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- Convenors:
-
David Leslie
(The Alan Turing Institute)
James Wright (The Alan Turing Institute)
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- Format:
- Panel
- Sessions:
- Tuesday 7 June, -
Time zone: Europe/London
Short Abstract:
This panel will look at how data justice movements and perspectives, particularly those that look beyond Western Europe and North America, are reshaping global debates on AI ethics and transforming its future from the ground up.
Long Abstract:
In recent years, narratives about an escalating “AI arms race” have become all-too-commonplace, portending a gloomy human future predetermined by escalating geopolitical sprints to some non-existent technoscientific finish line. At the same time, a parallel but more muted geopolitical race has intensified: a dash to develop international standards for AI ethics and governance. In an ideal world, the development of globally inclusive governance protocols and ethical standards would ensure that AI technologies are developed and implemented in “responsible” ways. Over the past decade, however, international policymaking and standards-setting ecosystems have largely been characterised by the “policy hegemony” of Western tech corporations and Global North geopolitical actors, who have asymmetrically wielded network power while simultaneously engaging in virtually unimpeded data capture and rent-seeking behaviour.
More recently, a growing body of data justice scholarship has confronted these power dynamics and reframed the ethical challenges of datafication through the social justice lens. This has spurred along a growing awareness in AI ethics of the sociotechnical dimensions of power and a greater focus on relations of inequity and extraction within and between societies. On the whole, this “data justice turn” may well signal the coalescence of an increasingly detranscendentalised AI ethics with closely aligned fields such as data feminism, design justice, data colonialism, and non-Western data ethics among others.
This panel will consider how data justice movements and perspectives, particularly those that look beyond Western Europe and North America, are reshaping global debates on AI ethics and transforming its future from the ground up.
Accepted papers:
Session 1 Tuesday 7 June, 2022, -David Leslie (The Alan Turing Institute) Rosamund Powell (The Alan Turing Institute)
Paper short abstract:
Here we argue for the importance of the deep history of data justice. Where the horizons of data justice research are widened beyond datafication processes, researchers can better bring into focus how long-term legacies of inequality, discrimination and oppression are drawn into present data work.
Paper long abstract:
Over the last decade, much of the growing academic literature on digital rights and data justice has been characterised by a near-sighted focus on “the big data revolution,” the “second machine age,” and the rise of “surveillance capitalism”. Such a cramped temporal lens runs the risk of reverting to modes of information-centrism and tech-centered short-sightedness that can impair researchers’ visions of the past, present, and future. It can impair understanding of the past by concealing longer term sociohistorical patterns of inequity that have cascading effects on data innovation ecosystems and that directly and indirectly influence the sociotechnical contexts of data collection and use. It can impair understanding of the present by limiting levels of explanation and analysis to areas circumscribed by the narrow set of normative and social justice issues that are seen to surface specifically in current constellations of data innovation practices. And, it can impair visions of the future by creating a false sense of the insuperability of the revolutionary momentum of current technoscientific change—leaving critics feeling disempowered in the face of a creeping technological determinism.
In this paper we argue for the importance of the deep history of data justice. Where the temporal horizons of the study of data justice are appropriately widened, slower and more subtle patterns of injustice become discernible. This can bring into focus how longer-term legacies of inequality, discrimination, and oppression have both shaped the history of applied statistical and computational techniques of social administration and, ultimately, been drawn into contemporary data work.
Antonella Perini (The Alan Turing Institute) Morgan Briggs (The Alan Turing Institute) Smera Jayadeva (Alan Turing Institute)
Paper short abstract:
Initiatives and organisations across the globe are interrogating the sociotechnical structures and practices that underline data injustices. This paper explores the trends identified in over 100 case studies of data justice advocacy and activist work as well as associated challenges to data justice.
Paper long abstract:
Data-intensive technologies are profoundly impacting our societies in multiple and interconnected dimensions. Whilst scholars have addressed current injustices derived from data collection, governance, and use, initiatives and organisations across the globe are interrogating the sociotechnical structures and practices that underline these injustices; not only evidencing transformational movements but also emphasising that data justice is contextually determined. Understanding data justice from a broad and inclusive perspective requires examining the empirical challenges identified by communities impacted by datafication, the transformational practices of data activists, and the institutionalised forms of counterpressure developed by organisations advancing data rights and justice.
To contribute to this goal, we constructed a repository of over 100 case studies that illustrate instances of data justice advocacy and activist work as well as cases of associated challenges to data justice. The repository highlights an ecosystem of lived experiences that are shaping the imaginaries of data collection, governance, and use. The proposed paper will explore the trends identified in the repository, in terms of the themes that the challenges and transformational cases relate to, the pillars of data justice they address, the affected people and communities, the types of actions taken – e.g., education, litigation, policy development, research –, and the paths organisations followed to integrate data justice into their work. The case studies illustrate how affected communities, activists, and organisations across the world seek to appropriate technology and set an agenda of data justice that considers their needs, contexts, and aspirations.
Mhairi Aitken (The Alan Turing Institute)
Paper short abstract:
Environmental Data Justice interrogates and challenges dominant power structures to address inequitable impacts of innovation. This paper draws on scholarship from Science and Technology Studies to explore the role of knowledge and power in environmental data justice.
Paper long abstract:
The environmental justice, climate justice and data justice movements have much in common: Each are concerned with interrogating and challenging dominant power structures and addressing the inequitable impacts of technologies and innovation. These movements seek to redress power imbalances in amplifying the voices and experiences of impacted communities.
Recognising the complementarity of data justice and environmental and climate justice movements in calling for participatory and recognitional justice along with distributive and restorative justice, there is an emerging body of work pulling these areas together and proposing a new field of Environmental Data Justice. Researchers in the emerging field of Environmental Data Justice have called attention to the importance of including diverse perspectives and interests within data collection or data science approaches in order to ensure data are used and interpreted in ways which reflect the interests and experiences of impacted communities. This requires combining community engagement with data collection to mobilise communities and incorporate local, situated, and contextual knowledge into environmental data science.
This paper draws on scholarship from Science and Technology Studies (STS), to explore the ways in which social, cultural, and political factors shape knowledge and “expertise” relating to data and the environment. STS highlights the importance of engaging with diverse sources and forms of knowledge to inform justice-oriented discussions of science and technology. This paper will explore the centrality of knowledge and power within environmental data justice and discuss the importance of harnessing plurality of knowledge to advance environmental data justice.