Tim Davies

Tim Davies

Tim Davies

Although I’m definitely missing the in-person interaction of co-located conferences, one of the advantages of online-only RightsCon was that I could still tune in and join sessions, even with an absolutely stinking cold. Even so, I still had to take a day and a half off this week, so it’s been another shorter week, hence these later and somewhat disjointed weeknotes.

RightsCon reflections

It’s not everyday that you hear a Head of State talking about their government’s approach to data governance, but that’s how RightsCon 2022 started for me as I logged onto the launch livestream to hear New Zealand PM Jacinda Ardhern talking about the country’s data governance approach. There is lots to dig into on the New Zealand Government’s data governance pages. Although the ‘holistic data governance’ model proposed there does not explicitly include touch-points for participatory data governance, it usefully challenges conventional top-down models for governing data, and provides tools that might be adapted to map the decision points around data that affected communities should have a say over. The prominence given to work on Co-designing Māori data governance is also striking, and a demonstration of the growing importance of Indigenous Data Sovereignty thinking.

After the opening plenary, over the rest of RightsCon, I tended to opt for more workshop style sessions, with a mix of data-focussed sessions, and a few looking more broadly at participatory practice, or issues framed in terms of artificial intelligence. I really valued the opportunity to join and learn from sessions on centering the global south in developing tools to advance the UNESCO Recommendation on Ethics in AI, and from African feminists exploring how to build a movement for Afrofeminist data governance. From that session, I picked up a link to the very rich Afrofemist Data Futures report. I’ve only skimmed it so far, but want to share this extended quote from the final section on the future of feminist data governance:

“Feminist STS (science and technology studies) often grapple with undoing hegemonic narratives. It seeks to explore the social, cultural and political factors that shape the technology around us and is committed to understanding technology through the lens of situatedness, embodiment and care. There are multiple aspects of care worth considering including an understanding of the invisible labour involved in producing data, whether that means an individual’s content and knowledge, or the burden placed upon citizens and civil society to collect data for the betterment of society. Even the landscape of social services is rapidly becoming dependent on data systems where technological determinism, i.e. placing the burden on the apps, algorithms or devices, is practised rather than a nuanced analysis of contexts and power dynamics at play (Fotopoulou, 2019).

“As Nissenbaum stated in an interview in 2018, technologists must move beyond providing illegible Terms and Conditions or tweaking consent mechanisms on digital platforms to think more holistically about how data flows could work in a way that distributes costs and benefits fairly across society and upholds the values of social domains such as health, democracy, balance lifestyles etc (Berinato, 2018).”

(Source: Iyer, N., Chair, C. and Achieng, G. (2021) Afrofeminist Data Futures. Pollicy)

In calling for data governance that examines power, embraces pluralism, and considers context, the work of Connected by Data is very much aligned with a Data Feminist agenda, and I’ll be reflecting more on how we can more explicitly draw on these roots.

I also took part in a fascinating session titled “Path independent: forging new models of tech infrastructure through community participation” which Nate Matias has written up here. In particular, I appreciated Anna Lee Steele’s pointer to the Turing Way, an effort to make “collaborative, reusable and transparent research ‘too easy not to do’.” The Turing Way model of capacity-building (resource/handbook + community + collaboration) is something we might learn from in thinking about how to shift data governance practice in a more participatory direction in future.

In the breakout I joined, the session also touched on participation in conditions of vastly unequal power. Faced with the power of tech giants, many participatory processes about the redesign of technology can feel tokenistic or futile: able to tinker around the edges at best. This got me thinking: are there learnings we can draw from the design of (mandated) participatory processes in other conditions of vastly unequal power (e.g. around extractive industries) which would be instructive when thinking about participatory data governance particularly in the big tech space?

And on Friday morning I took part in an interesting workshop on “Participatory Data Stewardship in Practice” run by the Ada Lovelace Institute team. The session took the form of a role-played scenario, where attendees were asked to act as members of an international energy data-cooperative receiving their first applications for data access, and charged with deciding whether or not to approve the requests. Besides feeling rather reminiscent of how I used to spend my Friday mornings when I was a member of Open Data Services Co-op (the Friday meeting was our weekly all-hands governance session), the session provided a really interesting opportunity to test out a collective data governance lens. Power in a data co-operative technically belongs to the members, though it is often exercised by those who turn up. Yet, the consequences of data collected and governed in a co-op being used may not only fall upon members. For example, in the scenario we considered, cooperatively held data could be used to develop new products or tariffs by an energy company, leading to certain populations (not necessarily the members of the co-op) paying more for their fuel in future. Even a data stewardship structure like a co-operative needs a prompt to consider the communities affected by their decisions, and to think about the involvement those communities should have in the data governance decisions that get made.

Platform governance

I spent a bit of time on Monday digging into the platform governance literature. Whilst I’ve not had a chance to follow up on it yet, the key take-away so far is that there is a lot of existing work on democratising governance, and building more participatory processes, that we might look towards when thinking about participatory data governance.

Governance innovation

The RSA have a call out for proposals on ‘Rethinking public dialogue’ and so I spent a bit of time on Friday brainstorming what a Connected by Data angle on this could look like: focussing in particular on better interfacing public dialogue with existing governance processes, and finding engaging ways to have meaningful dialogue about data, without requiring lots of up-front ‘teaching’ about the data specifics of a problem space, but rather having resources that allow these to emerge as a dialogue develops. I’ll be spending some more time on this over the week to come, and exploring whether we might find a partner to work with on a proposal.