About

Audrey Bennett is a professor at the University of Michigan's Stamps School of Art & Design, where she specializes in graphic design with a focus on cross-cultural and trans-disciplinary design that utilizes images permeating global culture. Her research explores how engaging users with images enhances their communicative effectiveness across different cultures, emphasizing active participation in the production, distribution, and consumption of images. Bennett develops the concept of interactive aesthetics, which uses technology to facilitate virtual collaboration between designers and lay users, aiming to democratize control of images in society. Her fieldwork is conducted globally, investigating the application of interactive aesthetics to promote social change, including efforts to prevent HIV infections in Kenya and Ghana, and to diversify STEM education through indigenous art curricula. Bennett's scholarly contributions include numerous publications on design and social change, and she has received awards such as the Andrew W. Mellon Distinguished Scholar and the NSF Career Campaign Award. She is actively involved in editorial and professional organizations, co-editing the Icograda Design Education Manifesto 2011 and serving on editorial boards and boards of directors related to art and design.

Research topics

• Sociology
• Political Science
• Computer Science
• Pedagogy
• Social Science
• Public relations
• Psychology
• Medical education
• Engineering ethics
• Medicine
• Law
• Knowledge management
• Economic growth
• Mathematics education
• Engineering
• Economics

Selected publications

• Computing for community-based economies: A sociotechnical ecosystem for democratic, egalitarian, and sustainable futures

  The Information Society · 2025-09-23

  article
  PublisherDOI

• Understanding Online Conversations Through Fractal Dimension: A Case Study Linking Semantic and Structural Analysis of Reddit posts on AI

  Research Square · 2025-12-01

  preprintOpen access
  PublisherOA PDFDOI

• Computing for Community-Based Economies: A Sociotechnical Ecosystem for Democratic, Egalitarian and Sustainable Futures

  ArXiv.org · 2025-04-08

  preprintOpen access

  Automation and industrial mass production, particularly in sectors with low wages, have harmful consequences that contribute to widening wealth disparities, excessive pollution, and worsened working conditions. Coupled with a mass consumption society, there is a risk of detrimental social outcomes and threats to democracy, such as misinformation and political polarization. But AI, robotics and other emerging technologies could also provide a transition to community-based economies, in which more democratic, egalitarian, and sustainable value circulations can be established. Based on both a review of case studies, and our own experiments in Detroit, we derive three core principles for the use of computing in community-based economies. The prefigurative principle requires that the development process itself incorporates equity goals, rather than viewing equity as something to be achieved in the future. The generative principle requires the prevention of value extraction, and its replacement by circulations in which value is returned back to the aspects of labor, nature, and society by which it is generated. And third, the solidarity principle requires that deployments at all scales and across all domains support both individual freedoms and opportunities for mutual aid. Thus we propose the use of computational technologies to develop a specifically generative form of community-based economy: one that is egalitarian regarding race, class and gender; sustainable both environmentally and socially; and democratic in the deep sense of putting people in control of their own lives and livelihoods.

  PublisherOA PDFDOI

• Ubuntu AI

  2025-05-21

  book-chapter

  Abstract Current AI technologies amplify exploitation by training on human-created images and text taken from the internet, without any return to its creators. Companies can then use AI to displace paid employees and compete with independent creators, amplifying wealth inequality. Black populations are especially vulnerable to this appropriation. This article describes how alternative AI services and platforms might reverse its potentially debilitating impact on Black artisans by combining the capabilities from two projects. Ubuntu-AI, funded by the OpenAI Foundation, is a platform that allows African artists and designers to license images for use in AI. Artisanal Futures, funded by the National Science Foundation, examines how Black artisans in Detroit can use digital fabrication and machine learning for economic empowerment. The project this article describes creates a collaboration between those two platforms, and examines the possibilities for redesigning AI and its applications to circulate value in community-based production, rather than allow its extraction by corporations or the state. Because production within a community, no matter how regenerative, is also dependent on external exchanges, we stress the importance of creating layered ecosystems of exchange which minimize value alienation, while expanding regenerative practices. We envision this expansion as a democratization of AI at multiple scales, from community-based ownership of creative production, to global principles for maintaining human rights and egalitarian futures.

  PublisherDOI

• AI governance through fractal scaling: integrating universal human rights with emergent self-governance for democratized technosocial systems

  AI & Society · 2024-07-30 · 5 citations

  article
  PublisherDOI

• Computational reparations as generative justice: Decolonial transitions to unalienated circular value flow

  Big Data & Society · 2024-01-08 · 14 citations

  articleOpen access

  The Latin roots of the word reparations are “re” (again) plus “parere” which means “to give birth to, bring into being, produce”. Together they mean “to make generative once again”. In this sense, the extraction processes that cause labor injustice, ecological devastation, and social degradation cannot be repaired by simply transferring money. Reparations need to take on the full sense of “restorative”: the transition to a decolonial system that can support value generators in the control of their own systems of production, protect the value they create from extraction, and circulate value in unalienated forms that benefit the human and non-human communities that produced that value. With funding from the National Science Foundation, we have developed a research framework for this process that starts with “artisanal labor”: employee-owned business and worker collectives that have people doing what they love, despite low incomes. Focusing primarily on Detroit's Black-owned urban farms, artisanal textile businesses, Black hair salons, worker collectives, and other community-based production, with additional connections to Indigenous and other communities, we have introduced digital fabrication technologies, sensors, artificial intelligence, server-side apps and other computational support for a transition to unalienated circular value flow. We will report on our investigations with the challenges at multiple scales. At each level, we show how computational supports can act as restorative mechanisms for lost circular value flows, and thus address both past and ongoing disenfranchisement.

  PublisherOA PDFDOI

• Making exploratory search engines using qualitative case studies: a mixed method implementation using interviews with Detroit Artisans

  Journal of integrated global STEM · 2024-06-01 · 2 citations

  articleOpen accessSenior author

  Abstract Search engine algorithms are increasingly subjects of critique, with evidence indicating their role in driving polarization, exclusion, and algorithmic social harms. Many proposed solutions take a top-down approach, with experts proposing bias-corrections. A more participatory approach may be possible, with those made vulnerable by algorithmic unfairness having a voice in how they want to be “found.” By using a mixed methods approach, we sought to develop search engine criteria from the bottom-up. In this project we worked with a group of 16 African American artisanal entrepreneurs in Detroit Michigan, with a majority female and all from low-income communities. Through regular in-depth interviews with select participants, they highlighted their important services, identities and practices. We then used causal set relations with natural language processing to match queries with their qualitative narratives. We refer to this two-step process-- deliberately focusing on social groups with unaddressed needs, and carefully translating narratives to computationally accessible forms--as a “content aware” approach. The resulting content aware search outcomes place themes that participants value, in particular greater relationality, much earlier in the list of results when compared with a standard Web search. More broadly, our use of participatory design with “content awareness” adds evidence to the importance of addressing algorithmic bias by considering who gets to address it; and, that participatory search engine criteria can be modeled as robust linkages between interviews and semantic similarity using causal set relations.

  PublisherOA PDFDOI

• Broadening Participation in the Museum Experience Through Interactive Aesthetics: Enabling Access to Pluripositionality in the Inclusive Co-Creation and Dissemination of Audio Descriptions

  The International Journal of the Inclusive Museum · 2024-01-01 · 1 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

• Introduction

  2023-04-21

  book-chapterOpen access1st authorCorresponding

  Critical mapping—a problematizing, reflective approach to design inquiry—investigates how existing design outcomes (DOs) can be coupled to form a wicked solution to address a wicked problem. We have found that visual framing married to affinity organization is one of the most important strengths in critical mapping, helping to communicate the concepts to stakeholders, structure our analysis, and identify places to intervene in the system to design a more sustainable future. In this book, we apply critical mapping to the challenge of identifying and compiling food DOs that are equitable, just, and resilient against ecological and economic changes; that is, the wicked solution must entail sustainable design. “Sustainable design” in this context refers to the manifestation of creative problem solving across a range of intangible and tangible design forms of varying degrees of sustainability. Using food insecurity as the wicked problem, this chapter introduces a visual framework for critically mapping a wicked solution, a diagram onto which existing sustainable DOs are charted and analyzed to identify places where designers should intervene to impact the current state of the system—in the specific case of food—and shift it towards a future of sustainable food security within the realm of equity and justice.

  PublisherOA PDFDOI

• Decolonization, Computation, Propagation

  2023-01-01 · 1 citations

  otherOpen access
  PublisherDOI

Recent grants

• FW-HTF-R: Race, Gender and Class Equity in the Future of Work: Automation for the Artisanal Economy

  NSF · $1.6M · 2021–2026

Frequent coauthors

• Ron Eglash

  University of Michigan–Ann Arbor

  36 shared

• Michael Lachney

  Michigan State University

  17 shared

• William Babbitt

  Rensselaer Polytechnic Institute

  15 shared

• Lionel Robert

  University of Michigan–Ann Arbor

  11 shared

• Kwame Porter Robinson

  Wayne State University

  10 shared

• Sansitha Nandakumar

  University of Michigan–Ann Arbor

  3 shared

• Jennifer A. Vokoun

  3 shared

• Mukkai S. Krishnamoorthy

  Rensselaer Polytechnic Institute

  2 shared

Awards & honors

• 2015 Andrew W. Mellon Distinguished Scholar of the Universit…
• 1997 College Art Association Professional Development Fellow
• Best Poster Paper Award at CoDesign 2000 conference
• National Science Foundation Career Campaign Award (2007)
• AIGA grant to create GLIDE (2007)