Data Intermediaries

Exploring Data Intermediaries as Infrastructure for a Human-Centric Data Economy: Speculations & Critical Reflections

My Roles
Second Author
UX & Visual Design
Concept Ideation
Personal Data
Speculative Design
Design Fiction
Data Agency
Data Privacy

Tensions with the current Data Economy

Through participating in our contemporary digitally-mediated society individuals are often surveilled where data is generated about them that is analyzed and aggregated to create computational models of their everyday habits, desires, anxieties, and wellbeing [1]. Once data about an individual has been generated, they have little meaningful control over how it is used [6,7]. there is a critical need for more diverse approaches to conceptualize the roles, agencies, and potentialities that should be afforded to people within the data economy.

⚪ Problem
Little is known about how data intermediaries could or should be designed and the new forms of data-driven services that they could give rise to.
◉ Research Question 1
In what ways can data intermediaries increase personal agency for individuals and social groups in everyday life?
◉ Research Question 2
What services might be enabled through data intermediaries, and how could they encourage participation in a more human-centric data economy?
◉ Research Question 3
What potential benefits, tensions, and consequences exist in this emerging design space?

What are Data Intermediaries?

Data intermediaries (DIs) mediate data exchanges between an individual, a source of data, and a data user to ensure equitable, more transparent uses of personal data [2]. They offer individuals more control over what data is collected and how it is used; would afford the agency to stop the flow of data and even to request the deletion of previously shared data; and, importantly, open up opportunities to re-use the data about them in new ways [3].

↑ A data intermediary mediating the data flow between a data source, a wearable fitness tracker, a data user, and a fitness tracking application.

Our Definition of Data Intermediaries

As interaction designers and HCI researchers, we approach data intermediaries from the perspective of the end user. We interpret and define data intermediaries as:

  • A digital service that mediates the flow of personal data between an individual, and service or entity that uses personal data.
  • The data intermediary holds a duty of care over the user’s data and is beholden to their desires for fair use.
  • For the benefit of both individuals and data users, data is verified and authenticated.
  • An individual has the ability to choose between one or more data intermediaries, that have different specializations and foci.
↑ Different specializations of DI's

Design Research Process

Our approach unfolded over two years, as the research team engaged with:

  • An ongoing review of literature on data intermediaries and a human-centric data economy.
  • An exploration of the related areas of privacy, data policy, data activism, and surveillance capitalism.
  • A hands-on exploration of current data intermediary services.
  • And the development of design fiction proposals that shaped a design space for data intermediaries in a human-centric data economy.

Proposal 1: Data Enricher

This proposal presents ways that individuals can enrich their personal data to manifest what they perceive as a more authentic representation of their current interests and future desires.

  • What would it mean for individuals to directly participate in replacing inferred data about themselves with their own truths?

This proposal addresses the tension between the commercial interests of tech corporations (i.e., YouTube, TickTock, or Instagram) vying for an individual’s attention with hyper-personalized recommendation algorithms and an individual’s agency to take ownership over what they are exposed to.

Proposal 5: University Admission

This proposal responds to the current practice of universities surveilling and purchasing data about potential students during the application and recruitment process [4], to speculate on how data intermediaries might provide more agency to individuals in these vulnerable positions.

Proposal 7: University Admission

Moving beyond how data intermediaries may bring value to an individual, our process led us to explore how personal data might be shared to bring value to a community. Data altruism has been characterized as the consent regarding an individual for the use of their personal data to benefit communities and society [5]. This proposal moves beyond this to formalize an example of how data intermediaries could support data altruism, by showing how individuals might donate data to a local social enterprise.

  • In the current data economy, the same data that is described in this proposal is extracted from individuals surreptitiously, without their consent, or in exchange for the use of a service.
  • In a possible near future, would it not be preferable to agentically share this data with a cause one might support?

↓ Check out the full Publication


  1. Pam Briggs, Elizabeth Churchill, Mark Levine, James Nicholson, Gary W. Pritchard, and Patrick Olivier. 2016. Everyday Surveillance. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA ’16), Association for Computing Machinery, New York, NY, USA, 3566–3573. DOI:
  2. J Langford, A Poikola, W Janssen, V Lähteenoja, and M Rikken. 2020. Understanding MyData operators. MyData Global. Retrieved from
  3. Jaron Lanier and E. Glen Weyl. 2018. A Blueprint for a Better Digital Society. Harvard Business Review. Retrieved February 15, 2022 from
  4. Douglas MacMillan and Nick Anderson. Student tracking, secret scores: How college admissions offices rank prospects before they apply. Washington Post. Retrieved January 12, 2022 from
  5. Marianne Bårtvedt van Os, László Bencze, Peter Bezzegh, Antal Bódi, István Csizmadia, Nanna Alida Grit Fredheim, Željka Gluhak, Zdeněk Gütter, Andrija Hermanović, Saara Malkamäki, Tatjana Pavešković, Marja Pirttivaara, and Kornél Tóth. 2021. Presentation of a first set of data altruism definitions, use cases and findings. The Joint Action Towards the European Health Data Space (TEHDAS). Retrieved from◊
  6. Shoshana Zuboff. 2015. Big other: surveillance capitalism and the prospects of an information civilization. J Inf Technol 30, 1 (March 2015), 75–89. DOI:
  7. Shoshana Zuboff. 2019. The age of surveillance capitalism: The fight for a human future at the new frontier of power. Profile books.
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