Responsible Data versus Data Transactions: the coming culture clash
5 minute read
SIMLab’s recent consultation on responsible data in practice demonstrated a deep disconnect between two opposing visions of data in social change work: one, rights-based and respectful of the ownership of the people we serve of their own data; and the other, data-centric and focussed on transactional exchanges of development gains in return for data access and monetization.
The consultation, part of the Good Data Collaborative funded by Stanford’s Center on Philanthropy and Civil Society, which we announced back in May, was published in full today. The consultation was part of the work of the Collaborative, a joint project with the Center for Democracy and Technology (CDT), Future of Privacy Forum (FPF) and The Engine Room (TER), to look at the resources available to help social change organizations to manage data more responsibly.
Our findings suggest that RD is a complex issue, and rarely handled effectively even in organizations that recognize the need to improve their compliance with RD principles. For many of our respondents, ‘responsible data’ is a new concept, without organizational compliance mechanisms or even broad understanding. Our interviewees see data practices as largely left to individual actors to implement, monitor and enforce; people do not know where to go for help, and even where they do understand the basic principles of RD, they express feeling overwhelmed by the complexity of implementing the required practices in their organization. In many cases, they respond to the uncertainty and discomfort by putting the responsibility for becoming compliant on other colleagues. Many express concern about not properly understanding the law covering data management, and many do not publicly admit to their uncertainty. Donors and platform providers are equally challenged to provide guidance and investment in a challenging and potentially expensive area with such strong links to legal liability and capacity-building.
You can read more about our findings on the need for infrastructure investment, improved tools and guidance, mapping of the legal issues involved, and resources that work for beginners, in the report, available in machine readable and PDF format here.
But, critically, the consultation also brought out a brewing ‘culture clash’ between data-centric and rights-based approaches to technology in social change projects which will needs open discussion.
Two points of view
Respondents interviewed as part of our consultation held opposing visions of data in social change work: one, rights-based and respectful of the ownership of the people we serve of their own data; and the other, data-centric and focussed on data access and monetization.
Some institutional donors are investing in Responsible Data toolkits, mostly through staff engagement with the issue at conferences and events, participation and support for broader ethical codes such as the Principles for Digital Development, or by directly developing their own toolkits and guides — USAID’s work is due out later this year.
Others are taking their investments in a completely different direction, expressing enthusiasm about the opportunity they see in monetizing data about clients, service users or aid recipients as part of poverty reduction work, as long as the data relationships featured ‘trust and transparency’. They highlighted services aimed at low-income people that rely on personally identifiable data, such as mobile data usage, to generate benefits such as credit histories and access to low-interest microloans.
Our interviews pointed to a widening gap between proponents of RD and the enthusiasm and funding flows towards data-centric, utilitarian projects which prioritize access to and monetization of data over RD principles. These opposing views might arise even within the same institution, in some cases. The data-centric vision of tech for social change, though, appears well-represented among a group of donors with relatively large spending power, lighter emphasis on evidence-based granting, and swift decision-making — although SIMLab also sees it at work in the ‘innovation’ spaces around technology, particularly in humanitarian aid.
What this means for implementation
These powerful organizations can heavily influence practice beyond their grantees. One conversation painted a picture of a pendulum swinging too far towards data as a good in itself, with a more context-specific and grounded analysis of risk and benefit seen as negative, expensive and too conservative, in the face of the limitless potential of data-driven work. This translates into lack of funding and interest in implementation of RD, and perhaps more damagingly, lots of funding for data-centric approaches that do not respect the rights of data owners. In this analysis, there will be no way to promote or encourage a cautious, human-centric approach to data management until ‘the pendulum swings the other way.’
This raises urgent and, to SIMLab, disturbing questions about power and the role of data and ethics in the tech for social good space. These rapidly polarizing views of and approaches to RD are setting up inconsistencies between and across platforms and projects that would make it impossible for data subjects to navigate the marketplace of such projects and make informed decisions about who should get their data and how it would be managed. We need to explore and openly discuss the tension between data positivism and the responsible data movement, so that at least this disconnect is understood and acknowledged.
Read the report, get involved on the Digital Principles forum where you can discuss Principle 8, Addressing Privacy and Security, and follow the #responsibledata hashtag. Later in the year we’ll be sharing new tools developed, redeveloped or finished off on the ResponsibleData.io site as part of the Good Data Collaborative project. And tell me what you think.
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Originally published at simlab.org on November 1, 2017.