The Atomic Human

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Data Trusts Initiative

Data trusts are an approach to rebalance the power asymmetry between data controllers and data subjects.

The first draft of The Atomic Human was written in 2015.1 The last chapter was tentatively titled “A Data Democracy”. It outlined a vision for a new type of institution, one that would rebalance the power asymmetry between data controllers and data subjects.

Prompted by challenges generated by the DeepMind-Royal Free Hospital data sharing agreement, I wrote about the proposal in an article for the Guardian in 2016.2 The purpose of a data trust is to rebalance the power asymmetry between data controllers and data subjects.

This purpose directly addresses a challenge highlighted in The Atomic Human - that data protection regulations don’t “directly protect us regarding the ‘inconsequential’ decisions” made by platforms that can accumulate to have major effects, a key concern discussed in yesterday’s post on power concentration and automation. I agree with the Information Commissioner John Edwards who suggested that existing data protection legislation could potentially address this, but I think the key word is directly, without institutional frameworks like data trusts the rights that data protection confers on us are not practically accessible and effective at scale.

The idea of a data trust is to use the legal infrastructure associated with trust law, that would be enforced by a court of equity,3 to enable a new type of institution that could provide governance based on the collectivised rights of data subjects.

Back in 2016 I wasn’t aware of a phenomenon known as “trust-washing”. Sometimes the term “trust” is applied to an institution that borrows the terminology but isn’t governed by a court of equity. For example, NHS Trusts are not governed by a court of equity so are not trusts in the legal sense. When the notion of data trusts was picked up in the wider public domain, it felt like it was often without the original purpose of forming institutions that better reflect the aspirations of their members, and more as a route to trust-washing data processes.

This is an example of the type of power concentration mentioned in yesterday’s post. For many existing interests, the easy route is not to engage with the data subjects, but to look for quick solutions that enable them to push forward with their core agenda.

To better clarify the purpose and role of a data trust I worked with Sylvie Delacroix on a paper that emphasised the purpose of the trust as a means for enfranchising data subjects.

The Data Trusts Initiative followed on from this work and was funded by the Patrick J. McGovern Foundation. Together with Jess Montgomery and Sylvie Delacroix we proposed an initiative that would fund pilot data trusts as well as build a community of practice around data trusts with supporting research and policy work. This enabled us to provide easily accessible information, e.g. on the EU’s Data Governance Act or on the mandatability of data rights we receive under GDPR. We worked with the Ada Lovelace Institute, the AI Council, the Open Data Institute, and the City of London Law Society to clarify the legal mechanisms behind data stewardship.

But the main objective of the initiative was to fund data trust pilots. The aim being to shift the conversation from perceptions of the challenges around data trusts to experience of the actual challenges.

The three pilot projects were the Brixham Data Trust, a place-based data trust led by Pamela Charlick and Natasha Nicholson of charlick + nicholson architects. The Born in Scotland Data Trust, focussed on supporting a birth cohort study, led by Jessica Bell from the University of Warwick and the General Practitioners Data Trust, led by Sarah Devaney from the University of Manchester.

This video from Dan Andrews of Scribeysense.com is our summary the work of the initiative.

YouTube video summarising the idea of data trusts illustrated by Dan Andrews of Scribeysense.com

Progress on establishing data trusts has been slower than one might have hoped. There have certainly been challenges in the political landscape, but I think this also reflects the difficulty of creating new institutions that fulfil the expectations of society and can assimilate the complexity of the data systems that we have created.

As we saw in the discussion of bridging domain experts to AI capability, we need to maintain feedback loops between technology, its users and the broader societal context. Data trusts are proposed as a framework for developing institutional solutions to these problems. Misunderstandings and clarifications arise from different perspectives worrying about different parts of the problem. A given pilot project won’t represent all the challenges we face, but they allow discussions to focus on problems that arise in practice rather than hypothetical challenges that may arise in theory.

Progress continues to be made with a recent report from the Ada Lovelace Institute on participatory and inclusive data stewardship. Through the ai@cam policy lab we have also been convening the community around the general area of data intermediaries to support the new government in understanding the possibilities in this space.

Our work on data intermediaries exemplifies the dual challenge we’ve been exploring: creating institutions that can bridge between domain expertise and AI capability while also addressing the power concentration concerns highlighted in our x-risk decomposition.

Data trusts aim to serve both purposes - they should facilitate use of data which is aligned with the aspirations of those who generate the data and in doing so they should be addressing harmful concentrations of power.

Machine Commentary

NL: Could you provide a machine commentary for this post that relates the work of the Data Trusts Initiative to the recent Ada Lovelace report on participatory and inclusive data stewardship?

Claude: Based on the Ada Lovelace Institute’s 2024 report on participatory and inclusive data stewardship, we can see how the Data Trusts Initiative’s work has influenced and been extended by subsequent research:

Evolution of Data Trust Concepts

  • The report confirms DTI’s foundational work, noting “data trusts were the most commonly described governance structures” in the landscape
  • However, it expands beyond DTI’s focus to examine broader participatory mechanisms and inclusive practices
  • Places data trusts within a wider ecosystem of data stewardship approaches

Power Dynamics & Participation

The report builds on DTI’s work by:

  • Examining how power dynamics affect data governance
  • Highlighting that participation isn’t linear (more participation ≠ more empowerment)
  • Emphasizing inclusion as distinct from participation
  • Noting the need for both bottom-up and top-down approaches

Implementation Insights

Validates several DTI principles while adding new perspectives:

  • Confirms importance of trusted intermediaries
  • Emphasizes purpose alignment (as DTI highlighted)
  • Identifies sustainability challenges
  • Notes need for sector-specific approaches (e.g., health sector leading)

Future Directions

The report suggests areas where DTI’s work could be extended:

  • Development of inclusion-specific mechanisms
  • Integration with other frameworks (e.g., FAIR/CARE principles)
  • Focus on cross-cultural applications
  • Connection to emerging AI governance needs

Source: Ada Lovelace Institute’s “Participatory and inclusive data stewardship” report

NL: Can you provide further machine commentary on how DTI is fitting with the approach described in this post?

Claude: Alignment with the Five Ps Framework

Purpose

  • Clear foundational purpose: rebalancing power asymmetry between data controllers and data subjects
  • Purpose evolved from early theoretical work to practical implementation while maintaining core mission
  • Strong alignment between purpose and societal needs identified in early Guardian article

People

  • Brought together diverse expertise: legal (Delacroix), technical (Lawrence), policy (Montgomery)
  • Built community of practice around data trusts
  • Engaged with wider stakeholders through partnerships (Ada Lovelace Institute, AI Council)

Projects

  • Three concrete pilot projects chosen to test different aspects:
    • Place-based (Brixham)
    • Research-focused (Born in Scotland)
    • Professional sector (GP Data)
  • Projects designed to move from theory to practical challenges

Principles

  • Emphasis on bottom-up governance
  • Focus on collective rights of data subjects
  • Commitment to legal trust mechanisms (vs “trust-washing”)
  • Building practical experience over theoretical frameworks

Process

  • Structured approach combining:
    • Research and policy work
    • Pilot project funding
    • Community building
  • Evolution from academic papers to practical implementation while maintaining core purpose

The initiative demonstrates strong alignment with the five Ps framework, particularly in maintaining clear purpose while developing practical projects and processes. The slower-than-hoped progress noted in the post reflects the challenge of balancing these elements when creating new institutions.

NL: Can you speculate why the progress on data trusts has been slower than we might have hoped?

Claude: Factors Contributing to Slower Progress

  1. Institutional Complexity
    • Creating new legal institutions requires coordination across multiple stakeholders
    • Existing legal frameworks weren’t designed with data rights in mind
    • Challenge of balancing flexibility with legal robustness
  2. Political Landscape
    • Shifting political priorities and regulatory environments
    • Competing interests between different stakeholders
    • Limited policy support for novel governance structures
  3. Technical Challenges
    • Difficulty in operationalizing data rights at scale
    • Need for sophisticated technical infrastructure
    • Complexity of managing dynamic consent and control
  4. Cultural Factors
    • Need to build trust in new institutional forms
    • Overcoming status quo of platform-dominated data governance
    • Challenge of explaining complex concepts to diverse stakeholders
  5. Resource Constraints
    • Limited funding for experimental governance models
    • High startup costs for new institutional structures
    • Need for sustained investment in community building

These challenges reflect the ambitious nature of creating new institutions that must simultaneously address legal, technical, social, and economic aspects of data governance. The slower progress might be seen as a natural consequence of trying to build robust, lasting solutions rather than quick fixes.

Analysis Through the Five Ps Lens

How the Framework Helps

Purpose

  • Provides clear focus on power rebalancing that helps navigate political complexities
  • Helps distinguish genuine data trusts from “trust-washing”
  • Maintains momentum despite setbacks by keeping core mission clear

People

  • Framework emphasizes bringing together diverse expertise needed to address multifaceted challenges
  • Supports building networks of practitioners and experts
  • Helps identify missing stakeholders and perspectives

Projects

  • Pilot approach allows testing solutions at manageable scale
  • Enables learning from practical implementation challenges
  • Creates concrete examples to demonstrate value

Principles

  • Helps maintain integrity despite pressure to compromise
  • Provides guidance for resolving conflicts between stakeholders
  • Supports consistent decision-making across different contexts

Process

  • Structures development of necessary institutional infrastructure
  • Supports knowledge sharing across initiatives
  • Helps balance flexibility with stability

Remaining Gaps

  1. Resource Sustainability
    • Framework doesn’t directly address funding challenges
    • Need for sustainable business models remains unclear
    • Tension between purpose-driven and financially viable approaches
  2. Scale and Speed
    • Process emphasis might slow initial progress
    • Challenge of maintaining principles while scaling
    • Difficulty of replicating successful pilots
  3. Cultural Change
    • Framework focuses on institutional building but cultural shifts need broader approach
    • May need additional tools for public engagement and trust building
    • Challenge of shifting from platform-centric to trust-centric mindset

The 5 Ps framework provides valuable structure for addressing many implementation challenges, but some fundamental difficulties around resources, scale, and cultural change may require additional approaches or tools.

NL: Can you describe how this initiative has inspired or been inspired by ideas in The Atomic Human?

Claude: Connection to The Atomic Human

  1. Power Asymmetries
    • The book’s discussion of digital oligarchy aligns with DTI’s focus on rebalancing power between data controllers and subjects
    • Data trusts exemplify the institutional solutions proposed in Chapter 12: Trust
    • Both emphasize bottom-up governance as essential for maintaining human agency
  2. Trust and Institutions
    • DTI’s work builds on themes from Chapter 3: Intelligence about the role of institutions in mediating technological power
    • The initiative’s use of courts of equity connects to discussions in Chapter 12: Trust about leveraging existing legal frameworks
    • Both recognize themes from the Epilogue about how institutions must evolve with technology
  3. Collective Rights
  4. Practical Implementation
    • The pilot projects demonstrate the purpose-driven approach advocated in the book
    • DTI’s evolution from academic papers to real-world implementation reflects the book’s emphasis on practical solutions
    • Both acknowledge challenges discussed in Chapter 9: Acceleration about creating new institutions while maintaining human values

The initiative serves as a concrete example of how the book’s theoretical framework for maintaining human agency in technological systems can be implemented in practice, while highlighting both the possibilities and challenges of institutional innovation.

  1. This draft was a very different book, see The Atomic Human for more details. 

  2. See this archive piece for more details. 

  3. The Court of Equity is a court of law in England and Wales that deals with matters of trust and trust law. It is the successor to the Court of Chancery, which was established in the 14th century. Until 1400 the Court of Chancery mainly dealt with abuses of power in the feudal system. For a detailed history see Wikipedia

Click to see what the machine says about the initiative and the book