while some machines may be agents, they cannot be moral agents, given their ostensible lack of the requisite phenomenal states. Against this thesis, I argue that the requirement of internal states for moral agency is philosophically unsound, as it runs up against the problem of other minds. In place of such intentional accounts of moral agency, I provide a functionalist alternative, which makes conceptual room for the existence of AMAs. The implications of this thesis are that at some point in the future we may be faced with situations for which no human being is morally responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not. (shrink)

Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fieldʼs proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are safe due to (...) their internal design. (shrink)

Longtermists claim that what we ought to do is mainly determined by how our actions might affect the very long-run future. A natural objection to longtermism is that these effects may be nearly impossible to predict -- perhaps so close to impossible that, despite the astronomical importance of the far future, the expected value of our present actions is mainly determined by near-term considerations. This paper aims to precisify and evaluate one version of this epistemic objection to longtermism. To that (...) end, I develop two simple models for comparing "longtermist" and "neartermist" interventions, incorporating the idea that it is harder to make a predictable difference to the further future. These models yield mixed conclusions: if we simply aim to maximize expected value, and don't mind premising our choices on minuscule probabilities of astronomical payoffs, the case for longtermism looks robust. But on some prima facie plausible empirical worldviews, the expectational superiority of longtermist interventions depends heavily on these "Pascalian" probabilities. So the case for longtermism may depend either on plausible but non-obvious empirical claims or on a tolerance for Pascalian fanaticism. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

A probable solution of the Fermi paradox; and a necessary step in humanity’s cosmic development; is the construction of a Bracewell-Von Neumann Artificial General Intelligence. The use of BN probes is the most plausible method of initial galactic exploration and communication for advanced ET civilizations; and our own cosmic evolution lies firmly in the utilization of; and cooperation with; AGI agents. To establish these claims; I explore the most credible developmental path from carbon-based life forms to planetary civilizations and AI (...) creation. I consider the likely physical characteristics of extraterrestrial AI probes and propose ways to predict their behavior. Lastly; I ponder the possible trajectories for humanity’s cosmic future. (shrink)

We are living through an era of increased robotisation. Some authors have already begun to explore the impact of this robotisation on legal rules and practice. In doing so, many highlight potential liability gaps that might arise through robot misbehaviour. Although these gaps are interesting and socially significant, they do not exhaust the possible gaps that might be created by increased robotisation. In this article, I make the case for one of those alternative gaps: the retribution gap. This gap arises (...) from a mismatch between the human desire for retribution and the absence of appropriate subjects of retributive blame. I argue for the potential existence of this gap in an era of increased robotisation; suggest that it is much harder to plug this gap than it is to plug those thus far explored in the literature; and then highlight three important social implications of this gap. (shrink)

Die Übernahme des KI-Unternehmens DeepMind durch Google für rund eine halbe Milliarde US-Dollar signalisierte vor einem Jahr, dass von der KI-Forschung vielversprechende Ergebnisse erwartet werden. Spätestens seit bekannte Wissenschaftler wie Stephen Hawking und Unternehmer wie Elon Musk oder Bill Gates davor warnen, dass künstliche Intelligenz eine Bedrohung für die Menschheit darstellt, schlägt das KI-Thema hohe Wellen. Die Stiftung für Effektiven Altruismus (EAS, vormals GBS Schweiz) hat mit der Unterstützung von Experten/innen aus Informatik und KI ein umfassendes Diskussionspapier zu den Chancen (...) und Risiken der künstlichen Intelligenz verfasst und geht darin auf aktuelle, mittel- und langfristige Herausforderungen im Bereich der KI-Entwicklung ein. (shrink)

There is no strong reason to believe that human-level intelligence represents an upper limit of the capacity of artificial intelligence, should it be realized. This poses serious safety issues, since a superintelligent system would have great power to direct the future according to its possibly flawed motivation system. Solving this issue in general has proven to be considerably harder than expected. This paper looks at one particular approach, Oracle AI. An Oracle AI is an AI that does not act in (...) the world except by answering questions. Even this narrow approach presents considerable challenges. In this paper, we analyse and critique various methods of controlling the AI. In general an Oracle AI might be safer than unrestricted AI, but still remains potentially dangerous. (shrink)

If the intelligence of artificial systems were to surpass that of humans significantly, this would constitute a significant risk for humanity. Time has come to consider these issues, and this consideration must include progress in AI as much as insights from the theory of AI. The papers in this volume try to make cautious headway in setting the problem, evaluating predictions on the future of AI, proposing ways to ensure that AI systems will be beneficial to humans – and critically (...) evaluating such proposals. (shrink)

An advanced artificial intelligence could pose a significant existential risk to humanity. Several research institutes have been set-up to address those risks. And there is an increasing number of academic publications analysing and evaluating their seriousness. Nick Bostrom’s superintelligence: paths, dangers, strategies represents the apotheosis of this trend. In this article, I argue that in defending the credibility of AI risk, Bostrom makes an epistemic move that is analogous to one made by so-called sceptical theists in the debate about the (...) existence of God. And while this analogy is interesting in its own right, what is more interesting are its potential implications. It has been repeatedly argued that sceptical theism has devastating effects on our beliefs and practices. Could it be that AI-doomsaying has similar effects? I argue that it could. Specifically, and somewhat paradoxically, I argue that it could amount to either a reductio of the doomsayers position, or an important and additional reason to join their cause. I use this paradox to suggest that the modal standards for argument in the superintelligence debate need to be addressed. (shrink)

Suppose there are no in-principle restrictions on the contents of arbitrarily intelligent agents’ goals. According to “instrumental convergence” arguments, potentially scary things follow. I do two things in this paper. First, focusing on the influential version of the instrumental convergence argument due to Nick Bostrom, I explain why such arguments require an account of “promotion,” i.e., an account of what it is to “promote” a goal. Then, I consider whether extant accounts of promotion in the literature -- in particular, probabilistic (...) and fit-based views of promotion -- can be used to support dangerous instrumental convergence. I argue that neither account of promotion can do the work. The opposite is true: accepting either account of promotion undermines support for instrumental convergence arguments’ existentially worrying conclusions. The conclusion is that we needn’t be scared -- at least not because of arguments concerning instrumental convergence. (shrink)

The greatest existential threats to humanity stem from increasingly powerful advanced technologies. Yet the “risk potential” of such tools can only be realized when coupled with a suitable agent who; through error or terror; could use the tool to bring about an existential catastrophe. While the existential risk literature has provided many accounts of how advanced technologies might be misused and abused to cause unprecedented harm; no scholar has yet explored the other half of the agent-tool coupling; namely the agent. (...) This paper aims to correct this failure by offering a comprehensive overview of what we could call “agential riskology.” Only by studying the unique properties of different agential risk types can one acquire an accurate picture of the existential danger before us. (shrink)

Language agents are AI systems capable of understanding and responding to natural language, potentially facilitating the process of encoding human goals into AI systems. However, this paper argues that if language agents can achieve easy alignment, they also increase the risk of malevolent agents building harmful AI systems aligned with destructive intentions. The paper contends that if training AI becomes sufficiently easy or is perceived as such, it enables malicious actors, including rogue states, terrorists, and criminal organizations, to create powerful (...) AI systems devoted to their nefarious aims. Given the strong incentives for such groups and the rapid progress in AI capabilities, this risk demands serious attention. In addition, the paper highlights considerations suggesting that the negative impacts of language agents may outweigh the positive ones, including the potential irreversibility of certain negative AI impacts. The overarching lesson is that various AI-related issues are intimately connected with each other, and we must recognize this interconnected nature when addressing those issues. (shrink)

Especialistas em desenvolvimento de Inteligência Artificial prevêem que o avanço no desenvolvimento de sistemas e agentes inteligentes irá remodelar áreas vitais em nossa sociedade. Contudo, se tal avanço não for realizado de maneira prudente e crítico-reflexiva, pode resultar em desfechos negativos para a humanidade. Por este motivo, diversos pesquisadores na área têm desenvolvido uma concepção de IA robusta, benéfica e segura para a preservação da humanidade e do meio-ambiente. Atualmente, diversos dos problemas em aberto no campo de pesquisa em IA (...) advêm da dificuldade de evitar comportamentos indesejados de agentes e sistemas inteligentes, e ao mesmo tempo especificar o que realmente queremos que tais sistemas façam, especialmente quando prospectamos a possibilidade de agentes inteligentes atuarem em vários domínios ao longo prazo. É de suma importância que agentes inteligentes artificiais tenham seus valores alinhados com os valores humanos, dado ao fato de que não podemos esperar que uma IA desenvolva valores morais humanos por conta de sua inteligência, conforme é discutido na Tese da Ortogonalidade. Talvez tal dificuldade venha da maneira que estamos abordando o problema de expressar objetivos, valores e metas, utilizando de métodos cognitivos representacionais. Uma solução para este problema seria a abordagem dinâmica proposta por Dreyfus, que com base na filosofia fenomenológica mostra que a experiência humana do ser-no-mundo em diversos aspectos não é bem representada pelo método cognitivo simbólico ou conexionista, especialmente na questão de aprendizagem de valores. Uma possível abordagem para esse problema seria a utilização de modelos téoricos como SED para abordar o porblema de aprendizagem de valores em IA. (shrink)

Recent discussion of the alleged adverse consequences of space colonization by Phil Torres in this journal is critically assessed. While the concern for suffering risks should be part of any strategic discussion of the cosmic future of humanity, the Hobbesian picture painted by Torres is largely flawed and unpersuasive. Instead, there is a very real risk that the skeptical arguments will be taken too seriously and future human flourishing in space delayed or prevented.

The development of artificial intelligence will require systems of ethical decision making to be adapted for automatic computation. However, projects to implement moral reasoning in artificial moral agents so far have failed to satisfactorily address the widespread disagreement between competing approaches to moral philosophy. In this paper I argue that the proper response to this situation is to design machines to be fundamentally uncertain about morality. I describe a computational framework for doing so and show that it efficiently resolves common (...) obstacles to the implementation of moral philosophy in intelligent machines. (shrink)

The central aim of this paper is to argue that there is a meaningful sense in which a concept of rationality can apply to a city. The idea will be that a city is rational to the extent that the collective practices of its people enable diverse inhabitants to simultaneously live the kinds of life they are each trying to live. This has significant implications for the varieties of social practices that constitute being more or less rational. Some of these (...) implications may be welcome to a theorist that wants to identify collective rationality with a notion of justice, while others are unwelcome. There are some significant challenges to this use of the concept of rationality, but I claim that these challenges at the city level have parallels at the individual level, and may thus help deepen our understanding of rationality at all levels. (shrink)

Accelerating advancements in artificial intelligence (AI) have increased concerns about serious risks, including potentially catastrophic risks to humanity. Prevailing trends of AI R&D are leading to increasing humanization of AI, to the emergence of concerning behaviors, and toward possible recursive self-improvement. There has been increasing speculation that these factors increase the risk of an AI takeover of human affairs, and possibly even human extinction. The most extreme of such speculations result at least partly from anthropomorphism, but since AIs are being (...) humanized, it is challenging to disentangle valid from invalid anthropomorphic concerns. This publication identifies eight fundamentally unnatural attributes of digital AI, each of which should differentiate AI behaviors from those of biological organisms, including humans. All have the potential to accelerate AI evolution, which might increase takeover concerns; but surprisingly, most also have the potential to defuse the hypothetical conflicts that dominate takeover speculations. Certain attributes should give future AI long-term foresight and realism that are essentially impossible for humans. I conclude that claims of highly probable hostile takeover and human extinction suffer from excessive anthropomorphism and a lack of skepticism and scientific rigor. Given the evidence presented here, I propose a more plausible but still speculative future scenario: extensively humanized AIs will become vastly more capable than humans of making decisions that benefit humans, and rational people will want AI to assume progressively greater influence over human affairs. (shrink)

Decision theory aims to provide mathematical analysis of which choice one should rationally make in a given situation. Our current decision theory norms have been very successful, however, several problems have proven vexing for standard decision theory. In this paper, I show that these problems all share a similar structure and identify a class of problems which decision theory overvalues. I demonstrate that agents who follow current standard decision theory can be exploited and have their preferences reordered if offered decision (...) problems of this class. I show that preference reordering is a serious problem, which motivates my search for a decision theory which is immune to exploitation. I find Dr. Nick Smith’s theory of Rationally Negligible Probabilities cannot be exploited in this way and discuss why agents should adopt it. (shrink)

“My first long haul flight that didn’t fill up and an empty row for me. I have been blessed by the algorithm ”. The phrase ‘blessed by the algorithm’ expresses the feeling of having been fortunate in what appears on your feed on various social media platforms, or in the success or virality of your content as a creator, or in what gig economy jobs you are offered. However, we can also place it within wider public discourse employing theistic conceptions (...) of AI. Building on anthropological fieldwork into the ‘entanglements of AI and Religion’, this article will explore how ‘blessed by the algorithm’ tweets are indicative of the impact of theistic AI narratives: modes of thinking about AI in an implicitly religious way. This thinking also represents continuities that push back against the secularisation thesis and other grand narratives of disenchantment that claim secularity occurs because of technological and intellectual progress. This article will also explore new religious movements, where theistic conceptions of AI entangle technological aspirations with religious ones. (shrink)

Debates about the development of artificial superintelligence and its potential threats to humanity tend to assume that such a system would be historically unprecedented, and that its behavior must be predicted from first principles. I argue that this is not true: we can analyze multiagent intelligent systems (the best candidates for practical superintelligence) by comparing them to states, which also unite heterogeneous intelligences to achieve superhuman goals. States provide a model for several problems discussed in the literature on superintelligence, such (...) as principal-agent problems and Instrumental Convergence. Philosophical arguments about governance, therefore, provide possible solutions to these problems, or point out problems in previously suggested solutions. In particular, the liberal concept of checks and balances, and Hannah Arendt’s concept of legitimacy, describe how state behavior is constrained by the preferences of constituents that could also apply to artificial systems. However, they also point out ways in which present-day computational developments could destabilize the international order by reducing the number of decision-makers involved in state actions. Thus, interstate competition not only serves as a model for the behavior of dangerous computational intelligences but also as the impetus for their development. (shrink)

How do we ensure that future generally intelligent AI share our values? This is the value-alignment problem. It is a weighty matter. After all, if AI are neutral with respect to our wellbeing, or worse, actively hostile toward us, then they pose an existential threat to humanity. Some philosophers have argued that one important way in which we can mitigate this threat is to develop only AI that shares our values or that has values that ‘align with’ ours. However, there (...) is nothing to guarantee that this policy will be universally implemented—in particular, ‘bad actors’ are likely to flout it. In this paper, I show how the predictive processing model of the mind, currently ascendant in cognitive science, may ameliorate the value-alignment problem. In essence, I argue that there are a plurality of reasons why any future generally intelligent AI will possess a predictive processing cognitive architecture (e.g. because we decide to build them that way; because it is the only possible cognitive architecture that can underpin general intelligence; because it is the easiest way to create AI.). I also argue that if future generally intelligent AI possess a predictive processing cognitive architecture, then they will come to share our pro-moral motivations (of valuing humanity as an end; avoiding maleficent actions; etc.), regardless of their initial motivation set. Consequently, these AI will pose a minimal threat to humanity. In this way then, I conclude, the value-alignment problem is significantly ameliorated under the assumption that future generally intelligent AI will possess a predictive processing cognitive architecture. (shrink)

From his preliminary analysis in 1965, Hubert Dreyfus projected a future much different than those with which his contemporaries were practically concerned, tempering their optimism in realizing something like human intelligence through conventional methods. At that time, he advised that there was nothing “directly” to be done toward machines with human-like intelligence, and that practical research should aim at a symbiosis between human beings and computers with computers doing what they do best, processing discrete symbols in formally structured problem domains. (...) Fast-forward five decades, and his emphasis on the difference between two essential modes of processing, the unconscious yet purposeful mode fundamental to situated human cognition, and the “minded” sense of conscious processing characterizing symbolic reasoning that seems to lend itself to explicit programming, continues into the famous Dreyfus–McDowell debate. The present memorial reviews Dreyfus’ early projections, asking if the fears that punctuate current popular commentary on AI are warranted, and in light of these if he would deliver similar practical advice to researchers today. (shrink)