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(Featured) Could a Conscious Machine Deliver Pastoral Care?

Could a Conscious Machine Deliver Pastoral Care?

At the intersection of theology, philosophy, and futures studies, Andrew Proudfoot examines of the potential for genuine encounter between humans and hypothetically conscious artificial intelligence (CAI) from the perspective of Barthian theology. The author utilizes Karl Barth’s fourfold schema of encounter, which includes address, response, assistance, and gladness, as a framework for this exploration. The article’s premise is the hypothetical existence of CAI, which, for the sake of argument, is assumed to lack capax Dei, or the capacity for God.

In the first part of the article, the author discusses the initial two aspects of Barthian encounter—address and response. The author speculates that a CAI, with its presumed self-awareness and rationality, could engage in verbal discourse with humans, thus fulfilling these two aspects. However, the author emphasizes the importance of maintaining a clear distinction between humans and AI, even if the AI appears to be human-like. This delineation is crucial to ensure that the encounter is authentic and not misleading or manipulative.

Next, the author delves into the third and fourth stages of Barthian encounter—assistance and gladness. While a CAI cannot provide the same depth of assistance as a human or divine entity, it could provide help commensurate with its abilities. The author also postulates that a CAI could exhibit a form of formal gladness, equivalent to non-Christian eros love, if it is designed with an intrinsic desire for social interaction. However, the lack of capax Dei limits the CAI’s pastoral role and the depth of its encounters with humans.

The article’s philosophical significance lies in the way it prompts us to examine the nature of encounter, consciousness, and authenticity in a world where AI technologies are becoming increasingly advanced. It asks us to rethink the nature of interaction and relationship in a context that transcends the human sphere. The author uses Barthian theology as a lens to explore these themes, but the implications extend beyond this particular theological framework, touching upon broader philosophical discussions about selfhood, otherness, and the ethics of AI.

The research article paves the way for several future research directions. One such direction could involve a more in-depth exploration of the ontological and metaphysical commitments needed to support the notion of a conscious computer within a Christian theological framework. Another potential avenue could be an investigation into the relationship between consciousness and capax Dei, contemplating whether the latter could emerge from the former or if it necessitates divine intervention. Finally, the author’s suggestion that non-human personas might be more beneficial for AI poses an intriguing question for future research, prompting us to reflect on the nature of deception and authenticity in AI-human relationships. The article thus not only contributes to our understanding of potential AI-human encounters but also opens the door to myriad further explorations in the field.

Abstract

Could Artificial Intelligence (AI) play an active role in delivering pastoral care? The question rests not only on whether an AI could be considered an autonomous agent, but on whether such an agent could support the depths of relationship with humans which is essential to genuine pastoral care. Theological consideration of the status of human-AI relations is heavily influenced by Noreen Herzfeld, who utilises Karl Barth’s I-Thou encounters to conclude that we will never be able to relate meaningfully to a computer since it would not share our relationship to God. In this article, I look at Barth’s anthropology in greater depth to establish a more comprehensive and permissive foundation for human-machine encounter than Herzfeld provides—with the key assumption that, at some stage, computers will become conscious. This work allows discussion to shift focus to the challenges that the alterity of the conscious computer brings, rather than dismissing it as a non-human object. If we can relate as an I to a Thou with a computer, then this allows consideration of the types of pastoral care they could provide.

Could a Conscious Machine Deliver Pastoral Care?
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(Featured) The Ethics of Technology: How Can Indigenous Thought Contribute?

The Ethics of Technology: How Can Indigenous Thought Contribute?

John Weckert and Rogelio Bayod present a comprehensive examination of the intersection between ethics, technology, and Indigenous worldviews. The authors argue that the ethics of technology, which largely remains a peripheral concern in technological developments, could significantly benefit from the incorporation of Indigenous perspectives. They contend that the entrenched paradigms of Western thought, with their focus on materialism, individualism, efficiency, and progress, often marginalize ethical considerations. This, they suggest, is where Indigenous worldviews, which emphasize relationality, spirituality, and a reciprocal relationship with the Earth, could offer a potent alternative.

A key aspect of Indigenous thought highlighted in the paper is the concept of relationality. Indigenous worldviews often consider all entities, living and non-living, as interconnected and mutually influential. This view contrasts with the Western conceptualization of individual entities as distinct and primarily self-interested. Consequently, incorporating this perspective into the ethics of technology could help shift the focus from the maximization of individual benefits to the maintenance of collective well-being. The paper also underscores the Indigenous emphasis on spirituality, where both natural and man-made objects can hold spiritual or non-material significance. This perspective could help challenge the prevailing Western materialistic worldview, fostering a more holistic understanding of technological artifacts and their value.

The authors propose that integrating these Indigenous concepts could provide a foundation for a reimagined Western worldview, even if these elements are interpreted metaphorically rather than literally. Such a worldview, they argue, would not only challenge the prevailing emphasis on materialistic values but could also facilitate a more beneficial development and use of technology. This reframed paradigm would prioritize environmental health, reduce the production of disposable products, and lessen the focus on profitability, efficiency, and individualism. Instead, it would place greater emphasis on care for the Earth, kinship, relationships, and spirituality.

This research contributes to broader philosophical discussions around the ethics of technology and futures studies. It offers a critical reframing of our relationship with technology, drawing on Indigenous worldviews to challenge dominant Western paradigms. By doing so, it highlights the value of diverse perspectives in shaping our technological futures and raises critical questions around the role of values and worldviews in guiding technological development. This paper thus adds to ongoing debates around decolonizing technology and futures studies, and extends them into the sphere of ethics.

The paper suggests numerous avenues for future research. Given its emphasis on the potential of Indigenous worldviews, further explorations could delve deeper into specific Indigenous perspectives on technology, drawing from a wider range of cultures and traditions. Another promising area for future research could involve examining how these Indigenous values could be operationalized within different technological domains, and the possible impacts this could have. Finally, there is a significant need for empirical research on how this paradigm shift might be achieved, and the potential barriers and facilitators involved. This research paper thus opens the door to a rich array of investigations that could fundamentally reshape our understanding of the ethics of technology.

Abstract

The ethics of technology is not as effective as it should. Despite decades of ethical discussion, development and use of new technologies continues apace without much regard to those discussions. Economic and other forces are too powerful. More focus needs to be placed on the values that underpin social attitudes to technology. By seriously looking at Indigenous thought and comparing it with the typical Western way of seeing the world, we can gain a better understanding of our own views. The Indigenous Filipino worldview provides us with a platform for assessing our own core values and suggests modifications to those values. It also indicates ways for broadening and altering the focus of the ethics of technology to make it more effective in helping us to use technologies in ways more conducive to human well-being.

The Ethics of Technology: How Can Indigenous Thought Contribute?
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(Featured) Research Ethics in the Age of Digital Platforms

Research Ethics in the Age of Digital Platforms

José Luis Molina et al. explore the ethical implications of microwork, a novel form of labor facilitated by digital platforms. The authors articulate the nuanced dynamics of this field, focusing primarily on the asymmetrical power relations between microworkers, clients, and platform operators. The piece scrutinizes the transactional nature of microwork, where workers are subject to the platform’s regulations and risk the arbitrary denial of payment or termination of their accounts. Microworkers’ reputation, determined by their prior task success rate, often dictates the quality and quantity of tasks they receive, creating a system of algorithmic governance that perpetuates an exploitative dynamic.

The authors further illustrate this situation by examining the biomedical research standards developed in the aftermath of World War II, which they argue are ill-equipped to address the ethical quandaries posed by microwork. They argue that the conditions of microwork, such as lack of payment floors and the potential for anonymity and segmentation, exacerbate the vulnerability of these workers, aligning them more closely with the exploitation of vulnerable populations in traditional research contexts. They propose a reconceptualization of microworkers as “guest workers” in “digital autocracies,” where the platforms exercise a quasi-governmental control over the working conditions, identity, and compensation of the microworkers.

The authors posit that these digital autocracies extract value through “heteromation” – a process where labor is mediated between cheap human labor and computers, and through the appropriation of workers’ rights to privacy and personal data protection. They argue that microwork platforms, due to their transnational nature and lack of comprehensive regulation, can impose conditions on their workforce that would be unacceptable in traditional employment contexts. They stress the importance of recognizing microworkers as vulnerable populations in research ethics reviews and propose a set of criteria for researchers to ensure the protection of these workers’ rights.

Positioning microwork within the broader philosophical discourse, the authors’ analysis suggests a reevaluation of labor, autonomy, and ethical standards in the digital age. The “digital autocracies” mirror Foucault’s concept of biopower, where power is exerted not merely through coercion but through the management and control of life processes, in this case, the economic existence of microworkers. The situation also reflects Marx’s concept of alienation, as microworkers are distanced from the fruits of their labor, the process of their work, and their fellow workers. The algorithmic governance system also raises questions about agency and autonomy, echoing concerns raised by philosophers such as Hannah Arendt and Jürgen Habermas regarding the instrumentalization of human beings.

Future research in this domain could explore multiple avenues. First, a more extensive empirical study could be conducted to quantify and analyze the conditions of microworkers across different platforms and geographical regions. Second, a comparative study could be undertaken to examine how different regulatory environments impact the working conditions and rights of microworkers. Lastly, a philosophical exploration of notions such as autonomy, justice, and dignity within the digital labor context could provide a more profound understanding of this emerging labor paradigm. The complex interplay of labor, ethics, technology, and globalization, as exemplified by microwork, provides a rich and crucial area for futures studies.

Abstract

Scientific research is growingly increasingly reliant on “microwork” or “crowdsourcing” provided by digital platforms to collect new data. Digital platforms connect clients and workers, charging a fee for an algorithmically managed workflow based on Terms of Service agreements. Although these platforms offer a way to make a living or complement other sources of income, microworkers lack fundamental labor rights and basic safe working conditions, especially in the Global South. We ask how researchers and research institutions address the ethical issues involved in considering microworkers as “human participants.” We argue that current scientific research fails to treat microworkers in the same way as in-person human participants, producing de facto a double morality: one applied to people with rights acknowledged by states and international bodies (e.g., the Helsinki Declaration), the other to guest workers of digital autocracies who have almost no rights at all. We illustrate our argument by drawing on 57 interviews conducted with microworkers in Spanish-speaking countries.

Research Ethics in the Age of Digital Platforms
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(Featured) Can robots be trustworthy?

Can robots be trustworthy?

Ines Schröder et al. present an in-depth exploration of the phenomenological and ethical implications of socially assistive robots (SARs), with a specific focus on their role within the medical sector. Central to the discussion is the concept of responsivity, a construct that the authors argue is inherent to human experience and mirrored, to a certain extent, in human-robot interactions. They explore the nature of this perceived responsivity and its implications for the philosophical understanding of human-robot relations.

The article begins by drawing a distinction between human and artificial responsivity, elucidating the phenomenological structure of human responsivity and how it is translated into SARs’ design. The authors underscore how SARs’ design parameters, such as AI-enhanced speech recognition, physical mobility, and social affordances, culminate in a form of ‘virtual responsivity.’ This virtual responsivity serves to mimic human interaction, creating a semblance of empathy and understanding. However, the authors also emphasize the limitations of this approach, highlighting the potential for deception and the lack of essential direct reciprocity inherent in genuine ethical responsivity.

The crux of the article lies in its examination of the ethical implications of this constructed responsivity. The authors grapple with the potential ethical pitfalls, tensions, and challenges of SARs, particularly within the domain of medical applications. They articulate concerns regarding the preservation of patient autonomy, the balancing of beneficial impact against inherent risks, and the principle of justice in relation to access to advanced technologies. The authors further highlight the three ethically relevant dimensions of vulnerability, dignity, and trust in relation to responsivity, emphasizing the importance of these dimensions in human-robot interactions.

Broadly, the research intersects with larger philosophical themes concerning the nature of consciousness, personhood, and the moral status of non-human entities. The authors’ analysis of SARs’ ‘virtual responsivity’ challenges conventional understandings of these concepts, raising critical questions about the attribution of moral status and the potential for emotional attachment to non-human entities. The exploration of ethical dimensions of vulnerability, dignity, and trust in the context of human-robot interactions further elucidates the evolving dynamics of human-machine relationships, providing a nuanced perspective on the philosophical implications of advanced technology.

Looking towards the future, the research opens several avenues for further exploration. One potential focus is the development of a robust ethical framework for the design and use of SARs, especially in sensitive domains such as healthcare. There is a need for research into ‘ethically sensitive responsiveness,’ which could provide a basis for setting appropriate boundaries in human-robot interactions and ensuring the clear communication of a robot’s capabilities and limitations. Additionally, empirical research exploring the psychological effects of human-robot interactions, particularly in relation to the formation of trust, would be invaluable. Overall, the ethical and philosophical implications of artificial responsivity necessitate a multidisciplinary approach, inviting further dialogue between fields such as robotics, ethics, philosophy, and psychology.

Abstract

Definition of the problem

This article critically addresses the conceptualization of trust in the ethical discussion on artificial intelligence (AI) in the specific context of social robots in care. First, we attempt to define in which respect we can speak of ‘social’ robots and how their ‘social affordances’ affect the human propensity to trust in human–robot interaction. Against this background, we examine the use of the concept of ‘trust’ and ‘trustworthiness’ with respect to the guidelines and recommendations of the High-Level Expert Group on AI of the European Union.

Arguments

Trust is analyzed as a multidimensional concept and phenomenon that must be primarily understood as departing from trusting as a human functioning and capability. To trust is an essential part of the human basic capability to form relations with others. We further want to discuss the concept of responsivity which has been established in phenomenological research as a foundational structure of the relation between the self and the other. We argue that trust and trusting as a capability is fundamentally responsive and needs responsive others to be realized. An understanding of responsivity is thus crucial to conceptualize trusting in the ethical framework of human flourishing. We apply a phenomenological–anthropological analysis to explore the link between certain qualities of social robots that construct responsiveness and thereby simulate responsivity and the human propensity to trust.

Conclusion

Against this background, we want to critically ask whether the concept of trustworthiness in social human–robot interaction could be misguided because of the limited ethical demands that the constructed responsiveness of social robots is able to answer to.

Can robots be trustworthy?
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(Featured) Beyond the hype: ‘acceptable futures’ for AI and robotic technologies in healthcare

Beyond the hype: ‘acceptable futures’ for AI and robotic technologies in healthcare

Giulia De Togni et al. delve into the complex dynamics of technoscientific expectations surrounding the future of artificial intelligence (AI) and robotic technologies in healthcare. By focusing on surgery, pathology, and social care, they examine the strategies employed by scientists, clinicians, and other stakeholders to navigate and construct visions of an AI-driven future in healthcare. The authors illustrate the challenges faced by these stakeholders, who must balance promissory visions with more realistic expectations, while acknowledging the performative power of high expectations in attracting investment and resources.

The participants in the study engage in a balancing act between high and low expectations, drawing boundaries to maintain credibility for their research and practice while distancing themselves from the hype. They recognize that over-optimistic visions may create false hope and unrealistic expectations of performance, potentially harming AI and robotics research through deflated investment if the outcomes fail to match expectations. The authors demonstrate how the stakeholders negotiate the tension between sustaining and nurturing the hype while calling for the recalibration of expectations within an ethically and socially responsible framework.

Central to the participants’ visions of acceptable futures is the changing nature of human-machine relationships. Through balancing different social, ethical, and technoscientific demands, the participants articulate futures that are perceived as ethically and socially acceptable, as well as realistically achievable. They frame their articulations of both the present and future potential and limitations of AI and robotics technologies within an ethics of expectations that position normative considerations as central to how these expectations are expressed.

This research article contributes to broader philosophical debates concerning the role of expectations and imaginaries in shaping our understanding of technoscientific innovation, human-machine relationships, and the ethics of care. By exploring the dynamic interplay between these factors, the authors shed light on how the future of AI and robotics in healthcare is being constructed and negotiated. This study resonates with key themes in the philosophy of futures studies, including the co-constitution of technological visions and sociotechnical imaginaries, the performativity of expectations, and the ethical dimensions of forecasting and envisioning the future.

To further enrich our understanding of these complex dynamics, future research could explore the perspectives of additional stakeholders, such as patients and policymakers, to gain a more comprehensive picture of the expectations surrounding AI and robotics in healthcare. Additionally, cross-cultural and comparative studies could reveal how different cultural contexts and healthcare systems influence expectations and acceptance of these technologies. Ultimately, by continuing to examine the societal implications of AI and robotic technologies, including their impact on patient autonomy, privacy, and the human aspects of care, scholars can contribute to a more nuanced and ethically responsible vision of the future of healthcare.

Abstract

AI and robotic technologies attract much hype, including utopian and dystopian future visions of technologically driven provision in the health and care sectors. Based on 30 interviews with scientists, clinicians and other stakeholders in the UK, Europe, USA, Australia, and New Zealand, this paper interrogates how those engaged in developing and using AI and robotic applications in health and care characterize their future promise, potential and challenges. We explore the ways in which these professionals articulate and navigate a range of high and low expectations, and promissory and cautionary future visions, around AI and robotic technologies. We argue that, through these articulations and navigations, they construct their own perceptions of socially and ethically ‘acceptable futures’ framed by an ‘ethics of expectations.’ This imbues the envisioned futures with a normative character, articulated in relation to the present context. We build on existing work in the sociology of expectations, aiming to contribute towards better understanding of how technoscientific expectations are navigated and managed by professionals. This is particularly timely since the COVID-19 pandemic gave further momentum to these technologies.

Beyond the hype: ‘acceptable futures’ for AI and robotic technologies in healthcare
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(Featured) Modifying the Environment or Human Nature? What is the Right Choice for Space Travel and Mars Colonisation?

Modifying the Environment or Human Nature? What is the Right Choice for Space Travel and Mars Colonisation?

Maurizio Balistreri and Steven Umbrello engage in a critical exploration of the philosophical, ethical, and practical implications of human space travel and extraterrestrial colonization. The authors offer an in-depth analysis of two main strategies proposed in the literature: terraforming (geoengineering) and human bioenhancement. The first approach implies transforming extraterrestrial environments, such as Mars, to make them habitable for human life. The second approach involves modifying the human genetic heritage to make us more resilient and adaptable to non-terrestrial environments. The authors meticulously scrutinize these alternatives, considering not only feasibility and cost but also the ethical and philosophical implications.

The authors underscore the potential of terraforming as a method to establish human settlements on Mars. However, this possibility raises several ethical concerns, including the potential destruction of extraterrestrial life forms, the alteration of untouched landscapes, and the potential overstepping of human dominion. On the other hand, human bioenhancement, though a promising path, engenders its own set of ethical dilemmas. The authors caution against reckless enthusiasm for genetic modification, drawing attention to the potential creation of a new ‘human species’ and the consequent risk of divisions and misunderstandings.

A central theme in the article is the comparison of natural and artificial constructs. The authors challenge the assumption that the natural is always superior to the artificial. Drawing on posthumanist perspectives, they suggest that, given our influence on Earth’s environment, nature is already an artificial product. The argument is extended to other planets, indicating that the traditional dichotomy between the natural and the artificial may not hold in the context of extraterrestrial colonization.

The article contributes to broader philosophical discourses about the human relationship with nature and our place in the universe. It resonates with themes of transhumanism and posthumanism, contemplating the potential of technology to overcome human vulnerabilities and achieve a new evolutionary stage. The authors invite us to question and possibly redefine our notions of ‘natural’ and ‘artificial.’ This study, therefore, serves as a significant touchstone for futures studies, linking the practical considerations of space travel with philosophical reflections on human nature and our interaction with the environment.

For future research, the authors’ comparative analysis of terraforming and human bioenhancement opens several avenues. While the ethical implications of both strategies have been discussed, a more comprehensive ethical framework could be developed, perhaps drawing on principles of bioethics, environmental ethics, and space ethics. Additionally, the potential of hybrid approaches combining elements of both strategies could be explored. Lastly, given the increasing likelihood of extraterrestrial colonization, a more detailed analysis of the potential social, cultural, and psychological impacts on human populations in these new environments would be a valuable contribution.

Abstract

As space travel and intentions to colonise other planets are becoming the norm in public debate and scholarship, we must also confront the technical and survival challenges that emerge from these hostile environments. This paper aims to evaluate the various arguments proposed to meet the challenges of human space travel and extraterrestrial planetary colonisation. In particular, two primary solutions have been present in the literature as the most straightforward solutions to the rigours of extraterrestrial survival and flourishing: (1) geoengineering, where the environment is modified to become hospitable to its inhabitants, and (2) human (bio)enhancement where the genetic heritage of humans is modified to make them more resilient to the difficulties they may encounter as well as to permit them to thrive in non-terrestrial environments. Both positions have strong arguments supporting them but also severe philosophical and practical drawbacks when exposed to different circumstances. This paper aims to show that a principled stance where one position is accepted wholesale necessarily comes at the opportunity cost of the other where the other might be better suited, practically and morally. This paper concludes that case-by-case evaluations of the solutions to space travel and extraterrestrial colonisation are necessary to ensure moral congruency and the survival and flourishing of astronauts now and into the future.

Modifying the Environment or Human Nature? What is the Right Choice for Space Travel and Mars Colonisation?
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(Featured) Machine learning in bail decisions and judges’ trustworthiness

Machine learning in bail decisions and judges’ trustworthiness

Alexis Morin-Martel navigates the intricate landscape of judicial decision-making and advances the concept of Judge Assistance Systems (JAS), proposing it as a tool for enhancing the trustworthiness of judges in bail decisions. The argument is grounded in the relational theory of procedural justice, which emphasizes the role of trust, voice, neutrality, and respect in the administration of justice. The research underpins its analysis through an exploration of the nuanced terrain of trustworthiness, distinguishing between actual and rich trustworthiness, and articulating the potential role of JAS in amplifying both.

The author leverages the empirical study by Kleinberg et al. (2017a) to illustrate how JAS, equipped with complex algorithms, can assist judges in making more precise bail decisions, thereby enhancing their actual trustworthiness. A key idea espoused is the potential for JAS to act as a check on judicial decision-making, allowing judges to reconsider decisions that deviate significantly from statistical norms. However, the author acknowledges that the implementation of JAS should not undermine the principle of voice, one of the pillars of relational justice, ensuring that defendants have the opportunity to influence the decision-making process.

Further, the study takes into account the perceived trustworthiness of judges when using a JAS. It acknowledges the inherent public skepticism towards algorithmic decisions, often due to their perceived opacity. The argument is made that focusing on accuracy, rather than transparency, of these algorithms is more likely to enhance perceived trustworthiness. Importantly, the author suggests that regular audits within legal institutions could effectively monitor the accuracy of JAS, thus reinforcing public trust over time. However, the author admits that while the ‘voice’ and ‘neutrality’ criteria could likely be met by JAS, its ability to meet the ‘respect’ requirement remains uncertain and needs further examination.

The research article finds a nexus with broader philosophical themes, particularly those concerning human-machine interaction and the ethical implications of algorithmic decision-making. The proposal of JAS as a tool to enhance judicial trustworthiness is reflective of the broader trend towards technocratic governance. This trend raises critical questions about the balance between human judgment and algorithmic precision, and the philosophical implications of delegating traditionally human tasks to artificial intelligence. Moreover, the emphasis on accuracy over transparency in JAS echoes the larger debate on the ethical trade-offs in AI applications, especially in high-stake public decisions.

Future research could explore several intriguing avenues. The extension of JAS to other areas of judicial decision-making, beyond bail decisions, could be considered. Studies could also focus on the development of more transparent and interpretable models without compromising accuracy, addressing public distrust of ‘black box’ algorithms. Furthermore, future research might investigate the potential impact of JAS on other aspects of the relational theory of procedural justice, particularly the ‘respect’ requirement. Lastly, empirical studies evaluating the effectiveness and reliability of JAS in real-world court settings could provide valuable insights into the practicality of implementing such systems.

Abstract

The use of AI algorithms in criminal trials has been the subject of very lively ethical and legal debates recently. While there are concerns over the lack of accuracy and the harmful biases that certain algorithms display, new algorithms seem more promising and might lead to more accurate legal decisions. Algorithms seem especially relevant for bail decisions, because such decisions involve statistical data to which human reasoners struggle to give adequate weight. While getting the right legal outcome is a strong desideratum of criminal trials, advocates of the relational theory of procedural justice give us good reason to think that fairness and perceived fairness of legal procedures have a value that is independent from the outcome. According to this literature, one key aspect of fairness is trustworthiness. In this paper, I argue that using certain algorithms to assist bail decisions could increase three different aspects of judges’ trustworthiness: (1) actual trustworthiness, (2) rich trustworthiness, and (3) perceived trustworthiness.

Machine learning in bail decisions and judges’ trustworthiness
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(Featured) In Conversation with Artificial Intelligence: Aligning language Models with Human Values

In Conversation with Artificial Intelligence: Aligning language Models with Human Values

Atoosa Kasirzadeh and Iason Gabriel embark on an ambitious analysis of how large-scale conversational agents, such as AI language models, can be better designed to align with human values. The premise of the article is grounded in the philosophy of language and pragmatics, employing Gricean maxims and Speech Act Theory to establish the importance of context and cooperation in achieving effective and ethical linguistic communication. The authors underscore the necessity of considering pragmatic norms and concerns in the design of conversational agents and illustrate their proposition through three discursive domains: science, civic life, and creative exchange.

The authors present a novel approach, suggesting the operationalization of Gricean maxims of quantity, quality, relation, and manner, to aid in cooperative communication between humans and AI. They also emphasize the diversity of utterances, asserting that there is no single universal condition of validity that applies to all. Instead, the validity of utterances often depends on different sorts of truth conditions which require different methodologies for substantiation, based on context-specific criteria of validity. They further stress the centrality of contextual information in the design of ideal conversational agents and highlight the need for research to theorise and measure the difference between the literal and contextual meaning of utterances.

The authors also delve into the implications of their analysis for future research into the design of conversational agents. They discuss the potential for anthropomorphisation of conversational agents and the constraints that might be imposed on them. They note that while anthropomorphism can sometimes be consistent with the creation of value-aligned agents, there are situations where it might be undesirable or inappropriate. They also advocate for the exploration of the potential for conversational agents to facilitate more robust and respectful conversations through context construction and elucidation. Lastly, they suggest that their analysis could be used to evaluate the quality of interactions between conversational agents and users, providing a framework for refining both human and automatic evaluation of conversational agent performance.

The research article resonates with broader philosophical themes, particularly those concerning the interplay between technology and society. It touches upon the ethical dimensions of AI, hinting at the moral responsibility of designing AI systems that align with human values and norms. The exploration of Gricean maxims and Speech Act Theory in the context of AI conversational agents provides a unique blend of AI ethics, philosophy of language, and pragmatics, reflecting the interdisciplinary nature of contemporary AI research. In doing so, the article stimulates dialogue about the role of AI in shaping our social and communicative practices, challenging conventional boundaries between humans and machines, and highlighting the potential of AI as a tool for fostering effective and ethically sound communication.

In terms of future avenues of research, the authors’ analysis opens up a myriad of possibilities. First, while the paper focuses primarily on the English language, a fruitful direction of research could involve the exploration of norms and pragmatics in other languages, thereby ensuring the cultural inclusivity and sensitivity of AI systems. Second, the proposed alignment of AI conversational agents with Gricean maxims and discursive ideals could be further operationalized and tested empirically to assess its effectiveness in real-world scenarios. Third, the article alludes to the potential of AI in fostering more robust and respectful conversations, which suggests an opportunity to investigate how AI can play an active role in shaping discourse norms and facilitating constructive dialogues. Lastly, the authors’ work can be further enriched by drawing from other sociological and philosophical traditions, such as Luhmann’s system theory or Latour’s actor-network theory, to offer a more comprehensive and nuanced understanding of the complex interplay between AI, language, and society.

Abstract

Large-scale language technologies are increasingly used in various forms of communication with humans across different contexts. One particular use case for these technologies is conversational agents, which output natural language text in response to prompts and queries. This mode of engagement raises a number of social and ethical questions. For example, what does it mean to align conversational agents with human norms or values? Which norms or values should they be aligned with? And how can this be accomplished? In this paper, we propose a number of steps that help answer these questions. We start by developing a philosophical analysis of the building blocks of linguistic communication between conversational agents and human interlocutors. We then use this analysis to identify and formulate ideal norms of conversation that can govern successful linguistic communication between humans and conversational agents. Furthermore, we explore how these norms can be used to align conversational agents with human values across a range of different discursive domains. We conclude by discussing the practical implications of our proposal for the design of conversational agents that are aligned with these norms and values.

In Conversation with Artificial Intelligence: Aligning language Models with Human Values
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(Featured) Against AI Understanding and Sentience: Large Language Models, Meaning, and the Patterns of Human Language Use

Against AI Understanding and Sentience: Large Language Models, Meaning, and the Patterns of Human Language Use

Christoph Durt, Thomas Fuchs, and Tom Froese investigate the astonishing capacities of Large Language Models (LLMs) to mimic human-like responses. They begin by acknowledging the unprecedented feats of these models, particularly GPT-3, which have led some to assert that they possess common-sense reasoning and even sentience. They caution, however, that these claims often overlook the instances where LLMs fail to produce sensical responses. Even as the models evolve and mitigate some of these limitations, the authors urge circumspection regarding the attribution of understanding and sentience to these systems.

The authors argue that the progress of LLMs invites a reassessment of long-standing philosophical debates about the limits of AI. The authors challenge the view, expressed by philosophers such as Hubertus Dreyfus, that AI is inherently incapable of understanding meaning. Given the emergent linguistic capabilities of these models, they query whether these advancements warrant attributing understanding to the computational system. Contrary to Dreyfus’s assertion that any formal system cannot be directly sensitive to the relevance of its situation, the authors propose that LLMs seem to exhibit this sensitivity in a pragmatic sense.

While the article explores the philosophical debates surrounding AI understanding and sentience, it does not definitively conclude whether LLMs truly understand or are sentient. The authors suggest that the human-like behaviour exhibited by these models may lead to the inference of a human-like mind. However, they argue that more nuanced and empirically informed positions are required. The authors further advocate for a more comprehensive assessment of LLM output, rather than relying on selective instances of impressive performance.

This research brings into focus the broader philosophical implications of our interaction with AI, particularly the ontological and epistemological assumptions we make when interacting with LLMs. The debate surrounding AI sentience and understanding illuminates the complexities inherent in defining consciousness and understanding, a philosophical quandary that dates back to Descartes and beyond. It forces us to interrogate the nature of understanding – is it a purely human phenomenon, or can it be replicated, even surpassed, by silicon-based entities? Moreover, it challenges our anthropocentric views of cognition and compels us to consider alternate forms of intelligence and understanding.

Looking forward, the study of AI and philosophy would benefit from an even deeper exploration of these questions. More empirical research is needed to understand the extent and limitations of LLMs’ capacities. Concurrently, philosophical inquiry can help define and refine the metrics by which we measure AI understanding and sentience. As we delve further into the AI era, it is crucial that we continue to scrutinize and challenge our assumptions about AI capabilities, not only to enhance our technological advancements but also to enrich our philosophical understanding of the world.

Abstract

Large language models such as ChatGPT are deep learning architectures trained on immense quantities of text. Their capabilities of producing human-like text are often attributed either to mental capacities or the modeling of such capacities. This paper argues, to the contrary, that because much of meaning is embedded in common patterns of language use, LLMs can model the statistical contours of these usage patterns. We agree with distributional semantics that the statistical relations of a text corpus reflect meaning, but only part of it. Written words are only one part of language use, although an important one as it scaffolds our interactions and mental life. In human language production, preconscious anticipatory processes interact with conscious experience. Human language use constitutes and makes use of given patterns and at the same time constantly rearranges them in a way we compare to the creation of a collage. LLMs do not model sentience or other mental capacities of humans but the common patterns in public language use, clichés and biases included. They thereby highlight the surprising extent to which human language use gives rise to and is guided by patterns.

Against AI Understanding and Sentience: Large Language Models, Meaning, and the Patterns of Human Language Use
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(Featured) A Loosely Wittgensteinian Conception of the Linguistic Understanding of Large Language Models like BERT, GPT-3, and ChatGPT

A Loosely Wittgensteinian Conception of the Linguistic Understanding of Large Language Models like BERT, GPT-3, and ChatGPT

Reto Gubelmann articulates a “loosely Wittgensteinian” conception of linguistic understanding, particularly in the context of advanced artificial intelligence (AI) models such as BERT, GPT-3, and ChatGPT. The author posits that these transformer-based natural language processing (NNLP) models are closing in on the capacity to genuinely understand language, a claim that is buttressed by both empirical and conceptual arguments. The empirical basis is grounded on the remarkable performance of these AI models on benchmarks like GLUE and SuperGLUE, which evaluate them on tasks that, in a human context, would necessitate a deep understanding of language, such as answering questions about a text, summarizing text, and discerning logical relationships between statements. The conceptual underpinnings of this claim draw upon the works of Glock, Taylor, and Wittgenstein to argue that linguistic understanding, a form of intelligence, is marked by flexibility in handling new tasks and novel inputs, as well as the capability to autonomously adapt to new tasks​​.

The article further navigates through the terrain of philosophical objections to the idea that AI can understand language. The author counters objections raised by Searle, Bender, Koller, Davidson, and Nagel, among others, arguing that understanding language does not necessitate any esoteric or mysterious component such as qualia. Rather, it is dependent on the competencies of the AI model, specifically its autonomous adaptability and performance in a wide array of linguistic tasks in diverse settings. By this definition, the author contends that current transformer-based NNLP models are inching closer to meeting the criteria for linguistic understanding​​.

The author also provides a succinct yet comprehensive overview of the evolution of AI models, from the era of “Good Old-Fashioned AI” (GOFAI), which relied on explicit rules and logical processing, to the emergence of neural network models or connectionist AI, which represent a fundamentally different approach to designing intelligent systems. The distinguishing feature of these neural network models, such as the transformer-based models under discussion, is their learning-based approach, which enables them to adapt to new tasks and exhibit flexibility in the face of novel inputs​​.

Embedding these discussions within broader philosophical issues, the article provides a fruitful platform for exploring the nature of intelligence, understanding, and language. The examination of whether or not AI models can understand language opens up questions about the definition of understanding and the conditions that must be met to ascribe understanding to a being. This interrogation is undergirded by a Wittgensteinian perspective, which has profound implications for our understanding of language, mind, and the possibilities of AI. It also prompts us to reconsider the boundaries we draw between human and machine intelligence.

Future research should continue to explore these Wittgensteinian conceptions of linguistic understanding, particularly as AI models continue to evolve and improve. More empirical work could be conducted to test the adaptability and flexibility of AI models in novel linguistic situations, providing more robust evidence for or against their capacity to understand language. Furthermore, the philosophical debate concerning language understanding in AI should continue to be pushed forward, with deeper explorations of the arguments against AI understanding and the development of new philosophical frameworks that can accommodate the rapidly advancing capabilities of AI. As this field advances, interdisciplinary collaboration between AI researchers, linguists, and philosophers will be vital in order to fully grasp the implications of these transformative technologies.

Abstract

In this article, I develop a loosely Wittgensteinian conception of what it takes for a being, including an AI system, to understand language, and I suggest that current state of the art systems are closer to fulfilling these requirements than one might think. Developing and defending this claim has both empirical and conceptual aspects. The conceptual aspects concern the criteria that are reasonably applied when judging whether some being understands language; the empirical aspects concern the question whether a given being fulfills these criteria. On the conceptual side, the article builds on Glock’s concept of intelligence, Taylor’s conception of intrinsic rightness as well as Wittgenstein’s rule-following considerations. On the empirical side, it is argued that current transformer-based NNLP models, such as BERT and GPT-3 come close to fulfilling these criteria.

A Loosely Wittgensteinian Conception of the Linguistic Understanding of Large Language Models like BERT, GPT-3, and ChatGPT