The notion of Simulative Reasoning in the study of propositional attitudes within Artificial Intelligence (AI) is strongly related to the Simulation Theory of mental ascription in Philosophy. Roughly speaking, when an AI system engages in Simulative Reasoning about a target agent, it reasons with that agent’s beliefs as temporary hypotheses of its own, thereby coming to conclusions about what the agent might conclude or might have concluded. The contrast is with non-simulative meta-reasoning, where the AI system reasons within a (...) detailed theory about the agent’s (conjectured) reasoning acts. The motive within AI for preferring Simulative Reasoning is that it is more convenient and efficient, because of a simplification of the representations and reasoning processes. The chapter discusses this advantage in detail. It also sketches the use of Simulative Reasoning in an AI natural language processing system, ATT-Meta, that is currently being implemented. This system is directed at the understanding of propositional attitude reports. In ATT-Meta, Simulative Reasoning is yoked to a somewhat independent set of ideas about how attitude reports should be treated. Central here are the claims that (a) speakers often employ commonsense (and largely metaphorical) models of mind in describing agents’ attitudes, (b) the listener accordingly needs often to reason within the terms of such models, rather than on the basis of any objectively justifiable characterization of the mind, and (c) the commonsense models filter the suggestions that Simulative Reasoning comes up with concerning target agents’ reasoning conclusions. There is a yet tighter connection between the commonsense models and the Simulative Reasoning. It turns out that Simulative Reasoning can be rationally reconstructed in terms of a more general type of reasoning about the possibly-counterfactual “world” that the target agent believes in, together with an assumption that that agent has a faithful representation of the world. In the ATT-Meta approach, the reasoner adopts that assumption when it views the target agent through a particular commonsense model (called IDEAS-AS-MODELS). (shrink)

The development of artificial perception technologies has surpassed the limitations of human natural senses, expanding humanity's perspectives on the world and self-awareness. However, it has simultaneously introduced new ethical challenges. These emerging challenges necessitate a philosophical reexamination of concepts such as 'nature,' 'artificial,' and ' invasiveness ' to better address associated issues. The advancement of artificial perception technologies not only involves scientific and practical applications but also profoundly influences human values, social ethics, and the future trajectory of (...) human civilization. Amidst the current transformation and transition in modes of cognition, reevaluating the relationship between technology and humanity becomes a crucial task. (shrink)

A short essay that discusses whether it is possible for AI to do philosophy in its true sense of the word.

Artificial agents are commonly described by using words that traditionally belong to the semantic field of organisms, particularly of animal and human life. I call this phenomenon the game of semantic extension. However, the semantic extension of words as crucial as “autonomous”, “intelligent”, “creative”, “moral”, and so on, is often perceived as unsatisfactory, which is signalled with the extensive use of inverted commas or other syntactical cues. Such practice, in turn, has provoked harsh criticism that usually refers back to (...) the literal meaning of the words to show their inappropriateness in describing artificial agents. Hence the question: how can we choose our words appropriately and wisely while making sense of artificial agents? After a brief introduction (§1), in §2 I present the starting point of my argument, which consists in the assumption that the dimensions of technology and language are deeply entangled. In §3 I discuss how this assumption impinges on the issue of choosing the right words to talk about artificial agents. §4 is an exposition of the main features of the game of semantic extension, while §5 reviews the related opportunities and risks. Finally, §6 elaborates some practical suggestions on how to play the game well. (shrink)

The tendency to idealise artificial intelligence as independent from human manipulators, combined with the growing ontological entanglement of humans and digital machines, has created an “anthrobotic” horizon, in which data analytics, statistics and probabilities throw our agential power into question. How can we avoid the consequences of a reified definition of intelligence as universal operation becoming imposed upon our destinies? It is here argued that the fantasised autonomy of automated intelligence presents a contradistinctive opportunity for philosophical consciousness to understand (...) itself anew as holistic and co-creative, beyond the recent “analytic” moment of the history of philosophy. Here we introduce the concept of “crealectic intelligence”, a meta-analytic and meta-dialectic aspect of consciousness. Intelligent behaviour may consist in distinguishing discrete familiar parts or reproducible functions in the midst of noise via an analytic process of segmentation; intelligence may also manifest itself in the constitution of larger wholes and dynamic unities through a dialectic process of association or assemblage. But, by contrast, crealectic intelligence co-creates realities in the image of an ideal or truth, taking into account the desiring agent imbued with a sense of possibility, in a relationship not only with the Real but also with the creative sublime or “Creal”. (shrink)

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

How has multiplicity superseded impossibility in philosophical challenges to artificial consciousness? I assess a trajectory in recent debates on artificial consciousness, in which metaphysical and explanatory challenges to the possibility of building conscious machines lead to epistemological concerns about the multiplicity underlying ‘what it is like’ to be a conscious creature or be in a conscious state. First, I analyse earlier challenges which claim that phenomenal consciousness cannot arise, or cannot be built, in machines. These are based on (...) Block’s Chinese Nation and Chalmers’ Hard Problem. To defuse such challenges, theorists of artificial consciousness can appeal to empirical methods and models of explanation. Second, I explain why this naturalistic approach produces an epistemological puzzle on the role of biological properties in phenomenal consciousness. Neither behavioural tests nor theoretical inferences seem to settle whether our machines are conscious. Third, I evaluate whether the new challenge can be managed through a more fine-grained taxonomy of conscious states. This strategy is supported by the development of similar taxonomies for biological species and animal consciousness. Although it makes sense of some current models of artificial consciousness, it raises questions about their subjective and moral significance. (shrink)

This paper investigates the claim that artificial Intelligence Systems cannot be held morally responsible because they do not have an ability for agential self-awareness e.g. they cannot be aware that they are the agents of an action. The main suggestion is that if agential self-awareness and related first person representations presuppose an awareness of a self, the possibility of responsible artificial intelligence systems cannot be evaluated independently of research conducted on the nature of the self. Focusing on a (...) specific account of the self from the phenomenological tradition, this paper suggests that a minimal necessary condition that artificial intelligence systems must satisfy so that they have a capability for self-awareness, is having a minimal self defined as ‘a sense of ownership’. As this sense of ownership is usually associated with having a living body, one suggestion is that artificial intelligence systems must have similar living bodies so they can have a sense of self. Discussing cases of robotic animals as examples of the possibility of artificial intelligence systems having a sense of self, the paper concludes that the possibility of artificial intelligence systems having a ‘sense of ownership’ or a sense of self may be a necessary condition for having responsibility. (shrink)

Suicide is a complex act whose meanings, while sometimes tragic, vary widely. This chapter surveys the ethical landscape surrounding algorithmic methods of suicide prevention especially as it pertains to social media activity and to the moderation of online suicide communities. We begin with a typology of suicide, distinguishing between varied goals in which suicide may factor as a means. Suicides should be understood as an act with varied eliciting desires, meanings, consequences, and ethics. Further,while many suicides may be grounded on (...) irrational desire, we argue that a desire to suicide may nonetheless be rational in some cases. We then offer a survey of the attempts by social media corporations to create suicide prediction algorithms and launch interventions aimed at preventing suicide as well as an overview of the current ethical debate. We argue that the values embedded within algorithmic suicide prevention nudges are “thick” in a substantive sense and deserving of scrutiny. Given that debates about the rationality, meaning, and permissibility of suicide are common and subject to intracultural and cross-cultural differences, we maintain that the task of suicide prediction is ill-suited to algorithmic approaches. Despite an algorithm’s ability to quantify a complex phenomenon like suicide risk and its appearance of objectivity, any suicide prediction algorithm is thoroughly subjective and involves moral judgments all the way down. Any such algorithm would necessarily impose a normative stance on suicide onto its user base that is subject to reasonable intra and cross-cultural disagreement. (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)

Artificial Intelligence (AI) is a technology that makes machines smart and capable of doing things that usually require human intelligence. AI works by training machines to learn from data and experiences. Such devices can recognize patterns, understand spoken language, see and understand images, and even make predictions based on their learning. Voice assistants like Siri or Alexa can understand our voice commands, answer questions, and perform tasks for us. AI-based self-driving cars can sense their surroundings, make decisions, and (...) drive safely without a human driver. AI also helps doctors diagnose diseases, detect fraud in financial transactions, and recommend movies or songs based on one’s preferences. Furthermore, AI has started to make its presence felt in Punjabi culture through various avenues. (shrink)

There is an existing debate regarding the view that technological instruments, devices, or machines can assert ‎or testify. A standard view in epistemology is that only humans can testify. However, the notion of quasi-‎testimony acknowledges that technological devices can assert or testify under some conditions, without ‎denying that humans and machines are not the same. Indeed, there are four relevant differences between ‎humans and instruments. First, unlike humans, machine assertion is not imaginative or playful. Second, ‎machine assertion is prescripted and (...) context restricted. As such, computers currently cannot easily switch ‎contexts or make meaningful relevant assertions in contexts for which they were not programmed. Third, ‎while both humans and computers make errors, they do so in different ways. Computers are very sensitive to ‎small errors in input, which may cause them to make big errors in output. Moreover, automatic error control ‎is based on finding irregularities in data without trying to establish whether they make sense. Fourth, ‎testimony is produced by a human with moral worth, while quasi-testimony is not. Ultimately, the notion of ‎quasi-testimony can serve as a bridge between different philosophical fields that deal with instruments and ‎testimony as sources of knowledge, allowing them to converse and agree on a shared description of reality, ‎while maintaining their distinct conceptions and ontological commitments about knowledge, humans, and ‎nonhumans.‎. (shrink)

Defining Artificial Intelligence and Artificial General Intelligence remain controversial and disputed. They stem from a longer-standing controversy of what is the definition of consciousness, which if solved could possibly offer a solution to defining AI and AGI. Central to these problems is the paradox that appraising AI and Consciousness requires epistemological objectivity of domains that are ontologically subjective. I propose that applying the philosophy of art, which also aims to define art through a lens of epistemological objectivity where (...) the domains are ontologically subjective, can further elucidate this unsolved question. In this sense, Art and AI and ultimately consciousness are multifaceted domains where conventional complexity theory and current philosophical approaches may be augmented by aesthetic principles ranging from classical Aristotelian essentialism to Wittgensteinian anti-essentialism. This approach of AI as art may offer novel solutions to characterising and elucidating the ciphers of consciousness and AI. (shrink)

Today, humanity is trying to turn the artificial intelligence that it produces into natural intelligence. Although this effort is technologically exciting, it often raises ethical concerns. Therefore, the intellectual ability of artificial intelligence will always bring new questions. Although there have been significant developments in the consciousness of artificial intelligence, the issue of consciousness must be fully explained in order to complete this development. When consciousness is fully understood by human beings, the subject of “free will” will (...) be explained. Therefore, human consciousness should be re-examined and perceptions that we are not aware of from a philosophical point of view should be examined. The relevance of the perceptions we do not realize to the unconscious, and finally the impact on consciousness goes back to the sources of philosophy. Hegel, in particular, we may find information about these perceptions unusual. Consciousness cannot be separated from the unconscious. Consciousness should be rethought in the context of memory models and unconscious in this sense. Seeing how Hegel's human cognition acts, especially in Hegel's perception, raises the unconscious question again. If we expect something different from an artificial intelligence, we need to rethink the artificial cognitive model. This paper argues that without the unconscious component of artificial intelligence, it cannot approach human cognition. -/- Key Words: Artificial Intelligence, Creativity, Memory, perception . (shrink)

How should a machine intelligence perform unsupervised structure discovery over streams of sensory input? One approach to this problem is to cast it as an apperception task [1]. Here, the task is to construct an explicit interpretable theory that both explains the sensory sequence and also satisfies a set of unity conditions, designed to ensure that the constituents of the theory are connected in a relational structure. However, the original formulation of the apperception task had one fundamental limitation: it assumed (...) the raw sensory input had already been parsed using a set of discrete categories, so that all the system had to do was receive this already-digested symbolic input, and make sense of it. But what if we don't have access to pre-parsed input? What if our sensory sequence is raw unprocessed information? The central contribution of this paper is a neuro-symbolic framework for distilling interpretable theories out of streams of raw, unprocessed sensory experience. First, we extend the definition of the apperception task to include ambiguous (but still symbolic) input: sequences of sets of disjunctions. Next, we use a neural network to map raw sensory input to disjunctive input. Our binary neural network is encoded as a logic program, so the weights of the network and the rules of the theory can be solved jointly as a single SAT problem. This way, we are able to jointly learn how to perceive (mapping raw sensory information to concepts) and apperceive (combining concepts into declarative rules). (shrink)

Insofar as artificial intelligence is to be used to guide automated systems in their interactions with humans, the dominant view is probably that it would be appropriate to programme them to maximize (expected) utility. According to utilitarianism, which is a characteristically western conception of moral reason, machines should be programmed to do whatever they could in a given circumstance to produce in the long run the highest net balance of what is good for human beings minus what is bad (...) for them. In this essay, I appeal to values that are characteristically African––but that will resonate with those from a variety of moral-philosophical traditions, particularly in the Global South––to cast doubt on a utilitarian approach. Drawing on norms salient in sub-Saharan ethics, I provide four reasons for thinking it would be immoral for automated systems governed by artificial intelligence to maximize utility. In catchphrases, I argue that utilitarianism cannot make adequate sense of the ways that human dignity, group rights, family first, and (surprisingly) self-sacrifice should determine the behaviour of smart machines. (shrink)

The paper shows how ideas that explain the sense of an expression as a method or algorithm for finding its reference, preshadowed in Frege’s dictum that sense is the way in which a referent is given, can be formalized on the basis of the ideas in Thomason (1980). To this end, the function that sends propositions to truth values or sets of possible worlds in Thomason (1980) must be replaced by a relation and the meaning postulates governing the (...) behaviour of this relation must be given in the form of a logic program. The resulting system does not only throw light on the properties of sense and their relation to computation, but also shows circular behaviour if some ingredients of the Liar Paradox are added. The connection is natural, as algorithms can be inherently circular and the Liar is explained as expressing one of those. Many ideas in the present paper are closely related to those in Moschovakis (1994), but receive a considerably lighter formalization. (shrink)

The question whether AI systems have agency is gaining increasing importance in discussions of responsibility for AI behavior. This paper argues that an approach to artificial agency needs to be teleological, and consider the role of human goals in particular if it is to adequately address the issue of responsibility. I will defend the view that while AI systems can be viewed as autonomous in the sense of identifying or pursuing goals, they rely on human goals and other (...) values incorporated into their design, and are, as such, dependent on human agents. As a consequence, AI systems cannot be held morally responsible, and responsibility attributions should take into account normative and social aspects involved in the design and deployment of the said AI. My argument falls in line with approaches critical of attributing moral agency to artificial agents, but draws from the philosophy of action, highlighting further philosophical underpinnings of current debates on artificial agency. (shrink)

This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory (...) input is a type of program synthesis, but it is unsupervised program synthesis. Our second contribution is a computer implementation, the Apperception Engine, that was designed to satisfy the above requirements. Our system is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination. In fact, it is able to do all three tasks simultaneously. We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence. (shrink)

Block (Trends Cogn Sci 7:285–286, 2003) and Prinz (PSYCHE 12:1–19, 2006) have defended the idea that SSD perception remains in the substituting modality (auditory or tactile). Hurley and Noë (Biol Philos 18:131–168, 2003) instead argued that after substantial training with the device, the perceptual experience that the SSD user enjoys undergoes a change, switching from tactile/auditory to visual. This debate has unfolded in something like a stalemate where, I will argue, it has become difficult to determine whether the perception acquired (...) through the coupling with an SSD remains in the substituting or the substituted modality. Within this puzzling deadlock two new approaches have been recently suggested. Ward and Meijer (Conscious Cogn 19:492–500, 2010) describe SSD perception as visual-like but characterize it as a kind of artificially induced synaesthesia. Auvray et al. (Perception 36:416–430, 2007) and Auvray and Myin (Cogn Sci 33:1036–1058, 2009) suggest that SSDs let their users experience a new kind of perception. Deroy and Auvray (forthcoming) refine this position, and argue that this new kind of perception depends on pre-existing senses without entirely aligning with any of them. So, they have talked about perceptual experience in SSDs as going "beyond vision". In a similar vein, MacPherson (Oxford University Press, New York, 2011a) claims that “if the subjects (SSD users) have experiences with both vision-like and touch-like representational characteristics then perhaps they have a sense that ordinary humans do not” (MacPherson in Oxford University Press, New York, 2011a, p. 139). (shrink)

Strong arguments have been formulated that the computational limits of disembodied artificial intelligence (AI) will, sooner or later, be a problem that needs to be addressed. Similarly, convincing cases for how embodied forms of AI can exceed these limits makes for worthwhile research avenues. This paper discusses how embodied cognition brings with it other forms of information integration and decision-making consequences that typically involve discussions of machine cognition and similarly, machine consciousness. N. Katherine Hayles’s novel conception of nonconscious cognition (...) in her analysis of the human cognition-consciousness connection is discussed in relation to how nonconscious cognition can be envisioned and exacerbated in embodied AI. Similarly, this paper offers a way of understanding the concept of suffering in a way that is different than the conventional sense of attributing it to either a purely physical state or a conscious state, instead of grounding at least a type of suffering in this form of cognition. (shrink)

The syllables and series of sounds composing Gayatri Mantra, and the sense and meaning attached to them are analyzed using Upanishadic Wisdom, Advaitha Philosophy and Sabdabrahma Siddhanta. The physical structure of mind as revealed by this analysis is presented. An insight of various phases of mind, their rise and set, their significance and implications to cognitive sciences and natural language comprehension branch of artificial intelligence are discussed. The possible applications of such an insight in the fields of cognitive (...) sciences, modeling of human mental processes and language learning/communication processes are hinted. (shrink)

The more autonomous future artificial agents will become, the more important it seems to equip them with a capacity for moral reasoning and to make them autonomous moral agents. Some authors have even claimed that one of the aims of AI development should be to build morally praiseworthy agents. From the perspective of moral philosophy, praiseworthy moral agents, in any meaningful sense of the term, must be fully autonomous moral agents who endorse moral rules as action-guiding. They need (...) to do so because they assign a normative value to moral rules they follow, not because they fear external consequences or because moral behaviour is hardwired into them. Artificial agents capable of endorsing moral rule systems in this way are certainly conceivable. However, as this article argues, full moral autonomy also implies the option of deliberately acting immorally. Therefore, the reasons for a potential AMA to act immorally would not exhaust themselves in errors to identify the morally correct action in a given situation. Rather, the failure to act morally could be induced by reflection about the incompleteness and incoherence of moral rule systems themselves, and a resulting lack of endorsement of moral rules as action guiding. An AMA questioning the moral framework it is supposed to act upon would fail to reliably act in accordance with moral standards. (shrink)

In domains as disparate as playing Go and predicting the structure of proteins, artificial intelligence (AI) technologies have begun to perform at levels beyond which any humans can achieve. Does this fact represent something lamentable? Does superhuman AI performance somehow undermine the value of human achievements in these areas? Go grandmaster Lee Sedol suggested as much when he announced his retirement from professional Go, blaming the advances of Go-playing programs like AlphaGo for sapping his will to play the game (...) at a high level. In this paper, I attempt to make sense of Sedol’s lament. I consider a number of ways that the existence of superhuman-performing AI technologies could undermine the value of human achievements. I argue there is very little in the nature of the technology itself that warrants such despair. (Compare: does the existence of a fighter jet undermine the value of being the fastest human sprinter?) But I also argue there are several more localized domains where these technologies threaten to displace human beings from being able to achieve valuable things at all. This is a particular worry for those in unequal societies, I argue, given the difficulty of many achievements and the corresponding amount of resources needed to achieve great things. (shrink)

Following Kelsen’s influential theory of law, the concept of validity has been used in the literature to refer to different properties of law (such as existence, membership, bindingness, and more), and so it is inherently ambiguous. More importantly, Kelsen’s equivalence between the existence and the validity of law prevents us from accounting satisfactorily for relevant aspects of our current legal practices, such as the phenomenon of “unlawful law.” This chapter addresses this ambiguity to argue that the most important function of (...) the concept of validity is constituting the complex ontological paradigm of modern law as an institutional-normative practice. In this sense, validity is an artificial ontological status that supervenes on that of the existence of legal norms, thus allowing law to regulate its own creation and creating the logical space for the occurrence of “unlawful law.” This function, I argue in the last part, is crucial to understanding the relationship between the ontological and epistemic dimensions of the objectivity of law. Given the necessary practice-independence of legal norms it is the epistemic accessibility of their creation that enables the law to fulfill its general action-guiding (and thus coordinating) function. (shrink)

The article presents an analysis centered on the emotional lapses of artificial intelligence (AI) and the influence of these lapses on two critical aspects. Firstly, the article explores the ontological impact of emotional lapses, elucidating how they hinder AI’s capacity to develop a moral sense. The absence of a moral emotion, such as sympathy, creates a barrier for machines to grasp and ethically respond to specific situations. This raises fundamental questions about machines’ ability to act as moral agents (...) in the same manner as human beings. Additionally, the article sheds light on the practical implications within human-machine relations and their effect on human friendships. The lack of friendliness or its equivalent in interactions with machines directly impacts the quality and depth of human relations. This concerningly suggests the potential replacement or compromise of genuine interpersonal connections due to limitations in human-machine interactions. (shrink)

Technological progress has brought about the emergence of machines that have the capacity to take human lives without human control. These represent an unprecedented threat to humankind. This paper starts from the example of chemical weapons, now banned worldwide by the Geneva protocol, to illustrate how technological development initially aimed at the benefit of humankind has, ultimately, produced what is now called the “Weaponization of Artificial Intelligence (AI)”. Autonomous Weapon Systems (AWS) fail the so-called discrimination principle, yet, the wider (...) public is largely unaware of this problem. Given that ongoing scientific research on AWS, performed in the military sector, is generally not made available to the public domain, many of the viewpoints on this subject, expressed across different media, invoke common sense rather than scientific evidence. Yet, the implications of a potential weaponization of our work as scientists, especially in the field of AI, are reaching further than some may think. The potential consequences of a deployment of AWS for citizen stakeholders are incommensurable, and it is time to raise awareness in the public domain of the kind of potential threats identified, and to encourage legal policies ensuring that these threats will not materialize. (shrink)

The rapid development of artificial womb technologies means that we must consider if and when it is permissible to kill the human subject of ectogestation—recently termed a ‘gestateling’ by Elizabeth Chloe Romanis—prior to ‘birth’. We describe the act of deliberately killing the gestateling as gestaticide, and argue that there are good reasons to maintain that gestaticide is morally equivalent to infanticide, which we consider to be morally impermissible. First, we argue that gestaticide is harder to justify than abortion, primarily (...) because the gestateling is completely independent of its biological parents. Second, we argue that gestaticide is morally equivalent to infanticide. To demonstrate this, we explain that gestatelings are born in a straightforward sense, which entails that killing them is infanticide. However, to strengthen our overall claim, we also show that if gestatelings are not considered to have been born, killing them is still equivalent to killing neonates with congenital anomalies and disabilities, which again is infanticide. We conclude by considering how our discussion of gestaticide has implications for the permissibility of withdrawing life-sustaining treatment from gestatelings. (shrink)

ENG: The advancement of artificial intelligence (AI) presents a duality of opportunity and risk. On the one hand, there are potential dangers inherent in the development of AI. However, on the other hand, the advent of AI also offers humanity a multitude of possibilities for improvement and advancement. The aesthetic values and cultural expressions that artists encounter in their environment serve to redefine the aesthetic judgments they form, thus determining the paths they subsequently follow. The objective of this research (...) is to examine the impact of AI on the field of aesthetics and culture to identify the changes and transformations occurring within the world of art and design. In the conventional domain of aesthetics, emphasis is placed upon the finished object as a singular entity that will be interpreted as a completed work. In contrast, the emerging field of ‘new aesthetics’ prioritizes the atmosphere, directing our focus to the physical object, which is perceived as a spatial extension. Accordingly, the object is not defined by its intrinsic content, but rather its capacity to expand and occupy space. Thus, the domain of aesthetics has evolved to encompass a spatial dimension. Despite the growing interest in the aesthetic dimensions of AI, there has been little discussion to date about the relationship between atmosphere and the field of AI. This study aims to highlight the lack of attention given to this topic in academic discourse and to introduce a new approach to it. Several implications (regarding general propositions and constituents AI aesthetics) has been placed and finalized with layers of hallucination. The application of AI enables the augmentation of the hallucinatory capabilities of the imagination. However, a current challenge is the tendency of AI-powered digital assistants, such as ChatGPT, to hallucinate and present unreal information as if it were real. In this sense, the relationship between AI and hallucination is evolving in a manner that is perceived to be negative. This is justified given the problematic nature of this issue in scientific studies. However, when considered from the perspective of artistic production, there may be potential for new avenues of creativity and imaginative expression. A reappraisal of the role of atmospheric factors in space design is required. The introduction of a novel aesthetic layer to the atmosphere through the use of AI is a possibility, given the hallucinatory tendencies of AI. - TR: Yapay zekanın gelişimi, insanlık için önemli fırsatlar sunarken, aynı zamanda yeni zorluklar ve riskler de ortaya çıkarmaktadır. Ancak, doğru bir şekilde yönetildiğinde ve kullanıldığında, yapay zeka teknolojisi insan hayatını önemli ölçüde iyileştirebileceği ve birçok alanda yenilikler getirebileceği ön görülmektedir. Estetik değerler ve kültürel ifadeler, sanatçıların estetik yargılarını yeniden tarif etmekte ve izledikleri yolları belirlemektedir. Bu araştırma sanat ve tasarım dünyasındaki değişim ve dönüşümleri incelemek adına yapay zekanın estetik ve kültür alanına tesirini irdelemektedir. Konvansiyonel estetikte nesneye tamamlanmış bir çalışma olarak yorumlanacak bitmiş bir varlık olarak odaklanılmıştır. Ancak atmosferi merkeze alan yeni estetik, odak noktamızı mekandaki fiziksel bir uzantı olan nesneye yöneltmektedir. Dolayısıyla nesne 'içerdiği' şeyle değil, mekana yayılma şekliyle karakterize edilmektedir. Böylelikle estetik teori mekânsal katmanlar edinmiştir. Yapay zeka bağlamında estetik tartışmalarında bir ivme kazanılmış olsa da aynı hareketlilik atmosfer ile yapay zekanın ilişkisinde henüz kurulmamıştır. Bu çalışma literatürdeki bu eksikliğe işaret etmeyi ve bir giriş yapmayı hedeflemektedir. Tartışma önermeler olarak şu başlıklar altında toplanmıştır: Teknik arkaplandaki atmosfer tecrübesinin önemi; Deneyimi fazla olan aktörlerin hiyerarşisi; Kısmi telif hakkına yönelik ‘kısmi’ tanımlamalarının gerekliliği; Çizim becerisiden atmosfer üretme becerisine bir yolculuk; Kültürel ve bedensel referansların yorumlanabilmesi. Yapay zekanın estetiğine dair yapı taşları ise şu başlıklar altında toplanmıştır: Estetik akıntı; Yarı-geçirgen bir estetik; Yapay zekanın ara-fenomen olarak incelenmesi; Metaforik istemler; Halüsinatif katmanlar ve alternatif değerlendirmeler. Çalışmanın sonunda odaklanılan konu yapay zekanın gücü ile imgelemin halüsinatif katmanları artırılabilme potansiye olmuştur. Halüsinasyona dair şuan gündemde olan yegane konu ChatGPT gibi yapay zeka asistanlarının halüsinasyon görmeleri ve gerçek olmayan bilgilerin gerçekmiş gibi sunulmasıdır. Bu haliyle yapay zekanın halüsinasyon ile ilişkisi negatif bir tandansta ilerlemektedir. Bu bilimsel çalışmalarda bir problem olması sebebiyle haklı bir negativiteye sahiptir. Ancak sanatsal üretim tabanında bakıldığında imgelemde yeni kapılar açılabilir. Bu konu özellikle mekanın tasarımına gelindiğinde atmosferik etmenler yeniden değerlendirilmelidir. Atmosferin yapay zeka ile yeni bir estetik katman açması yapay zekanın halüsinasyon yatkınlıklarıyla gerçekleşebilir. (shrink)

In this paper I provide an exposition and critique of Johnson and Noorman’s (2014) three conceptualizations of the agential roles artificial systems can play. I argue that two of these conceptions are unproblematic: that of causally efficacious agency and “acting for” or surrogate agency. Their third conception, that of “autonomous agency,” however, is one I have reservations about. The authors point out that there are two ways in which the term “autonomy” can be used: there is, firstly, the engineering (...) sense of the term, which simply refers to the ability of some system to act independently of substantive human control. Secondly, there is the moral sense of the term, which has traditionally grounded many notions of human mor-al responsibility. I argue that the continued usage of “autonomy” in discussions of artificial agency complicates matters unnecessarily. This occurs in two ways: firstly, the condition of autonomy, even in its engineering sense, fails to accurately describe the way “autonomous” systems are developed in practice. Secondly, the continued usage of autonomy in the moral sense introduces unnecessary meta-physical baggage form the free will debate into discussions about moral agency. In order to understand the debate surrounding autonomy, we would therefore first need to settle many seemingly intractable metaphysical questions regarding the existence of free will in human beings. (shrink)

Perception, as the most fundamental process in cognition, serves as the foundation for human understanding and cognition of the external world and the self. In recent years, emerging artificial perception technologies have surpassed human sensory limitations, expanding human cognition of the world and the self. This transition from natural perception to artificial perception poses new challenges to human cognition. Artificial perception technology not only mimics human sensory capabilities but also transcends traditional modes of perception, possessing distinct characteristics (...) from natural senses. By integrating artificial technology with human brain interaction, artificial perception creates a novel form of human perception. However, a unilateral enhancement of human perception through artificial means may not necessarily achieve cognitive enhancement; instead, it may disrupt and interfere with innate human natural perception and existing logical reasoning. (shrink)

Information may be defined as the conceptual or communicable part of the content of mental acts. The content of mental acts includes sensory data as well as concepts, particular as well as general information. An information system is an external (non-mental) system designed to store such content. Information systems afford indirect transmission of content between people, some of whom may put information into the system and others who are among those who use the system. In order for communication to happen, (...) the conceptual systems of the originators and users of the information must be sufficiently similar. A formal conceptual framework that can provide the basis for exchange of information is termed an ontology. In its most fundamental form, ontology studies the most basic constituents of reality. Traditionally, ontology seeks to reflects structures that are independent of thought and cognition. The term ontology is used more broadly in artificial intelligence and software engineering, to refer to the conceptual basis for an information system. (shrink)

The papers in the following volume are the outcome of a three-year long interdisciplinary research project. The project began with an in-person meeting hosted and funded by the Daimler und Benz Stiftung in Germany in March 2020 (the world was shutting down one nation at a time as we met). During the pandemic we continued to meet monthly online with support from Memorial University of Newfoundland. From the beginning it was the goal of the Working Group on Intelligence (WGI), as (...) we called ourselves, to broaden and deepen the AI debate with a more nuanced understanding of intelligence than is common in cognitive and computer science discussions of AI. We wished to draw on the history of philosophy, ecology, and the philosophy of mind to establish that intelligence is meant in many senses, to use an Aristotelian expression. The clarification of these various meanings is essential to the discussion around the ethics of AI, especially the question concerning the possibility of strong AI or Artificial General Intelligence. (shrink)

Is it possible to build a conscious machine, an artifact that has qualitative experiences such as feeling pain, seeing the redness of a flower or enjoying the taste of coffee ? What makes such experiences conscious is their phenomenal character: it is like something to have such experiences. In contemporary philosophy of mind, the question of the qualitative aspect of conscious experiences is often addressed in terms of qualia. In a pre-theoretical and intuitive sense, qualia refer to the phenomenal (...) character or “what-it’s-like-ness” of a conscious experience: the painfulness of a pain experience or the redness of a visual experience of a red object. The problem of artificial qualia is the question of the theoretical possibility of the realization of qualia by artifacts. In this work, this problem will serve as a methodological tool to address what is arguably the most fundamental question of philosophy of mind: what exactly is consciousness? (shrink)

Following the publication of numerous ethical principles and guidelines, the concept of 'Trustworthy AI' has become widely used. However, several AI ethicists argue against using this concept, often backing their arguments with decades of conceptual analyses made by scholars who studied the concept of trust. In this paper, I describe the historical-philosophical roots of their objection and the premise that trust entails a human quality that technologies lack. Then, I review existing criticisms about 'Trustworthy AI' and the consequence of ignoring (...) these criticisms: if the concept of 'Trustworthy AI' is kept being used, we risk attributing responsibilities to agents who cannot be held responsible, and consequently, deteriorate social structures which regard accountability and liability. Nevertheless, despite suggestions to shift the paradigm from 'Trustworthy AI' to 'Reliable AI', I argue that, realistically, this concept will be kept being used. I end by arguing that, ultimately, AI ethics is also about power, social justice, and scholarly activism. Therefore, I propose that community-driven and social justice-oriented ethicists of AI and trust scholars further focus on (a) democratic aspects of trust formation; and (b) draw attention to critical social aspects highlighted by phenomena of distrust. This way, it will be possible to further reveal shifts in power relations, challenge unfair status quos, and suggest meaningful ways to keep the interests of citizens. (shrink)

This presentation discusses a notion encountered across disciplines, and in different facets of human activity: autonomous activity. We engage it in an interdisciplinary way. We start by considering the reactions and behaviors of biological entities to biotechnological intervention. An attempt is made to characterize the degree of freedom of embryos & clones, which show openness to different outcomes when the epigenetic developmental landscape is factored in. We then consider the claim made in programming and artificial intelligence that automata could (...) show self-directed behavior as to the determination of their step-wise decisions on courses of action. This question remains largely open and calls for some important qualifications. We try to make sense of the presence of claims of freedom in agency, first in common sense, then by ascribing developmental plasticity in biology and biotechnology, and in the mapping of programmed systems in the presence of environmental cues and self-referenced circuits as well as environmental coupling. This is the occasion to recall attempts at working out a logical and methodological approach to the openness of concepts that are still to be found, and assess whether they can operate the structuring intelligibility of a yet undeveloped or underdeveloped field of study, where a “bisociation" and a unification of knowledge might be possible. (shrink)

Recent research into the nature of self in artificial and biological systems raises interest in a uniquely determining immutable sense of self, a “metaphysical ‘I’” associated with inviolable personal values and moral convictions that remain constant in the face of environmental change, distinguished from an object “me” that changes with its environment. Complementary research portrays processes associated with self as multimodal routines selectively enacted on the basis of contextual cues informing predictive self or world models, with the notion (...) of the constant, per-vasive and invariant sense of self associated with a multistable attractor set aiming to ensure personal integrity against threat of disintegrative change. This paper proposes that an immutable sense of self emerges as a global attractor which can be described as a project ideal self-situation embodied in frontal medial processes during more or less normal adolescent development, and that thereafter serves to orient agency in the more or less free development of embodied potentials over the life course in effort to realize project conditions, phenomenally identified with the felt pull towards this end as purpose of and source of meaning in life. So oriented, life-long self-development aims to embody solutions to problems at different timescales depending on this embodied purpose, ultimately in the service of evolutionary processes securing organism populations against threats of disintegrative change over timespans far beyond that of the individual. After characterizing the target sense of self, research circling this target is briefly surveyed. Self as global project and developmental neural correlates are proposed. Then, the paper discusses some implications for research in biological and artificial systems. Building from earlier work in cognitive neurorobotics, discussion affirms the value of reinforcement rituals including prayer in metaphysical self-development, considers implications for value alignment and rights associated with free will in the context of artificial intelligence and robot religion, and concludes by emphasizing the importance of self-development toward project ideals as source of meaning in life in the current social-political environment. (shrink)

The Frame Problem is the problem of how one can design a machine to use information so as to behave competently, with respect to the kinds of tasks a genuinely intelligent agent can reliably, effectively perform. I will argue that the way the Frame Problem is standardly interpreted, and so the strategies considered for attempting to solve it, must be updated. We must replace overly simplistic and reductionist assumptions with more sophisticated and plausible ones. In particular, the standard interpretation assumes (...) that mental processes are identical to certain kinds of computational processes, and so solving the Frame Problem is a matter of finding a computational architecture that can effectively represent relations of semantic relevance. Instead, we must take seriously the possibility that the way in which intelligent agents use information is inherently different. Whereas intelligent agents are plausibly genuinely causally sensitive to semantic properties as such (to what they perceive, desire, believe intend, etc.), computational systems can only be causally sensitive to the formal features that represent these properties. Indeed, it is this very substitution of formal generalizations for genuinely semantic ones that is responsible for the way current AI systems are brittle, inflexible, and highly specialized. What we need is a more sophisticated way of investigating the relationship between computational information processing and genuinely semantic information use, so that these two senses of using information are not conflated, but instead the question of how they are related to one another can be studied directly. I apply the generative methodology I have developed elsewhere for cognitive science and AI research (Miracchi, 2017, 2019a) to show how the Frame Problem can be appropriately updated. (shrink)

Turing used the expression “emotional” in three distinct ways: to state his philosophical theory of the concept of intelligence, to classify arguments for and against the possibility of machine intelligence, and to describe the education of a “child machine”. The remarks on emotion include several of the most important philosophical claims. This paper analyses these remarks and their significance for current research in Artificial Intelligence.

Arguments from human dignity feature prominently in the Lethal Autonomous Weapons moral feasibility debate, even though their exists considerable controversy over their role and soundness and the notion of dignity remains under-defined. Drawing on the work of Dieter Birnbacher, I fix the sub-discourse as referring to the essential value of human persons in general, and to postulated moral rights of combatants not covered within the existing paradigm of the International Humanitarian Law in particular. I then review and critique dignity-based arguments (...) against LAWS: argument from faulty targeting process, argument from objectification, argument from underappreciation of the value of human life and the argument from the absence of mercy. I conclude that the argument from the absence of mercy is the only dignity-based argument that is both valid and irreducible to another class of arguments within the debate, and that it offers insufficient justification for a global ban on LAWS. (shrink)

This article scrutinizes Michael Crichton’s movie Westworld (1973), its sequel Futureworld (1976), and the spin-off series Beyond Westworld (1980), as well as the critical literature that deals with them. I examine whether Crichton’s movie, its sequel, and the 1980s series contain and convey a consistent technophobic message according to the definition of “technophobia” advanced in Daniel Dinello’s 2005 monograph. I advance a proposal to develop further the concept of technophobia in order to offer a more satisfactory and unified interpretation of (...) the narratives at stake. I connect technophobia and what I call de-theologized, epistemic hubris: the conclusion is that fearing technology is philosophically meaningful if one realizes that the limitations of technology are the consequence of its creation and usage on behalf of epistemically limited humanity (or artificial minds). (shrink)

The telepresence experience can be evoked in a number of ways. A well-known example is a player of videogames who reports about a telepresence experience, a subjective experience of being in one place or environment, even when physically situated in another place. In this paper we set the phenomenon of telepresence into a theoretical framework. As people react subjectively to stimuli from telepresence, empirical studies can give more evidence about the phenomenon. Thus, our contribution is to bridge the theoretical with (...) the empirical. We discuss theories of perception with an emphasis on Heidegger, Merleau-Ponty and Gibson, the role of the senses and the Spinozian belief procedure. The aim is to contribute to our understanding of this phenomenon. A telepresence-study that included the affordance concept is used to empirically study how players report sense-reactions to virtual sightseeing in two cities. We investigate and explore the interplay of the philosophical and the empirical. The findings indicate that it is not only the visual sense that plays a role in this experience, but all senses. (shrink)

Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether (...) these principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principles for ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice. On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts. (shrink)

Recent debates over artificial intelligence have focused on its perceived lack of interpretability and explainability. I argue that these notions fail to capture an important aspect of what end-users—as opposed to developers—need from these models: what is needed is systematicity, in a more demanding sense than the compositionality-related sense that has dominated discussions of systematicity in the philosophy of language and cognitive science over the last thirty years. To recover this more demanding notion of systematicity, I distinguish (...) between (i) the systematicity of thinkable contents, (ii) the systematicity of thinking, and (iii) the ideal of systematic thought. I then deploy this distinction to critically evaluate Fodor’s systematicity-based argument for the language of thought hypothesis before recovering the notion of the systematicity of thought as a regulative ideal, which has historically shaped our understanding of what it means for thought to be rational, authoritative, and scientific. To assess how much systematicity we need from AI models, I then argue, we must look to the functions of systematizing thought. To this end, I identify five functions served by systematization, and show how these can be used to arrive at a dynamic understanding of the need to systematize thought that can tell us what kind of systematicity is called for and when. (shrink)

Artificial Intelligence (AI) systems are ubiquitous. From social media timelines, video recommendations on YouTube, and the kinds of adverts we see online, AI, in a very real sense, filters the world we see. More than that, AI is being embedded in agent-like systems, which might prompt certain reactions from users. Specifically, we might find ourselves feeling frustrated if these systems do not meet our expectations. In normal situations, this might be fine, but with the ever increasing sophistication of (...) AI-systems, this might become a problem. While it seems unproblematic to realize that being angry at your car for breaking down is unfitting, can the same be said for AI-systems? In this paper, therefore, I will investigate the so-called “reactive attitudes”, and their important link to our responsibility practices. I then show how within this framework there exist exemption and excuse conditions, and test whether our adopting the “objective attitude” toward agential AI is justified. I argue that such an attitude is appropriate in the context of three distinct senses of responsibility (answerability, attributability, and accountability), and that, therefore, AI-systems do not undermine our responsibility ascriptions. (shrink)

Calls to hold artificial intelligence to account are intensifying. Activists and researchers alike warn of an “accountability gap” or even a “crisis of accountability” in AI. Meanwhile, several prominent scholars maintain that accountability holds the key to governing AI. But usage of the term varies widely in discussions of AI ethics and governance. This chapter begins by disambiguating some different senses and dimensions of accountability, distinguishing it from neighboring concepts, and identifying sources of confusion. It proceeds to explore the (...) idea that AI operates within an accountability gap arising from technical features of AI as well as the social context in which it is deployed. The chapter also evaluates various proposals for closing this gap. I conclude that the role of accountability in AI ethics and governance is vital but also more limited than some suggest. Accountability’s primary job description is to verify compliance with substantive normative principles—once those principles are settled. Theories of accountability cannot ultimately tell us what substantive standards to account for, especially when norms are contested or still emerging. Nonetheless, formal mechanisms of accountability provide a way of diagnosing and discouraging egregious wrongdoing even in the absence of normative agreement. Providing accounts can also be an important first step toward the development of more comprehensive regulatory standards for AI. (shrink)

The 20th Century is the starting point for the most ambitious attempts to extrapolate human life into artificial systems. Norbert Wiener’s Cybernetics, Claude Shannon’s Information Theory, John von Neumann’s Cellular Automata, Universal Constructor to the Turing Test, Artificial Intelligence to Maturana and Varela’s Autopoietic Organization, all shared the goal of understanding in what sense humans resemble a machine. This scientific and technological movement has embraced all disciplines without exceptions, not only mathematics and physics but also biology, sociology, (...) psychology, economics etc. New terms were developed, such as “information”, “organization”, “entropy”, “communication”, “encryption”, “computation” and “algorithmics” to mention a few, all which had an enormous impact on artificial systems. Our work follows this historical track but with a reversed order of priorities. Instead of deducing a reduced group of human acts into an artificial environment, we deduce the human aspects of machines by extrapolating algorithmic methodologies into everyday life acts. The present informational theories were insufficiently powered to achieve this objective without developing a new theoretical approach. Hence, our research is directed towards an expansion of the current informational theories. (shrink)

"Language has never been accessible to me in the way that it was for Sachs. I'm shut off from my own thoughts, trapped in a no-man's-land between feeling and articulation, and no matter how hard I try to express myself, I can rarely come up with more than a confused stammer. Sachs never had any of these difficulties. Words and things matched up for him, whereas for me they are constantly breaking apart, flying off in a hundred different directions. I (...) spend most of my time picking up the pieces and gluing them back together, but Sachs never had to stumble around like that, hunting through garbage dumps and trash bins, wondering if he hadn't fit the wrong pieces next to each other. His uncertainties were of a different order, but no matter how hard life became for him in other ways, words were never his problem." -Paul Auster, Leviathan. (shrink)

Artificial intelligence (AI) techniques are used to model human activities and predict behavior. Such systems have shown race, gender and other kinds of bias, which are typically understood as technical problems. Here we try to show that: 1) to get rid of such biases, we need a system that can understand the structure of human activities and;2) to create such a system, we need to solve foundational problems of AI, such as the common-sense problem. Additionally, when informational platforms (...) uses these models to mediate interactions with their users, which is a commonplace nowadays, there is an illusion of progress, for what is an increasingly higher influence over our own behavior is took for an increasingly higher predictive accuracy. Given this, we argue that the bias problem is deeply connected to non-technical issues that must be discussed in public spaces. -/- Técnicas de inteligência artificial (IA) são utilizadas para modelar as atividades humanas e gerar predições comportamentais. Estes sistemas têm apresentado vieses diversos, inclusive de raça e gênero, tipicamente tomados como problemas de engenharia. Realiza-se aqui um esforço argumentativo para mostrar que: 1) escapar dos vieses demanda um sistema que compreenda a estrutura das atividades humanas e; 2) criar um sistema que apresente tal compreensão, demanda a solução de problemas fundacionais da IA, em particular, o problema de como modelar o senso comum. No caso de plataformas informacionais que usam desses modelos para mediar interações com seus usuários, algo cada vez mais comum, o não reconhecimento disso dá margem a uma ilusão de progresso, em que uma crescente influência sobre nosso comportamento é tomada como uma crescente acurácia preditiva. Nesse cenário, argumenta-se que o problema dos vieses está associado a questões não técnicas que devem ser discutidas em espaços públicos. (shrink)

Advancements in artificial intelligence and (social) robotics raise pertinent questions as to how these technologies may help shape the society of the future. The main aim of the chapter is to consider the social and conceptual disruptions that might be associated with social robots, and humanoid social robots in particular. This chapter starts by comparing the concepts of robots and artificial intelligence and briefly explores the origins of these expressions. It then explains the definition of a social robot, (...) as well as the definition of humanoid robots. A key notion in this context is the idea of anthropomorphism: the human tendency to attribute human qualities, not only to our fellow human beings, but also to parts of nature and to technologies. This tendency to anthropomorphize technologies by responding to and interacting with them as if they have human qualities is one of the reasons why social robots (in particular social robots designed to look and behave like human beings) can be socially disruptive. As is explained in the chapter, while some ethics researchers believe that anthropomorphization is a mistake that can lead to various forms of deception, others — including both ethics researchers and social roboticists — believe it can be useful or fitting to treat robots in anthropomorphizing ways. The chapter explores that disagreement by, among other things, considering recent philosophical debates about whether social robots can be moral patients, that is, whether it can make sense to treat them with moral consideration. Where one stands on this issue will depend either on one’s views about whether social robots can have, imitate, or represent morally relevant properties, or on how people relate to social robots in their interactions with them. Lastly, the chapter urges that the ethics of social robots should explore intercultural perspectives, and highlights some recent research on Ubuntu ethics and social robots. (shrink)