Vol. 2: No. 3: 2020

A Social Science Perspective on Artificial Intelligence: Building Blocks for a Research Agenda

ABSTRACT

In this article, we discuss and outline a research agenda for social science research on artificial intelligence. We present four overlapping building blocks that we see as keys for developing a perspective on AI able to unpack the rich complexities of sociotechnical settings. First, the interaction between humans and machines must be studied in its broader societal context. Second, technological and human actors must be seen as social actors on equal terms. Third, we must consider the broader discursive settings in which AI is socially constructed as a phenomenon with related hopes and fears. Fourth, we argue that constant and critical reflection is needed over how AI, algorithms and datafication affect social science research objects and methods. This article serves as the introduction to this JDSR special issue about social science perspectives on AI.

Digital Limit Situations: Anticipatory Media Beyond 'The New AI Era'

ABSTRACT

In the present age AI (artificial intelligence) emerges as both a medium to and message about (or even from) the future, eclipsing all other possible prospects. Discussing how AI succeeds in presenting itself as an arrival on the human horizon at the end times, this theoretical essay scrutinizes the ‘inevitability’ of AI-driven abstract futures and probes how such imaginaries become living myths, by attending how the technology is embedded in broader appropriations of the future tense. Reclaiming anticipation existentially, by drawing and expanding on the philosophy of Karl Jaspers – and his concept of the limit situation – I offer an invitation beyond the prospects and limits of ‘the new AI Era’ of predictive modelling, exploitation and dataism. I submit that the present moment of technological transformation and of escalating multi-faceted and interrelated global crises, is a digital limit situation in which there are entrenched existential and politico-ethical stakes of anticipatory media. Attending to them as a ‘future present’ (Adam and Groves 2007, 2011), taking responsible action, constitutes our utmost capability and task. The essay concludes that precisely here lies the assignment ahead for pursuing a post-disciplinary, integrative and generative form of Humanities and Social Sciences as a method of hope, that engages AI designers in the pursuit of an inclusive and open future of existential and ecological sustainability.

Coproduction, Ethics and Artificial Intelligence: A Perspective from Cultural Anthropology

ABSTRACT

Over the past five years, artificial intelligence (AI) has been endorsed as the technical underpinning of innovation. Sensationalist representations of AI have also been accompanied by assumptions of technological determinism that distract from the ordinary, sometimes unassuming consequences of interaction with its systems and processes. Drawing on scholarship from cultural anthropology, along with science and technology studies (STS), this paper examines coproduction in a Canadian AI research and development context. Through interview responses and field observations it presents sites of sociotechnical entanglement and ethical discussion to highlight potential spaces of mediation for anthropological practice. Emerging themes from the experiences of AI specialists include the negotiability of technology, an ethics of the everyday and critical collaboration. Together this returns to an initial approach into a situated understanding of artificial intelligence, negotiating with broad, sensationalist perspectives and the more commonplace, backgrounded cases of narrow research.

What is Data and What Can It Be Used For? Key Questions in the Age of Burgeoning Data-Essentialism

ABSTRACT

In this article we describe the rise of a data orthodoxy that we suggest to label ‘data-essentialism’. We question this data-essentialism by problematizing its premises, and unveil its ideological indebtedness to deeper (previous) currents in Western thought and history. Data-essentialism is the assumption that data is the essence of basically everything, and thus provides the ideological underpinnings for the imagination of creating an Artificial Intelligence (AI) that would transform the human race and our existence. The imagination of data as an essence is in contrast to, while often conflated with, ideas of data as traces we leave behind existing in highly connected societies. This confusion over what data is, and can be used for, underlines the importance to engage in questions of the nature of data, whether everything in the universe can be described in terms of data and the implications of subscribing to such a data-essentialist worldview. We connect data- essentialism to a revival of positivism, critique a belief in the objectivity of data and that predictions based on data correlations can be fully accurate. We end the article with a discussion of how some aspects of AI rely on data- essentialist accounts and how these have a history and roots in Modernity.

Practical AI Transparency: Revealing Datafication and Algorithmic Identities

ABSTRACT

How does one do research on algorithms and their outputs when confronted with the inherent algorithmic opacity and black box-ness as well as with the limitations of API-based research and the data access gaps imposed by platforms’ gate-keeping practices? This article outlines the methodological steps we undertook to manoeuvre around the above-mentioned obstacles. It is a “byproduct” of our investigation into datafication and the way how algorithmic identities are being produced for personalisation, ad delivery and recommendation. Following Paßmann and Boersma’s (2017) suggestion for pursuing “practical transparency” and focusing on particular actors, we experiment with different avenues of research. We develop and employ an approach of letting the platforms speak and making the platforms speak. In doing so, we also use non-traditional research tools, such as transparency and regulatory tools, and repurpose them as objects of/for study. Empirically testing the applicability of this integrated approach, we elaborate on the possibilities it offers for the study of algorithmic systems, while being aware and cognizant of its limitations and shortcomings.

Artificial Intelligence and Video Game Creation: A Framework for the New Logic of Autonomous Design

ABSTRACT

Autonomous, intelligent tools are reshaping all sorts of work practices, including innovative design work. These tools generate outcomes with little or no user intervention and produce designs of unprecedented complexity and originality, ushering profound changes to how organizations will design and innovate in future. In this paper, we formulate conceptual foundations to analyze the impact of autonomous design tools on design work. We proceed in two steps. First, we conceptualize autonomous design tools as ‘rational’ agents which will participate in the design process. We show that such agency can be realized through two separate approaches of information processing: symbolic and connectionist. Second, we adopt control theory to unpack the relationships between the autonomous design tools, human actors involved in the design, and the environment in which the tools operate. The proposed conceptual framework lays a foundation for studying the new kind of material agency of autonomous design tools in organizational contexts. We illustrate the analytical value of the proposed framework by drawing on two examples from the development of Ubisoft’s Ghost Recon Wildlands video game, which relied on such tools. We conclude this essay by constructing a tentative research agenda for the research into autonomous design tools and design work.