Understand the ethical issues impacting your initiative
Data ethics is a branch of ethics that evaluates data practices with the potential to adversely impact people and society. Data ethics relates to good practice around how data is collected, used and shared. It is especially relevant for data access initiatives as they are created with the goal of positively impacting people and society, and are likely to do so both directly and indirectly.
Data access initiatives are meant to have a positive impact by improving access to data. The question of whether and when more data or more access to data will create positive impact requires a data ethics lens from the outset. Does more data really need to be collected? Could positive impact be achieved through more groups being represented in the data but with less data about the individuals, or for a shorter period of time (following the principle of data minimisation)?
For example, an automated data model might be used to inform decisions or recommendations about how to respond to public health or environmental emergencies. And decisions about what data to collect – and what to exclude – could impact different groups in a society differently. Historically, data collection and use practices have been asymmetrical, often resulting in under-representation of communities in some datasets and over-representation in others, and giving greater knowledge to those with authority, influence and capability than those without, amplifying inequality and power imbalances.
To help mitigate these risks and harm, data ethics should be addressed at all stages in the initiative:
Stewarding data – collecting, maintaining and sharing the data. What data is collected and how, what data is excluded and who has access to that data will determine the range of impacts the initiative can have, both positive and negative. This foundation will determine the biases of the initiative and set the course for future decision making.
Creating information from that data – in the form of products and services, analysis and insights, or stories and visualisations. How the insights of the data are communicated is both determined by, and will determine who gets to benefit from the data and who is adversely affected by it. You should consider how products and services are accessed, and who gets to use them.
Deciding what to do – informed by information from multiple sources along with experience and understanding. Data-informed decision making is a powerful tool for creating impact, both positive and negative. You should consider the kinds of decisions data might be used to inform, who makes them, and the biases and limitations of the data to support them.
The Data Ethics Canvas
One way to explore these data ethics issues is using the Data Ethics Canvas, a tool for anyone who collects, shares or uses data. It helps identify and manage ethical issues at the start of a data access initiative and throughout the implementation process.
It encourages you to ask important questions about data access initiatives, and reflect on the responses such as:
What is your primary purpose for using data in this initiative?
Who could be negatively impacted by this initiative?
Why are you collecting certain data, and excluding others?
How are you communicating your data practices to relevant communities?
How will ongoing data ethics issues be measured, monitored, discussed and actioned?
The Data Ethics Canvas provides a framework to develop ethical guidance to address the following topics that suits any context, whatever your initiative’s size or scope:
Data: understanding the key data sources your initiative needs to improve access to, how you can share it with others, and the rights and limitations to collecting and using this data.
Impact: defining the purpose of collection and use of this data and assessing both the negative and positive effects of that collection and use on for people, communities or organisations.
Engagement: thinking of how open you can be about the initiative, what you can publish and how people can engage with it.
Process: planning how you are going to iterate, review and evaluate the data infrastructure and the specific data you are using.
Data ethics assessments should be taken early on when scoping your initiative, as they will enable you to gain greater visibility of the consequences of the initiative, both positive and negative, in addressing your challenge. There will always be unpredictable consequences from activities, but negative consequences should not be ignored: these should be recognised and mitigated. If they are accepted, this should be done consciously and transparently. We recommend you revisit this exercise throughout the initiative, and include all relevant stakeholders, not just those within your organisation.
Special focus: Data ethics and data justice
There is growing discussion about the uses and limits of ‘data ethics’ as a lens for exploring the fair and equitable impact of data infrastructure on society, and arguments for an increased focus on ‘data justice’. As mentioned earlier, data ethics focuses on good data practice that people can engage in. Data justice focuses on how to explicitly challenge, rather than reproduce, structural inequalities when collecting, using and sharing data.
Some scholars argue that a focus on self-reflection as individuals and as an organisation, rather than on structural issues, is unlikely to mitigate the likelihood that new data infrastructure will perpetuate an unjust status quo.
Tools like Consequence Scanning and that Data Ethics Canvas can be used to help reflect on and explore deeper power imbalances and structural issues, understand the limitations that data sources, and decisions driven by this data, might have, and the impact and consequences on people, communities or organisations. To do so, though, you will need to engage with a broad and diverse set of stakeholders and deliberately seek out those who provide critique and challenge.
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