Google paper advocates for LLMs to express uncertainty clearly
Google Research has published a paper advocating for large language models (LLMs) to better express their uncertainty. The research introduces a new metric called 'faithful response uncertainty' to measure the gap between a model's confidence and its actual certainty. The authors emphasize the need for models to communicate uncertainty effectively to enhance AI trustworthiness.
- ▪The paper argues that current LLMs struggle to match their verbal confidence with their internal certainty.
- ▪The new metric evaluates whether a model's stated confidence aligns with its computed confidence.
- ▪The authors recommend that models should hedge their responses when there is genuine doubt.
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Google paper advocates for LLMs to express uncertainty clearly New research from Google introduces a metric for measuring whether AI models honestly communicate what they don't know, with implications for anyone relying on AI-generated analysis. Share Add us on Google by Editorial Team May. 25, 2026 window.sevioads = window.sevioads || []; var sevioads_preferences = []; sevioads_preferences[0] = {}; sevioads_preferences[0].zone = "01f21ccf-2092-46b1-9ac7-8c44cc782e0f"; sevioads_preferences[0].adType = "native"; sevioads_preferences[0].inventoryId = "c5700508-581b-472c-8fdd-a931cdbfc8e1"; sevioads_preferences[0].accountId = "1e47efc1-ec2d-4fca-a8b9-354e249e5095"; sevioads.push(sevioads_preferences); Google Research has published a paper arguing that large language models need to get much…
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