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Negotiation is a hard-to-measure competency, involving a dynamic balance of relational and outcome-oriented dimensions. Generative AI has opened avenues for delivering real-time assessment and feedback after a negotiation simulation. However, there is a tension between the “black box” architecture of GenAI and the “glass box” approach of stealth assessment. This case study uses a mixed-method approach to compare ratings and feedback given by GenAI and a human expert on seven negotiation transcripts. The results illustrate that with predetermined criteria, GenAI provides more formulaic feedback across various simulations, while the human expert’s feedback is more contextually sensitive and adapted to the uniqueness of each negotiation exchange. Implications for stealth assessment and negotiation feedback are discussed.
Cao et al. (Tue,) studied this question.
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