As a firm that transforms information into action, Scale Strategic Solutions is responsible for collecting and using information with integrity, fairness, and justice. This effort goes beyond intention to reflecting on our practice and embedding approaches to justice in our work. Societies all over the world are figuring out how to move further along the “arc of the moral universe as it bends towards justice,” to paraphrase Dr. Martin Luther King, Jr. As our technology advances, we are now disabused of the notion of its neutrality since its artificial intelligence is built on the inequities, discrimination, and bias of our real collective experiences. Just look at what happens in algorithms in financial services and healthcare. The evolving literature on data justice--the relationship between big data, artificial intelligence, social justice, and decision-making---is critical to strategic decisions, capacity building, research and evaluation.  

Reflecting on the American Evaluation Association’s AEA365 blog Decolonizing Evaluation Week this month, we must understand the different ways of knowing and shifting beyond colonial paradigms of understanding and valuing information. There are so many rich ways of comprehending our world to cultivate practical solutions. Being equity-minded, just, and inclusive is an ongoing effort requiring continuous improvement, hard work, and a commitment to growth. In the execution of our work, these are just three of many questions we pose in our Data Equity and Justice Framework:

Changing language may seem like a simple act but it requires conscious, consistent choices. For instance, we use the terms ‘allowlist’ and ‘denylist’ instead of ‘blacklist’ and ‘whitelist’ regarding technology permissions. The terms ‘whitelist’ and ‘blacklist’ have been so commonplace to talk about what emails or websites get through to users. We have become vigilant internally and with partnerships to use clearer, more accurate language that avoids perpetuation of negative and positive associations with color. In fact, terms like ‘allowlist’ and ‘denylist’ are more accurate for the intended use.

In the past, it may have been common to reference the data of a small group as ‘statistically insignificant.’ However, that approach heightens ignorance. We have committed to referencing small numbers in disaggregated studies as ‘n less than a number x’ so that we do not run the risk of disclosing identity, but we do not act if those groups do not exist. With qualitative data, we strive for ways to highlight the direct voice and quotes so that people speak for themselves and the evaluators are not always speaking for them. We are practicing data collection and engagement approaches that are participatory in nature.

      3. How do we grow in awareness and knowledge?

We all have biases, and we all must hold ourselves and each other accountable to mitigating those biases. Confirmation bias is particularly threatening in our space as we may run the risk of interpreting new evidence as a confirmation of our own pre-existing beliefs. We have to grow in our knowledge of inclusive practices and strategies and of various cultures and human experiences. Our team is committed to learning. One of the resources we are starting to read is Research & Reconciliation:  Unsettling Ways of Knowing through Indigenous Relationships by Wilson, Breen, and DuPré.

Our pursuit of data equity and justice is beyond a slogan and is parallel to many journeys to grow and excel. As we proceed on this journey, we look forward to learning from our participants and collaborators so systems and communities can become life and liberty enhancing for all. We are also beginning to share our approach and learning with others as they build their organizational capacity.