{"title":"What AIs are not learning (and why)","authors":"Mark Stefik","doi":"10.1002/aaai.12213","DOIUrl":null,"url":null,"abstract":"<p>Today's robots do not yet learn the general skills that are necessary to provide home care, to be nursing assistants, to interact with people, or do household chores nearly as well as people do. Addressing the aspirational goal of creating service robots requires improving how they are created. Today's mainstream AIs are not created by agents learning from experiences doing tasks in real-world contexts and interacting with people. Today's robots do not learn by sensing, acting, doing experiments, and collaborating. Future robots will need to learn from such experiences in order to be ready for robust deployment in human service applications. This paper investigates what aspirational future autonomous human-compatible service robots will need to know. It recommends developing <i>experiential</i> (robotic) foundation models (FMs) for bootstrapping them.</p>","PeriodicalId":7854,"journal":{"name":"Ai Magazine","volume":"46 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aaai.12213","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ai Magazine","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aaai.12213","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Today's robots do not yet learn the general skills that are necessary to provide home care, to be nursing assistants, to interact with people, or do household chores nearly as well as people do. Addressing the aspirational goal of creating service robots requires improving how they are created. Today's mainstream AIs are not created by agents learning from experiences doing tasks in real-world contexts and interacting with people. Today's robots do not learn by sensing, acting, doing experiments, and collaborating. Future robots will need to learn from such experiences in order to be ready for robust deployment in human service applications. This paper investigates what aspirational future autonomous human-compatible service robots will need to know. It recommends developing experiential (robotic) foundation models (FMs) for bootstrapping them.
期刊介绍：
AI Magazine publishes original articles that are reasonably self-contained and aimed at a broad spectrum of the AI community. Technical content should be kept to a minimum. In general, the magazine does not publish articles that have been published elsewhere in whole or in part. The magazine welcomes the contribution of articles on the theory and practice of AI as well as general survey articles, tutorial articles on timely topics, conference or symposia or workshop reports, and timely columns on topics of interest to AI scientists.
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