Studying and discussing the relevant characteristics of data making them such a challenging resource to handle. In order to enable appropriate data provisioning, this article introduces a holistic research concept from data source to data sink that respects the processing requirements of data producers, as well as the quality requirements of data consumers and, moreover, ensures a trustworthy data administration.

This paper situates digital capitalism as a continuation of longer running post-Fordist trends of financialisation, digitalisation, and privatisation. As the platform model is founded on monopolising regulation, platforms come into direct competition with states and public institutions, which they pursue through a set of distinct techno-political strategies to claim power to govern. While the digital proprietary markets are continuities of existing trends, they bring new pressures and affordances, thus producing discontinuities in social regulation.

Technology is a product of our social knowledge and past labour, and it holds out the promise of basic material security and freedom from drudgery for all. We chafe against technologically mediated orders because we are social beings who need respect, community, and space for creativity. Those instincts could be the basis for a new politics of technology, which ultimately seeks to subject production to real democratic control. Data-driven technologies could then help meet social needs and enable us to choose our labours, making them a source of dignity and self-worth.

Societies’ increasing use of technology through the years has massively changed the way people live and move in the world. But the human impact of data-driven technologies is far from universally positive. How can data-driven technologies be deployed in ways that are compatible with the values of social justice?

Existing conceptions of data rights and protection and copyright or licensing-based models offer some instructive priors, but are ill-suited for the issues that may arise from models trained on commons-based data. Forward-looking proposals include investments in standardised dataset/model disclosure and other kinds of transparency when it comes to generative models’ training and capabilities, consortia-based funding for monitoring/standards/auditing organisations, and structures for shared ownership based on individual or community provision of fine-tuning data.

In January 2023, international and Canadian experts attended a virtual workshop to explore implications of digital data for markets and rethink the policy frameworks underlying those markets in light of the Government of Canada’s ongoing consultation on the Competition Act. Their discussion centred on two themes: first, policy actions that international peers have taken and what Canada might learn from them, and second, how regulatory coordination and coherence across interlocking frameworks (possibly in tension) might play a role in addressing challenges, both present and future, in a digital economy. This report presents the key takeaways from their discussion.

This article examines the historical and contemporary shaping of feminist artificial intelligence (FAI). It begins by looking at the microhistory of FAI through the writings of Alison Adam and her graduate students to enrich the plural histories of AI and to write back feminist history into AI. Then, it explores contemporary examples of how FAI is being shaped today and how it deploys a multiplicity of meanings.

The internet has become a battleground. Although it was unlikely to live up to the hype and hopes of the 1990s, only the most skeptical cynics could have predicted the World Wide Web as we know it today: commercial, isolating, and full of, even fueled by, bias. This was not inevitable. Jessa Lingel argues that much like our cities, the internet has become gentrified, dominated by the interests of business and capital rather than the interests of the people who use it.

Industry’s AI successes are easy to see on the news, but those headlines are the heralds of a much larger, more systematic shift as industry increasingly dominates the three key ingredients of modern AI research: computing power, large datasets, and highly skilled researchers. This domination of inputs is translating into AI research outcomes: Industry is becoming more influential in academic publications, cutting-edge models, and key benchmarks.

This book examines the ever-increasing impact of technology on our lives and explores a range of legal and constitutional questions that this raises. It considers the extent to which concepts such as 'cyberspace' and 'digital rights' advance or undermine our understanding of this development and proposes a number of novel approaches to the effective protection of our rights in this rapidly evolving environment.

This paper asks what happens when the state – whose purpose is to guarantee the rights of citizens – becomes a political and business partner with corporations whose profit model hinges on exploitative data-driven advertising, platform services, and gig work. The framework of ‘data colonialism’ is used to examine the historical roots of these new forms of extractivism. Suggestions are reviewed for how the public can help prevent the deployment of discriminatory algorithms, and hold states and corporations accountable when this happens.