When Artificial Intelligence Meets Research Thinking

Artificial intelligence is transforming the way research is conducted, from formulating computational solutions to writing code, analyzing data, and developing applications. To adapt research training to these changes, the Faculty will launch a new seminar in Semester B for graduate students, led by Dr. Ron Orbach: Artificial Intelligence for Scientific Research: From Idea Development to a Computational Tool.

The seminar is designed to provide participants with a structured and critical research approach to working with artificial intelligence, rather than focusing on the technical use of a specific AI tool. Participants will learn how to move from a precise definition of a research problem, through the design and implementation of a computational solution, to its evaluation and refinement.

The course will be based on group work, critical discussion, and peer review. To gain a deeper understanding of the challenges and limitations of AI, participants will present not only the tools they develop but also the process behind them, including unsuccessful attempts, coding errors, inaccurate outputs, hidden assumptions, and the modifications made along the way. The tools will be tested by fellow participants, and the feedback received will be used to improve them through an iterative cycle of development, evaluation, and revision that mirrors authentic research practice.

Through this seminar, the Faculty seeks to train researchers who not only use artificial intelligence, but also know how to critically evaluate its outputs and integrate it responsibly into their research. Alongside the development of new solutions, emphasis will be placed on validation, reliability, reproducibility, and transparency, principles that remain essential even as research tools continue to evolve.