Despite their flaws, large language models (LLMs) deserve a fair chance to prove their mettle against human experts, who are often plagued with biases, conflicts of interest, and other frailties. For epistemically unprivileged laypeople struggling to access expert knowledge, the accessibility advantages of LLMs could prove crucial. While complaints about LLMs' inconsistencies and arguments for human superiority are often justified (for now), they distract from the urgent need to prepare for the likely scenario of LLMs' continued ascent. Experimentation with both (...) the capabilities and institutional architecture of LLMs is necessary. Neither tech-bashing nor excessive gatekeeping will suffice. As LLMs are here to stay and they keep improving, it is high time we started thinking about how to navigate the impending wave of their proliferation. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (shrink)

Theories of action tend to require agents to have mental representations. A common trope in discussions of artificial intelligence (AI) is that they do not, and so cannot be agents. Properly understood there may be something to the requirement, but the trope is badly misguided. Here we provide an account of representation for AI that is sufficient to underwrite attributions to these systems of ownership, action, and responsibility. Existing accounts of mental representation tend to be too demanding and unparsimonious. We (...) offer instead a minimalist account of representation that ascribes only those features necessary for explaining action, trimming the “extra” features in existing accounts (e.g., representation as a “mental” phenomenon). Our account makes ‘representation’ whatever it is that, for example, the thermostat is doing with the thermometer. The thermostat is disposed to act as long as the thermometer is outside a given range of parameters.. Our account allows us to offer a new perspective on the ‘responsibility gap’, a problem raised by the actions of sophisticated machines: because nobody has enough control over the machine’s actions to be able to assume responsibility, conventional approaches to responsibility ascription are inappropriate. We argue that there is a distinction between finding responsible and holding responsible and, in order to resolve the responsibility gap, we must first clarify the conceptual terrain on which agent is in fact responsible. (shrink)

This article holds that governmental investments in quantum technologies speak to the imaginable futures of digital sovereignty and digital infrastructures, two major areas of change driven by related technologies like AI and Big Data, among other things, in international law today. Under intense development today for future interpolation into digital systems that they may alter, quantum technologies occupy a sort of liminal position, rooted in existing assemblages of computational technologies while pointing to new horizons for them. The possibilities they raise (...) are neither certain nor determinate, but active investments in them (legal, political and material investments) offer perspective on digital technology-driven influences on an international legal imagination. In contributing to visions of the future that are guiding ambitions for digital sovereignty and digital infrastructures, quantum technologies condition digital technology-driven changes to international law and legal imagination in the present. Privileging observation and description, I adapt and utilize a diffractive method with the aim to discern what emerges out of the interference among the several related things assembled for this article, including material technologies and legal institutions. In conclusion, I observe ambivalent changes to an international legal imagination, changes which promise transformation but appear nonetheless to reproduce current distributions of power and resources. (shrink)

This paper considers recent experiments in art and artificial intelligence that crystallize around training algorithms to generate artworks based on datasets derived from the Western art historical canon. Over the last decade, a shift towards the rejection of canonicity has begun to take shape in art historical discourse. At the same time, algorithmically enabled practices in the US and Europe have emerged that entrench the Western canon as a locus and guarantor of aesthetic value. Operating within the epistemic framework of (...) a “view from nowhere,” this tendency in generative art inherits the coloniality of both art history and artificial intelligence. Producing “art histories from nowhere,” this tendency conflates the conceptual category of visual art with the histories of Western cultural production. It reproduces a set of aesthetic values that entrench the mythology of the artist-genius and his imputed whiteness and masculinity; the extolment of innovation and novelty as self-evident virtues; disembodied Cartesian models of knowing and sensing; and the erasure of contributions that have been occluded from canonical visibility. As we encounter systems trained on particular visions of art history and of the artist, how might we remain attentive to the specific lens through which they are taught to see? This essay addresses that question by bringing the coloniality of recent experiments into view, bridging data feminisms and decolonial studies to formulate alternative visions of encounters between art and AI. (shrink)

As China and the United States strive to be the primary global leader in AI, their visions are coming into conflict. This is frequently painted as a fundamental clash of civilisations, with evidence based primarily around each country’s current political system and present geopolitical tensions. However, such a narrow view claims to extrapolate into the future from an analysis of a momentary situation, ignoring a wealth of historical factors that influence each country’s prevailing philosophy of technology and thus their overarching (...) AI strategies. In this article, we build a philosophy-of-technology-grounded framework to analyse what differences in Chinese and American AI policies exist and, on a fundamental level, why they exist. We support this with Natural Language Processing methods to provide an evidentiary basis for our analysis of policy differences. By looking at documents from three different American presidential administrations––Barack Obama, Donald Trump, and Joe Biden––as well as both national and local policy documents (many available only in Chinese) from China, we provide a thorough comparative analysis of policy differences. This article fills a gap in US–China AI policy comparison and constructs a framework for understanding the origin and trajectory of policy differences. By investigating what factors are informing each country’s philosophy of technology and thus their overall approach to AI policy, we argue that while significant obstacles to cooperation remain, there is room for dialogue and mutual growth. (shrink)

The growing use of automated decision-making (ADM) systems in the public sector and the need to control these has raised many legal questions in academic research and in policymaking. One of the timely means of legal control is accountability, which traditionally includes the ability to impose sanctions on the violator as one dimension. Even though many risks regarding the use of ADM have been noted and there is a common will to promote the safety of these systems, the relevance of (...) the safety research has been discussed little in this context. In this article, I evaluate regulating accountability over the use of ADM in the public sector in relation to the findings of safety research. I conducted the study by focusing on ongoing regulatory projects regarding ADM, the Finnish ADM legislation draft and the EU proposal for the AI Act. The critical question raised in the article is what the role of sanctions is. I ask if official accountability could mean more of an opportunity to learn from mistakes, share knowledge and compensate for harm instead of control via sanctions. (shrink)

Algorithmic systems that provide services to people by supporting or replacing human decision-making promise greater convenience in various areas. The opacity of these applications, however, means that it is not clear how much they truly serve their users. A promising way to address the issue of possible undesired biases consists in giving users control by letting them configure a system and aligning its performance with users’ own preferences. However, as the present paper argues, this form of control over an algorithmic (...) system demands an algorithmic literacy that also entails a certain way of making oneself knowable: users must interrogate their own dispositions and see how these can be formalized such that they can be translated into the algorithmic system. This may, however, extend already existing practices through which people are monitored and probed and means that exerting such control requires users to direct a computational mode of thinking at themselves. (shrink)

This article discusses the key existential stakes of implementing biometrics in human lifeworlds. In this pursuit, we offer a problematization and reinvention of central values often taken for granted within the “ethical turn” of AI development and discourse, such as autonomy, agency, privacy and integrity, as we revisit basic questions about what it means to be human and embodied. Within a framework of existential media studies, we introduce an existential ethics of care—through a conversation between existentialism, virtue ethics, a feminist (...) ethics of care and post-humanist ethics—aiming to deepen and nuance our understanding of the human behind “human-centered” AI directives. The key argument is that biometrics implicates humans through unprecedented forms of objectification, through which the existential body—the relational, intimate and frail human being—is at risk. We interrogate these risks as they become visible at three sites where embodied humans are challenged by biometrics, and thus where the existential body is challenged by the biometric body. This occurs through reductionism (biometric passports nailing bodies to identities, removing human judgment and compromising agency at the AI border), enforced transparency (smart home assistants surveying human intimacies and invading intimate spaces in the bedroom) and the breaching of bodily integrity (chipping bodies to capture sensory data, challenging the very concept of bodily integrity through self-invasive biohacking). Our existential ethics of care is importantly not a solutionist list of principles or suggestions, but a manifesto for a way of thinking about the ethical challenges of living with biometrics in today’s world, by raising the right questions. We argue that a revitalized discussion of the basic existential stakes within human lived experience is needed and should serve as the foundation on which comprehensive frameworks can be built to address the complexities and prospects for ethical machines, responsible biometrics and AI. (shrink)

Social media has revolutionized the way information is distributed throughout society, as folks continue to rely entirely on these apps for information on current events, health protocols, and socio-political discussions. However, these containers of knowledge do not appear in the same shape for every user; Algorithms, informed by capitalist agendas, determine what information sifts through its networks and to whom. Data scientists, researchers, and activists have dissected the hidden mechanics fueling these popular platforms, inciting critical conversations around the harmful biases (...) embedded in algorithms. These studies often skim the surface of how these algorithms digitally marginalize people of color, if acknowledging it at all. Even fewer have attempted to examine the role these algorithms play in the social activism and digital community organizing happening amongst communities of color via social media. Referring to indigenous scholar Marisa Elena Duarte’s book Network Sovereignty as a framework of thought, this paper roots itself in the notion that technology is an extension of the agenda utilizing it. Through dissecting the algorithmic structures of popular social platforms among communities of color, this paper examines how social media distributes information within its networks and how its encoded biases silence Black, brown, and indigenous voices. This paper also provides insight into how BIPOC content-creators, when informed on how the algorithms work, can use these platforms to their advantage and effectively facilitate socio-political discourse online; Changing the narrative of social networks from being yet another landscape of white supremacy to instead a communal canvas for radical change. (shrink)

Artificial intelligence (AI) governance and auditing promise to bridge the gap between AI ethics principles and the responsible use of AI systems, but they require assessment mechanisms and metrics. Effective AI governance is not only about legal compliance; organizations can strive to go beyond legal requirements by proactively considering the risks inherent in their AI systems. In the past decade, investors have become increasingly active in advancing corporate social responsibility and sustainability practices. Including nonfinancial information related to environmental, social, and (...) governance (ESG) issues in investment analyses has become mainstream practice among investors. However, the AI auditing literature is mostly silent on the role of investors. The current study addresses two research questions: (1) how companies’ responsible use of AI is included in ESG investment analyses and (2) what connections can be found between principles of responsible AI and ESG ranking criteria. We conducted a series of expert interviews and analyzed the data using thematic analysis. Awareness of AI issues, measuring AI impacts, and governing AI processes emerged as the three main themes in the analysis. The findings indicate that AI is still a relatively unknown topic for investors, and taking the responsible use of AI into account in ESG analyses is not an established practice. However, AI is recognized as a potentially material issue for various industries and companies, indicating that its incorporation into ESG evaluations may be justified. There is a need for standardized metrics for AI responsibility, while critical bottlenecks and asymmetrical knowledge relations must be tackled. (shrink)

Much more than their machinic reality, current iterations of AI rely on imagined divisions of human and non-human properties and skills that have genealogical ties to colonization. For this reason, research efforts have recently been made to historicize these imaginaries, connecting them to colonial ideals that delegate black and brown colonized people into the realm of the non-human. Atanasoski and Vora (Surrogate humanity. Race, robots and the politics of technological futures, Duke, Durham and London, 2019) have called this a “surrogate (...) humanity”, where narratives of autonomous technologies function to disappear precisely the formerly colonized peoples that are enveloped in its production process. At the same time, the gendered and racialized roots of this maternal figure represents an opportunity to uncover and critique the invisibilization of embodied resources necessary to produce AI, precarious bodies labouring to produce algorithmic infrastructures in a manner that can be considered in a genealogy of carework and reproduction. These genealogies complicate the detachment suggested by the surrogate figure and go beyond it to proclaim a more generative function of the relationship between the black maternal figure and AI. The article analyses Tabita Rezaire’s multi-media artwork Sugar Walls Teardom to think through decolonial and queer renderings of the black female bodies upon which technological imaginaries rest, to extend beyond AI surrogacy and towards notions of kinship, care and world-making by producing an AI aesthetics that is relational, embodied, and celebratory of other ways of liveness. (shrink)

Human computer interaction (HCI) has grown into a mature field of research. With artificial intelligence (AI) finding ubiquitous applications, HCI research is now moving ahead towards accommodating and integrating these approaches. A part of the research community is of the opinion that HCI and AI are fundamentally opposed to each other: with AI-powered devices being demonic and humans are to lose in a race against them and HCI-oriented products being human centred being the flag bearers of the human race. In (...) this paper, we look at and analyse this perspective of how HCI relates to AI and the potential HCI–AI integration. We suggest that humans evolve by having dynamic identities. We further discuss its implications on the AI critique and suggest some new perspectives on the possible integration of HCI and AI research which we hope would be useful for the community. (shrink)

This study aims to identify artificial intelligence (AI) technologies that are applied in climate-smart agricultural practices and address ethical concerns of deploying those technologies from legal perspectives. As climate-smart agricultural AI, the study considers those AI-based technologies that are used for precision agriculture, monitoring peat lands, deforestation tracking, and improved forest management. The study utilized a systematic literature review approach to identify and analyze AI technologies employed in climate-smart agriculture and associated ethical and legal concerns. The study findings indicate several (...) ethical concerns for deploying AI in climate-smart agricultural practices pertaining to data inaccuracy, other technical errors based on wrong recommendations or wrongful acts, data ownership and intellectual property issues, and economic issues resulting in digital division and privacy and security related issues. In this study, the ethical concerns were further examined based on criminal law, tort law, privacy and data protection law, and intellectual property law. In this regard, the study finds that the current tort law pattern is more suitable than the criminal law pattern to address some major ethical concerns, such as data inaccuracy and other technical errors based on wrong recommendations or wrongful acts. Finally, the study recommends that at the global level, all countries need to fill up the current gap of international law on climate-smart agriculture through agreeing on a standard set of legal provisions and enhancing collaboration in innovation and deployment of climate-smart agricultural AI. It further recommends that at the local level, countries need to adopt suitable regulations addressing multi-stakeholders’ interests associated with the deployment of climate-smart agricultural AIs. (shrink)

Mobility robots may soon be among us, triggering a need for safety regulation. Robot safety regulation, however, remains underexplored, with only a few articles analyzing what regulatory approaches could be feasible. This article offers an account of the available regulatory strategies and attempts to theorize the effects of simulation-based safety regulation. The article first discusses the distinctive features of mobility robots as regulatory targets and argues that emergent behavior constitutes the key regulatory concern in designing robot safety regulation regimes. In (...) contrast to many accounts, the article posits that emergent behavior dynamics do not arise from robot autonomy, learning capability, or code unexplainability. Instead, they emerge from the complexity of robot technological constitutions coupled with near-infinite environmental variability and non-linear performance dynamics of the machine learning components. Second, the article reviews rules-based and performance-based regulation and argues that both will fail adequately constrain emergent robot behaviors. The article claims that controlling mobility robots requires a simulation-based regulatory approach. Simulation-based regulation is a novelty with significant theoretical and practical implications. The article argues that the approach signifies a radical break in regulatory forms of knowledge and temporalities. Simulations enact virtual futures to create a new regulatory knowledge type. Practically, the novel safety knowledge type may destabilize the existing conceptual space of safety politics and liability allocation patterns. (shrink)

The General Data Protection Regulation (GDPR) of the EU confirms the protection of personal data as a fundamental human right and affords data subjects more control over the way their personal information is processed, shared, and analyzed. However, where data are processed by artificial intelligence (AI) algorithms, asserting control and providing adequate explanations is a challenge. Due to massive increases in computing power and big data processing, modern AI algorithms are too complex and opaque to be understood by most data (...) subjects. Articles 15 and 22 of the GDPR provide a modest regulatory framework for automated data processing by, among other things, mandating that data controllers inform data subjects about when it is being used, and its logic and ramifications. Nevertheless, due to the phrasing of the articles and the numerous exceptions they allow, doubts have arisen about their effectiveness. In this paper, we empirically evaluate the quality and effectiveness of AI disclosures as mandated by the GDPR. By means of an online survey (N = 835), we investigated how data subjects expect to be informed about the automated processing of their data. We then conducted a content analysis of the AI disclosures of N = 100 companies and organizations. The combined findings reveal that current GDPR-mandated disclosures do not meet the expectations and needs of data subjects. Explanations drawn up following the guidelines of the generic formulations of the GDPR differ widely and are often vague, incomplete and lack transparency. In our conclusions we identify a path towards standardizing and optimizing AI information notices. (shrink)

As the pagan classical world was subsumed into Christianity sexually hyperactive gods and goddesses transmuted into saints, their former statues that glorified the perfection of their bodies smashed into pieces and reimagined as austere two-dimensional icons to be worshipped by the new faithful. That dualistic and polemic narrative, where the soul’s purpose was to annihilate the body, survives today in the distinction between software and hardware, algorithms and robots, the former as the “ghosts” that animate the empty vessels, the “machines”. (...) But how does this narrative impact our cultural and social fantasies in the twenty-first century as we accelerate toward coexisting, uniting, or merging with intelligent artifacts? How does “humanness” blur when it is claimed by no-biological human-like entities too, or when humans augment their perception, consciousness and physical power through genetic engineering, drugs, or software and mechanical prostheses? Suppose we are destined to remake ourselves in the image of our ancient gods. Will it be through the embodiment of technologies in the physical reality, or through the complete disembodiment of our minds inside virtual worlds? (shrink)

Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems lack (...) the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualization holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

“Throw away anything that sounds too complicated. Only keep what is simple to grasp...If the information appears fuzzy and causes the brain to implode after two sentences, toss it away and stop listening. Doing so will make the news as orderly and simple to understand as the truth.” - In “GHG emissions,” The Kingfisher Story Collection, (Vuong 2022a).

Many researchers and intellectuals warn about extreme risks from artificial intelligence. However, these warnings typically came without systematic arguments in support. This paper provides an argument that AI will lead to the permanent disempowerment of humanity, e.g. human extinction, by 2100. It rests on four substantive premises which it motivates and defends: first, the speed of advances in AI capability, as well as the capability level current systems have already reached, suggest that it is practically possible to build AI systems (...) capable of disempowering humanity by 2100. Second, due to incentives and coordination problems, if it is possible to build such AI, it will be built. Third, since it appears to be a hard technical problem to build AI which is aligned with the goals of its designers, and many actors might build powerful AI, misaligned powerful AI will be built. Fourth, because disempowering humanity is useful for a large range of misaligned goals, such AI will try to disempower humanity. If AI is capable of disempowering humanity and tries to disempower humanity by 2100, then humanity will be disempowered by 2100. This conclusion has immense moral and prudential significance. (shrink)

Recently in this journal, Jessica Morley and colleagues (AI & SOC 2023 38:411–423) review AI ethics and education, suggesting that a cultural shift is necessary in order to prepare students for their responsibilities in developing technology infrastructure that should shape ways of life for many generations. Current AI ethics guidelines are abstract and difficult to implement as practical moral concerns proliferate. They call for improvements in ethics course design, focusing on real-world cases and perspective-taking tools to immerse students in challenging (...) situations with relatable personal, social and environmental implications. The present paper considers the ACTWith model of moral cognition for use in such training contexts. Morley and colleagues' paper and contemporary literature are reviewed. Whistleblowing as a source for relatable case studies is discussed, and the purpose of ethics education considered. The ACTWith model is introduced, and correlations with contemporaries noted. The ACTWith model has been successfully employed in a broad range of technology ethics courses in the Netherlands and South Korea. Illustrations are offered. Correlations with contemporary efforts are drawn in the context of software engineering. Summary discussion considers strengths and limitations of the ACTWith program. Overall, the paper emphasizes training high-level moral reasoning through guided inquiry education informing lifetime professional practice, and indicates an outstanding need for teachers able to do the job. (shrink)