The “Community Tech Workers”: A Community-Driven Model to Support Economic Mobility and Bridge the Digital Divide in the U.S.
Lead PI:
Tawanna Dillahunt

Information and communication technologies allow individuals to apply for benefits like health care and housing, to have groceries delivered to their homes, to schedule/attend healthcare appointments, and to apply for employment. However, digital inequalities in terms of access, use, and self-efficacy reflect offline socioeconomic inequalities and pose a serious threat to today's increasingly tech-reliant society. The digital divide is a multidimensional phenomenon that refers to three levels of differences: first, in who has access to the Internet; second, who has skills to use the Internet; and third, how the Internet is actually used. Many efforts to bridge the digital divide have failed because they only address the first level (e.g., providing public Wifi, computers, computer labs) without continued onboarding and training support. This project aims to address digital disparities in Southeast Michigan by leveraging and building the digital literacy of local experts (level 2) to provide digital support to communities (levels 2 and 3). Inspired by the transformative Community Health Worker model, this work proposes "Community Tech Workers" (CTW), a community-driven, "train the trainer" approach that promotes digital literacy in communities. Participants include a public housing authority in Detroit's Eastside neighborhood, a refugee resettlement agency that serves refugees in a public housing community in Ypsilanti, an advisory board consisting of local workforce development agencies and industry representation, and a steering committee of individuals who are involved in outreach, education, and interventions related to increasing digital proficiency and public health.

The research will (1) develop and validate a survey instrument measure to assess community digital capacity; (2) develop an initial CTW training program; (3) assess the training, learning experience, and impact of the CTWs within each community; and (4) capture and evaluate the economic value of the CTW model. The survey instrument will extend existing assessments for measuring individual digital capacity to create a novel instrument that measures digital capacities at a community grain size. This instrument will be validated across two communities, and then be used to measure the impact of the CTW activities on the two communities over time. CTW training activities will be evaluated via interviews with participants and observations of the training sessions. Recommendations for a credentialing system to document CTW proficiency and for a marketplace system to promote employment opportunities will be elicited via participatory co-design sessions, information which can be used to inform integration with or development of job recommendation and gig work applications. Finally, data on costs will be collected to generate a cost-benefit analysis of the CTW model, to explore its further scalability. Secondary outcomes of the work include providing local residents with free training to obtain the necessary skills to become a CTW, and in the future, temporary employment for selected tech workers and connections to local IT employment opportunities. Incorporating the model across multiple communities will help uncover generalizable requirements for creating equitable socio-technical infrastructures that support community digital capacity and expand local opportunities. This systemic perspective on the development and deployment of the CTW model aligns well with the goal of the NSF Smart and Connected Communities (S&CC) program, which is to accelerate the creation of the scientific and engineering foundations that will enable smart and connected communities to bring about new levels of economic opportunity and growth, safety and security, health and wellness, accessibility and inclusivity, and overall quality of life. This project is also supported by the Improving Undergraduate STEM Education program, which seeks to support projects that have high potential for broader societal impacts, including improved diversity of students and instructors participating in STEM education, professional development for instructors to ensure adoption of new and effective pedagogical techniques that meet the changing needs of students, and projects that promote institutional partnerships for collaborative research and development.

Tawanna Dillahunt
I completed my Ph.D. at the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University under the advisement of Dr. Jennifer Mankoff. I received a Bachelors of Science degree in Computer Engineering from North Carolina State University and started my career as a software engineer with Intel Corporation. I developed desktop and network products for Original Equipment Manufacturers. While at Intel, I received a Masters of Science in Computer Science from the Oregon Graduate Institute at the Oregon Health and Science University before leaving to pursue my Ph.D. I was a recipient of the IBM Ph.D. Fellowship (2011, 2012), the Fran Allen IBM Ph.D. Fellowship Award (2011), and served on the program committee for FLAIRS in 2011. I hold three patents with IBM Research.
Performance Period: 01/01/2022 - 12/31/2024
Institution: Regents of the University of Michigan - Ann Arbor
Award Number: 2125012