Professor Sets Strict AI Rules
Claudia Goldman requires Hebrew University students to document human reasoning and reject fully generated answers in data science classes.
By Marco Whitaker ·
Prof. Claudia V. Goldman has set specific rules for artificial intelligence use in her data science classes at the Hebrew University Business School in Jerusalem.
Goldman joined the faculty as an associate professor in July 2024. She teaches students to use AI tools for real-world problem solving but demands clear proof of human effort. Her background includes 15 years in the automotive industry and 24 patents.
In a recent interview at her office, Goldman explained that students must credit AI when they use it. They must also explain exactly how the technology helped them. She does not accept answers that are fully generated by AI. Students know she can detect machine-written text.
The professor encourages brainstorming with AI but requires critical thinking. Students must check for bias in the output. They must verify that cited sources actually exist. This approach forces learners to stay engaged with the material rather than relying on automated responses.
Goldman assesses understanding through in-person activities. This mix includes classwork, presentations, and peer-organized discussions. These formats allow her to evaluate how students think and communicate directly. The curriculum also covers human responsibility and professional values.
When asked about Bill Gates’s idea of reserving certain jobs for humans, Goldman rejected a simple binary view. She argued that the focus should be on understanding AI benefits in different roles. She emphasized the critical skills needed to strengthen those roles with technology.
The Business School offers related courses such as AI for Social Good and Responsible AI. The Hebrew University also runs a Free Listener Program for senior citizens to audit classes. The fall semester is currently underway.
Goldman’s career includes research at Bar-Ilan University, the University of Massachusetts Amherst, and the University of Haifa. She worked as a team leader at Samsung Telecom Research in Herzliya for three years. She then spent 15 years as a research scientist at General Motors. At GM, she developed learning agents to help drivers understand autonomous features.
