This paper discusses how an interactive artwork, the Crowd-Sourced Intelligence Agency, can contribute to discussions of Big Data intelligence analytics. The CSIA is a publicly accessible Open Source Intelligence system that was constructed using information gathered from technical manuals, research reports, academic papers, leaked documents, and Freedom of Information Act files. Using a visceral heuristic, the CSIA demonstrates how the statistical correlations made by automated classification systems are different from human judgment and can produce false-positives, as well as how (...) the display of information through an interface can affect the judgment of an intelligence agent. The public has the right to ask questions about how a computer program determines if they are a threat to national security and to question the practicality of using statistical pattern recognition algorithms in place of human judgment. Currently, the public’s lack of access to both Big Data and the actual datasets intelligence agencies use to train their classification algorithms keeps the possibility of performing effective sous-dataveillance out of reach. Without this data, the results returned by the CSIA will not be identical to those of intelligence agencies. Because we have replicated how OSINT is processed, however, our results will resemble the type of results and mistakes made by OSINT systems. The CSIA takes some initial steps toward contributing to an informed public debate about large-scale monitoring of open source, social media data and provides a prototype for counterveillance and sousveillance tools for citizens. (shrink)

Academia-intelligence agency collaborations are on the rise for a variety of reasons. These can take many forms, one of which is in the classroom, using students to stand in for intelligence analysts. Classrooms, however, are ethically complex spaces, with students considered vulnerable populations, and become even more complex when layering multiple goals, activities, tools, and stakeholders over those traditionally present. This does not necessarily mean one must shy away from academia-intelligence agency partnerships in classrooms, but that these must (...) be conducted carefully and reflexively. This paper hopes to contribute to this conversation by describing one purposeful classroom encounter that occurred between a professor, students, and intelligence practitioners in the fall of 2015 at North Carolina State University: an experiment conducted as part of a graduate-level political science class that involved students working with a prototype analytic technology, a type of participatory sensing/self-tracking device, developed by the National Security Agency. This experiment opened up the following questions that this paper will explore: What social, ethical, and pedagogical considerations arise with the deployment of a prototype intelligence technology in the college classroom, and how can they be addressed? How can academia-intelligence agency collaboration in the classroom be conducted in ways that provide benefits to all parties, while minimizing disruptions and negative consequences? This paper will discuss the experimental findings in the context of ethical perspectives involved in values in design and participatory/self-tracking data practices, and discuss lessons learned for the ethics of future academia-intelligence agency partnerships in the classroom. (shrink)

Academia-intelligence agency collaborations are on the rise for a variety of reasons. These can take many forms, one of which is in the classroom, using students to stand in for intelligence analysts. Classrooms, however, are ethically complex spaces, with students considered vulnerable populations, and become even more complex when layering multiple goals, activities, tools, and stakeholders over those traditionally present. This does not necessarily mean one must shy away from academia-intelligence agency partnerships in classrooms, but that these must (...) be conducted carefully and reflexively. This paper hopes to contribute to this conversation by describing one purposeful classroom encounter that occurred between a professor, students, and intelligence practitioners in the fall of 2015 at North Carolina State University: an experiment conducted as part of a graduate-level political science class that involved students working with a prototype analytic technology, a type of participatory sensing/self-tracking device, developed by the National Security Agency. This experiment opened up the following questions that this paper will explore: What social, ethical, and pedagogical considerations arise with the deployment of a prototype intelligence technology in the college classroom, and how can they be addressed? How can academia-intelligence agency collaboration in the classroom be conducted in ways that provide benefits to all parties, while minimizing disruptions and negative consequences? This paper will discuss the experimental findings in the context of ethical perspectives involved in values in design and participatory/self-tracking data practices, and discuss lessons learned for the ethics of future academia-intelligence agency partnerships in the classroom. (shrink)

Thanks to advances in machine learning in recent years the ability of AI agents to act independently of human oversight, respond to their environment, and interact with other machines has significantly increased, and is one step closer to human-like performance. For this reason, we can observe contemporary researchers’ efforts towards modeling agency in artificial systems. In this light, the aim of this paper is to develop a dual-process approach to the problem of AI agency perception, and to discuss (...) possible triggers of various agency perceptions. The article discusses the agency attribution phenomenon, based on which the argument for the dual-process nature of agency perception is developed. Two distinct types of thinking involved in human reasoning on AI agency are suggested: Type 1 and Type 2. The first one is fast, automatic, routine, and often unconscious; the second is a slower, controlled, more conscious one. These two distinct types of processing can yield differing and sometimes conflicting results for human cognition and interaction. The preliminary philosophical findings may contribute to further investigations in philosophy of mind or cognitive psychology and could also be empirically tested in HCI and UX studies. (shrink)

Thanks to advances in machine learning in recent years the ability of AI agents to act independently of human oversight, respond to their environment, and interact with other machines has significantly increased, and is one step closer to human-like performance. For this reason, we can observe contemporary researchers’ efforts towards modeling agency in artificial systems. In this light, the aim of this paper is to develop a dual-process approach to the problem of AI agency perception, and to discuss (...) possible triggers of various agency perceptions. The article discusses the agency attribution phenomenon, based on which the argument for the dual-process nature of agency perception is developed. Two distinct types of thinking involved in human reasoning on AI agency are suggested: Type 1 and Type 2. The first one is fast, automatic, routine, and often unconscious; the second is a slower, controlled, more conscious one. These two distinct types of processing can yield differing and sometimes conflicting results for human cognition and interaction. The preliminary philosophical findings may contribute to further investigations in philosophy of mind or cognitive psychology and could also be empirically tested in HCI and UX studies. (shrink)

The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have rights (...) and a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical. (shrink)

Book review of Carlos Montemayor's "The Prospect of a Humanitarian Artificial Intelligence: Agency and Value Alignment" || Reseña del libro "The Prospect of a Humanitarian Artificial Intelligence: Agency and Value Alignment", escrito por Carlos Montemayor.

Ethically significant consequences of artificially intelligent artifacts will stem from their effects on existing social relations. Artifacts will serve in a variety of socially important roles—as personal companions, in the service of elderly and infirm people, in commercial, educational, and other socially sensitive contexts. The inevitable disruptions that these technologies will cause to social norms, institutions, and communities warrant careful consideration. As we begin to assess these effects, reflection on degrees and kinds of social agency will be required (...) to make properly informed decisions concerning the deployment of artificially intelligent artifacts in important settings. The social agency of these systems is unlike a human social agency, and this paper provides a methodological framework that is more suited for inquiry into artificial social agents than conventional philosophical treatments of the concept of agency. Separate aspects and dimensions of agency can be studied without assuming that agency must always look like adult human agency. This revised approach to the agency of artifacts is conducive to progress in the topics studied by AI ethics. (shrink)

What kind of activity are non-human animals capable of? A venerable tradition insists that lack of language confines them to ‘mere behaviour’. This article engages with this ‘lingualism’ by developing a positive, bottom-up case for the possibility of animal agency. Higher animals cannot just act, they can act intelligently, rationally, intentionally and for reasons. In developing this case I draw on the interplay of behaviour, cognition and conation, the unduly neglected notion of intelligence and its connection to rationality, the (...) need to recognize that reasons are objective conditions, and the difference between the ability to act for reasons and the capacity to reflect on reasons. (shrink)

Philosophical and sociological approaches in technology have increasingly shifted toward describing AI (artificial intelligence) systems as ‘(moral) agents,’ while also attributing ‘agency’ to them. It is only in this way – so their principal argument goes – that the effects of technological components in a complex human-computer interaction can be understood sufficiently in phenomenological-descriptive and ethical-normative respects. By contrast, this article aims to demonstrate that an explanatory model only achieves a descriptively and normatively satisfactory result if the concepts of (...) ‘(moral) agent’ and ‘(moral) agency’ are exclusively related to human agents. Initially, the division between symbolic and sub-symbolic AI, the black box character of (deep) machine learning, and the complex relationship network in the provision and application of machine learning are outlined. Next, the ontological and action-theoretical basic assumptions of an ‘agency’ attribution regarding both the current teleology-naturalism debate and the explanatory model of actor network theory are examined. On this basis, the technical-philosophical approaches of Luciano Floridi, Deborah G. Johnson, and Peter-Paul Verbeek will all be critically discussed. Despite their different approaches, they tend to fully integrate computational behavior into their concept of ‘(moral) agency.’ By contrast, this essay recommends distinguishing conceptually between the different entities, causalities, and relationships in a human-computer interaction, arguing that this is the only way to do justice to both human responsibility and the moral significance and causality of computational behavior. (shrink)

The objective of this work is to explore the notion of “action” and “agency” in artificial intelligence (AI). It employs a metaphysical notion of action and agency as an epistemological tool in the critique of the notion of “action” and “agency” in artificial intelligence. Hence, both a metaphysical and cognitive analysis is employed in the investigation of the quiddity and nature of action and agency per se, and how they are, by extension employed in the language (...) and science of artificial intelligence. The advent of the science of artificial intelligence and cognitive science, and the technological applications of artificial intelligence in the production of agents such as driverless cars and expert systems, have raised the question of moral, ethical and/or legal responsibility in AI agents. This has re-emphasized the importance of the philosophical discourse on the notions of action and agency, which in contemporary intellectual discourse are now perceived to be phenomena within the epistemic competence of the natural sciences. This paper argues that AI systems do not and cannot possess free agency and autonomy, thus cannot be morally and ethically responsible, hence, it recommends a socio-political response to the question of responsibility in AI. It is then the duty of individual nations, or the global community to define and enact policies on who shoulders the responsibility of actions executed by AIs. (shrink)

Emotional intelligence (EI) has been put forward as a distinctive kind of intelligence and, by popularizers such as Daniel Goleman, as an indicator of moral and life skills. Critics, however, have been concerned EI-testing measures conformity or the ability to manipulate own or others' emotions, and relies on a problematic assumption that there are definitive, universal “right” answers when it comes to feelings. Such worries have also been raised about the original concept developed by Peter Salovey and John D. Mayer; (...) that version is the focus here. While it improves on the largely unreflective reliance on particular belief- and value-systems in Goleman's account, however, it does not entirely succeed in being context- and value-neutral. A useful way forward is to apply Ronald de Sousa's notion that emotions are shaped by ideology: this in turn affects attempts to measure any putative “intelligence” with respect to them. Once the ideological dimension is bracketed, a clearer picture of both the usefulness and the limitations of the EI-concept can emerge—and also a better sense of its possible contributions to value theory and moral psychology. The ideological dimension itself may also be unavoidable; squarely facing this possibility is preferable to ignoring it. (shrink)

The article examines the challenges involved in the process of developing artificial ethical agents. The process involves the creators or designing professionals, the procedures to develop an ethical agent and the artificial systems. There are two possibilities available to create artificial ethical agents: (a) programming ethical guidance in the artificial Intelligence (AI)-equipped machines and/or (b) allowing AI-equipped machines to learn ethical decision-making by observing humans. However, it is difficult to fulfil these possibilities due to the subjective nature of ethical decision-making. (...) The challenge related to the developers is that they themselves lack training in ethical skills. The creators who develop an artificial ethical agent should be able to foresee the ethical issues and have knowledge about ethical decision-making to improve the ethical use of AI-equipped machines. The suggestion is that the focus should be on training professionals involved in the process of developing these artificial systems in ethics rather than developing artificial ethical agents and thereby attributing ethical agency to it. (shrink)

The article examines the challenges involved in the process of developing artificial ethical agents. The process involves the creators or designing professionals, the procedures to develop an ethical agent and the artificial systems. There are two possibilities available to create artificial ethical agents: (a) programming ethical guidance in the artificial Intelligence (AI)-equipped machines and/or (b) allowing AI-equipped machines to learn ethical decision-making by observing humans. However, it is difficult to fulfil these possibilities due to the subjective nature of ethical decision-making. (...) The challenge related to the developers is that they themselves lack training in ethical skills. The creators who develop an artificial ethical agent should be able to foresee the ethical issues and have knowledge about ethical decision-making to improve the ethical use of AI-equipped machines. The suggestion is that the focus should be on training professionals involved in the process of developing these artificial systems in ethics rather than developing artificial ethical agents and thereby attributing ethical agency to it. (shrink)

This paper discusses the philosophical issues pertaining to Kantian moral agency and artificial intelligence. Here, our objective is to offer a comprehensive analysis of Kantian ethics to elucidate the non-feasibility of Kantian machines. Meanwhile, the possibility of Kantian machines seems to contend with the genuine human Kantian agency. We argue that in machine morality, ‘duty’ should be performed with ‘freedom of will’ and ‘happiness’ because Kant narrated the human tendency of evaluating our ‘natural necessity’ through ‘happiness’ as the (...) end. Lastly, we argue that the Kantian ‘freedom of will’ and ‘faculty of choice’ do not belong to any deterministic model of ‘agency’ as these are sacrosanct systems. The conclusion narrates the non-feasibility of Kantian AI agents from the genuine Kantian ethical outset, offering a utility-based Kantian ethical performer instead. (shrink)

Determining the agency-status of machines and AI has never been more pressing. As we progress into a future where humans and machines more closely co-exist, understanding hallmark features of agency affords us the ability to develop policy and narratives which cater to both humans and machines. This paper maintains that decision-making processes largely underpin agential action, and that in most instances, these processes yield good results in terms of making good choices. However, in some instances, when faced with (...) two (or more) choices, an agent may find themselves with equal reasons to choose either - thus being presented with a tie. This paper argues that in the event of a tie, the ability to create a voluntarist reason is a hallmark feature of agency, and second, that AI, through current tie-breaking mechanisms does not have this ability, and thus fails at this particular feature of agency. (shrink)

Popular Frankfurt-style theories of autonomy hold that (i) autonomy is motivation in action by psychological attitudes that have ‘authority’ to constitute the agent's perspective, and (ii) attitudes have this authority in virtue of their formal role in the individual's psychological system, rather than their substantive content. I pose a challenge to such ‘psychologistic’ views, taking Frankfurt's and Bratman's theories as my targets. I argue that motivation by attitudes that play the roles picked out by psychologistic theories is compatible with radically (...) unintelligible behavior. Because of this, psychologistic views are committed to classifying certain agents as ‘autonomous’ whom we intuitively find to be dysfunctional. I then argue that a necessary condition for autonomy is that an agent's behavior is intelligible in a particular way: autonomy necessarily involves acting from a subjective practical perspective that is, in principle, minimally comprehensible to others – not simply in a causal sense, but in a substantive, socio-cultural sense. (shrink)

Humans have invented intelligent machinery to enhance their rational decision-making procedure, which is why it has been named ‘augmented intelligence’. The usage of artificial intelligence (AI) technology is increasing enormously with every passing year, and it is becoming a part of our daily life. We are using this technology not only as a tool to enhance our rationality but also heightening them as the autonomous ethical agent for our future society. Norbert Wiener envisaged ‘Cybernetics’ with a view of a (...) brain-machine interface to augment human beings' biological rationality. Being an autonomous ethical agent presupposes an ‘agency’ in moral decision-making procedure. According to agency's contemporary theories, AI robots might be entitled to some minimal rational agency. However, that minimal agency might not be adequate for a fully autonomous ethical agent's performance in the future. If we plan to implement them as an ethical agent for the future society, it will be difficult for us to judge their actual stand as a moral agent. It is well known that any kind of moral agency presupposes consciousness and mental representations, which cannot be articulated synthetically until today. We can only anticipate that this milestone will be achieved by AI scientists shortly, which will further help them triumph over ‘the problem of ethical agency in AI’. Philosophers are currently trying a probe of the pre-existing ethical theories to build a guidance framework for the AI robots and construct a tangible overview of artificial moral agency. Although, no unanimous solution is available yet. It will land up in another conflicting situation between biological, moral agency and autonomous ethical agency, which will leave us in a baffled state. Creating rational and ethical AI machines will be a fundamental future research problem for the AI field. This paper aims to investigate ‘the problem of moral agency in AI’ from a philosophical outset and hold a survey of the relevant philosophical discussions to find a resolution for the same. (shrink)

This essay begins with the story of Vincent Lloyd who recounts a disturbing experience he had while teaching a course to a group of students of color. What does pedagogical uptake under conditions of systemic oppression require of educators? In the first section, I explore philosopher Nancy Potter’s (Nancy Potter. “Giving Uptake”. Social Theory and Practice 26/3 (2000) 479–508; Nancy Potter. The Virtue of Defiance and Psychiatric Engagement (Oxford: Oxford University Press, 2016)) work on uptake, whose focus on the mental (...) health field is important because she acknowledges power imbalances. Nevertheless, her understanding of uptake may be insufficient for considering such classroom cases that introduced this essay. The second section shifts the focus of uptake from a psychological approach to a more epistemic understanding of uptake that underscores credibility and intelligibility. Uptake as credibility and intelligibility reveals the everyday patterns of uptake failure that marginalized knowers experience in the socio-epistemic world, described in section three. A recent turn in the scholarship of epistemic injustice towards epistemic agency and resistance is taken up in the subsequent section and applied to the conceptualization of uptake. In the concluding section, I begin to explore how these insights contribute to a notion of pedagogical uptake under conditions of systemic oppression. (shrink)

John Harris discusses the problem of other minds, not as it relates to other human minds, but rather as it relates to artificial intelligences. He also discusses what might be called bilateral mind-reading: humans trying to read the minds of artificial intelligences and artificial intelligences trying to read the minds of humans. Lastly, Harris discusses whether super intelligent AI – if it could be created – should be afforded moral consideration, and also how we might convince super intelligent (...) AI that we ourselves should be treated with moral consideration. In this commentary, I discuss these issues brought up by Harris. I focus specifically on robots (rather than AI in general), and I set aside future super intelligent AI to instead focus on more limited forms of AI. I argue that the human tendency to attribute minds even to robots with very limited AI and whether such robots should be given moral consideration are more pressing issues than those that Harris discusses, even though I certainly agree with Harris that the potential for super intelligent AI is a fascinating topic to speculate about. (shrink)

Recently, scholars across disciplines raised ethical, legal and social concerns about the notion of human intervention, control, and oversight over Artificial Intelligence (AI) systems. This observation becomes particularly important in the age of ubiquitous computing and the increasing adoption of AI in everyday communication infrastructures. We apply Nicholas Garnham's conceptual perspective on mediation to users who are challenged both individually and societally when interacting with AI-enabled systems. One way to increase user agency are mechanisms to contest faulty or flawed (...) AI systems and their decisions, as well as to request redress. Currently, however, users structurally lack such mechanisms, which increases risks for vulnerable communities, for instance patients interacting with AI healthcare chatbots. To empower users in AI-mediated communication processes, this article introduces the concept of active human agency. We link our concept to contestability and redress mechanism examples and explain why these are necessary to strengthen active human agency. We argue that AI policy should introduce rights for users to swiftly contest or rectify an AI-enabled decision. This right would empower individual autonomy and strengthen fundamental rights in the digital age. We conclude by identifying routes for future theoretical and empirical research on active human agency in times of ubiquitous AI. (shrink)

The concept of agency is of crucial importance in cognitive science and artificial intelligence, and it is often used as an intuitive and rather uncontroversial term, in contrast to more abstract and theoretically heavy-weighted terms like “intentionality”, “rationality” or “mind”. However, most of the available definitions of agency are either too loose or unspecific to allow for a progressive scientific program. They implicitly and unproblematically assume the features that characterize agents, thus obscuring the full potential and challenge of (...) modeling agency. We identify three conditions that a system must meet in order to be considered as a genuine agent: a) a system must define its own individuality, b) it must be the active source of activity in its environment (interactionalasymmetry) and c) it must regulate this activity in relation to certain norms (normativity). We find that even minimal forms of proto-celular systems can already provide a paradigmatic example of genuine agency. By abstracting away some specific details of minimal models of living agency we define the kind of organization that is capable to meet the required conditions for agency (which is not restricted to living organisms). On this basis, we define agency as an autonomous organization that adaptively regulates its coupling with its environment and contributes to sustaining itself as a consequence. We find that spatiality and temporality are the two fundamental domains in which agency spans at different scales. We conclude by giving an outlook to the road that lies ahead in the pursuit to understand, model and synthesis agents. (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)

Learning from contemporary natural, formal, and social sciences, especially from current biology, as well as from humanities, particularly contemporary philosophy of nature, requires updates of our old definitions of cognition and intelligence. The result of current insights into basal cognition of single cells and evolution of multicellular cognitive systems within the framework of extended evolutionary synthesis (EES) helps us better to understand mechanisms of cognition and intelligence as they appear in nature. New understanding of information and processes of physical (morphological) (...) computation contribute to novel possibilities that can be used to inspire the development of abiotic cognitive systems (cognitive robotics), cognitive computing and artificial intelligence. (shrink)

This comprehensive analysis dives deep into the intricate interplay between artificial intelligence (AI) and human agency, examining the remarkable capabilities and inherent limitations of large language models (LLMs) such as GPT-3 and ChatGPT. The paper traces the complex trajectory of AI's evolution, highlighting its operation based on statistical pattern recognition, devoid of self-consciousness or innate comprehension. As AI permeates multiple spheres of human life, it raises substantial ethical, legal, and societal concerns that demand immediate attention and deliberation. The metaphorical (...) illustration of humans as “shepherds” of AI, coupled with a thought-provoking examination of “agency without intelligence,” engenders deep reflections on the future of human-AI interplay and the associated philosophical, ethical, and practical ramifications. The paper further elucidates critical challenges associated with AI, such as ethical dilemmas, “agency without intelligence,” the role of human oversight, and the environmental impact of AI technologies. In the pursuit of solutions, the paper maps prospective directions, emphasizing the need for robust AI policies, improved AI literacy, sustainable AI practices, and a continued dialogue on the multifaceted issues surrounding AI. Through a holistic exploration of AI, this paper underlines the necessity for a multidisciplinary, collaborative approach to chart an ethical, beneficial, and sustainable AI future, enabling society to harness the potential of AI responsibly while mitigating the associated risks. (shrink)

Should artificial intelligences ever be included as co-authors of democratic decisions? According to the conventional view in democratic theory, the answer depends on the relationship between the political unit and the entity that is either affected or subjected to its decisions. The relational conditions for inclusion as stipulated by the all-affected and all-subjected principles determine the spatial extension of democratic inclusion. Thus, AI qualifies for democratic inclusion if and only if AI is either affected or subjected to decisions by the (...) political unit in relevant ways. This paper argues that the conventional view is too simple; that it neglects democratic reasons to recognize only agents and/or moral patients as participants in decision-making. The claim defended is that AAP and ASP implicitly affirm requirements for agency and patiency. In ASP, the entity included must be an agent understood either in terms of legal status, capacity to comply with the law or ability to recognize legitimate authority. In AAP, the entity included must be a patient, understood either in terms of capacity for sentience or consciousness. Thus, the idea here is to explore the potential democratic inclusion of artificial intelligences by an updated account of the relevant conditions of agency and patiency that are implicit in democratic theory. Although conceivable that AI is or will be either affected or subjected in relevant ways to decisions made by political units, it is far less clear that AI will ever be agents or patients in the sense required for democratic inclusion. (shrink)

Algorithmic systems and predictive analytics play an increasingly important role in various aspects of modern life. Scholarship on the moral ramifications of such systems is in its early stages, and much of it focuses on bias and harm. This paper argues that in understanding the moral salience of algorithmic systems it is essential to understand the relation between algorithms, autonomy, and agency. We draw on several recent cases in criminal sentencing and K–12 teacher evaluation to outline four key ways (...) in which issues of agency, autonomy, and respect for persons can conflict with algorithmic decision-making. Three of these involve failures to treat individual agents with the respect they deserve. The fourth involves distancing oneself from a morally suspect action by attributing one’s decision to take that action to an algorithm, thereby laundering one’s agency. (shrink)

In this article, we suggest that the study of social interactions and the development of a “sense of agency” in joint action can help determine the content of relevant explanations to be implemented in artificial systems to make them “explainable.” The introduction of automated systems, and more broadly of Artificial Intelligence, into many domains has profoundly changed the nature of human activity, as well as the subjective experience that agents have of their own actions and their consequences – an (...) experience that is commonly referred to as sense of agency. We propose to examine the empirical evidence supporting this impact of automation on individuals’ sense of agency, and hence on measures as diverse as operator performance, system explicability and acceptability. Because of some of its key characteristics, AI occupies a special status in the artificial systems landscape. We suggest that this status prompts us to reconsider human–AI interactions in the light of human–human relations. We approach the study of joint actions in human social interactions to deduce what key features are necessary for the development of a reliable sense of agency in a social context and suggest that such framework can help define what constitutes a good explanation. Finally, we propose possible directions to improve human–AI interactions and, in particular, to restore the sense of agency of human operators, improve their confidence in the decisions made by artificial agents, and increase the acceptability of such agents. (shrink)

In the age of artificial intelligence, writing machines or robot authors have already begun to produce narrative texts in a variety of genres, including short stories and poetry, as well as journalistic articles. This article is based on the prospect that the narrative ecosystem is in a transitional period of decisive disconnection as it enters the era of artificial intelligence. The primary force driving this transition is the formidable execution of artificial intelligence algorithms, which fully automate narrative communication and narrative (...) works. This article attempts to lay the groundwork for building a new paradigm of post-narrativity through a critical examination of several detailed themes in narrative semiotics and non-anthropocentric narratology. The process of narrative creation based on artificial intelligence algorithms is a key condition that constitutes post-narrativity. This presupposes a non-anthropocentric view. In the landscape of post-narrativity, human writers, paper books, computer screens, and invisible narrative algorithms are all agents with equal influence. Automated narrative production by algorithms accelerates the repositioning of other existing media and actors, and changes the narrative ecosystem by incorporating new elements into activities such as production, distribution, and reception of narratives. (shrink)

The way in which agency is conceptualised has implications for understanding human–machine interactions and the governance of technology, especially artificial intelligence (AI) systems. Traditionally, agency is conceptualised as a capacity, defined by intrinsic properties, such as cognitive or volitional facilities. I argue that the capacity-based account of agency is inadequate to explain the dynamics of human–machine interactions and guide technology governance. Instead, I propose to conceptualise agency as impact. Agents as impactful entities can be identified at (...) different levels: from the low level of individual entities to the high level of complex socio-technical systems. Entities can impact their surroundings through different channels, and more influential channels of impact lead to higher degrees of agency. Technology governance must take into account different channels of impact in the contexts of use, design and regulation. (shrink)

Thi Nguyen develops the view that games are, at least potentially, works of art that afford players the opportunity to experiment with agency and have aesthetically significant experiences. In this paper, I critically discuss this proposal. You can make art out of games, I argue, but only at the price of making bad games. I explore the significance of this rivalry between games and art.

Why does the problem of free will seem so intractable? I surmise that in large measure it does so because the free will debate, at least in its modern form, is conducted in terms of a mistaken approach to causality in general. At the heart of this approach is the assumption that all causation is fundamentally event causation. Of course, it is well-known that some philosophers of action want to invoke in addition an irreducible notion of agent causation, applicable only (...) in the sphere of intelligent agency. But such a view is generally dismissed as incompatible with the naturalism that has now become orthodoxy amongst mainstream analytical philosophers of mind. What I want to argue is that substances, not events, are the primary relata of causal relations and that agent causation should properly be conceived of as a species of substance causation. I shall try to show that by thus reconceiving the nature of causation and of agency, the problem of free will can be made more tractable. I shall also argue for a contention that may seem even less plausible at first sight, namely, that such a view of agency is perfectly compatible with a volitionist theory of action. (shrink)

I. There are two points of view: ___ From the personal point of view, an action is a person's doing something for a reason, and her doing it is found intelligible when we know the reason that led her to it. ___ From the impersonal point of view, an action would be a link in a causal chain that could be viewed without paying any attention to people, the links being understood by reference to the world's causal workings.

Why does the problem of free will seem so intractable? I surmise that in large measure it does so because the free will debate, at least in its modern form, is conducted in terms of a mistaken approach to causality in general. At the heart of this approach is the assumption that all causation is fundamentally event causation. Of course, it is well-known that some philosophers of action want to invoke in addition an irreducible notion of agent causation, applicable only (...) in the sphere of intelligent agency. But such a view is generally dismissed as incompatible with the naturalism that has now become orthodoxy amongst mainstream analytical philosophers of mind. What I want to argue is that substances, not events, are the primary relata of causal relations and that agent causation should properly be conceived of as a species of substance causation. I shall try to show that by thus reconceiving the nature of causation and of agency, the problem of free will can be made more tractable. I shall also argue for a contention that may seem even less plausible at first sight, namely, that such a view of agency is perfectly compatible with a volitionist theory of action. (shrink)

The currently developing fields of Ambient Intelligence and Persuasive Technology bring about a convergence of information technology and cognitive science. Smart environments that are able to respond intelligently to what we do and that even aim to influence our behaviour challenge the basic frameworks we commonly use for understanding the relations and role divisions between human beings and technological artifacts. After discussing the promises and threats of these technologies, this article develops alternative conceptions of agency, freedom, and responsibility that (...) make it possible to better understand and assess the social roles of Ambient Intelligence and Persuasive Technology. The central claim of the article is that these new technologies urge us to blur the boundaries between humans and technologies also at the level of our conceptual and moral frameworks. (shrink)

This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, which draws (...) attention to the issues of transparency and explainability. In contrast to standard discussions, however, it is then argued that this knowledge problem regarding agents of responsibility is linked to the other side of the responsibility relation: the addressees or “patients” of responsibility, who may demand reasons for actions and decisions made by using AI. Inspired by a relational approach, responsibility as answerability thus offers an important additional, if not primary, justification for explainability based, not on agency, but on patiency. (shrink)

When agents insert technological systems into their decision-making processes, they can obscure moral responsibility for the results. This can give rise to a distinct moral wrong, which we call “agency laundering.” At root, agency laundering involves obfuscating one’s moral responsibility by enlisting a technology or process to take some action and letting it forestall others from demanding an account for bad outcomes that result. We argue that the concept of agency laundering helps in understanding important moral problems (...) in a number of recent cases involving automated, or algorithmic, decision-systems. We apply our conception of agency laundering to a series of examples, including Facebook’s automated advertising suggestions, Uber’s driver interfaces, algorithmic evaluation of K-12 teachers, and risk assessment in criminal sentencing. We distinguish agency laundering from several other critiques of information technology, including the so-called “responsibility gap,” “bias laundering,” and masking. (shrink)

In How We Get Along, J. David Velleman argues for two related theses: first, that ‘making sense’ of oneself to oneself and others is a constitutive aim of action; second, that this fact about action grounds normativity. Examining each thesis in turn, I argue against the first that an agent may deliberately act in ways which make sense in terms of neither her self-conception nor others' conceptions of her. Against the second thesis, I argue that some vices are such that (...) the agents concerned would make more sense to neither themselves nor others if they were to reform, and, furthermore, that an agent may make more sense to herself and others by becoming more, rather than less, vicious. I conclude that both theses should be rejected. (shrink)

Agency and identity -- Necessitation -- Acts and actions -- Aristotle and Kant -- Agency and practical identity -- The metaphysics of normativity -- Constitutive standards -- The constitution of life -- In defense of teleology -- The paradox of self-constitution -- Formal and substantive principles of reason -- Formal versus substantive -- Testing versus weighing -- Maximizing and prudence -- Practical reason and the unity of the will -- The empiricist account of normativity -- The rationalist account (...) of normativity -- Kant on the hypothetical imperative -- Against particularistic willing -- Deciding and predicting -- Autonomy and efficacy -- The function of action -- The possibility of agency -- Non-rational action -- Action -- Attribution -- The psychology of action -- Expulsion from the garden : the transition to humanity -- Instinct, emotion, intelligence, and reason -- The parts of the soul -- Inside or outside -- Pull yourself together -- The constitutional model -- Models of the soul -- The city and the soul -- Platonic virtues -- Justice : substantive, procedural, and platonic -- Kant and the constitutional model -- Defective action -- The problem of bad action -- Being governed by the wrong law -- Or five bad constitutions -- Conceptions of evil -- Degrees of action -- Integrity and interaction -- Deciding to be bad -- The ordinary cases -- Dealing with the disunified -- Kant's theory of interaction -- My reasons -- Deciding to treat someone as an end in himself -- Interacting with yourself -- How to be a person -- What's left of me? (shrink)

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and (...) used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn. (shrink)

This book brings together philosophical approaches to cooperation and collective agency with research into human-machine interaction and cooperation from engineering, robotics, computer science and AI. Bringing these so far largely unrelated fields of study together leads to a better understanding of collective agency in natural and artificial systems and will help to improve the design and performance of hybrid systems involving human and artificial agents. Modeling collective agency with the help of computer simulations promises also philosophical insights (...) into the emergence of collective agency. The volume consists of four sections. The first section is dedicated to the concept of agency. The second section of the book turns to human-machine cooperation. The focus of the third section is the transition from cooperation to collective agency. The last section concerns the explanatory value of social simulations of collective agency in the broader framework of cultural evolution. (shrink)

The concept of agency as applied to technological artifacts has become an object of heated debate in the context of AI research because some AI researchers ascribe to programs the type of agency traditionally associated with humans. Confusion about agency is at the root of misconceptions about the possibilities for future AI. We introduce the concept of a triadic agency that includes the causal agency of artifacts and the intentional agency of humans to better (...) describe what happens in AI as it functions in real-world contexts. We use the VW emission fraud case to explain triadic agency since in this case a technological artifact, namely software, was an essential part of the wrongdoing and the software might be said to have agency in the wrongdoing. We then extend the case to include futuristic AI, imagining AI that becomes more and more autonomous. (shrink)

Conversational artificial intelligence (CAI) presents many opportunities in the psychotherapeutic landscape—such as therapeutic support for people with mental health problems and without access to care. The adoption of CAI poses many risks that need in-depth ethical scrutiny. The objective of this paper is to complement current research on the ethics of AI for mental health by proposing a holistic, ethical, and epistemic analysis of CAI adoption. First, we focus on the question of whether CAI is rather a tool or an (...) agent. This question serves as a framework for the subsequent ethical analysis of CAI focusing on topics of (self-) knowledge, (self-)understanding, and relationships. Second, we propose further conceptual and ethical analysis regarding human-AI interaction and argue that CAI cannot be considered as an equal partner in a conversation as is the case with a human therapist. Instead, CAI’s role in a conversation should be restricted to specific functions. (shrink)

Within the philosophy of biology, recently promising steps have been made towards a biologically grounded concept of agency. Agency is described as bio-agency: the intrinsically normative adaptive behaviour of human and non-human organisms, arising from their biological autonomy. My paper assesses the bio-agency approach by examining criticism recently directed by its proponents against the project of embodied robotics. Defenders of the bio-agency approach have claimed that embodied robots do not, and for fundamental reasons cannot, qualify (...) as artificial agents because they do not fully realise biological autonomy. More particularly, it has been claimed that embodied robots fail to be agents because agency essentially requires metabolism. I shall argue that this criticism, while being valuable in bringing to the fore important differences between bio-agents and existing embodied robots, nevertheless is too strong. It relies on inferences from agency-as-we-know-it to agency-as-it-could-be which are justified neither empirically nor conceptually. (shrink)

Highly sophisticated capabilities of artificial intelligence (AI) have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of AI is (...) on the rise in urban policy circles, there is limited understanding and lack of empirical studies on the city manager perceptions concerning urban AI systems. Bridging this gap is the rationale of this study. The methodological approach adopted in this study is twofold. First, the study collects data through semi-structured interviews with city managers from Australia and the US. Then, the study analyses the data using the summative content analysis technique with two data analysis software. The analysis identifies the following themes and generates insights into local government services: AI adoption areas, cautionary areas, challenges, effects, impacts, knowledge basis, plans, preparedness, roadblocks, technologies, deployment timeframes, and usefulness. The study findings inform city managers in their efforts to deploy AI in their local government operations, and offer directions for prospective research. (shrink)

AI systems play an increasingly important role in shaping and regulating the lives of millions of human beings across the world. Calls for greater _transparency_ from such systems have been widespread. However, there is considerable ambiguity concerning what “transparency” actually means, and therefore, what greater transparency might entail. While, according to some debates, transparency requires _seeing through_ the artefact or device, widespread calls for transparency imply _seeing into_ different aspects of AI systems. These two notions are in apparent tension with (...) each other, and they are present in two lively but largely disconnected debates. In this paper, we aim to further analyse what these calls for transparency entail, and in so doing, clarify the sorts of transparency that we should want from AI systems. We do so by offering a taxonomy that classifies different notions of transparency. After a careful exploration of the different varieties of transparency, we show how this taxonomy can help us to navigate various domains of human–technology interactions, and more usefully discuss the relationship between technological transparency and human agency. We conclude by arguing that all of these different notions of transparency should be taken into account when designing more ethically adequate AI systems. (shrink)

This paper presents a new trilemma with respect to resolving the control and alignment problems in machine ethics. Section 1 outlines three possible types of artificial moral agents (AMAs): (1) 'Inhuman AMAs' programmed to learn or execute moral rules or principles without understanding them in anything like the way that we do; (2) 'Better-Human AMAs' programmed to learn, execute, and understand moral rules or principles somewhat like we do, but correcting for various sources of human moral error; and (3) 'Human-Like (...) AMAs' programmed to understand and apply moral values in broadly the same way that we do, with a human-like moral psychology. Sections 2–4 then argue that each type of AMA generates unique control and alignment problems that have not been fully appreciated. Section 2 argues that Inhuman AMAs are likely to behave in inhumane ways that pose serious existential risks. Section 3 then contends that Better-Human AMAs run a serious risk of magnifying some sources of human moral error by reducing or eliminating others. Section 4 then argues that Human-Like AMAs would not only likely reproduce human moral failures, but also plausibly be highly intelligent, conscious beings with interests and wills of their own who should therefore be entitled to similar moral rights and freedoms as us. This generates what I call the New Control Problem: ensuring that humans and Human-Like AMAs exert a morally appropriate amount of control over each other. Finally, Section 5 argues that resolving the New Control Problem would, at a minimum, plausibly require ensuring what Hume and Rawls term ‘circumstances of justice’ between humans and Human-Like AMAs. But, I argue, there are grounds for thinking this will be profoundly difficult to achieve. I thus conclude on a skeptical note. Different approaches to developing ‘safe, ethical AI’ generate subtly different control and alignment problems that we do not currently know how to adequately resolve, and which may or may not be ultimately surmountable. (shrink)

In this contribution we will explore some of the implications of the vision of Ambient Intelligence (AmI) for law and legal philosophy. AmI creates an environment that monitors and anticipates human behaviour with the aim of customised adaptation of the environment to a person’s inferred preferences. Such an environment depends on distributed human and non-human intelligence that raises a host of unsettling questions around causality, subjectivity, agency and (criminal) liability. After discussing the vision of AmI we will present relevant (...) research in the field of philosophy of technology, inspired by the post-phenomenological position taken by Don Ihde and the constructivist realism of Bruno Latour. We will posit the need to conceptualise technological normativity in comparison with legal normativity, claiming that this is necessary to develop democratic accountability for the implications of emerging technologies like AmI. Lastly we will investigate to what extent technological devices and infrastructures can and should be used to achieve compliance with the criminal law, and we will discuss some of the implications of non-human distributed intelligence for criminal liability. (shrink)