We, the Data: Human Rights in the Digital Age
Open accessAbstract
A rallying call for extending human rights beyond our physical selves—and why we need to reboot rights in our data-intensive world. Our data-intensive world is here to stay, but does that come at the cost of our humanity in terms of autonomy, community, dignity, and equality? In We, the Data, Wendy H. Wong argues that we cannot allow that to happen. Exploring the pervasiveness of data collection and tracking, Wong reminds us that we are all stakeholders in this digital world, who are currently being left out of the most pressing conversations around technology, ethics, and policy. This book clarifies the nature of datafication and calls for an extension of human rights to recognize how data complicate what it means to safeguard and encourage human potential. As we go about our lives, we are co-creating data through what we do. We must embrace that these data are a part of who we are, Wong explains, even as current policies do not yet reflect the extent to which human experiences have changed. This means we are more than mere “subjects” or “sources” of data “by-products” that can be harvested and used by technology companies and governments. By exploring data rights, facial recognition technology, our posthumous rights, and our need for a right to data literacy, Wong has crafted a compelling case for engaging as stakeholders to hold data collectors accountable. Just as the Universal Declaration of Human Rights laid the global groundwork for human rights, We, the Data gives us a foundation upon which we claim human rights in the age of data.
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Nonrivalry and the Economics of Data
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Not Enough. Human Rights in an Unequal World
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THE ETHICS AND IMPACT OF DIGITAL IMMORTALITY
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Data Trusts: Ethics, Architecture and Governance for Trustworthy Data Stewardship
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Radical information literacy : reclaiming the political heart of the IL movement
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Flagged first, then by citations
Cited by
Sorted by citations
Hoskins, A. (2024) · Memory, Mind & Media · doi:10.1017/mem.2024.16 · Cited by 64 · see citing works
“For instance, M. Wong (2023) explains, ‘ The problem with using AI output to train future AI is straight-forward.”
- Authors
- Wong, W. H.
- Corresponding author
- Wong, Wendy H.
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 2023-10-10
- OpenAlex
- W4382600626
- Semantic Scholar
- 98997a07f7ccd4f7b1db05a868189245c42c040f
- Cited by
- 31
- References
- 274
- Citations by year
- 2026: 10 · 2025: 11 · 2024: 9 · 2023: 1
- FWCI
- 31.13
- Type
- book
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The MIT Press eBooks (publishedVersion)
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
- Keywords
- data rights, human rights, datafication, data collection, data tracking, data literacy, facial recognition technology, posthumous rights, digital rights, data ethics, data policy, autonomy, human dignity, Universal Declaration of Human Rights
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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