Brent Hecht

About

Brent Hecht is an Associate Professor of Computer Science and Communication Studies at Northwestern University. He holds a Ph.D. in computer science from Northwestern University, a Master's degree in geography from UC Santa Barbara, and dual Bachelor's degrees in computer science and geography from Macalester College. His research lies at the intersection of human–computer interaction, social computing, and spatial computing, with active areas including location-aware technologies and understanding and improving the interactions between algorithms and society. Dr. Hecht employs mixed methods approaches, emphasizing 'big data' projects, and has collaborated with prominent research institutions such as Google Research, Xerox PARC, and Microsoft Research. His work has been featured by various media outlets including NPR, Time Magazine, The Washington Post, and others. He has received awards for his research at top-tier venues like ACM CHI, ACM CSCW, ACM Mobile HCI, and COSIT, and has been a keynote speaker at events such as WikiSym.

Research topics

• Computer Science
• World Wide Web
• Political Science
• Engineering
• Psychology
• Internet privacy
• Sociology
• Information Retrieval
• Social Science
• Knowledge management

Selected publications

• SearchBuddies: Bringing Search Engines into the Conversation

  Proceedings of the International AAAI Conference on Web and Social Media · 2021 · 66 citations

  1st authorCorresponding

  Although people receive trusted, personalized recommendations and auxiliary social benefits when they ask questions of their friends, using a search engine is often a more effective way to find an answer. Attempts to integrate social and algorithmic search have thus far focused on bringing social content into algorithmic search results. However, more of the benefits of social search can be preserved by reversing this approach and bringing algorithmic content into natural question-based conversat…

  PublisherOA PDFDOI

• Behavioral Use Licensing for Responsible AI

  2022 ACM Conference on Fairness, Accountability, and Transparency · 2022-06-20 · 54 citations

  articleOpen access

  With the growing reliance on artificial intelligence (AI) for many different applications, the sharing of code, data, and models is important to ensure the replicability and democratization of scientific knowledge. Many high-profile academic publishing venues expect code and models to be submitted and released with papers. Furthermore, developers often want to release these assets to encourage development of technology that leverages their frameworks and services. A number of organizations have…

  PublisherOA PDFDOI

• It's Time to Do Something: Mitigating the Negative Impacts of Computing Through a Change to the Peer Review Process

  arXiv (Cornell University) · 2021 · 41 citations

  1st authorCorresponding

  The computing research community needs to work much harder to address the downsides of our innovations. Between the erosion of privacy, threats to democracy, and automation's effect on employment (among many other issues), we can no longer simply assume that our research will have a net positive impact on the world. While bending the arc of computing innovation towards societal benefit may at first seem intractable, we believe we can achieve substantial progress with a straightforward step: maki…

  PublisherOA PDFDOI

• The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers

  2023-06-12 · 30 citations

  articleOpen accessSenior author

  Many recent technological advances (e.g. ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with computing systems or scraped from the web (e.g. behavior logs, user-generated content, and artwork). However, data producers have little say in what data is captured, how it is used, or who it benefits. Organizations with the ability to access and process this data, e.g. OpenAI and Google, possess immense power in shaping…

  PublisherOA PDFDOI

• Measuring the Monetary Value of Online Volunteer Work

  Proceedings of the International AAAI Conference on Web and Social Media · 2022-05-31 · 30 citations

  articleOpen access

  Online volunteers are a crucial labor force that keeps many for-profit systems afloat (e.g. social media platforms and online review sites). Despite their substantial role in upholding highly valuable technological systems, online volunteers have no way of knowing the value of their work. This paper uses content moderation as a case study and measures its monetary value to make apparent volunteer labor’s value. Using a novel dataset of private logs generated by moderators, we use linear mixed-ef…

  PublisherOA PDFDOI

Recent grants

• CAREER: Understanding and Addressing Geographic Inequalities in Location-Aware Technologies

  NSF · $87k · 2016–2016

• III: Small: Collaborative Research: Automatically Generating Contextually-Relevant Visualizations

  NSF · $121k · 2014–2017

• CHS: Small: Collaborative Research: Human-Centered Semantic Relatedness

  NSF · $248k · 2015–2016

Frequent coauthors

• Johannes Schöning

  University of St. Gallen

  40 shared

• Nicholas Vincent

  University of East Anglia

  20 shared

• Isaac Johnson

  Wikimedia Foundation

  19 shared

• Loren Terveen

  University of Minnesota

  19 shared

• Jacob Thebault-Spieker

  University of Wisconsin–Madison

  18 shared

• Darren Gergle

  Northwestern University

  15 shared

• Jaime Teevan

  15 shared

• Hanlin Li

  The University of Texas at Austin

  12 shared

Awards & honors

• awards for his research at top-tier publication venues in hu…

Similar researchers at Northwestern University

• Tobin J. Marksh-176
• Joseph Hupph-171
• James D Thomash-160