Natural language processing based on large language models (LLMs) is a booming field of AI research. After neural networks have proven to outperform humans in games and practical domains based on pattern recognition, we might stand now at a road junction where artificial entities might eventually enter the realm of human communication. However, this comes with serious risks. Due to the inherent limitations regarding the reliability of neural networks, overreliance on LLMs can have disruptive consequences. Since it will be (...) increasingly difficult to distinguish between human-written and machine-generated text, one is confronted with new ethical challenges. This begins with the no longer undoubtedly verifiable human authorship and continues with various types of fraud, such as a new form of plagiarism. This also concerns the violation of privacy rights, the possibility of circulating counterfeits of humans, and, last but not least, it makes a massive spread of misinformation possible. (shrink)

Therapeutic strategies capable of inducing and enhancing prosthesis embodiment are a key point for better adaptation to and acceptance of prosthetic limbs. In this study, we developed a training protocol using an EMG-based human-machine interface that was applied in the preprosthetic rehabilitation phase of people with amputation. This is a case series with the objective of evaluating the induction and enhancement of the embodiment of a virtual prosthesis. Six men and a woman with unilateral transfemoral traumatic amputation without (...) previous use of prostheses participated in the study. Participants performed a training protocol with the EMG-based HMI, composed of six sessions held twice a week, each lasting 30 mins. This system consisted of myoelectric control of the movements of a virtual prosthesis immersed in a 3D virtual environment. Additionally, vibrotactile stimuli were provided on the participant’s back corresponding to the movements performed. Embodiment was investigated from the following set of measurements: skin conductance response, crossmodal congruency effect, ability to control the virtual prosthesis, and reports before and after the training. The increase in the skin conductance response in conditions where the virtual prosthesis was threatened, recalibration of the peripersonal space perception identified by the crossmodal congruency effect, ability to control the virtual prosthesis, and participant reports consistently showed the induction and enhancement of virtual prosthesis embodiment. Therefore, this protocol using EMG-based HMI was shown to be a viable option to achieve and enhance the embodiment of a virtual prosthetic limb. (shrink)

Machine learning systems are making considerable inroads in society owing to their ability to recognize and predict patterns. However, the decision-making logic of some widely used machine learning models, such as deep neural networks, is characterized by opacity, thereby rendering them exceedingly difficult for humans to understand and explain and, as a result, potentially risky to use. Considering the importance of addressing this opacity, this paper calls for research that studies empirically and theoretically how machine learning experts (...) and users seek to attain machine learning explainability. Focusing on automated trading, we take steps in this direction by analyzing a trading firm’s quest for explaining its deep neural network system’s actionable predictions. We demonstrate that this explainability effort involves a particular form of human–machine interaction that contains both anthropomorphic and technomorphic elements. We discuss this attempt to attain machine learning explainability in light of reflections on cross-species companionship and consider it an example of human–machine companionship. (shrink)

In recent years, the work of organizations in the area of digitization has intensified significantly. This trend is also evident in the field of recruitment where job application tracking systems (ATS) have been developed to allow job advertisements to be published online. However, recent studies have shown that recruiting in most organizations is not inclusive, being subject to human biases and prejudices. Most discrimination activities appear early but subtly in the hiring process, for instance, exclusive phrasing in job (...) advertisement discourages qualified applicants from minority groups from applying. The existing works are limited to analyzing, categorizing and highlighting the occurrence of bias in the recruitment process. In this paper, we go beyond this and develop machine learning models for identifying and classifying biased and discriminatory language in job descriptions. We develop and evaluate a machine learning system for identifying five major categories of biased and discriminatory language in job advertisements, i.e., masculine-coded, feminine-coded, exclusive, LGBTQ-coded, demographic and racial language. We utilized the combination of linguistic features with recent state-of-the-art word embeddings representations as input features for various machine learning classifiers. Our results show that the machine learning classifiers were able to identify all the five categories of biased and discriminatory language with a decent accuracy. The Random Forest classifier with FastText word embeddings achieved the best performance with tenfolds cross-validation. Our system directly addresses the bias in the attraction phase of hiring by identifying and classifying biased and discriminatory language and thus encouraging recruiters to write more inclusive job advertisements. (shrink)

In recent developments in Artificial Intelligence and especially in robotics we can observe a tendency towards building intelligent artefacts that are meant to be social, to have ‘human social’ characteristics like emotions, the ability to conduct dialogue, to learn, to develop personality, character traits, and social competencies. Care, entertainment, pet and educational robots are conceptualised as friendly, understanding partners and credible assistants which communicate ‘naturally’ with users, show emotions and support them in everyday life. Social robots are often designed (...) to interact physically, affectively and socially with humans in order to learn from them. To achieve this goal, roboticists often model the human‐robot interaction on early caregiver‐infant interactions. In this paper I want to analyse prominent visions of these ‘socio‐emotional’ machines as well as early prototypes and commercial products with regard to the human‐machine interface. By means of this I will ask how feminist critiques of technology could be applied to the field of social robotics in which concepts like sociality or emotion are crucial elements while, at the same time, these concepts play an important role in feminist critiques of technology. (shrink)

The ability to represent same-different relations is an important condition for abstract thought. However, there is mixed evidence for when this ability develops, both ontogenetically and phylogenetically. Apparent success in relational reasoning may be evidence for genuine conceptual understanding or may be the result of low-level, perceptual strategies. We introduce a method to discriminate these possibilities by pitting two conditions that are perceptually matched but conceptually different: in a "fused" condition, same and different objects are joined, creating single objects that (...) have the same perceptual features as the two object pairs in the "relational" condition. However, the "fused" objects do not provide evidence for the relation 'same.' Using this method with human toddlers in a causal relational reasoning task provides evidence for genuine conceptual understanding. This novel technique offers a simple manipulation that may be applied to a variety of existing match-to-sample procedures used to assess same-different reasoning to include in future research with non-human animals across species, as well as human infants. (shrink)

Interactions between humans and bots are increasingly common online, prompting some legislators to pass laws that require bots to disclose their identity. The Turing test is a classic thought experiment testing humans’ ability to distinguish a bot impostor from a real human from exchanging text messages. In the current study, we propose a minimal Turing test that avoids natural language, thus allowing us to study the foundations of human communication. In particular, we investigate the relative roles of conventions (...) and reciprocal interaction in determining successful communication. Participants in our task could communicate only by moving an abstract shape in a 2D space. We asked participants to categorize their online social interaction as being with a human partner or a bot impostor. The main hypotheses were that access to the interaction history of a pair would make a bot impostor more deceptive and interrupt the formation of novel conventions between the human participants. Copying their previous interactions prevents humans from successfully communicating through repeating what already worked before. By comparing bots that imitate behavior from the same or a different dyad, we find that impostors are harder to detect when they copy the participants’ own partners, leading to less conventional interactions. We also show that reciprocity is beneficial for communicative success when the bot impostor prevents conventionality. We conclude that machine impostors can avoid detection and interrupt the formation of stable conventions by imitating past interactions, and that both reciprocity and conventionality are adaptive strategies under the right circumstances. Our results provide new insights into the emergence of communication and suggest that online bots mining personal information, for example, on social media, might become indistinguishable from humans more easily. (shrink)

In this article, we carry out a Multimodal Critical Discourse Analysis of a sample from a larger corpus of Romanian news articles that covered the controversial camp evictions and repatriation of Romanian Roma migrants from France that began in 2010 and continue to the time of writing in 2017. These French government policies have been highly criticized both within France and by international political and aid organizations. However, the analysis shows how these brutal, anti-humanitarian events became recontextualized in the Romanian (...) Press to represent the French government’s actions as peaceful and consensual. In addition, the demonization of the Roma in the press serves as a strategy to continuously disassociate them from their Romanian counterparts. While there is a long history of discrimination against the Roma in Romania, these particular recontextualizations can be understood in the context of the Romanian government’s need to gloss over its failure to comply with the Schengen accession requirements and acquire full European Union membership. (shrink)

The work consists mainly of a critical examination of various arguments which seek to show that machines cannot do something which humans can do. In particular the abilities to think, act intelligently, and behave purposefully are examined. The arguments dealt with are from works by Alan Turing, Keith Gunderson, Hubert Dreyfus, Richard Taylor, and Norman Malcolm. The author also considers an argument of his own against machines being able to make mistakes. The main conclusion of the work is that (...) each of the arguments in question fails. That is, none of the arguments show that machines lack the ability in question. (shrink)

The ability of very wealthy individuals (or, as I will call them, the ‘super-rich’) to turn their economic power into political power has been—and remains—an important cause of political inequality. In response, this paper advocates an original solution. Rather than solving the problem through implementing a comprehensive conception of political equality, or through enforcing complex rules about financial disclosure etc., I argue that we should impose a choice on the super-rich. The super-rich must choose between (i) forfeiting the things that (...) make them super-rich, i.e., pay a 100 % tax on their wealth above a certain level, or, (ii) they must forfeit some of their political rights. These rights include entitlements to fund political parties; to stand for office; and to work or volunteer for political parties. The right to vote, though, is not limited. I defend my proposal against non-consequentialist and consequentialist objections. I also argue that it avoids two problems that many attempts to reduce political inequality face; these are the political egalitarian’s dilemma and the problem of political equality’s relative moral importance. (shrink)

The diagnosis of a new geological epoch, The 'Anthropocene', has implications far beyond geological science. If human activity has disrupted the planet, then this diagnosis potentially disrupts socio-political conventions. This article assesses the implications the Anthropocene has for democratic politics, by delineating three challenges: challenges of knowledge, time and boundary. In contrast to the claim that democratic institutions are unable to adequately respond to these challenges, I suggest that they might be strengthened through an engagement with them. Following an (...) 'agonistic' understanding of politics, I argue that the contestation instigated by the challenges of the Anthropocene is key to democratic renewal. Just as democracy in the Anthropocene can be enhanced through an agonistic approach, agonistic theory can be enriched through an engagement with the Anthropocene. (shrink)

Radical democratic thinking is becoming intrigued by the material situatedness of its political agents and by the role of nonhuman participants in political interaction. At stake here is the displacement of narrow anthropocentrism that currently guides democratic theory and practice, and its repositioning into what we call ‘the nonhuman condition’. This Critical Exchange explores the nonhuman condition. It asks: What are the implications of decentering the human subject via a new materialist reading of radical democracy? Does this reading dilute (...) political agency? Or should this be seen, on the contrary, as an invitation for new voices and demands to enter into democratic assemblages? How might engagement with the more-than-human disrupt or extend theories of radical democracy? Hans Asenbaum and Amanda Machin discuss the human democratic subject both through radical democratic and new materialist lenses. They suggest that a new materialist decentred subject does not lose agency but further gains political responsibility in radical democracy. Jean-Paul Gagnon highlights the possibility of becoming through loss. In losing our anthropocentric arrogance—our understanding of being other and better than animal—we become more connected and discover our place in human-nonhuman assemblages. Melissa Orlie agrees that something can be gained through renouncing dominant human fantasies and presents a ‘radical democratic naturalism’. By renouncing land violence and acknowledging nature’s subjectivity, we can further nonexploitative radical democratic politics. This is where the notion of ‘tidalectic’ processes introduced by James L. Smith is helpful. Focusing on water and the Indigenous knowledges around rivers, he considers how democracy and community can be reimagined as plural, cyclical and attentive to the nonhuman with which the human is inevitably entangled. Diana Leong offers a different approach. Considering the nonhuman from the perspective of Black Studies demands an awareness to how blackness has long been constituted as non- or partially human. (shrink)

Animals, including humans, are usually judged on what they could become, rather than what they are. Many physical and cognitive abilities in the ‘animal kingdom’ are only acquired (to a given degree) when the subject reaches a certain stage of development, which can be accelerated or spoilt depending on how the environment, training or education is. The term ‘potential ability’ usually refers to how quick and likely the process of attaining the ability is. In principle, things should not be (...) different for the ‘machine kingdom’. While machines can be characterised by a set of cognitive abilities, and measuring them is already a big challenge, known as ‘universal psychometrics’, a more informative, and yet more challenging, goal would be to also determine the potential cognitive abilities of a machine. In this paper we investigate the notion of potential cognitive ability for machines, focussing especially on universality and intelligence. We consider several machine characterisations (non-interactive and interactive) and give definitions for each case, considering permanent and temporal potentials. From these definitions, we analyse the relation between some potential abilities, we bring out the dependency on the environment distribution and we suggest some ideas about how potential abilities can be measured. Finally, we also analyse the potential of environments at different levels and briefly discuss whether machines should be designed to be intelligent or potentially intelligent. (shrink)

Clinical ethics can be viewed as a practical discipline that provides a structured approach to assist healthcare practitioners in identifying, analysing and resolving ethical issues that arise in practice. Clinical ethics can therefore promote ethically sound clinical and organisational practices and decision-making, thereby contributing to health organisation and system quality improvement. In order to develop students’ decision-making skills, as well as prepare them for practice, we decided to introduce a clinical ethics strand within an undergraduate medical curriculum. We designed a (...) programme of clinical ethics activities for teaching and assessment purposes that involved using ethical frameworks to analyse hypothetical and real-life cases in uni- and inter- professional groups. In this paper, we draw on medical student feedback collected over 6 years to illustrate the appeal to students of learning clinical ethics. We also outline the range of benefits for students, healthcare organisations, and the field of clinical ethics arising from tomorrow’s doctors experiencing clinical ethics early in their training. We conclude by briefly reflecting on how including clinical ethics within tomorrow’s doctors curricular can secure and continue future engagement in clinical ethics support services in the UK, alongside the dangers of preparing students for organisational cultures that might not exist. We anticipate the findings presented in the paper will contribute to wider debates examining the impact of ethics teaching, and its ability to inform future doctors’ practice. (shrink)

The United Nations ‘Transforming our world: the 2030 Agenda for Sustainable Development’ lays out 17 Sustainable Development Goals to address a range of global issues related to the future of the planet and human well-being. Critics, however, argue that the Agenda, a complex product of multi-stakeholder governance, in its drive to accommodate many competing voices, is overloaded with weakly defined, overlapping and contradictory issues, concepts and buzzwords. These serve to gloss over actual concrete global problems and forces, concealing an (...) underlying free-trade ideology. In this paper, using Multimodal Critical Discourse Analysis, we draw attention to the nature of the documents used to communicate the Agenda. These documents comprise an edifice of self-referential texts that rely heavily on infographics, bullet points, charts and tables. Such formats appear to helpfully simplify, distil information and break things down into workable components. But, we show, through the affordances of these formats, the the vagueness of buzzwords, contradictions and lack of clear causalities can be glossed over, presenting the Agenda as a highly technical, engaging, and above all moral process. These formats are important, therefore, for the legitimization and rhetorical power of the Agenda, necessary for its take-up by governments and organizations around the world. (shrink)

Ethical analyses of biomedical human enhancement often consider the issue of authenticity — to what degree can the accomplishments of those utilizing biomedical enhancements be considered authentic or worthy of praise? As research into Brain-Computer Interface technology progresses, it may soon be feasible to create a BCI device that enhances or augments natural human intelligence through some invasive or noninvasive biomedical means. In this article we will review currently existing BCI technologies and to what extent these can be (...) said to enhance or augment the capabilities of the respective users, describe one hypothetical type of BCI device that could augment or enhance a specific aspect of human knowledge — namely, mathematical ability, and relate these concepts to the active externalism view of the extended mind as espoused by Clark and Chalmers in order to argue that knowledge of mathematics derived from the usage of a BCI and the application thereof constitutes authentic knowledge and achievement. (shrink)

The implementation of moral decision making abilities in artificial intelligence (AI) is a natural and necessary extension to the social mechanisms of autonomous software agents and robots. Engineers exploring design strategies for systems sensitive to moral considerations in their choices and actions will need to determine what role ethical theory should play in defining control architectures for such systems. The architectures for morally intelligent agents fall within two broad approaches: the top-down imposition of ethical theories, and the bottom-up building (...) of systems that aim at goals or standards which may or may not be specified in explicitly theoretical terms. In this paper we wish to provide some direction for continued research by outlining the value and limitations inherent in each of these approaches. (shrink)

Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be recognized (...) as an ability to perform certain tasks. We extend this notion of scientific understanding by considering a set of questions that gauge different levels of scientific understanding, covering information retrieval, the capability to arrange information to produce an explanation, and the ability to infer how things would be different under different circumstances. We suggest building a Scientific Understanding Benchmark (SUB), formed by a set of these tests, allowing for the evaluation and comparison of scientific understanding. Benchmarking plays a crucial role in establishing trust, ensuring quality control, and providing a basis for performance evaluation. By aligning machine and human scientific understanding we can improve their utility, ultimately advancing scientific understanding and helping to discover new insights within machines. (shrink)

Scientific understanding is a fundamental goal of science. However, there is currently no good way to measure the scientific understanding of agents, whether these be humans or Artificial Intelligence systems. Without a clear benchmark, it is challenging to evaluate and compare different levels of scientific understanding. In this paper, we propose a framework to create a benchmark for scientific understanding, utilizing tools from philosophy of science. We adopt a behavioral conception of understanding, according to which genuine understanding should be recognized (...) as an ability to perform certain tasks. We extend this notion of scientific understanding by considering a set of questions that gauge different levels of scientific understanding, covering information retrieval, the capability to arrange information to produce an explanation, and the ability to infer how things would be different under different circumstances. We suggest building a Scientific Understanding Benchmark (SUB), formed by a set of these tests, allowing for the evaluation and comparison of scientific understanding. Benchmarking plays a crucial role in establishing trust, ensuring quality control, and providing a basis for performance evaluation. By aligning machine and human scientific understanding we can improve their utility, ultimately advancing scientific understanding and helping to discover new insights within machines. (shrink)

A half-billion years ago, a few species of single-celled protozoa stumbled irreversibly from loose social interaction into a tight, specialized interdependence. They became multi-celled metazoa, and human beings are one sort. Metazoa greatly transcend their constituent cells in lifetime, abilities, experiences and even materials (like bone). New kind of beings emerged out of the interactions of the old.

In God Emperor of Dune, Leto II explains to Moneo why people destroyed thinking machines in the Butlerian Jihad: "Humans had set those machines to usurp our sense of beauty, our necessary selfdom out of which we make living judgments." The Orange Catholic Bible (OCB), the key religious text in the Dune universe, forbids the creation of machines that imitate human thinking: "Thou shalt not make a machine in the likeness of a man's mind." The OCB focuses on (...) human mental abilities – especially computation, reason, and logic – that have a status that machines should not emulate. In Frank Herbert's universe, divine imitation and creation are presented in conflicting ways: on the one hand, they are strictly prohibited, on the other, they are aspirations for key characters. Mentats replace machines by use of hard, cold, logical thinking and reasoning with machine‐like efficiency. (shrink)

The more recent computer developments cause us to take a new look at human intelligence. The prevailing occidental view of human intelligence represents a very one-sided, logocentric approach, so that it is becoming more urgent to look for a more complete view. In this way, specific strengths of so-called human information processing are becoming particularly evident in a new way. To provide a general substantiation for this view, some elements of a phenomenological model for a dialectical coherence (...) of human expressions of life are briefly outlined. The starting point is the everyday experience of constantly being confronted with contradictory situations. A model of polar, or dualistic, dialectic is proposed, which attempts to systematically establish the contradictions and contingencies of human life in theoretical structures. It is assumed that formal logic fails to work — strictly speaking — when applied to real situations of human interaction. Instead, definite negations are supposed to be involved. In this way, four polarities, pairs of concepts which are mutually dependent on each other and negate each other definitely, are presented: process and structure, the individual and general (societal), acting and imagining, subject-subject-relation and subject-object-relation (love and work). The latter gives rise to the dialectic of emotion and cognition, which plays a decisive role in a comparison of human and computer-“intelligence”.To cope with the specific human strengths, which are expressed through these polarities, self-learning computers would have to be able to act and to love like human beings and to grow up in a society like people. Furthermore, the learning process would have to implement the process-structure-dialectic with its aspects of finality. In spite of the recent breath-taking achievements of computers, one can not imagine how computers would ever achieve this. Computers are, however, thought of, by virtue of their complexity, being qualitatively different from machines. But human abilities still represent a new level of complexity: the level of dialectic. (shrink)

The paper explores integrating AI into scholarly communication for enhanced human cognitive abilities. The conception of human-machine communication (HMC) approach that regards AI-based technologies not as interactive objects, but communicative subjects, throws issues that are more philosophical in scholarly communication. It is a known fact that, there is increased interaction between humans and machines especially consolidated by COVID-19 pandemic, which heightened the development of Individual Adaptive Learning System thereby necessarily requiring inputs from NI to strengthen AI. (...) This positioned university at the juxtaposition for ensuring the production of highly talented individuals who can continue to think beyond the thinkable intelligently and enabling AI experts to carry on building algorithms that can further the development of technology to the next level. To perform such a task, research output is paramount in connecting university and publishing industry. The paper critically examines important components and tries to do justice for emanating of critical questions from researchers (NI) thus feeding the development of technology (AI). (shrink)

One of the more compelling features of Denis Dutton’s The Art Instinct is its theoretical parsimony. Utilizing what essentially amounts to one explanatory principle—that of Darwinian selection—Dutton advances a theory of aesthetics that is at once general enough to account for cross-cultural variations in artistic production and sufficiently nuanced to promote insights into individual artworks. In doing this, Dutton’s work could not offer a greater contrast to some of the more vocal trends in contemporary aesthetic theory, where ponderous theorizing and (...) rebarbative jargons have violently opposed the idea—otherwise so modest—that aesthetic activities might draw on the evolved capacities of the human imagination. On .. (shrink)

Ethics review processes are frequently perceived as extending from codes and protocols rooted in biomedical disciplines. As a result, many researchers in the humanities and social sciences (HASS) find these processes to be misaligned, if not outrightly obstructive to their research. This leads some scholars to advocate against HASS participation in institutional review processes as they currently stand, or in their entirety. While ethics review processes can present a challenge to HASS researchers, these are not insurmountable and, in fact, present (...) opportunities for ethics review boards (ERBs) to mediate their practices to better attend to the concerns of the HASS disciplines. By highlighting the potential value of the ethics review process in recognising the nuances and specificity across different forms of research, this article explores the generative possibilities of greater collaboration between HASS researchers and ERBs. Remaining cognisant of the epistemic and methodological differences that mark different disciplinary formations in turn will benefit the ethical conduct of all researchers. (shrink)

Computers are already approving financial transactions, controlling electrical supplies, and driving trains. Soon, service robots will be taking care of the elderly in their homes, and military robots will have their own targeting and firing protocols. Colin Allen and Wendell Wallach argue that as robots take on more and more responsibility, they must be programmed with moral decision-making abilities, for our own safety. Taking a fast paced tour through the latest thinking about philosophical ethics and artificial intelligence, the authors (...) argue that even if full moral agency for machines is a long way off, it is already necessary to start building a kind of functional morality, in which artificial moral agents have some basic ethical sensitivity. But the standard ethical theories don't seem adequate, and more socially engaged and engaging robots will be needed. As the authors show, the quest to build machines that are capable of telling right from wrong has begun. -/- Moral Machines is the first book to examine the challenge of building artificial moral agents, probing deeply into the nature of human decision making and ethics. (shrink)

Whitehead believed that education must give us ideas that are usable in our actual lives. This line of thought is naturally provoked by the significant abundance of inert ideas that people pile up though education. The main reason for that, I claim, is the wrong focus of traditional education. It aims at producing individuals that would deliver high results on exams and tests. I take Whitehead’s claim the education must put emphasis on usable ideas as my starting point. I give (...) a specific interpretation of useable ideas as abilities or functions. This provides a ground for connecting Whiteheadian thought to an already existing educational platform, offered by Nel Noddings. Noddings develops a cognitive theory of education which places cognitive structures (I assume a robust analogy between structures, functions, and abilities) in the center of educational concern. At the end of the paper, I estimate some consequences from adopting the terminology of functions for connecting between human and machine learning. (shrink)

A growing body of literature critical of ethics review boards has drawn attention to the processes used to determine the ethical merit of research. Citing criticism on the bureaucratic nature of ethics review processes, this literature provides a useful provocation for (re)considering how the ethics review might be enacted. Much of this criticism focuses on how ethics review boards _deliberate,_ with particular attention given to the lack of transparency and opportunities for researcher recourse that characterise ethics review processes. Centered specifically (...) on the conduct of ethics review boards convened within university settings, this paper draws on these inherent criticisms to consider the ways that ethics review boards might enact more communicative and deliberative practices. Outlining a set of principles against which ethics review boards might establish strategies for engaging with researchers and research communities, this paper draws attention to how _Deliberative communication_, _Engagement with researchers_ and the _Distribution of responsibility_ for the ethics review might be enacted in the day-to-day practice of the university human ethics review board. This paper develops these themes via a conceptual lens derived from Habermas’ (The theory of communicative action. Volume 1: Reason and the rationalization of society, 1984 ) articulation of ‘communicative action’ and Fraser’s (Social Text, 25(26), 56–80, 1990 ) consideration of ‘strong publics’ to cast consideration of the role that human ethics review boards might play in supporting university research cultures. _Deliberative communication_, _Engagement with researchers_ and the _Distribution of responsibility_ provide useful conceptual prompts for considering how ethics review boards might undertake their work. (shrink)

Humans make decisions about social information efficiently, despite – or perhaps because of – the sheer scale of data available. Of these various signals, sex cues are vitally important, yet understanding whether participants perceive them as static or dynamic is unknown. The present study addressed the related question of how expertise impinges on sex judgements. Participants were asked to target female and male exemplars from a set of own- or other-race hand images. Data show: that the own-race sex categorisation advantage (...) observed previously using face stimuli can occur in relation to hands, and sensitivity of Asian participants, but not Caucasian participants, is dynamic relative to how many fe/males there are in a set. Implications of these findings are discussed as further evidence that there exists a pan-stimulus sex processor, and as fresh evidence that human sex perception can change probabilistically. (shrink)

This paper investigates the medical law and ethics learning needs of Foundation doctors by means of a national survey developed in association with key stakeholders including the General Medical Council and Health Education England. Four hundred sevnty-nine doctors completed the survey. The average self-reported level of preparation in MEL was 63%. When asked to rate how confident they felt in approaching three cases of increasing ethical complexity, more FYs were fully confident in the more complex cases than in the more (...) standard case. There was no apparent relationship with confidence and reported teaching at medical school. The less confident doctors were no more likely to ask for further teaching on the topic than the confident doctors. This suggests that FYs can be vulnerable when facing ethical decisions by being underprepared, not recognising their lack of ability to make a reasoned decision or by being overconfident. Educators need to be aware of this and provide practical MEL training based on trainee experiences and real-world ethics and challenge learners’ views. Given the complexities of many ethical decisions, preparedness should not be seen as the ability to make a difficult decision but rather a recognition that such cases are difficult, that doubt is permissible and the solution may well be beyond the relatively inexperienced doctor. Educators and supervisors should therefore be ensuring that this is clear to their trainees. This necessitates an environment in which questions can be asked and uncertainty raised with the expectation of a supportive response. (shrink)

There is a widely held view that visual representations (images) do not depict negation, for example, as expressed by the sentence, “the train is not coming.” The present study focuses on the real-world visual representations of photographs and comic (manga) illustrations and empirically challenges the question of whether humans and machines, that is, modern deep neural networks, can recognize visual representations as expressing negation. By collecting data on the captions humans gave to images and analyzing the occurrences of negation phrases, (...) we show some evidence that humans recognize certain images as expressing negation. Furthermore, based on this finding, we examined whether or not humans and machines can classify novel images as expressing negation. The humans were able to correctly classify images to some extent, as expected from the analysis of the image captions. On the other hand, the machine learning model of image processing was only able to perform this classification at about the chance level, not at the same level of performance as the human. Based on these results, we discuss what makes humans capable of recognizing negation in visual representations, highlighting the role of the background commonsense knowledge that humans can exploit. Comparing human and machine learning performances suggests new ways to understand human cognitive abilities and to build artificial intelligence systems with more human-like abilities to understand logical concepts. (shrink)

Lake et al. propose three criteria which, they argue, will bring artificial intelligence (AI) systems closer to human cognitive abilities. In this paper, we explore the application of these criteria to a particular domain of human cognition: our capacity for moral reasoning. In doing so, we explore a set of considerations relevant to the development of AI moral decision-making. Our main focus is on the relation between dual-process accounts of moral reasoning and model-free/model-based forms of machine (...) learning. We also discuss how work in embodied and situated cognition could provide a valu- able perspective on future research. (shrink)

Large language models (LLMs) represent the currently most relevant incarnation of artificial intelligence with respect to the future fate of democratic governance. Considering their potential, this paper seeks to answer a pressing question: Could LLMs outperform humans as expert advisors to democratic assemblies? While bearing the promise of enhanced expertise availability and accessibility, they also present challenges of hallucinations, misalignment, or value imposition. Weighing LLMs’ benefits and drawbacks compared to their human counterparts, I argue for their careful integration to (...) augment democracy’s ability to address complex policy issues. The paper posits that time-tested democratic procedures like deliberation and aggregation by voting provide safeguards effective against both human and machine advisor imperfections. Additional protective measures include custom LLM training for the advisory role, boosting representatives’ competencies in query formulation, or implementation of adversarial proceedings in which LLM advisors could debate each other and provide dissenting opinions. These could further mitigate the risks that LLMs present in advisory roles and empower human decision-makers toward increased autonomy and quality of their collective choices. My conceptual exploration offers a roadmap for the co-evolution of AI and democratic institutions, setting the stage for an empirical research agenda to finetune the implementation specifics. (shrink)

We propose that the prevalent moral aversion to AWS is supported by a pair of compelling objections. First, we argue that even a sophisticated robot is not the kind of thing that is capable of replicating human moral judgment. This conclusion follows if human moral judgment is not codifiable, i.e., it cannot be captured by a list of rules. Moral judgment requires either the ability to engage in wide reflective equilibrium, the ability to perceive certain facts as moral (...) considerations, moral imagination, or the ability to have moral experiences with a particular phenomenological character. Robots cannot in principle possess these abilities, so robots cannot in principle replicate human moral judgment. If robots cannot in principle replicate human moral judgment then it is morally problematic to deploy AWS with that aim in mind. Second, we then argue that even if it is possible for a sufficiently sophisticated robot to make ‘moral decisions’ that are extensionally indistinguishable from (or better than) human moral decisions, these ‘decisions’ could not be made for the right reasons. This means that the ‘moral decisions’ made by AWS are bound to be morally deficient in at least one respect even if they are extensionally indistinguishable from human ones. Our objections to AWS support the prevalent aversion to the employment of AWS in war. They also enjoy several significant advantages over the most common objections to AWS in the literature. (shrink)

As robots increasingly become part of our everyday lives, questions arise with regards to how to approach them and how to understand them in social contexts. The Western history of human–robot relations revolves around competition and control, which restricts our ability to relate to machines in other ways. In this study, we take a relational approach to explore different manners of socializing with robots, especially those that exceed an instrumental approach. The nonhuman subjects of this study are built to (...) explore non-purposeful behavior, in an attempt to break away from the assumptions of utility that underlie the hegemonic human–machine interactions. This breakaway is accompanied by ‘learning to be attuned’ on the side of the human subjects, which is facilitated by continuous relations at the level of everyday life. Our paper highlights this ground for the emergence of meanings and questions that could not be subsumed by frameworks of control and domination. The research-creation project Machine Ménagerie serves as a case study for these ideas, demonstrating a relational approach in which the designer and the machines co-constitute each other through sustained interactions, becoming attuned to one another through the performance of research. Machine Ménagerie attempts to produce affective and playful—if not unruly—nonhuman entities that invite interaction yet have no intention of serving human social or physical needs. We diverge from other social robotics research by creating machines that do not attempt to mimic human social behaviours. (shrink)

Autonomy has been central to moral and political philosophy for millenia, and has been positioned as a critical aspect of both justice and wellbeing. Research in psychology supports this position, providing empirical evidence that autonomy is critical to motivation, personal growth and psychological wellness. Responsible AI will require an understanding of, and ability to effectively design for, human autonomy (rather than just machine autonomy) if it is to genuinely benefit humanity. Yet the effects on human autonomy of (...) digital experiences are neither straightforward nor consistent, and are complicated by commercial interests and tensions around compulsive overuse. This multi-layered reality requires an analysis that is itself multidimensional and that takes into account human experience at various levels of resolution. We borrow from HCI and psychological research to apply a model (“METUX”) that identifies six distinct spheres of technology experience. We demonstrate the value of the model for understanding human autonomy in a technology ethics context at multiple levels by applying it to the real-world case study of an AI-enhanced video recommender system. In the process we argue for the following three claims: 1) There are autonomy-related consequences to algorithms representing the interests of third parties, and they are not impartial and rational extensions of the self, as is often perceived; 2) Designing for autonomy is an ethical imperative critical to the future design of responsible AI; and 3) Autonomy-support must be analysed from at least six spheres of experience in order to approriately capture contradictory and downstream effects. (shrink)

When discussing AI alignment, we usually refer to the problem of teaching or training advanced autonomous AI systems to make decisions that are aligned with human values or preferences. Proponents of this approach believe it can be employed as means to stay in control over sophisticated intelligent systems, thus avoiding certain existential risks. We identify three general obstacles on the path to implementation of value alignment: a technological/technical obstacle, a normative obstacle, and a calibration problem. Presupposing, for the purposes (...) of this discussion, that the technical and normative problems are solved, we focus on the problem of how to calibrate a system, for a specific value, to be on a specific location within a spectrum stretching between righteous and normal or average human behavior. Calibration, or more specifically mis-calibration, also raises the issue of trustworthiness. If we cannot trust AI systems to perform tasks the way we intended, we would not use them on our roads and at our homes. In an era where we strive to construct autonomous machines endowed with common sense, reasoning abilities and a connection to the world, so they would be able to act in alignment with human values, such mis-calibrations can make the difference between trustworthy and untrustworthy systems. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Consciousness and Machines:A Commentary Drawing on Japanese PhilosophyS. D. Noam Cook (bio)Viewed from within the great unity of consciousness, thinking is a wave on the surface of a great intuition.Kitarō NishidaIntroductionRecent developments in AI have made the long-standing debate about what computers can and can't do a major public concern. What we understand the properties of such machines to be, and consequently how we design [End Page 305] and (...) deploy them, will increasingly shape how we live and how we understand ourselves. Thus, there is an urgent need for better understanding of these issues.Susan Schneider, in her book Artificial You: AI and the Future of Your Mind, offers an exceptionally careful and insightful examination of key issues entailed in how we understand AI and ourselves. One of her central concerns is how we might test for machine consciousness. Given the variations in design and function among current and projected AIs, Schneider sees no likely one-size-fits-all test. So, she offers a battery of different tests that she believes together will make such testing more reliable. This seems a wise approach, and reflects the conceptual and pragmatic care Schneider takes throughout the book.Similarly, it seems to me that the question of machine consciousness should also include various understandings of consciousness itself. What consciousness is taken to be has varied widely both historically and culturally. No commonly accepted single understanding has emerged, and may never emerge. Just as having a battery of tests might help us better assess possible machine consciousness, having different understandings of consciousness might give us a better understanding of what we are testing for. The two should work in tandem, each gauging and shaping the other.Like the development of computers themselves, the predominant thinking about AI has been shaped, in part, by key presuppositions of a scientific worldview, with its origins in Western thought and culture. Among these presuppositions are materialism, reductionism, and a primary focus on objective behavior. These are reflected in the common concern with observable behavior of physical aspects of the brain in efforts to understand human consciousness, which in turn has become a familiar model for work on machine consciousness. All this is important and valuable work. But, in the spirit of Schneider's cautions, it should not be taken as one-size-fits-all. Accordingly, I offer one view of consciousness from a different perspective.In what follows, I sketch out an understanding of consciousness that draws on Japanese philosophy, particularly that of the highly influential early twentieth-century Japanese philosopher Kitarō Nishida (1870–1945). I then explore how the tests for machine consciousness that Schneider proposes might be viewed from that perspective.Consciousness: A Perspective from Japanese PhilosophyConsciousness was a central concern for Nishida, whose philosophy is deeply informed by Japanese culture and by Zen theory and practice. As one might expect from such a philosopher, Nishida's exploration of consciousness is not concerned with properties of the brain, but with what we might discern through disciplined reflection on the experience of our own consciousness. Ultimately, he views consciousness as an organic whole [End Page 306] of systemically organized interrelationships of activities and sensations within our subjective experience. This may be understood by first considering 'nothingness'.For Nishida, nothingness does not suggest an ultimate and absolute vacuity, as is often understandably assumed. In Nishida's sense, it is a singular "place" that mirrors the multifaceted world of our common experience. In understanding this, I am told by native Japanese speakers that the English word 'nothingness' has an advantage over the Japanese equivalent, 'mu', in that 'nothingness' can usefully be broken down as 'nothing-ness'. This suggests that nothingness is a state of consciousness where what we commonly experience as distinct (self, other, world, blue, ache, joy, etc.) is indistinct, a state of unified experience. This is consciousness without our finding or discriminating in it the myriad "things" of common experience, but rather a "pure experience" of a singular whole. Nishida introduces his concept of "pure experience" as follows:To experience means to know facts just as they are, to know in accordance with facts by completely relinquishing one... (shrink)

The World Wide Web (Web) provides access to a global space of information assets and computational services. It also, however, serves as a platform for social interaction (e.g., Facebook) and participatory involvement in all manner of online tasks and activities (e.g., Wikipedia). There is a sense, therefore, that the advent of the Social Web has transformed our understanding of the Web. In addition to viewing the Web as a form of information repository, we are now able to view the Web (...) in more social terms. In particular, it has become possible to see the Web as providing access to the human social environment. This is important, because issues of social embedding and social interaction have been seen to contribute to the emergence of human cognitive capabilities. The ability of the Web to provide access to the human social environment thus raises an important question: Can humanity play a productive role in the emergence of advanced forms of machine intelligence by virtue of their interactions and engagements with the online realm? The present paper attempts to show why this question is worth asking. It also attempts to highlight some of the ways in which Web-based forms of contact with the human social environment may be relevant to research into machine intelligence. (shrink)

Humans make decisions about social information efficiently, despite – or perhaps because of – the sheer scale of data available. Of these various signals, sex cues are vitally important, yet understanding whether participants perceive them as static or dynamic is unknown. The present study addressed the related question of how expertise impinges on sex judgements. Participants were asked to target female and male exemplars from a set of own- or other-race hand images. Data show: that the own-race sex categorisation advantage (...) observed previously using face stimuli can occur in relation to hands, and sensitivity of Asian participants, but not Caucasian participants, is dynamic relative to how many fe/males there are in a set. Implications of these findings are discussed as further evidence that there exists a pan-stimulus sex processor, and as fresh evidence that human sex perception can change probabilistically. (shrink)

Even if it is never possible to create a sentient robot that might lay claim to the status of personhood, a convincingly realistic robotic simulation of the human body could alter how human beings act towards one another. This article argues that the human face exerts a powerful influence over interpersonal interaction, creating empathetic connections that limit our capacity to engage in acts of cruelty; an ability to convincingly simulate the human face would detach it from (...) the attribution of human personhood and so encourage a dismissal of its affective charge. This possibility can be understood in the context of existing attempts to inoculate individuals against the appeal of the face so as to facilitate organised killing. (shrink)

This paper analyzes creative practice including virtual music composition by a human and sets of computer programs, improvisation of music and dance in human-robot ensembles, and drawings produced by a human and a robotic arm. In all of these examples, the paper argues that creativity arises from a process of human-robot collaboration. Human influences on the machines involved exist at many levels, from initial creation and programming, via processes of reprogramming and setup of underlying data (...) and parameters, to engagement throughout the process of creative production. The decision to value a machine as a creative other is supported most strongly when collaborating with the machine directly, while witnessing the creative team at work, as opposed simply to seeing the result, is more likely to bring an audience to a similar understanding. The creativity of the human-machine collaborations analyzed in this paper relies on close interaction, within which there is a continual recognition of the otherness of the machine and its nonhuman abilities. Such relations can be theorized by extending Emmanuel Levinas’ conception of the face-to-face encounter within which self and other are brought into proximity, but the alterity of the other is nonetheless retained. The paper’s analysis of creative interactions between humans and robots supports the idea that machines need not be regarded as challenging human artistic practice, but rather enable new ways for creativity to arise through human-machine collaborations within which human and nonhuman creative abilities are combined. (shrink)

Significant research has been devoted to detecting people in images and videos. In this paper we describe a human de- tection method that augments widely used edge-based fea- tures with texture and color information, providing us with a much richer descriptor set. This augmentation results in an extremely high-dimensional feature space (more than 170,000 dimensions). In such high-dimensional spaces, classical machine learning algorithms such as SVMs are nearly intractable with respect to training. Furthermore, the number of training samples (...) is much smaller than the dimensionality of the feature space, by at least an order of magnitude. Finally, the extraction of features from a densely sampled grid structure leads to a high degree of multicollinearity. To circumvent these data characteristics, we employ Partial Least Squares (PLS) analysis, an effi- cient dimensionality reduction technique, one which pre- serves significant discriminative information, to project the data onto a much lower dimensional subspace (20 dimen- sions, reduced from the original 170,000). Our human de- tection system, employing PLS analysis over the enriched descriptor set, is shown to outperform state-of-the-art tech- niques on three varied datasets including the popular INRIA pedestrian dataset, the low-resolution gray-scale Daim- lerChrysler pedestrian dataset, and the ETHZ pedestrian dataset consisting of full-length videos of crowded scenes. (shrink)

Harun Farocki's films make use of a category of images the director calls “operational”, a term describing images, either photographic or computer-generated, that perform or participate in tasks, usually in military or industrial settings. Treatments of Farocki's films have frequently used the notion of the operational image uncritically, and without comparing Farocki's definition of these images with existing semiotic categories. This article seeks to situate Farocki's operational imagery within a theory of visual communication, and to explore the implications of automated (...) and instrumental imagery for theories of communication in general. Abandoning the focus in much Farocki scholarship on the representative properties of operational imagery, this article focuses on the world-shaping abilities of images that are integral to war and labour. Drawing primarily on Farocki's Eye / Machine I–III series ( Auge / Maschine, 2000–2003) the article then elaborates on the ways in which the world-shaping capacity of operational images conditions human perception and action. In particular, the limitations imposed by operational images upon human actors who interact with them, or live in environments orchestrated by them, reduce the essential role played by indeterminacy and interpretation in communication. (shrink)

Through hypothetical scenarios, this paper analyses whether machine learning (ML) could resolve one of the main shortcomings present in Christopher Boorse’s Biostatistical Theory of health (BST). In doing so, it foregrounds the boundaries and challenges of employing ML in formulating a naturalist (i.e., prima facie value-free) definition of health. The paper argues that a sweeping dataist approach cannot fully make the BST truly naturalistic, as prior theories and values persist. It also points out that supervised learning introduces circularity, rendering (...) it incompatible with a naturalistic perspective. Additionally, it underscores the need for pre-existing auxiliary theories to assess results from unsupervised learning. It emphasizes the importance of understanding the epistemological entanglements between data and data processing methods to manage expectations about what data patterns can predict. In conclusion, the paper argues against delegating the final authority for defining complex concepts like health to AI systems, as it necessitates ethical judgment and capacities for deliberation that AI currently lacks. It also warns against granting creators and deployers of AI systems the discretionary authority to determine these definitions outside the wider social discussion, advocating for ongoing public engagement on normative notions. Failure to do so risks limiting individuals and collectives’ ability to shape a just digital future and diminishes their fundamental epistemic agency. (shrink)