{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/to-trust-or-not-to-trust-a-regressor","title":"To Trust or Not to Trust a Regressor: Estimating and Explaining Trustworthiness of Regression Predictions","arxiv_id":"2104.06982","date":"2021-04-14","proceeding":null,"authors":["Kim de Bie","Ana Lucic","Hinda Haned"],"abstract":"In hybrid human-AI systems, users need to decide whether or not to trust an algorithmic prediction while the true error in the prediction is unknown. To accommodate such settings, we introduce RETRO-VIZ, a method for (i) estimating and (ii) explaining trustworthiness of regression predictions. It consists of RETRO, a quantitative estimate of the trustworthiness of a prediction, and VIZ, a visual explanation that helps users identify the reasons for the (lack of) trustworthiness of a prediction. We find that RETRO-scores negatively correlate with prediction error across 117 experimental settings, indicating that RETRO provides a useful measure to distinguish trustworthy predictions from untrustworthy ones. In a user study with 41 participants, we find that VIZ-explanations help users identify whether a prediction is trustworthy or not: on average, 95.1% of participants correctly select the more trustworthy prediction, given a pair of predictions. In addition, an average of 75.6% of participants can accurately describe why a prediction seems to be (not) trustworthy. Finally, we find that the vast majority of users subjectively experience RETRO-VIZ as a useful tool to assess the trustworthiness of algorithmic predictions.","url_abs":"https://arxiv.org/abs/2104.06982v2","url_pdf":"https://arxiv.org/pdf/2104.06982v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"to-trust-or-not-to-trust-a-regressor","repo_url":"https://github.com/kimdebie/retroviz-tutorial","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2104.06982","atlas_url":"https://app.syntology.ai/?focus=2104.06982","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}