AI in Academia: The 24-Patent Portfolio Shaping New Classroom Rules

Twenty-four patents stand as a tangible measure of the industrial research background that now informs a new approach to academic instruction in Jerusalem. This specific intellectual property portfolio belongs to Prof. Claudia V. Goldman, who has applied her extensive experience in the private sector to the Data Science Department at the Hebrew University Business School since July 2024.

The numbers behind her career trajectory reflect a long tenure in high-level research and development. Prior to her current academic appointment, Goldman spent 15 years as a research scientist at General Motors' R&D organization in Herzliya. Before that stint, she served as a team leader at Samsung Telecom Research for three years. Her academic output includes more than 50 published papers, a body of work that supports her current role as an associate professor.

Goldman’s path to the business school began in Argentina, where she was born and raised until age 16. She moved to Israel with her family in January 1984 after attending a Jewish school in Buenos Aires where she studied in Yiddish, Hebrew, and Spanish. She completed high school at the Mae Boyer High School in 1986 and subsequently served in the army. She then returned to the Hebrew University, where she earned a BSc in computer science, mathematics, and electronics in 1991, an MSc in computer science in 1993, and a PhD in computer science in 1999 under the supervision of Prof. Jeff Rosenschein.

Between 1999 and 2005, she held research positions at Bar-Ilan University, the University of Massachusetts Amherst, and the University of Haifa. Her industry experience focused on integrating learning agents into vehicle user experiences at General Motors, aiming to help drivers focus on the road while understanding autonomous driving functions. This practical focus on human machine interaction now drives her pedagogical methods.

In a recent interview at her office, Goldman outlined a specific protocol for using artificial intelligence in her courses. She does not ban the technology but requires students to disclose its use and explain their process. Fully AI generated answers are rejected, and she informs students that she can detect machine written text. Instead, she encourages students to use AI for brainstorming while maintaining a critical perspective, such as checking for bias or verifying cited sources.

Her assessment strategy relies on a mix of classwork, presentations, and peer led activities to evaluate understanding in person. The curriculum also addresses the human element of technology, discussing values and professional responsibility. When asked about Bill Gates' concept of reserving certain jobs for humans, Goldman argued that the issue is not a binary choice of professions. She views it as a matter of understanding the benefits AI brings to different roles and identifying the critical skills needed to strengthen human performance in those contexts.

The Business School supports this focus with specific courses, including AI for Social Good, Responsible AI, and When AI Meets Humans and Society. The institution also operates a Free Listener Program that allows senior citizens to audit classes as the current fall semester begins. Goldman’s personal history remains tied to the campus where she met her husband, Prof. Roy Shenhar, a full professor at the Institute of Chemistry.

The couple first encountered each other on the stairs of the Ross Building on the Givat Ram campus in 1995. Following a Hebrew custom, he treated her to ice cream after their third unexpected meeting. They married in 1999, the same year she completed her doctorate. Her family background includes grandparents who emigrated to Argentina before the Holocaust, and she was the only child of Argentine born parents who made aliyah after she expressed a desire to grow up in Israel.

Goldman’s career illustrates a shift in the labor market for specialized tech roles. Her movement from automotive research to academia highlights the growing demand for experts who can bridge the gap between theoretical algorithms and practical human application. Her presence in the business school signals an institutional investment in preparing students for a workforce where AI tools are standard equipment rather than novel innovations.