What is Public Interest Technology?

By | PIT-KN

September 15, 2021
Written by Tayo Fabusuyi

A hallmark of a field in its infancy is ambiguity in its definition, and in this regard, the Public Interest Technology (PIT) field is no exception. While there is a consensus on the direction and broad contours of PIT, differences of opinion exist on the details of who or what is included and who or what is not. Varying definitions emanating from academia and the foundation community have typically emphasized a technological expertise prerequisite for being in PIT. Examples of these  include the New America, Cornell and Ford Foundation definitions of PIT. More recently, a New America working group of academics have defined PIT as the “study and application of technology expertise to advance the public interest/generate public benefits/promote the public good.”

In our assessment, such definitions address only a subset of the PIT ecosystem. Specifically, we make the case for a definition that puts a premium on technology while acknowledging that fundamentally these solutions are about people; and that is explicit about the equity dimensions of the PIT space. Towards this end, we define the field of PIT as that which aims to design, implement, and advocate for tech-enabled solutions with the goal of advancing the common good in an equitable manner.

Some of the most ardent advocates of the use of technology to address problems of public interest may not have expertise in tech. Our definition harkens to the need to make the PIT ecosystem more inclusive of these individuals who may not be technologists in the conventional sense but who advocate for equitable tech solutions.

A key element of PIT is that individuals who are developing tech solutions for the common good should meaningfully engage with those who are intimately familiar with the situation the tech solution is intended to improve and where possible, elevate their involvement in the project as co-creators of the solution. To enable this, more resources should be channeled towards adequately understanding and framing the problem, and only afterwards should the attention be on the technical features of the solution.

Which brings us to the equity dimensions, on which many PIT definitions are silent.  The PIT space is inequitable, a consequence of an asymmetric power structure and lack of representation of historically marginalized voices. Many of the disputes with data and algorithm bias stem from these issues and from the simple reality that individuals tasked with developing these solutions may have viewpoints or value systems that are not representative of the populations of interest. The result can be that inequities, both current and historic, are exacerbated rather than reduced. A PIT definition that is explicit about equity confronts this challenge head on.

In closing, we reiterate the argument for a “big tent” PIT field that is inclusive, with a primary focus on people, and that is composed of individuals committed to designing, implementing, and advocating for tech-enabled solutions with the goal of advancing the common good in an equitable manner.

Jing Liu

By | Voices of Our Researchers

Dr. Jing Liu, Managing Director of the Michigan Institute for Data Science, joins Innovators to discuss the Burgeoning and Expanding Field of Data Science.