This spring, a student team from the Mack Institute for Innovation Management collaborated with Penn’s Computational Social Science (CSS) Lab to explore how to bring the lab’s latest innovation, an AI-powered media bias detection tool, to market. The student team is Jieru Shi (WG’25), Keshav Ramesh (W’25) and Caleb Yam (COL’25), with Aswin Mannepalli (COL’09, G’19), founder of Mira Insight, as their industry advisor.
Media Bias Detector (MBD) is an open-source platform that analyzes news content in real time at the article level. Unlike traditional bias detection tools that focus on partisan scoring, MBD aggregates and visualizes media bias without making value judgments, allowing users to independently assess and compare biases. Through this collaboration, CSS Lab and the Mack Institute are working to transition MBD from an academic project into a self-sustaining product with broader market reach.
The student team conducted extensive stakeholder interviews and ran 600 simulations using Crowdwave, a platform that blends human interviews with AI-generated responses. Their research identified four high-potential customer segments: academia, media organizations, government agencies, and corporations.
User feedback highlighted key desired features for the tool, including interactive visual dashboards, transparent explanations of bias scoring, and custom filters by topic, region, or ideology. Many users expressed a preference for a hybrid model that combines AI-driven insights with human oversight. The student team estimates a U.S. market potential of $60-106 million annually and believes MBD’s more automated, article-specific approach offers a strong advantage over competitors that rely heavily on human-curated ratings.
Looking ahead, the team is considering expanding the tool’s coverage from 10 to 22 publishers and extending into social media and podcast analysis. They are also exploring different business models—including licensing, subscriptions, and direct partnerships—with an eye toward legal and ethical considerations around content sourcing and AI transparency.
As the project moves into its next phase, members of the student team plan to continue their work over the summer, supported by faculty mentors. They are also exploring opportunities to collaborate with major media organizations and commercialize the tool through Penn’s innovation ecosystem.