Evaluating Trust in AI
Researchers at Binghamton University, the University of Hawaii, and Clemson University have developed a software tool to automate the evaluation of trust in human/AI conversations.
Currently, evaluating the extent to which artificial intelligence (AI) gains a user's trust is done manually through surveys, interviews, and focus groups.
Despite the billions of lines of code written for execution by a large language model (LLM) to win a human's trust, in the end "trust" alone is a blunt instrument.
The new software tool sharpens and automates the identification of trust-building turns in a human/AI conversation, which consists of a series of turns, including queries from the human and responses from the AI.
- A "turn" in a human/AI conversation is a query from the human or a response from the AI.
- The collection of these turns over time makes up the whole conversation.
Author's summary: AI trust evaluation is now automated.
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