Artificial intelligence will lead to a rethinking in real estate education

Bob Martens

ERES from European Real Estate Society (ERES)

Abstract: The progressive integration of Artificial Intelligence (AI) in various areas of our lives raises a variety of questions and has considerable potential for polarization. The tension ranges from possibly exaggerated fears to unfulfillable hopes. Developments in the field of AI will certainly not leave real estate education unscathed. There is no doubt that text generation processes (using "prompt" as an instruction/specification) are turning some areas of performance assessment within the framework of (academic) education upside down. This makes it considerably more difficult to determine whether certain learning skills have actually been acquired. No extensive or lengthy training is required to generate detailed "answers" to any question using AI instruments. However, it is important to bear in mind that there is often a significant delay in keeping the knowledge base up to date. However, even in this environment, forecasting into the future would only be able to depict a supposed trend by means of extrapolation, as future developments have yet to take place. So far, even "real estate bubbles" could not be predicted precisely.What other implications could there be for education? Final theses, where an exposé has to be prepared first, are particularly tricky. The automated generation of an overview-like presentation using AI is not rocket science. It would probably hardly be noticeable that it was not created by humans. Subsequently, it would also be possible to write individual chapters in a similar way. However, it would still be necessary to do the literature research yourself to a certain extent. Or would it even be worth considering simply adopting the discussion of the research situation from a similar work? After all, tools for checking the probability that AI components are present in a textual representation are also on the rise. However, it is important to bear in mind that text components can also be falsely identified as AI-generated due to an existing range of fluctuation.

Keywords: Information Technology; Knowledge Exchange; Performance assessment; Text Generation (search for similar items in EconPapers)
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2024-01-01
New Economics Papers: this item is included in nep-ure
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