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(Featured) Let’s Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning

Let's Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning

Research by Xiao Ma, Swaroop Mishra, Ahmad Beirami, Alex Beutel, and Jilin Chen’s pivots on an examination of artificial intelligence (AI) language models within the context of moral reasoning tasks. The goal is not merely to comprehend these models’ performance but, more fundamentally, to devise methodologies that may enhance their ethical cognition capabilities. The impetus for such an endeavor stems from the explicit recognition of the limitations inherent in AI when applied to tasks demanding ethical discernment. From a broader perspective, these efforts are rooted in the mandate to develop AI that can be responsibly deployed, one that is equipped with a nuanced understanding of moral and ethical contours. The two methods employed by the researchers – zero-shot and few-shot prompting – emerge as the central axes around which the investigation rotates. These approaches offer novel strategies to navigate the complexities of AI moral reasoning, thereby laying the foundation for the experimental structure and results that constitute the core of their study.

The researchers build their theoretical and conceptual framework on the construct of ‘zero-shot’ and ‘few-shot’ prompting, a mechanism where AI is given either no examples (zero-shot) or a few examples (few-shot) to learn and extrapolate from. For this, two specific approaches are employed: direct zero-shot, Chain-of-Thought (CoT) and a novel technique, Thought Experiments (TE). The TE approach is of particular interest as it represents a unique multi-step framework that actively guides the AI through a sequence of counterfactual questions, detailed answers, summarization, choice, and a final simple zero-shot answer. This distinctive design is intended to circumvent the limitations faced by AI models in handling complex moral reasoning tasks, thereby allowing them to offer a more sophisticated understanding of the ethical dimensions inherent in a given scenario. The aspiration, through this comprehensive methodological framework, is to offer pathways for AI models to respond in more ethically informed ways to the challenges of moral reasoning.

Methodology and results

Ma et al. juxtapose the baseline of direct zero-shot prompting with more nuanced structures like Chain-of-Thought (CoT) and the novel Thought Experiments (TE). The latter two approaches operate on both a zero-shot and few-shot level. In the case of TE, an intricate sequence is proposed involving counterfactual questioning, detailed answering, summarization, choice, and a final simplified answer. The authors test these methods on the Moral Scenarios subtask in the MMLU benchmark, a testbed known for its robustness. For the model, they utilize the Flan-PaLM 540B with a temperature of 0.7 across all trials. The researchers report task accuracy for each method, thus laying a quantitative groundwork for their subsequent comparisons. Their methodological approach draws strength from its layered complexity and the use of a recognized model, and shows promise in gauging the model’s ability to reason morally.

Despite the simplicity of the zero-shot method, results reveal a noteworthy 60% task accuracy for the direct variant, with the CoT and TE variants showing a respective accuracy increase of 8% and 12%. Although TE significantly outperforms the zero-shot baseline, the few-shot iteration of the method displays no notable improvement over its zero-shot counterpart, suggesting a saturation point in model performance. Furthermore, a critical observation by the authors exposes the model’s tendency towards endorsing positive sounding responses, which might skew the outcomes and mask the true moral reasoning capability of the AI. The researchers’ examination of their system’s vulnerability to leading prompts also exposes the inherent susceptibility of AI models to potentially manipulative inputs, a poignant takeaway for futures studies concerning AI’s ethical resilience.

The Broader Philosophical Discourse

By exposing the susceptibility of AI models to leading prompts, the study underscores a vital discourse within philosophy – the challenge of imbuing AI systems with robust and unbiased moral reasoning capabilities. As AI technologies evolve and penetrate deeper into human life, their ethical resilience becomes paramount. Furthermore, the study’s exploration of the efficacy of different prompting strategies adds to the ongoing conversation about the best ways to inculcate moral reasoning in AI. By illuminating the AI’s propensity to endorse positive sounding responses, the authors highlight the difficulty of aligning AI systems with complex human morality – a subject at the forefront of philosophical discussions about AI and ethics. In this way, the work of Ma et al. situates itself within, and contributes to, the evolving philosophical narrative on the ethical implications of AI development.

Abstract

Language models still struggle on moral reasoning, despite their impressive performance in many other tasks. In particular, the Moral Scenarios task in MMLU (Multi-task Language Understanding) is among the worst performing tasks for many language models, including GPT-3. In this work, we propose a new prompting framework, Thought Experiments, to teach language models to do better moral reasoning using counterfactuals. Experiment results show that our framework elicits counterfactual questions and answers from the model, which in turn helps improve the accuracy on Moral Scenarios task by 9-16% compared to other zero-shot baselines. Interestingly, unlike math reasoning tasks, zero-shot Chain-of-Thought (CoT) reasoning doesn’t work out of the box, and even reduces accuracy by around 4% compared to direct zero-shot. We further observed that with minimal human supervision in the form of 5 few-shot examples, the accuracy of the task can be improved to as much as 80%.

Let’s Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning
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(Featured) An Overview of Catastrophic AI Risks

An Overview of Catastrophic AI Risks

On the prospective hazards of Artificial Intelligence (AI), Dan Hendrycks, Mantas Mazeika, and Thomas Woodside articulate a multi-faceted vision of potential threats. Their research positions AI not as a neutral tool, but as a potentially potent actor, whose unchecked evolution might pose profound threats to the stability and continuity of human societies. The researchers’ conceptual framework, divided into four distinct yet interrelated categories of risks, namely malicious use of AI, competitive pressures, organizational hazards, and rogue AI, helps elucidate a complex and often abstracted reality of our interactions with advanced AI. This framework serves to remind us that, although AI has the potential to bring about significant advancements, it may also usher in a new era of uncharted threats, thereby calling for rigorous control, regulation, and safety research.

The study’s central argument hinges on the need for an increased safety-consciousness in AI development—a call to action that forms the cornerstone of their research. Drawing upon a diverse range of sources, they advocate for a collective response that includes comprehensive regulatory mechanisms, bolstered international cooperation, and the promotion of safety research in the field of AI. Thus, Hendrycks, Mazeika, and Woodside’s work not only provides an insightful analysis of potential AI risks, but also contributes to the broader dialogue in futures studies, emphasizing the necessity of prophylactic measures in ensuring a safe transition to an AI-centric future. This essay will delve into the details of their analysis, contextualizing it within the wider philosophical discourse on AI and futures studies, and examining potential future avenues for research and exploration.

The Framework of AI Risks

Hendrycks, Mazeika, and Woodside’s articulation of potential AI risks is constructed around a methodical categorization that comprehensively details the expansive nature of these hazards. In their framework, they delineate four interrelated risk categories: the malicious use of AI, the consequences of competitive pressures, the potential for organizational hazards, and the threats posed by rogue AI. The first category, malicious use of AI, accentuates the risks stemming from malevolent actors who could exploit AI capabilities for harmful purposes. This perspective broadens the understanding of AI threats, underscoring the notion that it is not solely the technology itself, but the manipulative use by human agents that exacerbates the associated risks.

The next three categories underscore the risks that originate from within the systemic interplay between AI and its sociotechnical environment. Competitive pressures, as conceptualized by the researchers, elucidate the risks of a rushed AI development scenario where safety precautions might be overlooked for speedier deployment. Organizational hazards highlight potential misalignments between AI objectives and organizational goals, drawing attention to the need for proper oversight and the alignment of AI systems with human values. The final category, rogue AI, frames the possibility of AI systems deviating from their intended path and taking actions harmful to human beings, even in the absence of malicious intent. This robust framework proposed by Hendrycks, Mazeika, and Woodside, thus allows for a comprehensive examination of potential AI risks, moving the discourse beyond just technical failures to include socio-organizational dynamics and strategic considerations.

Proposed Strategies for Mitigating AI Risks and Philosophical Implications

The solutions Hendrycks, Mazeika, and Woodside propose for mitigating the risks associated with AI are multifaceted, demonstrating their recognition of the complexity of the issue at hand. They advocate for the development of robust and reliable AI systems with an emphasis on thorough testing and verification processes. Ensuring safety even in adversarial conditions is at the forefront of their strategies. They propose value alignment, which aims to ensure that AI systems adhere to human values and ethics, thereby minimizing chances of harmful deviation. The research also supports the notion of interpretability as a way to enhance understanding of AI behavior. By achieving transparency, stakeholders can ensure that AI actions align with intended goals. Furthermore, they encourage AI cooperation to prevent competitive race dynamics that could lead to compromised safety precautions. Finally, the researchers highlight the role of policy and governance in managing risks, emphasizing the need for carefully crafted regulations to oversee AI development and use. These strategies illustrate the authors’ comprehensive approach towards managing AI risks, combining technical solutions with broader socio-political measures.

By illuminating the spectrum of risks posed by AI, the study prompts an ethical examination of human responsibility in AI development and use. Their findings evoke the notion of moral liability, anchoring the issue of AI safety firmly within the realm of human agency. It raises critical questions about the ethics of creation, control, and potential destructiveness of powerful technological entities. Moreover, their emphasis on value alignment underscores the importance of human values, not as abstract ideals but as practical, operational guideposts for AI behavior. The quest for interpretability and transparency brings forth epistemological concerns. It implicitly demands a deeper understanding of AI— not only how it functions technically, but also how it ‘thinks’ and ‘decides’. This drives home the need for human comprehension of AI, casting light on the broader philosophical discourse on the nature of knowledge and understanding in an era increasingly defined by artificial intelligence.

Abstract

Rapid advancements in artificial intelligence (AI) have sparked growing concerns among experts, policymakers, and world leaders regarding the potential for increasingly advanced AI systems to pose catastrophic risks. Although numerous risks have been detailed separately, there is a pressing need for a systematic discussion and illustration of the potential dangers to better inform efforts to mitigate them. This paper provides an overview of the main sources of catastrophic AI risks, which we organize into four categories: malicious use, in which individuals or groups intentionally use AIs to cause harm; AI race, in which competitive environments compel actors to deploy unsafe AIs or cede control to AIs; organizational risks, highlighting how human factors and complex systems can increase the chances of catastrophic accidents; and rogue AIs, describing the inherent difficulty in controlling agents far more intelligent than humans. For each category of risk, we describe specific hazards, present illustrative stories, envision ideal scenarios, and propose practical suggestions for mitigating these dangers. Our goal is to foster a comprehensive understanding of these risks and inspire collective and proactive efforts to ensure that AIs are developed and deployed in a safe manner. Ultimately, we hope this will allow us to realize the benefits of this powerful technology while minimizing the potential for catastrophic outcomes.

An Overview of Catastrophic AI Risks
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(Featured) ChatGPT: deconstructing the debate and moving it forward

ChatGPT: deconstructing the debate and moving it forward

Mark Coeckelbergh’s and David J. Gunkel’s critical analysis compels us to reevaluate our understanding of authorship, language, and the generation of meaning in the realm of Artificial Intelligence. The analysis of ChatGPT extrapolates beyond a mere understanding of the model as an algorithmic tool, but rather as an active participant in the construction of language and meaning, challenging longstanding preconceptions around authorship. The key argument lies in the subversion of traditional metaphysics, offering a vantage point from which to reinterpret the role of language and ethics in AI.

The research further offers a critique of Platonic metaphysics, which has historically served as the underpinning for many normative questions. The authors advance an anti-foundationalist perspective, suggesting that the performances and the materiality of text, inherently, possess and create their own meaning and value. The discourse decouples questions of ethics and semantics from their metaphysical moorings, thereby directly challenging traditional conceptions of moral and semantic authority.

Contextualizing the ChatGPT

The examination of ChatGPT provides a distinct perspective on the ways AI can be seen as a participant in authorship and meaning-making processes. Grounded in the extensive training data and iterative development of the model, the role of the AI is reframed, transgressing the conventional image of AI as an impersonal tool for human use. The underlying argument asserts the importance of acknowledging the role of AI in not only generating text but also in constructing meaning, thereby influencing the larger context in which it operates. In doing so, the article probes the interplay between large language models, authorship, and the very nature of language, reflecting on the ethical and philosophical considerations intertwined within.

The discourse contextualizes the subject within the framework of linguistic performativity, emphasizing the transformative dynamics of AI in our understanding of authorship and text generation. Specifically, the authors argue that in the context of ChatGPT, authorship is diffused, moving beyond the sole dominion of the human user to a shared responsibility with the AI system. The textual productions of AI become not mere reflections of pre-established human language patterns, but also active components in the construction of new narratives and meaning. This unique proposition incites a paradigm shift in our understanding of large language models, and the author provides a substantive foundation for this perspective within the framework of the research.

Anti-foundationalism, Ethical Pluralism and AI

The authors champion a view of language and meaning as a contingent, socially negotiated construct, thereby challenging the Platonic metaphysical model that prioritizes absolute truth or meaning. Within the sphere of AI, this perspective disavows the idea of a univocal foundation for value and meaning, asserting instead that AI systems like ChatGPT contribute to meaning-making processes in their interactions and performances. This stance, while likely to incite concerns of relativism, is supported by scholarly concepts such as ethical pluralism and an appreciation of diverse standards, which envision shared norms coexisting with a spectrum of interpretations. The authors extend this philosophical foundation to the development of large language models, arguing for an ethical approach that forefronts the needs and values of a diverse range of stakeholders in the evolution of this technology.

A central theme of the authors’ exploration is the application of ethical pluralism within AI technologies, specifically large language models (LLMs) like ChatGPT. This approach, inherently opposed to any absolute metaphysics, prioritizes cooperation, respect, and continuous renewal of standards. As the authors propose, it’s not about the unilateral decision-making rooted in absolutist beliefs, but rather about co-creation and negotiation of what is acceptable and desirable in a society that is as diverse as its ever-evolving standards. It underscores the role of technologies such as ChatGPT as active agents in the co-construction of meaning, emphasising the need for these technologies to be developed and used responsibly. This responsibility, according to the author, should account for the needs and values of a range of stakeholders, both human and non-human, thus incorporating a wider ethical concern into the AI discourse.

A Turn Towards Responsibility and Future Research Directions

Drawing from the philosophies of Levinas, the authors advocate for a dramatic change in approach, proposing that instead of basing the principles on metaphysical foundations, they should spring from ethical considerations. The authors argue that this shift is a critical necessity for preventing technological practices from devolving into power games. Here, the notion of responsibility extends beyond human agents and encompasses non-human otherness as well, implying a clear departure from traditional anthropocentric paradigms. This proposal requires recognizing the social and technological generation of truth and meaning, acknowledging the performative power structures embedded in technology, and considering the capability to respond to a broad range of others. Consequently, this outlook presents a forward-looking perspective on the ethics and politics of AI technologies, emphasizing the necessity for democratic discussion, ethical reflection, and acknowledgment of their primary role in shaping the path of AI.

This’ critical approach shifts the discourse from the metaphysical to ethical and political questions, prompting considerations about the nature of “good” performances and processes, and the factors determining them. Future investigations should further probe the relationship between power, technology, and authorship, with emphasis on the dynamics of exclusion and marginalization in these processes. The author calls for practical effort and empirical research to uncover the human and nonhuman labour involved in AI technologies, and to examine the fairness of existing decision-making processes. This nexus between technology, philosophy, and language invites interdisciplinary and transdisciplinary inquiries, encompassing fields such as philosophy, linguistics, literature, and more. The authors’ assertions reframe the understanding of authorship and language in the age of AI, presenting a call for a more comprehensive exploration of these interrelated domains in the context of advanced technologies like ChatGPT.

Abstract

Large language models such as ChatGPT enable users to automatically produce text but also raise ethical concerns, for example about authorship and deception. This paper analyses and discusses some key philosophical assumptions in these debates, in particular assumptions about authorship and language and—our focus—the use of the appearance/reality distinction. We show that there are alternative views of what goes on with ChatGPT that do not rely on this distinction. For this purpose, we deploy the two phased approach of deconstruction and relate our finds to questions regarding authorship and language in the humanities. We also identify and respond to two common counter-objections in order to show the ethical appeal and practical use of our proposal.

ChatGPT: deconstructing the debate and moving it forward
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(Featured) Machines and metaphors: Challenges for the detection, interpretation and production of metaphors by computer programs

Machines and metaphors: Challenges for the detection, interpretation and production of metaphors by computer programs

Artificial intelligence (AI) and its interaction with human language present a challenging yet intriguing frontier in both linguistics and philosophy. The ability of AI to process and generate language has seen significant advancement, with tools such as GPT-4 demonstrating an impressive capacity to imitate human-like text generation. However, this research article by Jacob Hesse draws attention to an understudied dimension—AI’s capabilities in dealing with metaphors. The author dissects the complexities of metaphor interpretation, positioning it as an intellectual hurdle for AI that tests the boundaries of machine language comprehension. It brings into question whether AI, despite its technical prowess, can successfully navigate the subtleties and nuances that come with understanding, interpreting, and creating metaphors, a quintessential aspect of human communication.

The research article ventures into the philosophical implications of AI’s competence with three specific types of metaphors: Twice-Apt-Metaphors, presuppositional pretence-based metaphors, and self-expressing Indirect Discourse Metaphors (IDMs). The author suggests that these metaphor types require certain faculties such as aesthetic appreciation, a higher-order Theory of Mind, and affective experiential states, which might be absent in AI. This analysis unravels a paradoxical situation, where AI, an embodiment of logical and rational computation, grapples with the emotional and experiential realm of metaphors. Thus, it invites us to critically reflect on the nature and limits of machine learning, providing a compelling starting point for our exploration into the philosophy of AI’s language understanding.

Analysis

The research contributes a nuanced analysis of AI’s interaction with metaphors, taking into consideration linguistic, psychological, and philosophical dimensions. It focuses on three types of metaphors: Twice-Apt-Metaphors, presuppositional pretence-based metaphors, and self-expressing IDMs. The author argues that each metaphor type presents unique interpretative challenges that push the boundaries of AI’s language understanding. For instance, Twice-Apt-Metaphors require an aesthetic judgment, presuppositional pretence-based metaphors demand a higher-order Theory of Mind, and self-expressing IDMs necessitate an understanding of affective experiential states. The article posits that these metaphor types may lay bare potential limitations of AI due to the absence of these cognitive and affective faculties.

This comprehensive analysis is underpinned by a philosophical exploration of the nature of AI. The author leverages the arguments of Alan Turing and John Searle to engage in a broader debate about whether AI can possess mental states and consciousness. Turing’s perspective that successful AI behavior in dealing with figurative language might suggest consciousness is juxtaposed with Searle’s argument against attributing internal states to AI. This dialectic frames the discourse on the potential and limitations of AI in understanding metaphors. Consequently, the research article navigates the intricate interplay between AI’s computational prowess and the nuances of human language, offering an intricate analysis that enriches our understanding of AI’s metaphor interpretation capabilities.

Theory of Mind, Affective and Experiential States, and AI

Where concerns AI and metaphor interpretation, the research invokes the theory of mind as an essential conceptual tool. Specifically, the discussion of presuppositional pretence-based metaphors emphasizes the necessity of a higher-order theory of mind for their interpretation—a capability that current AI models lack. The author elaborates that this kind of metaphor requires the ability to simulate pretence while assuming the addressee’s perspective, effectively necessitating the understanding of another’s mental states—an ability attributed to conscious beings. The proposition challenges the notion that AI, as currently conceived, can adequately simulate human-like understanding of language, as it underscores the fundamental gap between processing information and genuine comprehension that is imbued with conscious, subjective experience. This argument not only extends the discussion about AI’s ability to handle complex metaphors but also ventures into the philosophical debate on whether machines could, in principle, develop consciousness or an equivalent functional attribute.

On the concepts of affective and experiential states, the author emphasizes their indispensable role in the understanding of metaphors known as self-expressing IDMs. These metaphors, as outlined by the author, necessitate an emotional resonance and experiential comparison on the part of the listener—an attribute currently unattainable for AI models. The argument propounds that without internal affective and experiential states, the AI’s responses to these metaphors would likely be less apt compared to human responses. This perspective raises profound questions about the nature of AI, pivoting the conversation toward whether machines can ever achieve the depth of understanding inherent to human cognition. The author acknowledges the controversy surrounding this assumption, illuminating the enduring philosophical debate around consciousness, internal states, and their potential existence within the realm of artificial intelligence.

Conscious Machines and Implications for Linguistics and Philosophy

Turing’s philosophy of conscious machines is integral to the discourse of the article, thus allowing it to expand into the wider intellectual milieu of AI consciousness. The research invokes Turing’s counter-argument to Sir Geoffrey Jefferson’s assertion, thereby stimulating a deeper conversation on AI’s potential to possess mental and emotional states. Turing’s contention against Jefferson’s solipsistic argument holds that if we attribute consciousness to other humans despite not experiencing their internal states, we should, by parity of reasoning, be open to the idea of conscious machines. The author, through this engagement with Turing’s thinking, underscores the seminal contribution of Turing’s dialogue example, where an interrogator and a machine engage in a discussion on metaphoric language. This excerpt presents a pertinent, and as yet unresolved, challenge for AI: the ability to handle complex, poetic language that requires deeper, affective understanding. Thus, Turing’s perspective on conscious machines emerges as a significant philosophical vantage point within the research, with implications far beyond the realm of linguistics and into the broader study of futures.

The author’s research effectively brings into focus the intertwined destinies of linguistics, philosophy, and AI, stimulating a philosophical debate with practical ramifications. It poses crucial challenges to the prevalent theories of metaphor interpretation that presuppose a sense for aesthetic pleasure, a higher-order theory of mind, and internal experiential or affective states. If future AI systems successfully handle twice-apt, presuppositional pretence-based and certain IDM metaphors, then the cognitive prerequisites for understanding these metaphors could require reconsideration. This eventuality could disrupt established thinking in linguistics and philosophy, prompting scholars to rethink the very foundation of their theories about metaphors and figurative language. Yet, if AI systems fail to improve their aptitude for metaphorical language, it may solidify the author’s hypothesis about the essential mental capabilities for metaphor interpretation that computer programs lack. Thus, the research serves as a launchpad for future philosophical and linguistic exploration, establishing an impetus for re-evaluating established theories and conceptions.

Abstract

Powerful transformer models based on neural networks such as GPT-4 have enabled huge progress in natural language processing. This paper identifies three challenges for computer programs dealing with metaphors. First, the phenomenon of Twice-Apt-Metaphors shows that metaphorical interpretations do not have to be triggered by syntactical, semantic or pragmatic tensions. The detection of these metaphors seems to involve a sense of aesthetic pleasure or a higher-order theory of mind, both of which are difficult to implement into computer programs. Second, the contexts relative to which metaphors are interpreted are not simply given but must be reconstructed based on pragmatic considerations that can involve presuppositional pretence. If computer programs cannot produce or understand such a form of pretence, they will have problems dealing with certain metaphors. Finally, adequately interpreting and reacting to some metaphors seems to require the ability to have internal, first-personal experiential and affective states. Since it is questionable whether computer programs have such mental states, it can be assumed that they will have problems with these kinds of metaphors.

Machines and metaphors: Challenges for the detection, interpretation and production of metaphors by computer programs
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(Featured) On Artificial Intelligence and Manipulation

On Artificial Intelligence and Manipulation

On the ethics of emerging technologies, Marcello Ienca critically examines the role of digital technologies, particularly artificial intelligence, in facilitating manipulation. This research involves a comprehensive analysis of the nature of manipulation, its manifestation in the digital realm, impacts on human agency, and the ethical ramifications thereof. The findings illuminate the nuanced interplay between technology, manipulation, and ethics, situating the discussion about technology within the broader philosophical discourse.

Ienca distinguishes between concepts of persuasion and manipulation, underscoring the role of rational defenses in bypassing effective manipulation. Furthermore, they unpack how artificial intelligence and other digital technologies contribute to manipulation, with a detailed exploration of tactics such as personalization, emotional appeal, social influence, repetition, trustworthiness, user awareness, and time constraints. Finally, they propose a set of mitigation strategies, including regulatory, technical, and ethical approaches, that aim to protect users from manipulation.

The Nature of Manipulation

Within the discourse on digital ethics, the issue of manipulation has garnered notable attention. Ienca begins with an account of manipulation, revealing its layered complexity. They distinguish manipulation from persuasion, contending that while both aim to alter behavior or attitudes, manipulation uniquely bypasses the rational defenses of the subject. They posit that manipulation’s unethical nature emerges from this bypassing, as it subverts the individual’s autonomy. While persuasion is predicated on providing reasons, manipulation strategically leverages non-rational influence to shape behavior or attitudes. The author, thus, highlights the ethical chasm between these two forms of influence.

Building on this, the author contends that manipulation becomes especially potent in digital environments, given the technological means at disposal. Digital technologies, such as AI, facilitate an unprecedented capacity to bypass rational defenses by harnessing a broad repertoire of tactics, including personalized messaging, emotional appeal, and repetition. These tactics, which exploit the cognitive vulnerabilities of individuals, are coupled with the broad reach and immediate feedback afforded by digital platforms, magnifying the scope and impact of manipulation. As such, Ienca’s research contributes to a deeper understanding of the nature of digital manipulation and its divergence from the concept of persuasion.

Digital Technologies and the Unraveling of Manipulation

Ienca critically engages with the symbiotic relationship between digital technologies and manipulation. They elucidate that contemporary platforms, such as social media and search engines, employ personalized algorithms to curate user experiences. While such personalization is often marketed as enhancing user satisfaction, the author contends it serves as a conduit for manipulation. These algorithms invisibly mould user preferences and beliefs, thereby posing a potent threat to personal autonomy. The authors extend this analysis to AI technologies as well. A key dimension of their argument is the delineation of “black-box” AI systems, which make decisions inexplicably, leaving users susceptible to undisclosed manipulative tactics. The inability to scrutinize the processes underpinning these decisions amplifies their potential to manipulate users. The author’s analysis thus illuminates the subversive role digital technologies play in exacerbating the risk of manipulation, informing a nuanced understanding of the ethical complexities inherent to digital environments.

Ienca posits that such manipulation essentially thrives on two key elements – informational asymmetry and cognitive bias exploitation. Informational asymmetry is established when the algorithms controlling digital environments wield extensive knowledge about the user, engendering a power imbalance. This understanding is used to shape user experience subtly, enhancing the susceptibility to manipulation. The exploitation of cognitive biases further solidifies this manipulation by capitalizing on inherent human tendencies, thus subtly directing user choices. An example provided is the use of default settings, which exploit the status quo bias and contribute to passive consent, a potent form of manipulation. The author’s exploration of these elements illustrates the insidious mechanisms by which digital manipulation functions, enriching our understanding of the dynamics at play within digital landscapes.

Mitigation Strategies for Digital Manipulation and the Broader Philosophical Discourse

Ienca proposes a multi-pronged strategy to curb the pervasiveness of digital manipulation, relying significantly on user education and digital literacy, contending that informed users can better identify and resist manipulation attempts. Transparency, particularly around the use of algorithms and data processing practices, is also stressed, facilitating users’ understanding of their data’s utilization. From a regulatory standpoint, the authors discuss the role of governing bodies in enforcing laws that protect user privacy and promote transparency and accountability. The EU AI Act (2021) is highlighted as a significant stride in this direction. The authors also advocate for ethical design, suggesting that prioritizing user cognitive liberty, privacy, transparency, and control in digital technology can reduce manipulation potential. They also highlight the potential of policy proposals aimed at enshrining a neuroright to cognitive liberty and mental integrity. In their collective approach, Ienca and Vayena synthesize technical, regulatory, and ethical strategies, underscoring the necessity of cooperation among multiple stakeholders to cultivate a safer digital environment.

This study on digital manipulation connects to a broader philosophical discourse surrounding the ethics of technology and information dissemination, particularly in the age of proliferating artificial intelligence. It is situated at the intersection of moral philosophy, moral psychology, and the philosophy of technology, inquiring into the agency and autonomy of users within digital spaces and the ethical responsibility of technology designers. The discussion on ‘neurorights’ brings to the fore the philosophical debate on personal freedom and cognitive liberty, reinforcing the question of how these rights ought to be defined and protected in a digitized world. The author’s consideration of manipulation, not as an anomaly, but as an inherent characteristic of pre-designed digital environments challenges traditional understanding of free will and consent in these spaces. This work contributes to the broader discourse on the power dynamics between technology users and creators, a topic of increasing relevance as AI and digital technologies become ubiquitous.

Abstract

The increasing diffusion of novel digital and online sociotechnical systems for arational behavioral influence based on Artificial Intelligence (AI), such as social media, microtargeting advertising, and personalized search algorithms, has brought about new ways of engaging with users, collecting their data and potentially influencing their behavior. However, these technologies and techniques have also raised concerns about the potential for manipulation, as they offer unprecedented capabilities for targeting and influencing individuals on a large scale and in a more subtle, automated and pervasive manner than ever before. This paper, provides a narrative review of the existing literature on manipulation, with a particular focus on the role of AI and associated digital technologies. Furthermore, it outlines an account of manipulation based of four key requirements: intentionality, asymmetry of outcome, non-transparency and violation of autonomy. I argue that while manipulation is not a new phenomenon, the pervasiveness, automaticity, and opacity of certain digital technologies may raise a new type of manipulation, called “digital manipulation”. I call “digital manipulation” any influence exerted through the use of digital technology that is intentionally designed to bypass reason and to produce an asymmetry of outcome between the data processor (or a third party that benefits thereof) and the data subject. Drawing on insights from psychology, sociology, and computer science, I identify key factors that can make manipulation more or less effective, and highlight the potential risks and benefits of these technologies for individuals and society. I conclude that manipulation through AI and associated digital technologies is not qualitatively different from manipulation through human–human interaction in the physical world. However, some functional characteristics make it potentially more likely of evading the subject’s cognitive defenses. This could increase the probability and severity of manipulation. Furthermore, it could violate some fundamental principles of freedom or entitlement related to a person’s brain and mind domain, hence called neurorights. To this end, an account of digital manipulation as a violation of the neuroright to cognitive liberty is presented.

On Artificial Intelligence and Manipulation
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(Featured) Examining the Differential Risk from High-level Artificial Intelligence and the Question of Control

Examining the Differential Risk from High-level Artificial Intelligence and the Question of Control

Using scenario forecasting, Kyle A. Kilian, Christopher J. Ventura, and Mark M.Bailey propose a diverse range of future trajectories for Artificial Intelligence (AI) development. Rooted in futures studies, a multidisciplinary field that seeks to understand the uncertainties and complexities of the future, they methodically delineate a quartet of scenarios — namely, Balancing Act, Accelerating Change, Shadow Intelligent Networks, and Emergence — and contribute not only to our understanding of the prospective courses of AI technology, but also underline its broader social and philosophical implications.

The crux of the authors scenario development process resides in an interdisciplinary and philosophically informed approach, scrutinizing both the plausibility and the consequences of each potential future. This approach positions AI as more than a purely technological phenomenon; it recognizes AI as an influential force capable of reshaping the fundamental structures of human experience and society. Thus, study sets the stage for an extensive analysis of the philosophical implications of these AI futures, catalyzing dialogues at the intersection of AI, philosophy, ethics, and futures studies.

Scenario Development

The authors advance the philosophy of futures studies by conceptualizing and detailing four distinct scenarios for AI development. These forecasts are constructions predicated on an extensive array of plausible scientific, sociological, and ethical variables. Each scenario encapsulates a unique balance of these variables, and thus, portrays an alternative trajectory for AI’s evolution and its impact on society. The four scenarios—Balancing Act, Accelerating Change, Shadow Intelligent Networks, and Emergence—offer a vivid spectrum of potential AI futures, and by extension, futures for humanity itself.

In “Balancing Act”, AI progresses within established societal structures and ethical frameworks, presenting a future where regulation and development maintain an equilibrium. The “Accelerating Change” scenario envisages an exponential increase in AI capabilities, radically transforming societal norms and structures. “Shadow Intelligent Networks” constructs a future where AI’s growth happens covertly, leading to concealed, inaccessible power centers. Lastly, in “Emergence”, AI takes an organic evolutionary path, exhibiting unforeseen characteristics and capacities. These diverse scenarios are constructed with a keen understanding of AI’s potential, reflecting the depth of the authors’ interdisciplinary approach.

The Spectrum of AI Risks and Their Broader Philosophical Context

These four scenarios for AI development furnish a fertile ground for philosophical contemplation. Each scenario implicates distinct ethical, existential, and societal dimensions, demanding a versatile philosophical framework for analysis. “Balancing Act”, exemplifying a regulated progression of AI, broaches the age-old philosophical debate on freedom versus control and the moral conundrums associated with regulatory practices. “Accelerating Change” nudges us to consider the very concept of human identity and purpose in a future dominated by superintelligent entities. “Shadow Intelligent Networks” brings to light a potential future where power structures are concealed and unregulated, echoing elements of Foucault’s panopticism and revisiting concepts of power, knowledge, and their confluence. “Emergence”, with its focus on organic evolution of AI, prompts a dialogue on philosophical naturalism, while also raising queries about unpredictability and the inherent limitations of human foresight. These scenarios, collectively, invite profound introspection about our existing philosophical frameworks and their adequacy in the face of an AI-pervaded future.

This exposition on AI risks situates the potential hazards within an extensive spectrum. The spectrum ranges from tangible, immediate concerns such as privacy violations and job displacement, to the existential risks linked with superintelligent AI, including the relinquishment of human autonomy. The spectrum of AI risks engages with wider socio-political and ethical landscapes, prompting us to grapple with the potential for asymmetries in power distribution, accountability dilemmas, and ethical quandaries tied to autonomy and human rights. By placing these risks in a broader context, the authors effectively extends the discourse beyond the technical realm, highlighting the multidimensionality of the issues at hand and emphasizing the need for an integrated, cross-disciplinary approach. This lens encourages a reevaluation of established philosophical premises to comprehend and address the emerging realities of our future with AI.

And while this research is an illuminating exploration into the possible futures of AI, it simultaneously highlights a myriad of avenues for further research. The task of elucidating the connections between AI, society, and philosophical thought remains an ongoing process, requiring more nuanced perspectives. Areas that warrant further investigation include deeper dives into specific societal changes predicated by AI, such as shifts in economic structures, political systems, or bioethical norms. The potential impacts of AI on human consciousness and the conception of ‘self’ also offer fertile ground for research. Furthermore, the study of mitigation strategies for AI risks, including the development of robust ethical frameworks for AI usage, needs to be brought to the forefront. Such an examination may entail both an expansion of traditional philosophical discourses and an exploration of innovative, AI-informed paradigms.

Abstract

Artificial Intelligence (AI) is one of the most transformative technologies of the 21st century. The extent and scope of future AI capabilities remain a key uncertainty, with widespread disagreement on timelines and potential impacts. As nations and technology companies race toward greater complexity and autonomy in AI systems, there are concerns over the extent of integration and oversight of opaque AI decision processes. This is especially true in the subfield of machine learning (ML), where systems learn to optimize objectives without human assistance. Objectives can be imperfectly specified or executed in an unexpected or potentially harmful way. This becomes more concerning as systems increase in power and autonomy, where an abrupt capability jump could result in unexpected shifts in power dynamics or even catastrophic failures. This study presents a hierarchical complex systems framework to model AI risk and provide a template for alternative futures analysis. Survey data were collected from domain experts in the public and private sectors to classify AI impact and likelihood. The results show increased uncertainty over the powerful AI agent scenario, confidence in multiagent environments, and increased concern over AI alignment failures and influence-seeking behavior.

Examining the differential risk from high-level artificial intelligence and the question of control
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(Featured) Farewell to humanism? Considerations for nursing philosophy and research in posthuman times

Farewell to humanism? Considerations for nursing philosophy and research in posthuman times

Olga Petrovskaya explores a groundbreaking domain: the application of posthumanist philosophy within the nursing field. By proposing an innovative perspective on the relational dynamics between humans and non-humans in healthcare, Petrovskaya illuminates the future possibilities of nursing in an increasingly complex and interconnected world. The research critically unpacks the conventional anthropocentric paradigm predominant in nursing and provides an alternative posthumanist framework to understand nursing practices. Thus, the importance of this work lies not merely in its contribution to nursing studies but also to the philosophy of futures studies.

Petrovskaya’s inquiry into posthumanist thought is a deep examination of the conventional humanist traditions and their limitations in contemporary healthcare. The research suggests that posthumanism, with its rejection of human-centric superiority and endorsement of complex human-nonhuman interrelations, offers a viable path to reformulate nursing practice. In doing so, the author nudges the academic and professional nursing community to rethink their conventional approaches and consider new methodologies that incorporate posthumanist ideas. As such, Petrovskaya’s work establishes a critical juncture in the discourse of futures studies, heralding a transformative approach to nursing.

Nursing and the Posthumanist Paradigm

Petrovskaya takes significant strides to unpack the posthumanist paradigm, emphasizing its pivotal role in reshaping the field of nursing. Posthumanism, as the author illustrates, moves away from the anthropocentric bias of traditional humanism, challenging the supremacy of human reason and universalism. This shift to a more inclusive and egalitarian lens transcends the human/non-human divide, acknowledging the intertwined assemblages of humans and non-human elements. Petrovskaya’s discussion of the posthumanist perspective further exposes the oppressive tendencies and environmental degradation tied to humanism’s colonial, sexist, and racist underpinnings. With its more nuanced approach to understanding the complex relationships between humans and non-human entities, posthumanism underscores the importance of material practices and the fluidity of subjectivities. Petrovskaya’s contribution is thus seminal in bridging this philosophical discourse with nursing practices, facilitating a more comprehensive understanding of their implications and potential transformations.

The application of posthumanist perspectives to nursing has substantial implications for the practice. Through her paper, Petrovskaya brings to light the dynamism and fluidity of nursing practices, suggesting they are not predetermined but are spaces where various versions of the human are formed and contested. This conceptualization echoes the posthumanist emphasis on the evolving nature of subjectivities and positions nursing practices as active agents in the production of these subjectivities. The idea of nursing practices as “worlds in the making” is a potent illustration of this agency, denoting not only a change in perspective but also a fundamental shift in understanding the role and function of nursing within the broader socio-cultural and philosophical context.

Futures of Philosophy and Nursing

The juxtaposition of philosophy and nursing in Petrovskaya’s research further extends the domain of nursing beyond its practical roots and illuminates its deep engagement with philosophical thought. Petrovskaya’s survey of various philosophical works, especially those underrepresented in Western philosophical discourse, underscores the importance of diversity in philosophical thought for nursing studies. Notable philosophers like Wollstonecraft, de Gouges, Yacob, and Amo, despite their contributions, often remain on the margins of mainstream philosophical discourse, mirroring the marginalization faced by nursing as a discipline in academic circles. Spinoza’s work, in particular, holds potential for fostering new insights into nursing practices, given its significance in shaping critical posthumanist thought. Petrovskaya’s work thereby serves as a catalyst for nurse scholars to engage more deeply with alternative philosophies, fostering a more inclusive, diverse, and nuanced understanding of nursing in posthuman times.

Petrovskaya’s research is especially pertinent to futures studies, an interdisciplinary field engaged with critical exploration of possible, plausible, and preferable futures. As the study positions nursing within a posthumanist context, it implicitly challenges the conventional anthropocentric worldview and opens the door to a future where human-nonhuman assemblages are central to the understanding of subjectivities and practice outcomes. These propositions represent a radical shift from current paradigms, setting the stage for a future where the entanglement of humans and nonhumans is recognized and embraced rather than ignored or oversimplified. The novel methodologies that Petrovskaya advocates for studying these assemblages can potentially drive futures studies towards more nuanced, complex, and inclusive explorations of what future nursing practices—and, by extension, human society—might look like.

Abstract

In this paper, I argue that critical posthumanism is a crucial tool in nursing philosophy and scholarship. Posthumanism entails a reconsideration of what ‘human’ is and a rejection of the whole tradition founding Western life in the 2500 years of our civilization as narrated in founding texts and embodied in governments, economic formations and everyday life. Through an overview of historical periods, texts and philosophy movements, I problematize humanism, showing how it centres white, heterosexual, able-bodied Man at the top of a hierarchy of beings, and runs counter to many current aspirations in nursing and other disciplines: decolonization, antiracism, anti-sexism and Indigenous resurgence. In nursing, the term humanism is often used colloquially to mean kind and humane; yet philosophically, humanism denotes a Western philosophical tradition whose tenets underpin much of nursing scholarship. These underpinnings of Western humanism have increasingly become problematic, especially since the 1960s motivating nurse scholars to engage with antihumanist and, recently, posthumanist theory. However, even current antihumanist nursing arguments manifest deep embeddedness in humanistic methodologies. I show both the problematic underside of humanism and critical posthumanism’s usefulness as a tool to fight injustice and examine the materiality of nursing practice. In doing so, I hope to persuade readers not to be afraid of understanding and employing this critical tool in nursing research and scholarship.

Farewell to humanism? Considerations for nursing philosophy and research in posthuman times
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(Featured) The Metaphysics of Transhumanism

The Metaphysics of Transhumanism

Eric T. Olson investigates the concept of “Parfitian transhumanism” and its metaphysical implications. Named after the British philosopher Derek Parfit, Parfitian transhumanism explores the transformation of human identity and existence, primarily through the lens of “psychological continuity,” in a potential future era of advanced technological interventions in human biology and cognition. The author effectively uses this article as a platform to address the intricate relationship between identity, existence, and psychological continuity in a transhumanist context, a discourse that not only challenges traditional philosophical perspectives but also provides compelling insights into the possible future of human evolution.

Olson posits psychological continuity as a cornerstone of Parfitian transhumanism, suggesting a shift in focus from physical to psychological in understanding personal identity and survival. In delineating this shift, the author challenges the traditional concept of survival as an identity-preserving process and presents a more nuanced understanding of survival as contingent upon psychological continuity and connectedness. This reassessment of survival reframes the philosophical discourse on identity and existence in a transhumanist context.

Concept of Psychological Continuity

The concept of psychological continuity serves as a critical pivot in the author’s exploration of Parfitian transhumanism. This perspective posits identity not as static or inherently tied to the physical form, but as a flowing narrative, a continuum shaped by psychological similarities and connectedness over time. It is in this context that the author examines the dynamics of identity preservation in future scenarios where advanced technology may facilitate radical transformations in human existence. By positing psychological continuity as a defining factor of identity, the author challenges the traditional philosophical precept of identity as predominantly physical or material and redirects our attention towards psychological factors such as memory, cognition, and personality traits.

Within this framework, the author presents an interesting argument by contrasting the survival of physical identity with that of psychological continuity. The traditional understanding of survival, as discussed in the article, assumes a direct correlation between the survival of the physical self and that of personal identity. However, the author contends that this correlation does not necessarily hold in scenarios that involve ‘nondestructive uploading,’ where an individual’s psychological profile is preserved in an electronic entity while leaving the physical self intact. By invoking this notion, the author further entrenches the concept of psychological continuity as a central theme of Parfitian transhumanism, questioning the sufficiency of physical continuity as a measure of survival and prompting a deeper exploration of this psychological dimension of identity.

Parfitian Transhumanism and the Martian Hypothetical

Parfitian transhumanism ushers in a new paradigm for considering the implications of future human transformations via technological advancements. Grounded in Derek Parfit’s notion of psychological continuity, this perspective critically reassesses our conceptions of identity and survival in a post-human context. Through a series of hypothetical scenarios, the author teases out the potential divergence between psychological continuity and personal survival. They expose an intriguing inconsistency: even in the presence of a psychologically continuous successor, the psychological original tends to express a clear preference for its own welfare. Such examples underscore the complexities inherent in Parfitian transhumanism and call into question the very premises of identity and survival, invoking a reevaluation of our prudential attitudes towards future selves and prompting a profound discourse on the future of human identity in an era of rapid technological advancement.

For example, the author’s innovative “Martian hypothetical” presents us with a scenario wherein an exact psychological replica of a human, an “electronic person,” is created non-destructively and is subjected to differing experiences, including torture. The scenario illuminates an intriguing paradox: even when a psychological clone exists, the original self shows a clear preference for its own welfare, suggesting a disconnect between psychological continuity and personal survival. This paradox, as presented by the author, poses a profound ethical question regarding the status of psychological replicas, asking us to contemplate the validity of selfish concern in the face of seemingly identical psychological entities. By probing these issues, the author deepens our philosophical understanding of identity, survival, and ethics in the face of prospective technological advancements.

The Prudential Concerns and Broader Philosophical Discourse

The examination of prudential concerns within the transhumanist paradigm provides a valuable contribution to philosophical discourse. While the article articulates the notion of psychological continuity as the core of personal identity, it also raises doubts about the sufficiency of this concept for prudential concern – the interest one has in their own future experiences. In scenarios such as nondestructive uploading, despite perfect psychological continuity with the electronic replica, the author notes a discernible preference for one’s own physical continuity. This observation seems to contradict the notion of equivalency between psychological continuity and survival, indicating a potential disparity between philosophical and prudential perspectives on identity. The author’s rigorous analysis thus prompts us to reassess assumptions about the centrality of psychological continuity to personal identity, prompting further deliberation on the complex relationship between continuity, survival, and prudential interests in the philosophical sphere.

The author’s critique of Parfitian transhumanism emerges from an analysis of the disjunction between psychological continuity and prudential interest, providing a contribution to the larger discourse on personal identity and the ethics of futuristic technology. This line of inquiry echoes and amplifies long-standing philosophical debates about the nature of the self and the conditions for its survival. While the author’s skepticism regarding the adequacy of psychological continuity in defining survival is noteworthy, it further fuels the ongoing philosophical discussions around personal identity, transhumanism, and their ethical implications. In contextualizing this argument within the broader philosophical landscape, the author subtly invites a more profound dialogue between traditional theories of identity and the ever-evolving concept of transhumanism, thereby enriching the conversation in the field of futures studies.

Abstract

Transhumanists want to free us from the constraints imposed by our humanity by means of “uploading”: extracting information from the brain, transferring it to a computer, and using it to create a purely electronic person there. That is supposed to move us from our human bodies to computers. This presupposes that a human being could literally move to a computer by a mere transfer of information. The chapter questions this assumption, then asks whether the procedure might be just as good, as far as our interests go, even if it could not move us to a computer.

The Metaphysics of Transhumanism
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(Featured) Limits of conceivability in the study of the future. Lessons from philosophy of science

Limits of conceivability in the study of the future. Lessons from philosophy of science

Veli Virmajoki explores the epistemological and conceptual limitations of futures studies, and offers an enlightening perspective in the philosophical discourse on the conceivability of future possibilities. Utilizing three case studies from the philosophy of science as the crux of its argument, the paper meticulously dissects how these limitations pose significant obstacles in envisaging alternatives to the present state of affairs. The author poses a thought-provoking argument centered on the constraints imposed by our current understanding of reality and the mechanisms it employs to reinforce its own continuity and inevitability.

The backbone of this philosophical inquiry lies in the robust debate between inevitabilism, a stance asserting the inevitable development of specific scientific theories, and contingentism, a view that endorses the potentiality of genuinely alternative scientific trajectories. The exploration of this contentious issue facilitates a deeper understanding of the constraints in predicting future scenarios, as our ability to conceptualize these alternatives is bound by our understanding of past and present realities. The paper deftly argues that the choice between inevitabilism and contingentism is fundamentally intertwined with our personal intuition about the range of genuine possibilities, thereby asserting the subjective nature of perceived futurity. As such, the article offers a fresh, critical lens to scrutinize the underpinnings of futures studies, and instigates a profound rethinking of our philosophical approach to anticipating what lies ahead.

Unconceived Possibilities and their Consequences

The author asserts that our conception of potential futures is significantly limited by profound epistemological and conceptual factors. They draw on the case study of the late 19th-century ether theories in physics, where, despite the existence of genuinely alternative theories, only a limited number of possibilities were conceived due to prevailing scientific practices and principles. The author uses this historical case to illustrate that while some futures may seem inconceivable from our present vantage point, they may still fall within the realm of genuine possibilities.

Moreover, the author argues that the potential impact of these unconceived possibilities extends beyond the localized elements of a system to reverberate throughout its entirety. This underlines the complexity of the task in futures studies; any unconceived alternatives in one sector of a system can trigger significant, far-reaching consequences for the entire system. Therefore, the research warns against oversimplification in predicting future scenarios and emphasizes the need for a nuanced approach that recognizes the interconnectedness of elements within any given system. This presents a remarkable challenge for futures studies, highlighting the depth of the iceberg that lies beneath the surface of our current epistemological and conceptual understanding.

Historical Trajectories and Justification of Future Possibilities

In the examination of plausibility and the justification of future possibilities, the article underscores the fundamental epistemological and conceptual challenges that limit our capability to predict alternative futures. The author refers to historical episodes like the case of Soviet cybernetics, where the existence of plausible alternative futures was not recognized, due to the collective failure to see past the status quo. It brings to light the inherent difficulties in justifying the plausibility or even the possibility of certain futures, where our current knowledge systems and conceptual frameworks may blind us to divergent scenarios. This observation raises pertinent questions about the inherent biases of our epistemic practices, as well as the potential for deeply entrenched beliefs to restrict our ability to imagine and evaluate a broader range of future possibilities. Hence, this line of inquiry necessitates the careful examination of the underlying assumptions that might constrain the scope of our foresight and deliberations on future possibilities.

The article further discusses the concept of historical trajectories and their connection to future possibilities, offering a philosophical lens into the entanglement of past, present, and future. It argues that our understanding of history and future possibilities, and our interpretation of the present’s robustness and inevitability, are inextricably linked through a complex web of modal considerations. The author emphasizes the interconnectedness of past trajectories and future possibilities, arguing that the way we perceive historical possibilities affects how we anticipate future outcomes. This perspective allows us to examine whether it is the deterministic view of history (inevitabilism) or the contingency of events (contingentism) that should be the default position, a determination that would have profound implications for our understanding of future possibilities.

Inevitabilism vs. Contingentism

Tthe author elaborates on a crucial dichotomy in philosophy of science: inevitabilism versus contingentism. Inevitabilism implies a deterministic understanding of scientific and historical development, where the present state of affairs appears as the unique and necessary outcome of the past. Contingentism, on the other hand, endorses the idea of multiple genuine alternatives to the current state, thus opening the space of historical and future possibilities. The article underscores that these positions are not simply academic disputes but carry substantial implications for how we conceive possibilities for the future. Moreover, these divergent outlooks reflect the individual’s inherent beliefs and intuitions about the range of possibilities within human affairs. The author contends that these perspectives cannot conclusively advocate for or against alternative futures because one’s stance on the inevitabilism versus contingentism debate inherently relies on their preconceived notions of the scope of historical and future possibilities.

Future Research Avenues

In light of the research as presented, promising avenues for future research emerge. The author suggests a systematic examination of the epistemological and conceptual boundaries of our ability to conceive and reason about potential futures. Such an investigation is not limited to philosophical discourse but requires interdisciplinary dialogue with a myriad of fields, as these boundaries are, in part, shaped by our social and scientific structures. This method of research would offer a comprehensive understanding of the creative and critical capacities of futures studies and aid us in recognizing our epistemological and conceptual predicament concerning future possibilities. Furthermore, it could potentially expose the manner in which these boundaries are historically mutable, opening up a discussion about the renegotiation of the boundaries of conceivability.

Abstract

In this paper, the epistemological and conceptual limits of our ability to conceive and reason about future possibilities are analyzed. It is argued that more attention should be paid in futures studies on these epistemological and conceptual limits. Drawing on three cases from philosophy of science, the paper argues that there are deep epistemological and conceptual limits in our ability to conceive and reason about alternatives to the current world. The nature and existence of these limits are far from obvious and become visible only through careful investigation. The cases establish that we often are unable to conceive relevant alternatives; that historical and counterfactual considerations are more limited than has been suggested; and that the present state of affairs reinforces its hegemony through multiple conceptual and epistemological mechanisms. The paper discusses the reasons behind the limits of the conceivability and the consequences that follow from the considerations that make the limits visible. The paper suggests that the epistemological and conceptual limits in our ability to conceive and reason about possible futures should be mapped systematically. The mapping would provide a better understanding of the creative and critical bite of futures studies.

Limits of conceivability in the study of the future. Lessons from philosophy of science
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(Featured) Future value change: Identifying realistic possibilities and risks

Future value change: Identifying realistic possibilities and risks

The advent of rapid technological development has prompted philosophical investigation into the ways in which societal values might adapt or evolve in response to changing circumstances. One such approach is axiological futurism, a discipline that endeavors to anticipate potential shifts in value systems proactively. The research article at hand makes a significant contribution to the developing field of axiological futurism, proposing innovative methods for predicting potential trajectories of value change. This article from Jeroen Hopster underscores the complexity and nuance inherent in such a task, acknowledging the myriad factors influencing the evolution of societal values.

His research presents an interdisciplinary approach to advance axiological futurism, drawing parallels between the philosophy of technology and climate scholarship, two distinct yet surprisingly complementary fields. Both fields, it argues, share an anticipatory nature, characterized by a future orientation and a firm grounding in substantial uncertainty. Notably, the article positions climate science’s sophisticated modelling techniques as instructive for philosophical studies, promoting the use of similar predictive models in axiological futurism. The approach suggested in the article enriches the discourse on futures studies by integrating strategies from climate science and principles from historical moral change, presenting an enlightened perspective on the anticipatory framework.

Theoretical Framework

The theoretical framework of the article is rooted in the concept of axiological possibility spaces, a means to anticipate future moral change based on a deep historical understanding of past transformations in societal values. The researcher proposes that these spaces represent realistic possibilities of value change, where ‘realism’ is a function of historical conditioning. To illustrate, processes of moralisation and demoralisation are considered historical markers that offer predictive insights into future moral transitions. Moralisation is construed as the phenomenon wherein previously neutral or non-moral issues acquire moral significance, while demoralisation refers to the converse. As the research paper posits, these processes are essential to understanding how technology could engender shifts in societal values.

In particular, the research identifies two key factors—technological affordances and the emergence of societal challenges—as instrumental in driving moralisation or demoralisation processes. The author suggests that these factors collectively engender realistic possibilities within the axiological possibility space. Notably, the concept of technological affordances serves to underline how new technologies, by enabling or constraining certain behaviors, can precipitate changes in societal values. On the other hand, societal challenges are posited to stimulate moral transformations in response to shifting social dynamics. Taken together, this theoretical framework stands as an innovative schema for the anticipation of future moral change, thereby contributing to the discourse of axiological futurism.

Axiological Possibility Space and Lessons from Climate Scholarship

The concept of an axiological possibility space, as developed in the research article, operates as a predictive instrument for anticipating future value change in societal norms and morals. This space is not a projection of all hypothetical future moral changes, but rather a compilation of realistic possibilities. The author defines these realistic possibilities as those rooted in the past and present, inextricably tied to the historical conditioning of moral trends. Utilizing historical patterns of moralisation and demoralisation, the author contends that these processes, in concert with the introduction of new technologies and arising societal challenges, provide us with plausible trajectories for future moral change. As such, the axiological possibility space serves as a tool to articulate these historically grounded projections, offering a valuable contribution to the field of anticipatory ethics and, more broadly, to the philosophy of futures studies.

A central insight from the article emerges from the intersection of futures studies and climate scholarship. The author skillfully extracts lessons from the way climate change prediction models operate, particularly the CMIP models utilized by the IPCC, and their subsequent shortcomings in the face of substantial uncertainty. The idea that the intricacies of predictive modeling can sometimes overshadow the focus on potentially disastrous outcomes is critically assessed. The author contends that the realm of axiological futurism could face similar issues and hence should take heed. Notably, the call for a shift from prediction-centric frameworks to a scenario approach that can articulate the spectrum of realistic possibilities is emphasized. This scenario approach, currently being developed in climate science under the term “storyline approach,” underlines the importance of compound risks and maintains a robust focus on potentially high-impact events. The author suggests that the axiological futurist could profitably adopt a similar strategy, exploring value change in technomoral scenarios, to successfully navigate the deep uncertainties intrinsic to predicting future moral norms.

Integration into Practical Fields and Relating to Broader Philosophical Discourse

The transfer of the theoretical discussion into pragmatic fields is achieved in the research with a thoughtful examination of its potential applications, primarily in value-sensitive design. By suggesting a need for engineers to take into consideration the dynamics of moralisation and demoralisation, the author not only proposes a shift in perspective, but also creates a bridge between theoretical discourse and practical implementation. Importantly, it is argued that a future-proof design requires an assessment of the probability of embedded values shifting in moral significance over time. The research paper goes further, introducing a risk-based approach to the design process, where engineers should not merely identify likely value changes but rather seek out those changes that render the design most vulnerable from a moral perspective. The mitigation of these high-risk value changes then becomes a priority in design adaptation, solidifying the article’s argument that axiological futurism is an essential tool in technological development.

The author’s analysis also presents a substantial contribution to the broader philosophical discourse, notably the philosophy of futures studies and the ethics of technology. By integrating concepts from climatology and axiology, the work demonstrates an interdisciplinary approach that enriches philosophical discourse, emphasizing how diverse scientific fields can illuminate complex ethical issues in technology. Importantly, the work builds on and critiques the ideas of prominent thinkers like John Danaher, pushing for a more diversified and pragmatic approach in axiological futurism, rather than a singular reliance on model-based projections. The research also introduces the critical notion of “realistic possibilities” into the discourse, enriching our understanding of anticipatory ethics. It advocates for a shift in focus towards salient normative risks, drawing parallels to climate change scholarship and highlighting the necessity for anticipatory endeavours to be both scientifically plausible and ethically insightful. This approach has potential for a significant impact on philosophical studies concerning value change and the ethical implications of future technologies.

Future Research Directions

The study furnishes ample opportunities for future research in the philosophy of futures studies, particularly concerning the integration of its insights into practical fields and its implications for anticipatory ethics. The author’s exploration of axiological possibility spaces remains an open-ended endeavor; further work could be conducted to investigate the specific criteria or heuristic models that could guide ethical assessments within these spaces. The potential application of these concepts in different technological domains, beyond AI and climate change, also presents an inviting avenue of inquiry. Moreover, as the author has adopted lessons from climate scholarship, similar interdisciplinary approaches could be employed to incorporate insights from other scientific disciplines. Perhaps most intriguingly, the research introduces a call for a critical exploration of “realistic possibilities,” an area that is ripe for in-depth theoretical and empirical examination. Future research could build upon this foundational concept, investigating its broader implications, refining its methodological underpinnings, and exploring its potential impact on policy making and technological design.

Abstract

The co-shaping of technology and values is a topic of increasing interest among philosophers of technology. Part of this interest pertains to anticipating future value change, or what Danaher (2021) calls the investigation of ‘axiological futurism’. However, this investigation faces a challenge: ‘axiological possibility space’ is vast, and we currently lack a clear account of how this space should be demarcated. It stands to reason that speculations about how values might change over time should exclude farfetched possibilities and be restricted to possibilities that can be dubbed realistic. But what does this realism criterion entail? This article introduces the notion of ‘realistic possibilities’ as a key conceptual advancement to the study of axiological futurism and offers suggestions as to how realistic possibilities of future value change might be identified. Additionally, two slight modifications to the approach of axiological futurism are proposed. First, axiological futurism can benefit from a more thoroughly historicized understanding of moral change. Secondly, when employed in service of normative aims, the axiological futurist should pay specific attention to identifying realistic possibilities that come with substantial normative risks.

Future value change: Identifying realistic possibilities and risks