Survey of Computer Science Faculty: Contributions of Content to AI Models

This comprehensive study explores how computer science faculty are engaging with AI model development, sharing their research and teaching materials, and responding to the evolving landscape of artificial intelligence in academia. What’s Inside the Report? The report provides detailed survey data and analysis on: Faculty perceptions of their research and teaching materials as potential AI training data Actual contributions of content to AI models, including voluntary submissions and unauthorized use Institutional and departmental efforts to collect and prepare content for AI Use of personal materials in class-specific chatbots and models Differences by institution type, academic rank, age, gender, scholarly focus, and more Five Key Data Findings Majority See Their Work as AI-Relevant: Over half (53.63%) of faculty believe they have content suitable for training AI models, with 49.28% answering “Yes” and another 4.35% saying “Yes, and I have taken measures to ready or archive these materials.” Actual Submissions Are Uncommon: Only 7.25% of respondents report having submitted their content for inclusion in an AI model, while 85.51% say “No.” Uncertainty About Unauthorized Use: Nearly half (43.48%) are unsure if their content has been used by an AI model without permission, with only 14.49% believing unauthorized use has occurred and 31.88% confident it has not. Course-Level AI Adoption Is Growing: Almost one in four faculty (23.19%) have used their own class and lecture notes, videos, or research work in a chatbot or model developed for their students, making this the most common form of AI content sharing. Institutional Efforts Are Limited: Only 4.35% of faculty report that their department has made any effort to collect and prepare content for use in AI models, indicating that organized initiatives are rare.