Tim's Blog

[Summary: another occasional cross-post of my Connected by Data weeknotes]

I work three days a week for Connected by Data. Outside that, as well as parenting two active under 10s, over the last few years I’ve been trying to get more involved in my local community, whether supporting democratic engagement delivering leaflets or wrangling data for Stroud District Green Party, helping out as a Parent, Teacher & Friends Association (PTFA) member and parent-governor at my child’s school, or joining the board of Create Gloucestershire, a county-wide non-profit with a mission to expand access to arts, culture and creativity.

In the last few months I’ve been struck by how often data governance issues have been coming up in these roles – and how rarely it has been possible to resolve those issues simply with the conceptual tools to hand in the form of GDPR, or a data protection policy.

In work time, a lot of the conversations I encounter about rethinking data governance focus on relatively large-scale interventions: like establishing new institutional forms (data trusts, co-ops etc), or changing policy to better regulate big tech. However, the idea that we are ‘connected by data’ can perhaps also apply very productively to everyday data governance.

To look at just two examples:

Class WhatsApp groups

My phone regularly pings with alerts from the WhatsApp group setup by parents of other children in my son’s class. Most classes at the school have a group like this. These informal, unofficial groups provide a stream of information and interaction: from questions about PE day or school trips, to confirming the week’s homework spellings, and sharing news of events.

When I was at primary school 30 years ago, this information might have been flowing as parents waited in the playground for school pickup. But, today, whether we’re all still standing a little future apart after COVID lockdowns, or because changing family structures and after school clubs mean there isn’t a common cohort of parents that meet each afternoon, the natter networks are somewhat broken, and platform-mediated WhatsApp groups are filling that gap.

This raises some challenges. Last week I got an e-mail from ClassList, the school-based social network, highlighting a legal opinion they commissioned that suggests school-based use of WhatsApp groups may not comply with GDPR. The fact that joining a WhatsApp group shares phone numbers, and some might be excluded if groups are the only formal route for sharing information, are amongst the concerns they raise.

Invoking GDPR might be a good marketing strategy to encourage risk-averse schools to adopt a platform that promises to ease compliance – but it converts a set of questions about how best to support communication and connection between families, into one about data controllers, notice, consent, and individual privacy controls. And in practice, questions of inclusive communication, and understanding the needs of different families, are likely to remain unaddressed.

Instead, I wonder how we might create light-weight models for conversations that allow the ad-hoc collectives convened, for example, in a WhatsApp group, to explore the norms and behaviours they want to jointly operate by, and the data governance (small d, small g) implications of those choices. For example, a set of conversation prompts might cover:

• What do we want this group to be here for?
• What impact does the information shared here have on others? On teachers? On students?
• What is it ok, and not-ok to share in this space?
• Should we move to another platform (e.g. Signal) that has more privacy-preserving features?

I’m not sure how starting a conversation like this would be received – and what other resources (e.g. background explainers etc.) might be needed to support a meaningful conversation. But it is the kind of discussion of platform data governance in the everyday that I think we need to be having alongside the big picture work to secure better platform defaults. Perhaps a bit of action research is required.

Catalysing creativity

On Wednesday I had a meeting of the board working group on data for Create Gloucestershire (CG). The group was set-up to support CG, as a small non-profit infrastructure organisation, to make better internal use of data and to catalyse good data practice amongst partners. GDPR was on our agenda this week, triggered by a need to work through the NHS Data Security and Protection Toolkit as part of new work with the NHS.

However, it quickly became clear that the conversation was not just about protection of personal data. Instead, it was also about a sense of data extractivism, and the feeling that voluntary sector organisations risk ending up in the middle of processes that capture data from communities, but that don’t provide insights or identified benefits in return. And it was about making sure data practices were the right-fit, applying strong protections to sensitive data, but not inhibiting sharing of community-level insights, or co-operative working on non-personal data. I was struck that, although the CG team introduced the item with questions about GDPR compliance, the language used to talk about what practices to encourage or require from partners, was much more a language of community, capacity building and collective responsibility.

The conversation ended with the idea for a local data unconference, to create a space that could both share practical data security and data management skills and give practitioners greater confidence in handling data at the individual level, at the same time as building a stronger collective voice amongst voluntary sector organisations to talk about how to data collection and sharing could work for them.

Just as the individuals whose lives are captured in the same dataset, or whose choices are shaped by its analysis, are connected by data, so too are organisations reporting to the same funders, or operating in policy landscapes governed by the same centralised metrics. If these organisations can find common voice, then there may be opportunities to shape more equitable data infrastructures that more effectively deliver the public good.

I took the idea of this unConference to Jeni and Jonathan at our regular check-in on Thursday, and they liked it. So I’m hoping to work with the CG team in the next few weeks to work up the idea more. If you might be interested in collaborating too – as a co-host, sponsor or attendee of a data-focussed day-long unconference in Gloucestershire, do drop me a line!

[Cross-posted from Connected by Data blog]

Well, as Jonathan said but two weeks ago, a week’s a long time… Just as we thought ministerial mayhem might mean we had a bit longer before the ‘Data Reform Bill’ (DRB) would be out, on Monday this week the ‘Data Protection and Digital Information Bill’ dropped (DPDIB) revealing not only the new name, but the scope, for the DRB. We’ve got a team retreat next week where we’ll be digging into the detail of the Connected by Data response, but suffice to say that, right now, collective impacts and public voice do not feature as strongly as we think they could and should.

As I skipped writing up weeknotes last week, a couple of different themes to reflect on this time around, and lots of assorted extra bits.

Digging into dialogue

One of the big challenges in seeking to embed participatory mechanisms for data governance into legislation, is that there is a big risk of creating yet-another-tick-box and ending up with low quality compliance-oriented engagement, rather than transformative forms of participation.

Over the last three weeks I’ve been an observer of the NHS AI Lab Public Dialogue on data stewardship: a process involving around 50 members of the public meeting for 12 hours (across four sessions) to share their ‘thoughts, aspirations, hopes and concerns’ about how access to healthcare data for AI purposes should be managed. I’ve got a full write up in the works, but it’s been a really interesting opportunity to watch a ‘dialogue on dialogue’ as members of the public explored different models for public engagement in governing access to health data.

I’ve also been trying to read up more on the history of public dialogue, as our expression of interest in partnership with OpenSAFELY to the RSA Rethinking Public Dialogue fund has made it through to the second round of bidding. Here’s the one paragraph summary of what we’re trying to develop:

“Connected By Data and OpenSAFELY will collaboratively develop a protocol for ‘dialogue on demand’: agile and inclusive mini-dialogues on data governance and research design decisions that are developed based on bottom-up input from affected groups, and that feed into both iterative data governance process refinement, and into focussed operational decision making.”

Plus, I had the opportunity last week to sit-in on a training delivered by Simon Burral of Involve for the Data Trusts Initiative on governance and engagement design.

All this has been really useful for starting to think about the different factors that might help deliver the ‘powerful say’ for data-affected communities that we’re calling for. For now, I’ve captured this as an opinionated statement on what meaningful and effective participation looks like:

Generally the more concrete the issue or situation that discussion can focus on, and the more ‘moving parts’ of that issue/situation that can be made legible to participants, the more meaningful the discussion is likely to be. And the more that points made in a discussion can be grounded in relatable lived experiences, the more powerful the messages from a discussion are likely to be.

Sector specifics

Over the last fortnight Jonathan and I have been round a few loops of trying to articulate simple (hypothetical) stories of how current data practices affect real people in our target sectors (debt; housing; education). It’s proven (surprisingly?) challenging to articulate the narratives for debt in short prose, I think for a number of reasons:

• I’ve been trying to focus on present problems rather than future fears. Reports like the fantastically useful Governing data and artificial intelligence for all: Models for sustainable and just data governance arguably have an easier job of it by looking primarily at (reasonably) imagined future AI harms, rather than quantified current harms.
• In many cases, I’ve been finding that present problems are covered by regulation in some form, even if the data component of the problem has limited governance. For example, we started looking at targeted loan advertising, but find that industry self-regulation has led to voluntary action not to take adverts from payday lenders. This limited governance at the application layer doesn’t remove the issue that data is collected, pooled and shared that could be used to target people with risky financial products, although it means that right now this harm isn’t generally observed.
• There are multiple stages, and multiple actors, in any story of how people are Connected by Data. Where I started by trying to present stories of single named individuals, I’ve now been experimenting with sketching scenarios with visual representations of the data flows that connect people, and that raise data governance questions.
• The data problems are often indirect. Jonathan did some great work developing problem trees for debt and data; demonstrating that there are a couple of steps between the abuse of data, and the ‘crunch’ of relatable harms. Those ‘harms’ are even trickier to land when they are the absence of actions (e.g. missing data-supported provision of support to someone in debt).

It’s feeling like (a) it might be a few more iterations before we land really clear example stories for each sector; (b) like we might be discovering some of the challenges with getting robust stories to land in the debt sector specifically. I’ll be looking next week at whether this means we should revisit some of our focus sector selection.

Reading and reflections

Critical data studies and outsider action

I skimmed through a fantastic new Critical Data Studies Reading List from Frances Corry and colleagues that is focussed on papers that critically explore the data pipeline for machine learning. I’ve found lots of background reading to add to my own backlog of papers to hopefully get to reading over this summer, but was also looking out for any papers that might hint towards a participatory response to the many problems in the AI data pipeline. The few that did jump out could be said to take a more or less an outsider advocacy approach: representing voices and perspectives from populations affected or harmed by the data choices of an AI system to highlight they were not considered in the initial dataset selection or design. Such advocacy has led, in a number of cases, to significant AI training datasets being withdrawn or substantially modified.

I’ve been reflecting on how such independent and outsider activism is a key part of a spectrum of participation: able to set the agenda for discussions in more formalised participative spaces, and to hold those spaces to account for their outcomes, to provide a check on corporate capture of participatory processes. There’s more to think about here, but it’s also worth explicitly noting that more formalised participation of groups affected by AI systems in dataset governance did not appear (at a read of titles / abstracts) to be part of the repertoire of solutions being put forward by researchers in the ML community covered by this particular reading list.

Legislating data loyalty

This interesting new paper on Legislating Data Loyalty has a lot of resonances with ideas around Connected by Data, framing data loyalty as made up of three key components: “a (1) relational duty; (2) that prohibits self-dealing (3) at the expense of a trusting party”

The concept felt slightly limited by restricting the duty of loyalty from a firm solely to those whose data they collect (data subjects) rather than those affected by the data (data stakeholders), but it makes for an interesting and challenging re-articulation of privacy law, with a focus on US privacy law debates.

Where the paper gets into the details of implementation (p 374) it explores an approach to dealing with “inevitable conflicts between [the interest of] trusting parties”, by proposing that firms have reference to the “collective best interests of trusting parties” although how this is to be determined is not explored. From a Connected by Data perspective, we might suggest that one way a firm can establish that it has sought to understand collective interests is through some form of robust independent dialogue with a broad cross-section of its ‘trusting parties’.

AI in the City: Building Civic Engagement & Public Trust

Lots of interesting short essays in this colloquium collection from Ana Branduescu and Jess Reia including points on the importance of power, doubt, open processes and voices of the marginalised when governing the introduction of technology into the urban setting.

Other things from the fortnight

Filed under ‘listing out stuff mainly so I don’t forget it’, and just in case it sparks a useful connection anywhere…

• I did some work this week on potential metrics and measurement tools aligned with our theory of change, looking at the outputs, outcomes and impacts we might want to track.
• I shared some feedback with colleagues at Research ICT Africa for a paper looking at African perspectives on data trusts and other collective data governance mechanisms.
• I’ve reviewed a couple of papers for Data & Policy
• I took part in an Institute for Government roundtable discussion on Data sharing during the pandemic and the confusingly named GPDPR (which, it turns out is just the start of the confusion…)
• The Data Values Project has published their final white paper on Reimagining Data and Power which we shared some input on earlier in the year. It also includes a good example of showing how consultation has been taken into account with a table of changes in response to feedback.
• Our proposal for a session on Collective Data Governance at the 2022 Internet Governance Forum was unfortunately not selected. I’ll be looking for other venues where we might take this conversation forward.

[Cross-posted from Connected by Data blog]

A bumper two-week weeknotes today, as I was travelling last week (delightful Rail+Sail journey over to the Netherlands for a workshop with The Land Portal and Eurostar back for my first international trip in more than two years).

Researching collective narratives

The first thing to share is that I’ve just posted a call for a contract researcher (or team) to help us map out existing cases and media stories that talk about the impacts of data with a collective lens. We’re looking for an individual or team who can work between August and October searching out relevant stories (in focus areas of health, housing, debt and education), and build a framework for analysing how they address the collective dimensions of data impact.

The idea for this broad piece of mapping work came from our team day on Monday, where we looked at our current plans to commission a series of stories that help land the point that data needs to be governed collectively, rather than solely through individual consents and controls. We identified the need to both track down existing stories that we might amplify, and to understand more of how a collective lens is currently being adopted in popular stories about where data is being used or abused to help or harm communities.

Building a more diverse network

We had some discussions over whether to just reach out to researchers we know for this project, or whether to run an open call. The deciding factor was that we have a better chance of reaching a more diverse network of potential researchers with an open call, so, drawing on the fantastic guide Gavin Freeguard developed for MySociety on commissioning research we put together the full CfP and an application process.

We’ve setup the application form both for this particular opportunity, and to allow people to opt-in to being part of a ‘research pool’ we could draw on in future, and we’ve included a question that can help us to, when other factors are equal, to prioritise applications that help us use our position and privilege to help increase the diversity of the data policy field.

Are you a member of a community that is under-represented in work on data, digital and AI in the UK and Europe, and if so, how?

We are asking this question because we are particularly keen to work with a diverse and inclusive network of partners. Please only provide details you are comfortable with sharing.

I’ve also, alongside the obligatory data processing consent statement, included an experimental ‘collective data governance’ question. After all, people will be taking time to submit their information to this form, and might have ideas for what more they would like to see done with it.

I have no idea what this will generate, if anything: but it will be interesting to see if it triggers any interesting ideas and responses.

Narratives and frames

As background to prepare the CfP, I spend some time going through an interesting paper from Skurka, Niederdeppe and Winett called ‘There’s More to the Story: Both Individual and Collective Policy Narratives Can Increase Support for Community-Level Action’ which uses an experimental design to explore whether individualised or collective narratives about food deserts, and narratives framed using left (equity) or right (loyalty) based language were more likely to solicit support for policy proposals based on a Social Determinants of Health (SDH) model. They present a detailed theoretical case for thinking through individual and collective storytelling, and mapping mechanisms such as identification, empathy, transportation, hostility and counterarguing that shape how an audience processes a story into policy support.

They highlight the concerns that “telling stories about individual cases – even when emphasising system and policy-level solutions- may inadvertently reinforce beliefs about personal responsibility for health, thereby undermining public willingness to support community-level efforts to address factors in the environment.”, although their experimental evidence does not appear to bear out this concern.

They also outline the distinction between narrative frameworks (which include a setting, characters, plot and moral), and message framing (the particular aspects of a story that are given emphasis). Critically, this highlights that both narrative frameworks, and message framing, may vary in their approach to an individual vs. collective dichotomy. For example, it is possible to have a narrative centred on an individual, but where the framing draws attention to collective level issues, or it is possible to have a narrative story told at the level of the community, but that emphasises issues of individual responsibility or action.

Whilst we’ve left things fairly broad in the CfP, just giving examples of the kinds of stories we hope to find, and planning to iterate with the selected researcher on the exact approach to categorising stories, I’m anticipating we might draw on some of the approaches and learning from the Global Voices Civic Media Observatory, which has developed a workflow for sourcing and annotating media stories to uncover the different frames at play.

Dialogue, decisions and design

I put the finishing touches to our expression of interest for the RSA’s call on Rethinking Public Dialogue this week, developed along with Jess Morely at OpenSAFELY. In a nutshell, our proposal is to explore a model of ‘dialogue on demand’: agile and inclusive mini-dialogues on data governance and research design decisions that are developed based on bottom-up input from affected groups, and that feed into both iterative data governance process refinement, and into focussed operational decision making.

Many of the public dialogues I’ve been looking at while building our participation cases database take the form of large-scale engagement activities with a broadly representative population, run over multiple weeks and months. Indeed, yesterday I had my first three hours as an observer for a current NHS AI focussed dialogue, run by IPSOS with the Open Data Institute, and that’s due to have three more three hour sessions (12 hours online dialogue time in all). Our working hypothesis for our RSA proposal is that, where this kind of model may be good at establishing general principles for how data should be governed, “A streamlined protocol for responsive informed dialogue, shaped by bottom-up inputs, can provide a scalable model for public engagement to be applied to live data and research governance.”.

Our proposal explores developing/adapting methods to map out the data flows involved in particular data-rich health research studies, and the potential outputs or outcomes from research, and then using visual and text artefacts from this mapping to solicit initial input from people who might be affected by a particular study, the data it uses, or the issues it might raise. From this, having potentially found communities affected by a given set of data governance decisions, we would then design shorter focussed dialogues rooted around very concrete cases, which, we hypothesise, will be more tangible than discussions about data sharing or governance ‘in general’, even if they can generate higher-level lessons for data governance practice.

Working out, in practice, how different publics can be engaged in data governance decisions is going to be really important to our work in the coming year, and is a piece of the work I’m particularly excited about.

We’ll hear more in the next few weeks about whether we can take this particular idea forward to a full proposal for the RSA, or whether we might need to find other ways to take it forward.

The intersection of data and AI governance

I’ve still got an outstanding task of trying to map where data and platform governance intersect, but this week I’ve been looking a bit more at how current work on data and AI governance might connect. Key to that was reading the new paper “Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem” from Sasha Constanza-Chock, Inioluwa Deborah Raji, and Joy Buolamwini (who, as an aside I must note, are each some of the most inspiring, thoughtful and engaged scholars and humans anyone could hope to learn from). It has a number of useful insights for our thinking about the potential to embed collective data governance into organisational practice.

In their interviews with ten leading algorithmic auditors, and a survey of more than 150 people connected to algorithmic audit, they find significant gaps in the involvement of affected stakeholders in the algorithmic audit process, with just 30% of auditors saying that consider real-world harm to stakeholders when auditing algorithms, and only two providing examples of this. As a result, Sasha, Deborah and Joy recommend that_ “It should be a priority for regulators to ensure that audits include affected stakeholders, and for organisations to establish internal policy that promotes direct involvement of the stakeholders most likely to be harmed by AI systems.”_ going on to argue that, whilst participatory practice can be messy, “Solutions should be informed by the existing field of participatory design, and by the growing community of design justice practitioners, and should be supported by a field-wide investment in strategies to meaningfully engage community partners and support community-led processes for algorithmic accountability.”

The paper also describes some of the challenges that internal (first-party), or contracted (second-party) teams involved in algorithmic audit face, in terms of resistance of organisations to engaging with audit processes that might lead to a need to change profitable practices, or restrictions on making audit findings public. This resonates with themes I’ve found in Waldman’s Industry Unbound, around the way in which corporate structures can significantly inhibit the freedom of workers to insert public interests into private enterprise, and points to some of the significant challenges that efforts to embed collective and participatory models of data governance will face.

I’ve also got a few other FAccT papers on my reading list thanks to Catherine D’Ignazio’s fantastic thread that picks out a number of the key findings. In particular, as we explore the point in our Theory of Change (update on that coming soon) that addresses developing a community of practice, this piece on tech worker organising looks particularly important to consider.

Learning to govern

The last two Monday evenings I’ve been undertaking mandatory online training as a new school parent governor at my son’s school. In the UK, over a quarter of a million people volunteer as school governors, taking on a strategic and oversight role for finance, staffing and school development. The training, unsurprisingly, was heavy on running through all the processes and practical activities of governance: from making and writing up school observation visits, to plotting a calendar of policy reviews and a cycle of meetings setting and tracking progress against improvement plans. We also spent some time exploring the different structures of governing boards depending on the type of school (local authority, foundation, multi-school trust etc.), and the different kinds of governor (some appointed by parents, others by the local authority or trust, others from the staff body etc.).

Of course, school governance is very well established, and models have, more-or-less, settled into place (albeit with constant government reforms leading to updates and changes). But reflecting on this day-to-day bit of the national governance infrastructure, and it’s strengths and weaknesses in practice (in the break-out sessions there was a bit of opportunity hear from other governors about how well the theory presented in the training represents the reality in their schools), has me wondering what sort of scale and structure collective data governance at scale might take? Do we need 1000s of people on standing structures, with robust training and development programmes in place, to govern our shared data infrastructures? Or is collective data governance most often going to be a ‘function’ that fits into existing governance structures? Or are there new models entirely that can take the best of new technical approaches, while remaining inclusive, accessible and accountable?

Perhaps, most importantly, the training, and my recent conversations with other people who have experiences in school governance, highlight that governance in practice is, of course, about people. Personalities, a desire of a group to ‘get on’ and a recognition of the need to support resource-constrained teams, can all both help governance work well, and, at the same time, create barriers to effective scrutiny and accountability.

Other things

• Thanks to a kind invite from Asaf Lubin, I was on a Datasphere panel for the American Society of International Law last week, where our discussions touched on the interaction between agile regulation and public participation, and the need for data policy built on new narratives that understand the global and cross-boundary nature of contemporary data.
• For a couple of freelance projects with organisations that have defined their strategies around open data, I’ve been trying to write about some of the big trends of the last decade that have been reframing openness. I’ll hopefully have that in a blog post form soon.
• We had a team meeting day in Reading, which is written up in other’s team notes, and for which I spent some time digging into consultation responses to the Data Reform Bill (thanks to Peter Wells for this super helpful spreadsheet).
• I’ve been working on updates to our sectoral scoping on debt, again hopefully with more to share soon.
• I managed to follow most of the launch event for the Education Data Reality report from the Digital Futures Commission while on the train back from Amersfoort (super reliability of Dutch 4G) – which was packed full of useful insights to feed into our scoping of work on education as a sector. In short, there are a lot of questions to ask about how education data is being gathered and used, without a lot of good oversight right now (Note to self: explore whether the school governing board thinks about this at all!)

[Cross-posted from Connected by Data blog]

There are a couple of themes that have run through this week that I’ve been trying to reflect on for this week’s weeknotes. The first of those is around the role of narratives and imagination, and the second, on approaches to legislating around data protection and sharing.

Narratives and imagination

Over the last few weeks I’ve been reading Ari Ezra Waldman’s Industry Unbound which provides an account of how even strong privacy advocates within the technology industry become co-opted into serving the goals of data-hungry corporations. This occurs through the reframing of privacy in terms of security, and the articulation of compliance regimes that sidestep substantive privacy issues and instead cast privacy narrowly in terms of transparency/notice and consent. Ari’s account argues that the policy space for thinking about meaningful privacy practice has been intentionally eroded by corporate lobbying, and space for meaningful privacy action within firms has been shut-down by bureacratic organisational practice that means privacy practitioners inside firms are excluded from design decision-making, or downplay concerns to avoid being cut-out of future discussions.

In the context of Data Reform Bill proposals to reduce the independence (or even existence) of Data Protection Officers, and shift towards a more US framework of organisational ‘privacy programmes’, Industry Unbound feels like essential reading. I’m not all the way through yet, but I’m already taking away a deeper appreciation of the hard work we have ahead to make sure any policy proposals Connected by Data may bring forward are, as far as possible, designed with potential patterns of corporate resistance in mind, and shaped to try and protect against the risk of they are simply translated in compliance checkboxes with their force ultimately blunted.

This has got me thinking more about the importance of Connected by Data work on developing and embedding narratives that tap into a broader view of both what we mean by protecting data, and what we mean by data sharing. It’s not enough to have policies that provide the ‘letter of’ participatory data governance, if we’ve not also secured engagement with the ‘spirit’ of the proposals too.

Right now, this feels like quite an uphill task. I was struck in the Living with Data panel I attended at the Data Power conference how difficult it appeared to be for people to imagine collective control over data, and indeed, in many cases, to imagine control over data at all outside of straight resistance to data collection. In a week when the MyData 2022 conference has been talking place in Helsinki, essentially doubling-down on models of individual data sovereighty that do little to disrupt narrow data discourses, we’ve been spending some time, led by Jonathan, on the Connected by Data brand narrative. Central to this is working out how to bring the problems of current data practice more clearly into view, and thinking about ways to support clearer collective imagination about the ways community-centred data governance could transform things.

On my ToDo list for the coming weeks is to work on a blog post on ‘Questions to ask about data governance?’ to try and capture some critical tools to bring into relief the problems with the status quo (reliance on notice and consent; narrowing of both privacy and data sharing concepts; failures of transparency etc.) as a first step to then supporting exploration of alternatives. I also found it useful in preparing for the Open Futures Salon on Thursday to look at the flow-chart of data governance processes they have set-out in their proposal for future Business to Government (B2G) data sharing in Europe, and to reflect on the kinds of participatory governance that might be possible at each level.

I found the State of Open Data panel I chaired on Wednesday was also a powerful reminder of the importance of ‘re-imagination’. Where I had anticipated that our discussions might get drawn into a focus on the deficits around open data and AI, the inputs from Reneta Avilla, Jeni Tennison and Feng Gao all offered a number of points of hope around building more inclusive data futures, putting particularly emphasis on cultures of openness, and the power of openness to support collaborative and imaginative problem solving. Rather than presenting a case to ‘go back’ to the open data of old, they each offered a view of an open data landscape which has become more nuanced, and that has, in practice, adapted to a much more complex landscape of data access and use, even while overarching narratives around an open binary, and open licenses, have not been wholly updated – at least at the global level. From this point, the session started to sketch out a way forward, building on the collaborative potential of open data: something also picked up in a blog post from Leigh Dodds this week. Reflecting on this session makes me reflect on how to make sure the Connected by Data narrative is about the future of data governance, not about recapturing a lost (and fictional) past.

Legislating lists or processes

I noticed an interesting resonnance between the two bits of proposed legislation I’ve had on my radar this week. Both the EU Data Act, and the update on government proposals for the Data Reform Bill, get into the question of listing particular categories of data that might be covered by B2G data sharing, and use by firms without needing to carry out legitimate interest balancing tests, respectively. And in both cases, the process of creating such lists to ‘bake into’ legislation is problematic. Either, legislation is inflexible, or, if mechanisms are put in place (as proposed around the Data Reform Bill) for secondary legislation to add categories, then there are significant concerns about not having adequate scrutiny of new categories, and risks that corporate lobbying will be able to extend or limit data sharing and processing.

In general then, there may be case to be developed for setting out the robust participatory processes that can sit in the place of legislated lists, or at least, that can be embedded as part of the way in which lists may be extended (or indeed curtailed). I’ve more to explore on whether there is precendent in the governance innovation space for this kind of approach (ping me if you’ve got experience here and would be up for a chat!), and to work out some ideas more concretely – but it seems we should be making the case that legislation that embeds space for dialogue and participatory decision making is more likely to be able to cope with the pace of technological change, than legislation that tries, a priori, to identify all the boundaries between frictionless or barrier-encountering data use and sharing.

Other things

• I had a catch up with Michael Canare’s, where we talked a little about the Data Empowerment framework – which is something I need to dig into a bit more, particularly to explore the interaction of individual and collective empowerment around data.
• After almost two months not touching a line of code, I worked up some Google Apps Script to get project-classified data from our accounting tool, FreeAgent, into a Google Spreadsheet to help with our financial tracking and reporting. Still some tidying up to do, and then I’ll try and share a version.
• As of yet, I’ve not had any responses to the e-mails I sent last week to ask for details of company balancing tests.

Next week I’m off to Amsterdam (Monday) and Utrecht (Tuesday) for a bit of freelance work supporting Land Portal with their data strategy – but, on the off-chance, I should have a bit of time free both days if any Netherlands-based collective data governance folk fancy catching up for a chat. Let me know!.

[Cross-posted from Connected by Data blog]

It’s been a week of planning & strategising, in-between two conference and panel-heavy weeks last week and next. On that note, do join me for the State of Open Data panel on AI next Wednesday (1pm BST), and at Open Future’s first salon looking at Business to Government Data Sharing on Thursday. Plus, I’m hoping to make it along to some of the online components of the Data Power conference.

Iterating on the case database

It looks like we’re getting into a good pattern of Monday and Wednesday team meetings, which offers a mix of focus on what we need to deliver (Monday meetings with a work planning spreadsheet) and a space to reflect on what we’re learning through the week (Wednesday meetings, where I experimented this week with bringing a sketch of the case database development for team feedback).

I’ve been getting a bit stuck with working out how to move forward the work I’ve been doing to build a dataset of cases of participatory data governance, particularly working out how to align this with our wider advocacy and practice work. So, picking up on the suggestion that it is sometimes easier to brainstorm in slides than in a prose document, I pulled together a short deck outlining where I’ve got to, and providing some rough mock ups of possible ways to expose the case study research on the Connected by Data website.

Caption: Rough mock up of Connected by Data website with four ‘calls to action’ that build on the case database work.

Feedback from Jeni and Jonathan pointed to a number of useful areas to explore more, including thinking about how far we editorialise cases to highlight our opinions on what best practice is, how we might work with partners to provide a long-term home to any case and method library resource we create, and how, when allowing users to browse by methods, we clearly communicate that effective participatory governance often requires a mix of methods.

In the deck I shared a few experiments that try and get at this latter point – visually presenting the ‘structure’ of the different cases I’ve surveyed to highlight that they involve multiple related components. I had initially thought that it might be possible to generate a ‘graph’ of relationships between components, but experimenting with mermaid.js graphs (And its nifty text to graph syntax) quickly revealed that it was going to be tricky to generate elegant presentations this way. Instead, I turned to a more linear approach to showing the structure of an example case, using icons from the noun project to start to pull out relevant facts about each component of a participatory data governance case, such as whether engagement activities are one-off, repeated, or ongoing, and whether they involved a single group over time, or multiple groups.

I’m going to do some work in the coming weeks to explore engaging with a designer on a next iteration of this, helping to firm up some of the key concepts we want to communicate about getting the practice of participatory governance right.

Sector selection

As Jeni has explored in her weeknotes, we spent some time this week looking at selecting a small number of sectors in which to focus our work over the next year, settling on a shortlist of debt, education and housing. I’ve started writing up a scoping document for our sectoral focus on Debt, (incorporating consumer finance and gambling) to sketch out some of the key data governance issues, key stakeholders, and potential policy influence opportunities related to data governance. At this stage, the focus is on rapid research to validate whether or not this should be a focus sector for us, and to develop our shared understanding of the scope of the sector.

Campaign strategy

I also spent a bit of time this week talking with Jonathan about our next steps of campaign planning, and how to facilitate our next stage of work on the Data Rights Bill. More on that in the coming weeks.

Other notes

Workshop on Governing Knowledge Commmons

On Monday I dropped into an online session of the Workshop on Governing Knowledge Commons set-up for discussions of ‘half baked research ideas’ linked to smart cities and knowledge commons. There were a couple of really useful insights from the discussions, including tips from Brett Fischman on making sense of complex phenomena (like adoption of smart city technology, or, indeed, collective governance of data) through analysing in different action arenas from Macro (i.e. how is the city as a whole adopting a collective approach to data governance?), to Meso (how is work in the housing sector in the city adopting collective data governance?), to Micro (how is a particular project making use of a collective approach to data governance?).

Katherine Strandberg pointed to the particular features of the Governing Knowledge Commons (GKC) framework, as opposed to Ostrom’s commons governance work, in dealing with the fact that “knowledge commons are especially likely to have impact (positive or negative) beyond the community obviously involved in creating the knowledge”, such as in cases of patients involved in rare disease research.

In response to some of my musing on how we can use our Connected by Data case research to understand the kinds of governance appropriate to different situations, Brett offered the concept of externalities as one tool to use. Depending on the data and context in play, there may be different positive or negative externalities from data collection and use to worry about, and different kinds of governance institutions may be more or less effective at managing these.

Indigenous Data Sovereignty

Thanks to Jeff Doctor for sparing the time to chat through some of the ways Indigenous tech firm Animikii are thinking about data governance, and about some of the data (and wider) issues facing Indigenous communities. We touched on the challenge of identifying the legitimate collectives that have a role in governing data, particularly in cases where the claim of states to jurisdiction over territory and peoples remains contested, and the need to recognise the ongoing struggle that many Indigenous people face to find security, and to avoid being criminalised or marginalised through data-driven forms of surveillance and control. This brings into relief some of the challenge of designing participatory data governance approaches that engage those most affected by data use, whilst respecting that the point at which individuals and communities most experience data-based harms may be the point at which they have least capacity to engage in wider governance debates.

It was also insightful, amidst the talk that sometimes comes up around the Datasphere initiative of navigating data governance in a post-Westphalian order, to be reminded of the many Indigenous nation’s claims on land, that have long challenged the settled international boundaries taken for granted in so much work. Jeff pointed me in particular to the Land Rights statement of The Council of Chiefs of the Haudenosaunee, making a connection between data rights and land rights.

RightsCon

Building on last week’s weeknotes, I added a few bits into our write up of RightsCon which you can find here.

Visualising processes

On Wednesday I had a catch up with Mel Flanagan of Nook Studios, whose work seeks to make complex processes much more accessible through careful information design. Mel shared updates on the work they have been doing to join the dots between different open government initiatives and data silos, but we also talked briefly about ways the process-visualisations developed for this could be applied in data governance dialogue processes.

Legitimate interests research

Lastly, I ended the week by firing off a few ‘test requests’ for Legitimate Interest balancing tests from a selection of companies whose privacy policies invite users to request these.

Using the Princeton-Leuven Longitudinal Privacy Policy Dataset I’ve searched for “balancing test” and then identified a number of large websites that have text in their current privacy policies to the effect that: they process certain data on the basis of legitimate interests; they have carried out balancing tests; these balancing tests can be requested by emailing them.

Conscious of the controversy from the Princeton-Radboud Study on Privacy Law Implementation which sent simulated messages to request GDPR related implementation information to a large number of websites, triggering significant work by in-house legal teams, I’ve taken care to clearly identify in the outgoing messages that this is part of Connected by Data research work, and is not strictly a customer request, so I will be interested to see what replies, if any, we get.

This will help shape any future research work into how balancing tests are currently used, particularly relevant with the upcoming details of the Data Reform Bill.

[Cross-posted from Connected by Data blog]

These weeknotes are falling a little late, but as the Jubilee double bank holiday in the UK means it’s now a really short-week, I’ll cover two weeks for the price of one, while trying to focus in on just a few themes from the last 12 days of CONNECTED BY DATA work.

Narrative, Policy & Practice

A big focus of last week was our first team day. Besides being fantastic to properly meet my new colleague Jonathan, and have the day working face-to-face with Jeni and Jonathan, we were able to take a deep-dive into some of our Theory of Change, and to think about what it means to frame CONNECTED BY DATA as a campaign.

One of the key insights for me from the day was to more clearly articulate our position as a ‘bridge’. It’s not that there is a shortage of great thinking and experimentation out there about taking more collective approaches to data governance, nor that there is an absence of policy appetite for addressing data governance challenges. The gap to be addressed is arguably around testing, translating and communicating how data can be done differently. As Jeni has explored in her weeknotes, this involves being able to better articulate both the manifest harms from current data practices, and less tangible impacts that come from the data traces of our lives being treated as a natural resource for commercial exploitation.

I have the feeling that focussing on this bridging role will be really important to scope our future research work, and identify the kinds of activities that fit well within CONNECTED BY DATA , and those that we might support and work on with partners, but not directly lead on.

Framing governance & decision making

In a couple of conversations in the last two weeks, including a research design session with the team at Research ICT Africa, I’ve been feeling the need for a clearer conceptual map of where data governance decisions are made. In short, I’m looking to have a clearer articulation of the activities that data governance addresses (data collection, design, analysis, use, sharing, etc.), and the particular tools of governance, such as setting principles and policies, operational decision making, oversight, scrutiny and evaluation.

In thinking about what it means to make decisions more participatory, I’ve spent a bit of time looking back over my past work on youth participation: in particular a 2008 Open University Study Guide that accompanied a chapter in Leading Work with Young People. One of the study activities we included there was to ask youth workers to document every decision made as part of a recent event or session, and then to work out which were the decisions that mattered. The point was to emphasise that empowerment does not come from simply sharing every decision: but involves working out which decisions need to be shared, and what kind of participatory process there needs to be around them.

I was also struck reading Katya Abazajian’s critique of the use of Open 311 data (which, incidentally, hints at many broader issues of collective data governance) by the discussion of how the way questions are framed significantly shapes the outcomes.

We also touched on this point a little at our team day when Aidan Peppin from the Ada Lovelace Institute joined and shared insights from the public dialogues and citizen’s juries that he has been involved in. While some dialogues have led to participants adopting quite collective language for thinking about their _data, others have taken a more individualistic tone. As Jonathan has explored, some of this seems to be to do with how people feel about the _institutions behind the data. It also appears related to the framing of the subject matter being considered (health data vs. location data for example). However, I’m curious as to whether there are particular ways to sensitively offer collective language into public dialogues on data.

I had a go at thinking about this in providing some asynchronous feedback into the stakeholder group for a Data Stewardship Dialogue being run by the Open Data Institute for the NHS AI Lab, where I tried to draw out the distinction between ‘collective decision making’, in terms of decisions made by a group (but where participants may still be making their decisions based on individualism and self-interest, and the outcome might be based on simple majority voting for example), and ‘decision making for collective benefit’, where the process encourages greater thinking about our interdependence.

Building on all of this, in the next few weeks I’ll be seeking out, or sketching out, some sort of small methodological tools that might help with better mapping out and describing the detail of data governance decision making, to sharpen up how we both research existing practice, and how we frame our vision of what future policy and practice should be.

Other things

• I was left scrambling a bit on Tuesday when my main work computer, just about to be used to webcast a community meeting hosted at the lovely Stroud Brewery, had a run-in with a pint of ale. It’s at the repair shop hopefully drying out – but thank goodness for backups (apart, frustratingly, for five hours worth of data governance literature review write-up).
• I’ve submitted our proposal for a session on Collective Data Governance at the Internet Governance Forum (thanks to everyone who contributed!), and have been in conversations about a few other convening opportunities around research and policy, including chats with Christian Perone from ITS Rio, and Preeti Raghunath from Monash University.
• It was great to connect with other Datasphere Initiative fellows for our monthly meeting on Friday – where we were also hearing from Martin Pompéry of SINE Foundation on some of their work deploying both technical and organisational approaches to govern data sharing for carbon emission reporting across supply chains.
• I’ve been listening to this interview between Divya Siddarth and Douglas Rushkoff on Team Human, which offers some great insights into how tech communities are drawing on concepts of co-ops, commons and the pluriverse, including weaving it into the Declaration on the Interdependence of Cyberspace.
• I’m looking forward to being a delegate at RightsCon next week, and have been starting to put together a list of sessions to tune into over the week, as well as planning to keep my diary a bit more open for ad-hoc remote-conferencing connections.

[Cross-posted from Connected by Data blog]

It’s been a week of both thinking big about how we might, in the coming months and years, shift public and policy narratives about collective data governance, and focussing in on the details of what it might mean in practice to make data governance more participatory. In the iterative process of building out our case study database, and reviewing reports from a number of public dialogues, citizen’s juries and participatory processes linked to data governance, I’ve been reflecting on three themes, outlined under inevitably alliterative headings below.

Defaults and decisions

Skimming the Ada Lovelace review on UK Public Attitudes to regulating data and data-driven technologies reveals a fairly clear picture, and one backed up by many of the data dialogue reports I’ve read this week , that the public want to see more and better regulation of data, and expect innovative uses of data to be aligned with the public good.

At the same time, the Ada Lovelace review finds that “more research is needed on what the public expects ‘better’ regulation to look like” and ”determining what constitutes ‘public benefit’ from data requires ongoing engagement with the public”.

Having noticed that a lot of the cases I’ve gathered so far of public dialogue around data governance tend to inform, or design, fairly general principles or recommendations on how data should be handled, I’m finding it useful to think about participatory data governance on two levels:

1) How should public input shape the defaults that are in place for any uses of data?

There may be different defaults for different sectors, or potentially for different user groups (although Afsaneh Rigot’s recent report on Design from the Margins would suggest there are strong advantages in setting the overall default based on the needs of those most affected by a technology).

Not every organisation with data to govern will necessarily need to run its own engagement process to identify the right defaults: in many cases, desk research might identify clear public-backed principles to work with.

The legitimacy of any defaults may be affected by the extent to which they are derived from considering the particular impacts that a category or type of data may have, and the extent to which populations and communities affected by those impacts were part of developing the defaults.

2) What are the appropriate mechanisms for public engagement in the specific decisions that put those defaults into practice?

Where default setting might be periodic or one-off, there are many aspects of data governance which require day-to-day engagement. Where broad public engagement might be important for setting defaults, making decisions might require more focussed approaches, potentially with participants who have more background, training or ongoing role. I’m particularly interested in the coming weeks to try and explore different models being applied to data governance here: whether focussed on shaping decisions, sharing decisions, or providing scrutiny to decisions made.

The purpose of participation

I’ve been thinking a lot this week about the distinction between different institutional designs for data governance (including novel proposals for trusts, commons and co-ops), and questions of how decisions actually get made whatever the institutional structure. I was particularly struck by this critical piece from Rachel Adams at Research ICT Africa on the problems of reaching for a data trusts model in an African context.

I’ve found it helpful (this week at least!) to break down my thinking as follows:

• Fundamentally, participation aims to align the outcomes of any process with the interests of those affected by it.

  (This is compatible with recognising that some interests, and the way people or communities understand or articulate them, are not fixed, and may be refined or revised through participatory process).

• In the context of democratically governed public authorities, competitive markets, and/or a balance of power between actors, then participatory processes can help to align the interests of data powers and communities; but
• In conditions of vastly unequal power, other institutional mechanisms are required to create conditions in which the interests of authorities or firms and communities will end up aligned.

  Mechanisms, for example, like trusts, commons or co-ops that seek to change where decisions are made, and what the backstops are to protect against individual, private or external interests being put above community or collective interests.

Thinking about the purpose of participation in terms of aligning actions or outcomes from data governance with the interests of the populations affected also brings into relief the points that (a) different communities may have interests that are not aligned, or even entirely compatible; and (b) a lot hinges on how the community whose interests are to be explored is defined.

Components, connections and configurations

I’ve been starting to reflect on how to present the relationship between different parts of the participatory data governance cases I’ve been gathering. The case study schema has each case with multiple components that feed into each other, so that, for example, a citizens jury case might be broken down into the initial desk review and design, feeding into a set of roundtables that design materials, which are then used by main jury events, and which feed into an analysis process that produces a report. I’ve been thinking about whether it is useful to present this schematically (essentially a graph of the component relationships), and how this might also start to show where the participation process interfaces with organisational decisions. I might manage to get a quick prototype sorted soon.

Other stuff

I’ve also been:

• Preparing an activity to think about our Theory of Change for the team offsite next week;
• Setting up a Zotero group to keep track of Connected by Data literature;
• Working up a session proposal for a roundtable on Collective Data Governance for the 2022 Internet Governance Forum (Nov 28th – 2nd Dec). An open draft of the proposal is here. We have got a good panel coming together – but I’m still looking for potential participants to include who might be thinking about collective data governance from within private sector or governments;
• Starting a first few chats with researchers whose work touches on issues of participatory or collective data governance;
• Submitting our response to the Data Values Project – Reimagining Data and Power Roadmap consultation;
• Doing some preparation for a workshop with the team at Research ICT Africa next week.