Responsible Data (RD) is a concept outlining our collective duty to prioritise and respond to the ethical, legal, social and privacy-related challenges that come from using data in new and different ways in advocacy and social change.
RD encompasses a variety of issues which are sometimes thought about separately, like data privacy and data protection, or ethical challenges. We believe that in order for any of them to be truly addressed, they need to be considered together.
Key elements of Responsible Data include:
- Power dynamics: who are the least powerful actors in any situation, how are they affected by the data, and what do they make of the situation? How powerful are the people making decisions about data and technology in relation to those whose data is being collected and used?
- Unknown unknowns: we can’t see into the future, but we can build in checks and balances to alert us if something unexpected is happening.
- Precautionary principle: just because we can, doesn’t mean we should. If we can’t sufficiently evaluate the risk and understand the harms, then perhaps we should pause for a minute, and re-evaluate what we’re doing, and why.
- Thoughtful innovation: for new ideas to have the best possible chance of succeeding – and for everyone to benefit from those new ideas and projects – innovation needs to be approached with care and thought, not just speed.
- Holding ourselves high: in many cases, legal and regulatory frameworks have not yet caught up to the real-world effects of data and technology. How can we push ourselves to have higher standards and to lead by example?
- Diversity and bias: who makes the decisions? What perspectives are missing, and how can we include a diversity of thought and approach to ensure that a wide range of approaches are included?
- Building better behaviours: there is no one-size-fits-all for RD. Existing culture, context and behaviours change the implications and ways in which data is used.
Why Responsible Data?
Within social change work, there is usually a stark power asymmetry. From humanitarian work, to campaigning, documenting human rights violations to movement building, advocacy organisations are often led by – and work with – vulnerable or marginalised communities. We often approach social change work through a critical lens, prioritising how to mitigate power asymmetries. We believe we need to do the same thing when it comes to the data we work with – question it, understand its limitations, and learn from it in responsible ways.
In one way or another, all data is shaped by people and their decisions. How we treat data, how we think about what it tells us (or what it doesn’t), how we choose what to collect and what not to collect all have impacts upon people. Responsible Data practices are a way of bringing those considerations to the fore to ensure we use data in a way that strengthens our work and mitigates the unintended consequences of our work.
There are very few formulas to addressing responsible data challenges, and resources the community develops will encourage structured confrontation of the complexity inherent in responsible data. These resources also will propose ways to identify and address blind spots before they directly threaten the effectiveness of social change aims.