University of Michigan

Career Pipeline and Placement

A Knowledge Network for Underrepresented Public Interest Technology (PIT) Entrepreneurs

We aim to advance social justice by putting individuals from marginalized communities at the center of technological and social innovation. Our goal is to build a tool to accelerate 10 communities toward impact over the next decade. To accomplish this goal, our work focuses on strengthening the career pathways between marginalized communities, PIT entrepreneurs, and technology by aggregating communities, people and knowledge together on a digital platform. This platform will surface industry knowledge and community-focused solutions from the individuals most impacted, build connectivity and cohesion, and close the resource gap social entrepreneurs, students, and faculty currently experience. We will also design and deliver in-person workshops where participants can share personal reflections and stories of navigating systemic barriers with a keen understanding and clarity of how their lives have been shaped by race, class, and gender. The in-person workshops and the knowledge network technical platform will work in tandem to capture and analyze stories, increase reach by making connections to other practitioners, engage communities thoughtfully online and offline, and accelerate participants towards meaningful impact that’s necessary to build an inclusive and just tech future.

Principal Investigator

Tayo Fabusuyi, Assistant Research Scientist, University of Michigan Transportation Research Institute

Educational Offerings, Career Pipeline/Placement

Data Learning for Better Drinking Water in Small Utilities

The project will pilot, revise, and adapt the modules for use in both professional development contexts and classrooms to generate interest in public utility careers and enhance the data skills of existing workforces.

Principal Investigator

Rebecca D Hardin, Associate Professor, Environmental Justice Conservation + Restoration

Educational Offerings; Faculty and Institution Building

Rethinking Computer Science Education: Bringing Public Interest Technology into Undergraduate and Postdoctoral Training

We will rework UM’s undergraduate computer science curriculum to include sustained attention to social, moral, equity, and policy dimensions of data and technology, with help from a postdoctoral fellow who will bridge academic units, receive PIT training, and build supply and demand for PIT faculty.

Principal Investigator

Shobita Parthasarathy, Professor of Public Policy; Director, Science, Technology, and Public Policy Program

Career Pipeline/Placement; Strengthening the Public Interest Tech University Network

Strengthening PIT Career Pathways for Persons of Color: A Knowledge Network and Experiential Learning Approach

This project seeks to strengthen career pathways into PIT for historically underrepresented communities through the expansion of our year one experiential learning course and a partnership with the Public Policy and International Affairs (PPIA) program Junior Summer Institutes (JSIs). The project will also create a PIT-UN Knowledge Network learning platform (PIT-UN KN) to further support the career pathways and career placement of students and create a general PIT network resource to encourage new ideas, foster collaborations, and incentivize resource- and information-sharing among network members.

Principal Investigator

Tayo Fabusuyi, Assistant Research Scientist, Transportation Research Institute

Career Pipeline/Placement

PIT Career Paths and Constraints Faced by Persons of Color

We aim to identify the PIT career paths and constraints faced by persons of color. To accomplish this, we will conduct an analysis of nationwide employment data, and host workshops for PIT social entrepreneurs of color. Students will support this aim via an experiential learning course in the winter.

Principal Investigator

Robert Hampshire, Associate Professor of Public Policy and Research Associate Professor, U-M Transportation Research Institute’s (UMTRI) Human Factors group and Michigan Institute for Data Science (MIDAS)