Tokenization of everything? Exploring the limits of blockchain technologies in the governance of financial markets and assets | Finance and Society | Cambridge Core
Tokenization of everything? Exploring the limits of blockchain technologies in the governance of financial markets and assets
New Job! Postdoctoral Visitor in AI & Governance at #YorkU (Canada). Deadline 20 December 2024.
Working with myself, @rwg & Tesh Dagne
#STS #law #AIgovernance
More details about the role are contained in the job ad: https://www.yorku.ca/research/wp-content/uploads/sites/39/2024/11/FSc-PDV-job-posting-Postdoctoral-Visitor-in-AI-Governance.pdf
Excited to welcome Prof Barbara Prainsack to York's Institute for Technoscience & Society virtual seminar series.
Barbara will talk about "Making AI Ethical: What is Data Solidarity & Why Do We Need It?" 10.30am EST via Zoom.
Details: https://www.yorku.ca/research/its/events/
#AIEthics #STS #Solidarity
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Colleagues & I have two new papers out on #data & #edtech, second one ...
"Monetising Digital Data in Higher education: Analysing the Strategies and Struggles of EdTech Startups" (link.springer.com/article/10.1...)
#assetization
#STS
#highereducation
#education
#digital
Colleagues & I have two new papers out on #data & #edtech, first one ...
"Data as asset, data as rent? Rentiership
practices in EdTech startups" (www.tandfonline.com/doi/metrics/...)
#assetization
#STS
#highereducation
#education
#digital
#rentiership
New paper out! "Understanding Data Valuation: Valuing Google’s Data Assets" w/ Sarah Marquis & Guilherme Cavalcante Silva in IEEE Transactions on Technology & Society
#Google #data #Assets #assetization
https://ieeexplore.ieee.org/document/10525235?source=authoralert
Understanding Data Valuation: Valuing Google’s Data Assets
Digital personal data are increasingly understood as a key asset in our digital economies. But how should we value such data? Numerous policymakers, regulators, and stakeholders are trying to work out how to manage the collection, use, and valuation of data in order to balance the advantages and disadvantages of its collection and use. The negative implications of data practices may include privacy loss, data breaches, or declining market competition, while social and economic benefits include improved service delivery, more efficient welfare systems, or better products. Increasingly, data are conceptualized as an asset. To understand the value of data as an asset means understanding how data are configured as an asset; data value does not reflect ownership and property rights per se, but rather diverse modes of access and use restrictions (usually delineated by opaque contractual agreements). Data are increasingly controlled by a few, large digital technology firms, especially so-called ‘Big Tech’ firms. In this paper, we use Google as a case study of how Big Tech firms configure and value digital data as an asset. We analyse how Google understands, frames, values, and monetizes the data they collect from users. We qualitatively analyse an extensive dataset of financial documentary materials produced by and about Google to identify the different modes of access and use restrictions that Google deploys to turn digital data into a valuable asset. We conclude that, despite being highly ambiguous, Google’s approach to data value focuses on monetizing users.
The end of the generative artificial-intelligence bubble
At one point on Monday, Nvidia was down more than 7 per cent and the Magnificent Seven lost more than US$500-billion in market capitalization
Just out! New paper on #EdTech with Janja Komljenovic & Sam Sellars: "Turning universities into data-driven organisations: seven dimensions of change"
#datafication #HigherEducation #data #assetization #universities
https://link.springer.com/article/10.1007/s10734-024-01277-z
Turning universities into data-driven organisations: seven dimensions of change - Higher Education
Universities are striving to become data-driven organisations, benefitting from data collection, analysis, and various data products, such as business intelligence, learning analytics, personalised recommendations, behavioural nudging, and automation. However, datafication of universities is not an easy process. We empirically explore the struggles and challenges of UK universities in making digital and personal data useful and valuable. We structure our analysis along seven dimensions: the aspirational dimension explores university datafication aims and the challenges of achieving them; the technological dimension explores struggles with digital infrastructure supporting datafication and data quality; the legal dimension includes data privacy, security, vendor management, and new legal complexities that datafication brings; the commercial dimension tackles proprietary data products developed using university data and relations between universities and EdTech companies; the organisational dimension discusses data governance and institutional management relevant to datafication; the ideological dimension explores ideas about data value and the paradoxes that emerge between these ideas and university practices; and the existential dimension considers how datafication changes the core functioning of universities as social institutions.
Ben Waber
Thomas Ekman Jorgensen