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Man vs. Machine - Comparing the performance of Humans vs. LLMs vs. Human and LLMs in Medicine
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Man vs. Machine - Comparing the performance of Humans vs. LLMs vs. Human and LLMs in Medicine

📌 Key facts

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🙏Mission: Exploring whether humans, LLMs or the combination of both, humans and LLMs, is more successful/effective in medicine.
  • When: Start anytime. Applications are open!
  • How to apply: Send us an e-mail isabel.tretow@tum.de with your CV and a grade report.

💡 Background

Large Language Models (LLMs) are increasingly used for a variety of areas - one of them is in medicine. This study is supposed to be a systematic literature review, focused on examining in which areas LLMs are most commonly used, how they perform compared to only humans performing a task as well as comparing their performance when humans and LLMs jointly perform a task. Specifically, different use case areas should be identified, different types of LLMs used (e.g., depending on the use case), key benefits of LLMs, humans and their combination.

🦾Who We Are

The Chair for Strategy and Organization is focused on research with impact. This means we do not want to repeat old ideas and base our research solely on the research people did 10 years ago. Instead, we currently research topics that will shape the future. Topics such as Agile Organisations and Digital Disruption, Blockchain Technology, Creativity and Innovation, Digital Transformation and Business Model Innovation, Diversity, Education: Education Technology and Performance Management, HRTech, Leadership, and Teams.. We are always early in noticing trends, technologies, strategies, and organisations that shape the future, which has its ups and downs.

🎓 Profile

  • Interest in medicine (for now, overarching focus, no specific area in focus)
  • Interest in LLMs and the interaction of humans and LLMs
  • Organizational skills and proactive communication
  • Reliable and self-driven working style

📚 Further Reading

Goh E, Gallo R, Hom J, et al. Large Language Model Influence on Diagnostic Reasoning: A Randomized Clinical Trial. JAMA Netw Open. 2024;7(10):e2440969. doi:10.1001/jamanetworkopen.2024.40969

Hager, P., Jungmann, F., Holland, R. et al. Evaluation and mitigation of the limitations of large language models in clinical decision-making. Nat Med 30, 2613–2622 (2024). https://doi.org/10.1038/s41591-024-03097-1 Vaccaro, M., Almaatouq, A. & Malone, T. When combinations of humans and AI are useful: A systematic review and meta-analysis. Nat Hum Behav 8, 2293–2303 (2024). https://doi.org/10.1038/s41562-024-02024-1 📝 How to Apply

If you are interested, please contact Isabel.Tretow@tum.de by submitting your CV and grade report. Please also briefly outline your tentative research idea (research question, data and methods, possible outcomes with a tentative outline all in word as *.docx)

We're greatly looking forward to hearing more about you!

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Apply now!

📬 Contact

Put your contact information here.

Isabel Tretow (Chair for Strategy and Organization)

isabel.tretow@tum.de

© Chair for Strategy and Organization, Technical University of Munich

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