Impact of Artificial Intelligence, Misc

Danaher (2016) has argued that increasing robotization can lead to retribution gaps: Situation in which the normative fact that nobody can be justly held responsible for a harmful outcome stands in conflict with our retributivist moral dispositions. In this paper, we report a cross-cultural empirical study based on Sparrow’s (2007) famous example of an autonomous weapon system committing a war crime, which was conducted with participants from the US, Japan and Germany. We find that (i) people manifest a considerable willingness (...) to hold autonomous systems morally responsible, (ii) partially exculpate human agents when interacting with such systems, and that more generally (iii) the possibility of normative responsibility gaps is indeed at odds with people’s pronounced retributivist inclinations. We discuss what these results mean for potential implications of the retribution gap and other positions in the responsibility gap literature. (shrink)

The transformative power of artificial intelligence (AI) is coming to philosophy—the only question is the degree to which philosophers will harness it. In this paper, we argue that the application of AI tools to philosophy could have an impact on the field comparable to the advent of writing, and that it is likely that philosophical progress will significantly increase as a consequence of AI. The role of philosophers in this story is not merely to use AI but also to help (...) develop it and theorize about it. In fact, we argue that philosophers have a prima facie obligation to spend significant effort in doing so, at least insofar as they should spend effort philosophizing. (shrink)

Nudge is a popular public policy tool that harnesses well-known biases in human judgement to subtly guide people’s decisions, often to improve their choices or to achieve some socially desirable outcome. Thanks to recent developments in artificial intelligence (AI) methods new possibilities emerge of how and when our decisions can be nudged. On the one hand, algorithmically personalized nudges have the potential to vastly improve human daily lives. On the other hand, blindly outsourcing the development and implementation of nudges to (...) “black box” AI systems means that the ultimate reasons for why such nudges work, that is, the underlying human cognitive processes that they harness, will often be unknown. In this paper, we unpack this concern by considering a series of examples and case studies that demonstrate how AI systems can learn to harness biases in human judgment to reach a specified goal. Drawing on an analogy in a philosophical debate concerning the methodology of economics, we call for the need of an interdisciplinary oversight of AI systems that are tasked and deployed to nudge human behaviours. (shrink)

Can the evidence provided by software systems meet the standard of proof for civil or criminal cases, and is it individualized evidence? Or, to the contrary, do software systems exclusively provide bare statistical evidence? In this paper, we argue that there are cases in which evidence in the form of probabilities computed by software systems is not bare statistical evidence, and is thus able to meet the standard of proof. First, based on the case of State v. Loomis, we investigate (...) recidivism predictions provided by software systems used in the courtroom. Here, we raise problems for software systems that provide predictions that are based on bare statistical evidence. Second, by examining the case of People v. Chubbs, we argue that the statistical evidence provided by software systems in cold hit DNA cases may in some cases suffice for individualized evidence, on a view on which individualized evidence is evidence that normically supports the relevant proposition (Smith, in Mind 127:1193–1218, 2018). (shrink)

Since the beginning of the 21st century, technologies like neural networks, deep learning and “artificial intelligence” (AI) have gradually entered the artistic realm. We witness the development of systems that aim to assess, evaluate and appreciate artifacts according to artistic and aesthetic criteria or by observing people’s preferences. In addition to that, AI is now used to generate new synthetic artifacts. When a machine paints a Rembrandt, composes a Bach sonata, or completes a Beethoven symphony, we say that this is (...) neither original nor real art, but simply the complex imitation and reproduction of existing products of human culture. We face the old question concerning the nature of creativity: what kind of recombination of ideas, unusual analogies, and conceptual connections are considered the mark of originality? Can AI produce artworks? Could machines reach a point at which we consider them genuinely creative? We also need to investigate the challenges posed by AI-art to the notion of authoriality: Who is the author of an artificially generated artifact? An artificial system could be considered just an artist’s and a programmer’s tool. However, we are also fascinated by the idea of autonomous artificial creativity in the aesthetic domain, as a manifestation of highly intelligent behavior. This paper will try to define some key questions around what could it mean to consider a machine creative or even equipped with artistic intentionality. (shrink)

In exploring the intra-active, relational and material connections between humans and non- humans, proponents of posthumanism advocate a questioning of the ‘human’ beyond its traditional anthropocentric conceptualization. By referring specifically to controversial developments in mHealth applications, this paper critically diverges from posthuman accounts of human/non-human assemblages. Indeed, we argue that, rather than ‘dissolving’ the human subject, the power of assemblages lie in their capacity to highlight the antagonisms and contradictions that inherently affirm the importance of the subject. In outlining this (...) claim, we propose a turn from the posthuman to the inhuman as a way of understanding the contemporary landscape of (digital) health. (shrink)

This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an analysis of what arbitrariness means in this context. Second, it argues that arbitrariness is not of moral concern except when special circumstances apply. However, when the same algorithm or different algorithms based on the same data are used in multiple contexts, a person may be arbitrarily excluded from a broad range of opportunities. The third contribution is to explain (...) why this systemic exclusion is of moral concern and to offer a solution to address it. (shrink)

This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought forward. Learning without (...) prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems. Keywords: Hebbian learning; synaptic plasticity; neural networks; self-organization; brain; reinforcement; sensory processing; robot control . (shrink)

Forms of Artificial Intelligence (AI) are already being deployed into clinical settings and research into its future healthcare uses is accelerating. Despite this trajectory, more research is needed regarding the impacts on patients of increasing AI decision making. In particular, the impersonal nature of AI means that its deployment in highly sensitive contexts-of-use, such as in healthcare, raises issues associated with patients’ perceptions of (un) dignified treatment. We explore this issue through an experimental vignette study comparing individuals’ perceptions of being (...) treated in a dignified and respectful way in various healthcare decision contexts. Participants were subject to a 2 (human or AI decision maker) x 2 (positive or negative decision outcome) x 2 (diagnostic or resource allocation healthcare scenario) factorial design. We found evidence of a “human bias” (i.e., a preference for human over AI decision makers) and an “outcome bias” (i.e., a preference for positive over negative outcomes). However, we found that for perceptions of respectful and dignified interpersonal treatment, it matters more who makes the decisions in diagnostic cases and it matters more what the outcomes are for resource allocation cases. We also found that humans were consistently viewed as appropriate decision makers and AI was viewed as dehumanizing, and that participants perceived they were treated better when subject to diagnostic as opposed to resource allocation decisions. Thematic coding of open-ended text responses supported these results. We also outline the theoretical and practical implications of these findings. (shrink)

Although machine intelligence is increasingly employed in healthcare, the realm of decision-making in medical ethics remains largely unexplored from a technical perspective. We propose an approach based on fuzzy cognitive maps (FCMs), which builds on Beauchamp and Childress’ prima-facie principles. The FCM’s weights are optimized using a genetic algorithm to provide recommendations regarding the initiation, continuation, or withdrawal of medical treatment. The resulting model approximates the answers provided by our team of medical ethicists fairly well and offers a high degree (...) of interpretability. Possible applications of such a system include informal guidance on medical ethics dilemmas as well as educational purposes. (shrink)

Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...) difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence? (shrink)

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of synthetic audiovisual (...) media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

This chapter examines the possibility of using AI technologies to improve human moral reasoning and decision-making, especially in the context of purchasing and consumer decisions. We characterize such AI technologies as artificial ethics assistants (AEAs). We focus on just one part of the AI-aided moral improvement question: the case of the individual who wants to improve their morality, where what constitutes an improvement is evaluated by the individual’s own values. We distinguish three broad areas in which an individual might think (...) their own moral reasoning and decision-making could be improved: one’s actions, character, or other evaluable attributes fall short of one’s values and moral beliefs; one sometimes misjudges or is uncertain about what the right thing to do is in particular situations, given one’s values; one is uncertain about some fundamental moral questions or recognizes a possibility that some of one’s core moral beliefs and values are mistaken. We sketch why one might think that AI tools could be used to support moral improvement in those areas, and describe two types of assistance: preparatory assistance, including advice and training supplied in advance of moral deliberation; and on-the-spot assistance, including on-the-spot advice and facilitation of moral functioning over the course of moral deliberation. Then, we turn to some of the ethical issues that AEAs might raise, looking in particular at three under-appreciated problems posed by the use of AI for moral self-improvement: namely, reliance on sensitive moral data; the inescapability of outside influences on AEAs; and AEA usage prompting the user to adopt beliefs and make decisions without adequate reasons. (shrink)

One of the primary, if not most critical, difficulties in the design and implementation of autonomous systems is the black-boxed nature of the decision-making structures and logical pathways. How human values are embodied and actualised in situ may ultimately prove to be harmful if not outright recalcitrant. For this reason, the values of stakeholders become of particular significance given the risks posed by opaque structures of intelligent agents (IAs). This paper explores how decision matrix algorithms, via the belief-desire-intention model for (...) autonomous vehicles, can be designed to minimize the risks of opaque architectures. Primarily through an explicit orientation towards designing for the values of explainability and verifiability. In doing so, this research adopts the Value Sensitive Design (VSD) approach as a principled framework for the incorporation of such values within design. VSD is recognized as a potential starting point that offers a systematic way for engineering teams to formally incorporate existing technical solutions within ethical design, while simultaneously remaining pliable to emerging issues and needs. It is concluded that the VSD methodology offers at least a strong enough foundation from which designers can begin to anticipate design needs and formulate salient design flows that can be adapted to the changing ethical landscapes required for utilisation in autonomous vehicles. (shrink)

Contemporary research into the values, bias, and prejudices within “Artificial Intelligence” tends to operate in a crux of scholarship in computer science and engineering, sociology, philosophy, and science and technology studies (STS). Even so, getting the STEM fields to recognize and accept the importance of certain kinds of knowledge— the social, experiential kinds of knowledge— remains an ongoing struggle. Similarly, religious scholarship is still very often missing from these conversations because many in the STEM fields and the general public feel (...) that religion and technoscientific investigations are and should be separate fields of inquiry. Here I demonstrate that experiential knowledge and religious, even occult beliefs are always already embedded within and crucial to understanding the sociotechnical imaginaries animating many technologies, particularly in the areas of “AI.” In fact, it is precisely the unwillingness of many to confront these facts which allow for both the problems of prejudice embedded in algorithmic systems, and for the hype-laden marketing of the corporations and agencies developing them. This same hype then intentionally obfuscates the actions of both the systems and the people who create them, while confounding and oppressing those most often made subject to them. Further, I highlight a crucial continuity between bigotry and systemic social projects (eugenics, transhumanism, and “supercrip” narratives), revealing their foundation in white supremacist colonialist myths of whose and which kinds of lives count as “truly human.” We will examine how these myths become embedded into the religious practices, technologies, and social frameworks in and out of which “AI” and algorithms are developed, employing a composite theoretical lens made from tools such as intersectionality, ritual theory, intersubjectivity, daemonology, postphenomenology, standpoint epistemology, and more. This theoretical apparatus recontextualizes our understanding of how mythologies and rituals of professionalization, disciplinarity, and dominant epistemological hierarchies animate concepts such as knowledge formation, expertise, and even what counts as knowledge. This recontextualization is then deployed to suggest remedies for research, public policy, and general paths forward in “AI.” By engaging in both the magico-religious valences and the lived experiential expertise of marginalized people, these systems can be better understood, and their harms anticipated and curtailed. (shrink)

Democracy is widely praised as a great achievement of humanity. However, in recent years there has been an increasing amount of concern that its functioning across the world may be eroding. In response, efforts to combat such change are emerging. Considering the pervasiveness of technology and its increasing capabilities, it is no surprise that there has been much focus on the use of artificial intelligence (AI) to this end. Questions as to how AI can be best utilized to extend the (...) reach of democracy to currently non-democratic countries, how the involvement in the democratic process of certain demographic groups (e.g. ethnic minorities, women, and young people) can be increased, etc. are frequent topics of discussion. In this article I would like not merely to question whether this is desirable but rather argue that we should be trying to envisage ways of using AI for the exact opposite purpose: that of replacing democratic systems with better alternatives. (shrink)

Sebastian Sunday Grève calls on us to decide what kind of life with machines we want.

With the transition of the pandemic-gripped labor market en masse to remote capabilities to avert from a national or international economic meltdown, a concern arises that many job seekers simply cannot fit into the new roles being developed and implemented. Beyond the loss of on-site work, the market is unable to reverse the loss of many roles that are, and have been, taken over by artificial (computer) intelligence systems. The “business-as-usual” mentality that many have come to associate with pre-pandemic life (...) supposedly took these losses into account, much to various societies’ detriment during this international crisis. And unlike at the turn of the millennium, the market has come to realize that it cannot function without advanced computer intelligence (CI) systems. Arguments can be made that humanity’s currently most sophisticated CI systems come nowhere near replicating the nuances that would prompt one to classify the system as being “human-like,” and that they will remain this way for the foreseeable future. However, what is conveniently ignored in this assessment is how not even three generations have passed since computer systems became an integral aspect of daily life. While the loss of work for humans as a result of this advancement of technology may not immediately reach concerning levels, it still begs the question of how society should react to a lack of non-specialized work and the value of “humanness” in the labor market. This work intends to explore these concepts and provide anticipatory guidance on how humanity should adapt. (shrink)

A concise but informative overview of AI ethics and policy. -/- Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring homeowners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, and voters in liberal democracies? Authored by experts in fields (...) ranging from computer science and law to philosophy and cognitive science, this book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues such as transparency, bias, liability, privacy, and regulation. -/- Both business and government have integrated algorithmic decision support systems into their daily operations, and the book explores the implications for our lives as citizens. For example, do we take it on faith that a machine knows best in approving a patient's health insurance claim or a defendant's request for bail? What is the potential for manipulation by targeted political ads? How can the processes behind these technically sophisticated tools ever be transparent? The book discusses such issues as statistical definitions of fairness, legal and moral responsibility, the role of humans in machine learning decision systems, “nudging” algorithms and anonymized data, the effect of automation on the workplace, and AI as both regulatory tool and target. (shrink)

Artificial Intelligence (AI) is a diverse technology. It is already having significant effects on many jobs and sectors of the economy and over the next ten to twenty years it will drive profound changes in the way New Zealanders live and work. Within the workplace AI will have three dominant effects. This report (funded by the New Zealand Law Foundation) addresses: Chapter 1 Defining the Technology of Interest; Chapter 2 The changing nature and value of work; Chapter 3 AI and (...) the employment relationship; Chapter 4 Consumers, professions and society. The report includes recommendations to the New Zealand Government. (shrink)

A recent wave of academic and popular publications say that utopia is within reach: Automation will progress to such an extent and include so many high-skill tasks that much human work will soon become superfluous. The gains from this highly automated economy, authors suggest, could be used to fund a universal basic income (UBI). Today's employees would live off the robots' products and spend their days on intrinsically valuable pursuits. I argue that this prediction is unlikely to come true. Historical (...) precedent speaks against it, but the main problem is that the prediction fundamentally misunderstands how capitalism works—its incentives to increase or decrease production, its principles of income allocation, and the underlying conception of merit. (shrink)

An increasing number of automated and artificially intelligent (AI) systems make medical treatment recommendations, including “personalized” recommendations, which can deviate from standard care. Legal scholars argue that following such nonstandard treatment recommendations will increase liability in medical malpractice, undermining the use of potentially beneficial medical AI. However, such liability depends in part on lay judgments by jurors: When physicians use AI systems, in which circumstances would jurors hold physicians liable? To determine potential jurors’ judgments of liability, we conducted an online (...) experimental study of a nationally representative sample of 2,000 U.S. adults. Each participant read one of four scenarios in which an AI system provides a treatment recommendation to a physician. The scenarios varied the AI recommendation (standard or nonstandard care) and the physician’s decision (to accept or reject that recommendation). Subsequently, the physician’s decision caused a harm. Participants then assessed the physician’s liability. Our results indicate that physicians who receive advice from an AI system to provide standard care can reduce the risk of liability by accepting, rather than rejecting, that advice, all else equal. However, when an AI system recommends nonstandard care, there is no similar shielding effect of rejecting that advice and so providing standard care. The tort law system is unlikely to undermine the use of AI precision medicine tools and may even encourage the use of these tools. (shrink)

Coined in 1984 at the American Association of Artificial intelligence (now the Association for the Advancement of Artificial Intelligence or AAAI), the various boom and bust periods of AI research and funding lead AI researchers Marvin Minsky and Roger Schank to refer to the then-impending bust period as an AI Winter. Canadian AI researcher Daniel Crevier describes the phenomenon as a domino effect that begins with cynicism in the AI research community that then trickles to mass media and finally to (...) funding bodies. The result is a freeze in serious AI research and development. This initial pessimism is mainly attributed to the overly ambitious promises that AI can yield with the actual results being far humbler than expectations. (shrink)

The following aesthetic discussion examines in a philosophical-scientific way the relationship between computation and artistic creativity. Currently, there is a criticism about the possible artistic creativity that an algorithm could have. Supporting the above, the term computer-generated art (CG-Art) defined by Margaret Boden would seem to have no exponents yet. Moreover, it has been pointed out that, rather than a matter of primitive technological development, CG-Art would have in its very foundations the inability to exist. This, because art is considered (...) as one of the most unique and exclusive human manifestations of our species. On the contrary, I propose that the denial of CG-Art has an anthropocentric bias. For this, I use the recent studies that, from the cognitive sciences, have been carried out on artistic creativity. In this way, I intend to convince the reader that behind the denial of the creative artistic capacity to the machines, a negationist mysticism of the current scientific advances necessarily lies. (shrink)

Set aside fanciful doomsday speculations about AI. Even lower-level AIs, while otherwise friendly and providing us a universal basic income, would be able to do all our jobs. Also, we would over-rely upon AI assistants even in our personal lives. Thus, John Danaher argues that a human crisis of moral passivity would result However, I argue firstly that if AIs are posited to lack the potential to become unfriendly, they may not be intelligent enough to replace us in all our (...) jobs. If instead they are intelligent enough to replace us, the risk they become unfriendly increases, given that they would not need us and humans would just compete for valuable resources. Their hostility will not promote our moral passivity. Secondly, the use of AI assistants in our personal lives will become a problem only if we rely on them for almost all our decision-making and motivation. But such a (maximally) pervasive level of dependence raises the question of whether humans would accept it, and consequently whether the crisis of passivity will arise. (shrink)

アメリカと世界は、過去1世紀の人口過剰な人口増加から崩壊し、現在は第3世界の人々のために崩壊しています。資源の消費と40億ca.2100の追加は、産業文明を崩壊させ、驚異的な規模で飢餓、病気、暴力と戦 争をもたらすでしょう。地球は毎年表土の少なくとも1%を失うので、2100に近づくにつれて、その食糧栽培能力のほとんどはなくなりました。何十億人もの人が死んで、核戦争は確実です。アメリカでは、これは大規 模な移民と移民の生殖によって、民主主義によって可能になった虐待と相まって、非常に加速されています。堕落した人間性は、民主主義と多様性の夢を犯罪と貧困の悪夢に変えます。中国は、利己主義を制限する独裁政権 を維持する限り、アメリカと世界を圧倒し続けるだろう。崩壊の根本的な原因は、私たちの生来の心理学が現代世界に適応できないことであり、人々は無関係な人を共通の利益を持っているかのように扱う。人権の考え方は 、左翼が第三世界の母性によって地球の無慈悲な破壊から注意を引くために促進する邪悪なファンタジーです。これは、基本的な生物学と心理学の無知に加えて、民主的な社会を支配する部分的に教育を受けた人々のソーシ ャルエンジニアリングの妄想につながります。一人の人を助けた場合、誰かに危害を加える人はいませんが、無料のランチはなく、誰もが消費するアイテムが修復を超えて地球を破壊することを理解している人はほとんどい ません。その結果、至る所の社会政策は持続不可能であり、利己主義に対する厳格な統制なしに、すべての社会が一つ一つ無政府状態または独裁に崩壊する。最も基本的な事実は、ほとんど言及されていないが、貧困層のか なりの割合を貧困から引き上げ、そこに留めるのに十分な資源がアメリカや世界に存在しないことである。これを行う試みは、アメリカを破産させ、世界を破壊することです。私たちの遺伝的品質と同様に、食料を生産する 地球の能力は毎日低下します。そして今、いつものように、貧しい人々の最大の敵は他の貧しい人々であり、金持ちではありません。劇的かつ即時の変化がなければ、アメリカの崩壊や民主主義システムに続く国を防ぐ望み はありません。.

数年前、私は本のタイトルから、あるいは少なくとも章のタイトルから、どのような哲学的な間違いが起こり、どのくらいの頻度で分かることができるところまで達しました。名目上の科学的な研究の場合、これらは主に哲 学的なワックスや作品の意味または長期的な意義に関する一般的な結論を引き出そうとする特定の章に制限される可能性があります-。しかし、通常、事実の科学的な問題は、これらの事実が何を意味するのかについて、哲 学的なちんぷんかんぷんと寛大に絡み合っています。ヴィトゲンシュタインが約80年前に科学的な問題と様々な言語ゲームによる記述の間で述べた明確な区別はめったに考慮されないので、1つは交互に科学に驚き、その 支離滅裂な分析に失望しています。だから、このボリュームです。 多かれ少なかれ私たちのような心を作るのであれば、合理性と思考の2つのシステム(二重プロセス理論)の理解のための論理的な構造を持っている必要があります。このことについて哲学するならば、事実の科学的問題と 、問題となっている文脈における言語の仕組みの哲学的問題と、還元主義とサイエンティズムの落とし穴を避ける方法の区別を理解する必要がありますが、カーツワイルは、ほとんどの行動学生と同様に、ほとんど手がかり がない。彼はモデル、理論、概念、そして説明したいという衝動に魅了されていますが、ヴィトゲンシュタインは、私たちが記述する必要があり、理論、概念などは、明確なテストを持っている限り価値のある言語(言語ゲ ーム)を使用する方法にすぎないことを示しました(明確な真実主義者、またはジョン・サール(AIの最も有名な批評家)が言うのが好きです。私は最近の著作でこれに関するスタートを提供しようとしました。 現代の2つのシス・エムスの見解から人間の行動のための包括的な最新の枠組みを望む人は、私の著書「ルートヴィヒ・ヴィトゲンシュタインとジョン・サールの第2回(2019)における哲学、心理学、ミンと言語の論 理的構造」を参照することができます。私の著作の多くにご興味がある人は、運命の惑星における「話す猿--哲学、心理学、科学、宗教、政治―記事とレビュー2006-2019 第3回(2019)」と21世紀4日(2019年)の自殺ユートピア妄想st Century 4th ed (2019)などを見ることができます。 .

In his engaging book, James MacFarlane details the emergence of Technological Human Enhancement Advocacy (THEA) and provides a detailed ethnographic account of this phenomenon. Specifically, he aims to outline how transhumanism, as a specific offshoot of THEA, has “come to represent an enduring set of techno-optimistic ideas surrounding the future of humanity, with its advocates seeking to transcend limits of the body and mind according to an unwavering Enlightenment-derived faith in science, reason and individual freedom” (pg. 3).

Purpose This paper aims to formalize long-term trajectories of human civilization as a scientific and ethical field of study. The long-term trajectory of human civilization can be defined as the path that human civilization takes during the entire future time period in which human civilization could continue to exist. -/- Design/methodology/approach This paper focuses on four types of trajectories: status quo trajectories, in which human civilization persists in a state broadly similar to its current state into the distant future; catastrophe (...) trajectories, in which one or more events cause significant harm to human civilization; technological transformation trajectories, in which radical technological breakthroughs put human civilization on a fundamentally different course; and astronomical trajectories, in which human civilization expands beyond its home planet and into the accessible portions of the cosmos. -/- Findings Status quo trajectories appear unlikely to persist into the distant future, especially in light of long-term astronomical processes. Several catastrophe, technological transformation and astronomical trajectories appear possible. -/- Originality/value Some current actions may be able to affect the long-term trajectory. Whether these actions should be pursued depends on a mix of empirical and ethical factors. For some ethical frameworks, these actions may be especially important to pursue. (shrink)

Compartmentalizing our distinct personal identities is increasingly difficult in big data reality. Pictures of the person we were on past vacations resurface in employers’ Google searches; LinkedIn which exhibits our income level is increasingly used as a dating web site. Whether on vacation, at work, or seeking romance, our digital selves stream together. One result is that a perennial ethical question about personal identity has spilled out of philosophy departments and into the real world. Ought we possess one, unified identity (...) that coherently integrates the various aspects of our lives, or, incarnate deeply distinct selves suited to different occasions and contexts? At bottom, are we one, or many? The question is not only palpable today, but also urgent because if a decision is not made by us, the forces of big data and surveillance capitalism will make it for us by compelling unity. Speaking in favor of the big data tendency, Facebook’s Mark Zuckerberg promotes the ethics of an integrated identity, a single version of selfhood maintained across diverse contexts and human relationships. This essay goes in the other direction by sketching two ethical frameworks arranged to defend our compartmentalized identities, which amounts to promoting the dis-integration of our selves. One framework connects with natural law, the other with language, and both aim to create a sense of selfhood that breaks away from its own past, and from the unifying powers of big data technology. (shrink)

Today’s ethics of privacy is largely dedicated to defending personal information from big data technologies. This essay goes in the other direction; it considers the struggle to be lost, and explores two strategies for living after privacy is gone. First, total exposure embraces privacy’s decline, and then contributes to the process with transparency. All personal information is shared without reservation. The resulting ethics is explored through a big data version of Robert Nozick’s Experience Machine thought experiment. Second, transient existence responds (...) to privacy’s loss by ceaselessly generating new personal identities, which translates into constantly producing temporarily unviolated private information. The ethics is explored through Gilles Deleuze’s metaphysics of difference applied in linguistic terms to the formation of the self. Comparing the exposure and transience alternatives leads to the conclusion that today’s big data reality splits the traditional ethical link between authenticity and freedom. Exposure provides authenticity, but negates human freedom. Transience provides freedom, but disdains authenticity. (shrink)

In the article, the author analyzes the problems of human-computer communication in the context of artificial intelligence, augmented reality and a Turing methodology for comparing the capabilities of artificial and natural intelligence in a dialogue. It is argued that the tool with which the computer and humans communicate is of no less importance than the computer program with which the dialogue is conducted. As an example of the implementation of such visualization, the project “E.LENA” of a digital television anchor created (...) at the Sberbank Robotics Laboratory was considered. The author gives his own version of Turing's specific test to study the features of non- verbal communication interfaces between a person and a computer. The key idea formulated by the author for further discussion is to provide artificial intelligence with visual avatar in order to avoid the alienation of man and computer and the loss of semantic information during its transmission from computer to person. (shrink)

In this paper, I outline and investigate the notion of computational beliefs: beliefs formed on the basis of a deliverance from a machine learning algorithm. Given the increased usage of such algorithms through smart devices, such beliefs are becoming increasingly common in everyday life. First, I argue that such beliefs can be successful by outlining particular examples that possess epistemic properties taken to be indicative of successful beliefs. I then outline how computational beliefs are best understood as a form of (...) what Sosa describes as instrumental beliefs. As such, it may be thought that computational beliefs hold little epistemological interest insofar as they are reducible to more basic epistemic processes that are already the focus of epistemological attention. However, in the final section, I argue that computational beliefs hold epistemological importance insofar as they have specific epistemically normative repercussions i.e. they give rise to epistemic responsibility gaps. (shrink)

Purpose of the article is to identify the religious factor in the teaching of transhumanism, to determine its role in the ideology of this flow of thought and to identify the possible limits of technology interference in human nature. Theoretical basis. The methodological basis of the article is the idea of transhumanism. Originality. In the foreseeable future, robots will be able to pass the Turing test, become “electronic personalities” and gain political rights, although the question of the possibility of machine (...) consciousness and self-awareness remains open. In the face of robots, people create their assistants, evolutionary competition with which they will almost certainly lose with the initial data. For successful competition with robots, people will have to change, ceasing to be people in the classical sense. Changing the nature of man will require the emergence of a new – posthuman – anthropology. Conclusions. Against the background of scientific discoveries, technical breakthroughs and everyday improvements of the last decades, an anthropological revolution has taken shape, which made it possible to set the task of creating inhumanly intelligent creatures, as well as changing human nature, up to discussing options for artificial immortality. The history of man ends and the history of the posthuman begins. We can no longer turn off this path, however, in our power to preserve our human qualities in the posthuman future. The theme of the soul again reminded of itself, but from a different perspective – as the theme of consciousness and self-awareness. It became again relevant in connection with the development of computer and cloud technologies, artificial intelligence technologies, etc. If a machine ever becomes a "man", then can a man become a "machine"? However, even if such a hypothetical probability would turn into reality, we cannot talk about any form of individual immortality or about the continuation of existence in a different physical form. A digital copy of the soul will still remain a copy, and I see no fundamental possibility of isolating a substrate-independent mind from the human body. Immortality itself is necessary not so much for stopping someone’s fears or encouraging someone’s hopes, but for the final solution of a religious issue. However, the gods hold the keys to heaven hard and are unlikely to admit our modified descendants there. (shrink)

La numérisation va de pair avec un changement fondamental des méthodes qui a le potentiel de changer la pensée, les décisions et les actions des gens. Sur la base de cette thèse, une structure est proposée pour l’analyse de le changement de méthode induit par la numérisation. L’article donne un bref aperçu des forces motrices, des formes et des effets de ce changement méthodologique.

Digitalization goes hand in hand with a fundamental change in methods that has the potential to change people’s thinking, decisions and actions. Departing from this thesis, a structure is proposed for the analysis of the method change induced by digitalization. The article provides a brief outline of the driving forces, the forms and the effects of this method change.

Die Digitalisierung geht mit einem fundamentalen Methodenwandel einher, dem das Potential innewohnt, das Denken, Entscheiden und Handeln der Menschen nachhaltig zu verändern. Ausgehend von dieser These wird eine gliedernde Struktur zur näheren Betrachtung des durch die Digitalisierung induzierten Methodenwandels vorgeschlagen. Der Artikel bietet dazu einen kurzen Abriss über die Triebfedern, die Formen und die Auswirkungen dieses Methodenwandels.

The contemporary world is characterised by the pervasive presence of digital technologies that play a part in almost every aspect of our life. An urgent and much-debated issue consists in evaluating the repercussions of these technologies on our human condition. In this paper, I tackle this issue from the standpoint of Husserlian phenomenology. I argue that phenomenology offers a contribution to our understanding of the implications of digital technologies, in the light of its analysis of the essential structures of human (...) experience, and especially of its corporeal grounding. In the light of this analysis, it is possible to investigate the ways in which these essential structures are affected by digital technologies. In particular, it is possible to highlight the ways in which some digital technologies involve a process of disembodiment or simply a superficial embodiment of experience. (shrink)

In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will (...) lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature. (shrink)

Some years ago, I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...) philosophical gibberish as to what these facts mean. The clear distinctions which Wittgenstein described some 80 years ago between scientific matters and their descriptions by various language games are rarely taken into consideration, and so one is alternately wowed by the science and dismayed by its incoherent analysis. So it is with this volume. -/- If one is to create a mind more or less like ours, one needs to have a logical structure for rationality and an understanding of the two systems of thought (dual process theory). If one is to philosophize about this, one needs to understand the distinction between scientific issues of fact and the philosophical issue of how language works in the context at issue, and of how to avoid the pitfalls of reductionism and scientism, but Kurzweil, like most students of behavior, is largely clueless. He is enchanted by models, theories, and concepts, and the urge to explain, while Wittgenstein showed us that we only need to describe, and that theories, concepts etc., are just ways of using language (language games) which have value only insofar as they have a clear test (clear truthmakers, or as John Searle (AI’s most famous critic) likes to say, clear Conditions of Satisfaction (COS)). I have attempted to provide a start on this in my recent writings. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019) . (shrink)

Alguns anos atrás, cheguei ao ponto onde eu normalmente pode dizer a partir do título de um livro, ou pelo menos a partir dos títulos do capítulo, que tipos de erros filosóficos serão feitas e com que freqüência. No caso de obras nominalmente científicas, estas podem ser largamente restritas a certos capítulos que enceram filosóficos ou tentam tirar conclusões gerais sobre o significado ou significado a longo prazo do trabalho. Normalmente entretanto as matérias científicas do fato são misturado generosa com (...) o jargão filosófico a respeito do que estes fatos significam. As distinções claras que Wittgenstein descreveu cerca de 80 anos atrás entre questões científicas e suas descrições por vários jogos de linguagem são raramente levados em consideração, e assim um é alternadamente impressionados pela ciência e desanimado por sua incoerente Análise. Assim é com este volume. -/- Se alguém é para criar uma mente mais ou menos como a nossa, é preciso ter uma estrutura lógica para a racionalidade e uma compreensão dos dois sistemas de pensamento (teoria do processo dual). Se uma delas é filosofar sobre isso, é preciso entender a distinção entre questões científicas de fato e a questão filosófica de como a linguagem funciona no contexto em questão, e de como evitar as armadilhas do reducionismo e do cientismo, mas Kurzweil, como mais estudantes de comportamento, é em grande parte c sem noção. Ele está encantado com modelos, teorias e conceitos, e o impulso de explicar, enquanto Wittgenstein nos mostrou que só precisamos descrever, e que as teorias, conceitos etc, são apenas maneiras de usar a linguagem (jogos de linguagem) que têm valor apenas na medida em que eles têm uma clara teste (claro que os verdadeiros, ou como John Searle (crítico mais famoso da AI) gosta de dizer, claro condições de satisfação (COS)). Eu tentei fornecer um começo nisto em meus escritos recentes. -/- Aqueles que desejam um quadro até à data detalhado para o comportamento humano da opinião moderna dos dois sistemas consultar meu livros Falando Macacos 3ª Ed (2019), A Estrutura Lógica da Filosofia, Psicologia, Mente e Linguagem em Ludwig Wittgenstein e John Searle 2a Ed (2019), Suicídio Pela Democracia,4aEd(2019), Entendendo as Conexões entre Ciência, Filosofia, Psicologia, Religião, Política e Economia Artigos e Análises 2006-2019 (2019), Ilusões Utópicas Suicidas no 21St século 5a Ed (2019), A Estrutura Lógica do Comportamento Humano (2019), e A Estrutura Lógica da Consciência (2019) y outros. (shrink)

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used to (...) further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination. (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)

Interactions between an intelligent software agent and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality, we frame these interactions (...) as instances of an ISA whose reward depends on actions performed by the user. Such agents benefit by steering the user’s behaviour towards outcomes that maximise the ISA’s utility, which may or may not be aligned with that of the user. Video games, news recommendation aggregation engines, and fitness trackers can all be instances of this general case. Our analysis facilitates distinguishing various subcases of interaction, as well as second-order effects that might include the possibility for adaptive interfaces to induce behavioural addiction, and/or change in user belief. We present these types of interaction within a conceptual framework, and review current examples of persuasive technologies and the issues that arise from their use. We argue that the nature of the feedback commonly used by learning agents to update their models and subsequent decisions could steer the behaviour of human users away from what benefits them, and in a direction that can undermine autonomy and cause further disparity between actions and goals as exemplified by addictive and compulsive behaviour. We discuss some of the ethical, social and legal implications of this technology and argue that it can sometimes exploit and reinforce weaknesses in human beings. (shrink)

Predictions about autonomous weapon systems are typically thought to channel fears that drove all the myths about intelligence embodied in matter. One of these is the idea that the technology can get out of control and ultimately lead to horrifi c consequences, as is the case in Mary Shelley’s classic Frankenstein. Given this, predictions about AWS are sometimes dismissed as science-fiction fear-mongering. This paper considers several analogies between AWS and other weapon systems and ultimately offers an argument that nuclear weapons (...) and their effect on the development of modern asymmetrical warfare are the best analogy to the introduction of AWS. The fi nal section focuses on this analogy and offers speculations about the likely consequences of AWS being hacked. These speculations tacitly draw on myths and tropes about technology and AI from popular fi ction, such as Frankenstein, to project a convincing model of the risks and benefi ts of AWS deployment. (shrink)

Since the Enlightenment, there have been advocates for the rationalizing efficiency of enlightened sovereigns, bureaucrats, and technocrats. Today these enthusiasms are joined by calls for replacing or augmenting government with algorithms and artificial intelligence, a process already substantially under way. Bureaucracies are in effect algorithms created by technocrats that systematize governance, and their automation simply removes bureaucrats and paper. The growth of algorithmic governance can already be seen in the automation of social services, regulatory oversight, policing, the justice system, and (...) the military. However, there have also always been justified democratic and economic criticisms of autocracy, bureaucracy, technocracy, and algorithmic governance. Bureaucrats, technocrats, and algorithms embody biases that tend to serve the interests of elites, and all require transparency and democratic accountability, oversight individual citizens are ill equipped to exercise. As state apparatuses are increasingly automated, mechanisms for collective action and democratic oversight also need to be automated. Algorithms and cyborg citizenry will enable a posthuman democracy. Democratically accountable algorithmic governance, enabled by artificial intelligence and human enhancement, can automate bottom-up citizen surveillance, inform debate, aggregate decision making, and ensure the efficient working of the gradually withering state. As paid work disappears and we transition to a postcapitalist economy with a universal basic income, market mechanisms can be replaced with democratic planning. Indeed, only algorithmic governance can secure our future against accelerating threats from technological innovation. (shrink)

Some years ago I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...) philosophical gibberish as to what these facts mean. The clear distinctions which Wittgenstein described some 80 years ago between scientific matters and their descriptions by various language games are rarely taken into consideration, and so one is alternately wowed by the science and dismayed by its incoherent analysis. So it is with this volume. -/- If one is to create a mind more or less like ours, one needs to have a logical structure for rationality and an understanding of the two systems of thought (dual process theory). If one is to philosophize about this, one needs to understand the distinction between scientific issues of fact and the philosophical issue of how language works in the context at issue, and of how to avoid the pitfalls of reductionism and scientism, but Kurzweil, like nearly all students of behavior, is largely clueless. He, is enchanted by models, theories, and concepts, and the urge to explain, while Wittgenstein showed us that we only need to describe, and that theories, concepts etc., are just ways of using language (language games) which have value only insofar as they have a clear test (clear truthmakers, or as John Searle (AI’s most famous critic) likes to say, clear Conditions of Satisfaction (COS)). I have attempted to provide a start on this in my recent writings, such as The Logical Structure of Consciousness (behavior, personality, rationality, higher order thought, intentionality) (2016) and The Logical Structure of Philosophy, Psychology, Mind and Language as Revealed in the Writings of Ludwig Wittgenstein and John Searle (2016). Those interested in all my writings in their most recent versions may consult my e-book Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2016 662p (2016). I will give a very brief presentation of this framework since I have described it in great detail in many recent papers and several books, available on this site and others. -/- Also, as usual in ‘factual’ accounts of AI/robotics, he gives no time to the very real threats to our privacy, safety and even survival from the increasing ‘androidizing’ of society which is prominent in other authors (Bostrum, Hawking etc.) and frequent in scifi and films, so I make a few comments on the quite possibly suicidal utopian delusions of ‘nice’ androids, humanoids, democracy, diversity, and genetic engineering. -/- I take it for granted that technical advances in electronics, robotics and AI will occur, resulting in profound changes in society. However, I think the changes coming from genetic engineering are at least as great and potentially far greater, as they will enable us to utterly change who we are. And it will be feasible to make supersmart/super strong servants by modifying our genes or those of other monkeys. As with other technology, any country that resists will be left behind. But will it be socially and economically feasible to implement biobots or superhumans on a massive scale? And even if so, it does not seem remotely possible, economically or socially to prevent the collapse of industrial civilization. So, ignoring the philosophical mistakes in this volume as irrelevant, and directing our attention only to the science, what we have here is another suicidal utopian delusion rooted in a failure to grasp basic biology, psychology and human ecology, the same delusions that are destroying America and the world. I see a remote possibility the world can be saved, but not by AI/robotics,CRISPR, nor by democracy and equality. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019). (shrink)

In this paper, we focus on the most efficacious AI applications for life extension and anti-aging at three expected stages of AI development: narrow AI, AGI and superintelligence. First, we overview the existing research and commercial work performed by a select number of startups and academic projects. We find that at the current stage of “narrow” AI, the most promising areas for life extension are geroprotector-combination discovery, detection of aging biomarkers, and personalized anti-aging therapy. These advances could help currently living (...) people reach longevity escape velocity and survive until more advanced AI appears. When AI comes close to human level, the main contribution to life extension will come from AI integration with humans through brain-computer interfaces, integrated AI assistants capable of autonomously diagnosing and treating health issues, and cyber systems embedded into human bodies. Lastly, we speculate about the more remote future, when AI reaches the level of superintelligence and such life-extension methods as uploading human minds and creating nanotechnological bodies may become possible, thus lowering the probability of human death close to zero. We suggest that medical AI based superintelligence could be safer than, say, military AI, as it may help humans to evolve into part of the future superintelligence via brain augmentation, uploading, and a network of self-improving humans. Medical AI’s value system is focused on human benefit. (shrink)