The phrase ‘data-driven nonprofit’ is used to describe how traditional nonprofit organisations adapt to using data, but there’s an emerging ecosystem that can be described by flipping the phrase around. ‘Nonprofit-driven data’ describes an ecosystem of data institutions that place the key tenets of the nonprofit form (non-distribution constraint, trust, public benefit, accountability) at their heart. Here I briefly pull together what a nonprofit-driven data ecosystem may look like by exploring the opportunities and challenges it could present for the sector.
It makes sense for a new ecosystem comprising data intermediaries (e.g. 360Giving), data coops (e.g. Midata.coop), data trusts (e.g. UK Biobank) and personal data stores (e.g. Mydex) to be positioned more widely within a sector that delivers public benefit and has the knowledge and resources to navigate topics such as the role of trustees (as data trustees become a thing), preventing mission drift, and collaborating within and across sectors.
Nesta’s paper The New Ecosystem of Trust portrays a crisis of trust in how data is collected, governed, and used. The UK’s charity sector enjoys high levels of public trust (despite recurring reports of trust in the charity sector increasing/decreasing) and draws on public trust to make wider claims of normative legitimacy. While it is unfair for the sector to be treated as a homogenous entity, the only comparative measure of trust in data use that includes charities does so. This is an opportunity for the sector to show it can be trusted with data and technology in the same way we trust it to advocate for the homeless and care for our natural environment.
It is an opportunity to grow value-driven alternatives to Amazon Web Services (starting small…) and fill emerging spaces such as the gap between personal data governance and collective empowerment and learning, and provide situations where data processors are no longer detached from their subjects. Check out Sally Kerr’s great article on the possible role of data trusts in governing hyperlocal data, an application which could challenge or work with projects such as Alphabet’s Sidewalk Labs ambition. Regarding digital tools more generally, Lucy Bernholz makes a compelling case for establishing nonprofit alternatives to big tech and maintaining independence.
The two greatest challenges for the development of a new nonprofit-driven data ecosystem are regulation and funding. The variety of possible corporate structures and purposes mean there is no one-size-fits-all approach to regulation (that is not to say it can’t be done or regulated by existing bodies such as the Charity Commission or CIC regulator). What would public benefit look like for these organisations and what are the long term funding options, besides charging for data access?
Another challenge concerns how genuine nonprofit organisations establish and maintain distinction in a crowded and messy field. Data may be an asset class, but when trust is the central currency it’s inevitable that profit-making firms will free ride on the greater trust enjoyed by nonprofit firms. Jose van Dijck (p. 107) critiques a private health data platform that describes itself as having a “not-for-profit attitude”. In the absence of such explicit messaging, a combination of regulation, data literacy programmes, and complete transparency from nonprofits over how data is used may be the best way of ensuring distinction is maintained.
Distinction could be even more important in Dominic Cumming’s post-GDPR Wild West that is regulated by a toothless and underfunded ICO. If general trust in data use is undermined by lax data protection laws that are lightly enforced (such as the DPA 2018), most of us will not be able to distinguish between ethical and unethical/illegal data gathering, analysis, profiling, and sharing. Instead, we’ll look to stated organisational values and transparency to assess whether we want to engage with organisations or offer up our data.
It’s worth saying that lots of this isn’t new and data trusts in particular have been slow to develop (Lucy Bernholz wrote about this back in 2014). However, from my own research and that of others, it seems discussions around meaningful interventions by the sector in the data and tech sphere are picking up pace. While it looks like the GAFAM oligopoly is here to stay (notwithstanding EU interventions), that doesn’t mean alternatives can’t be developed and I think data governance could be a good way in for the nonprofit sector.
Further reading – some opinions from actual experts:
ODI’s work on Data Institutions (inc. this on charity data trusts)
Element AI and Nesta’s report on data trusts
Pinsent Masons’ paper on the legal and governance consideration of data trusts
Leading scholars Sylvie Delacroix and Neil Lawrence’s website on data trusts
‘Emerging models of data governance’ by Micheli et al., in Big Data and Society