F. Reeder, Carol Pomales, Diane M. Kotras, James Lockett
{"title":"使国防部的未来能够测试和评估人工智能系统","authors":"F. Reeder, Carol Pomales, Diane M. Kotras, James Lockett","doi":"10.1109/MIM.2023.10208252","DOIUrl":null,"url":null,"abstract":"While of great potential benefit, Artificial Intelligence (AI) presents new challenges and exacerbates some existing ones for the Department of Defense (DoD) Test and Evaluation (T&E) community. T&E professionals will need to work to ensure that AI-enabled systems' (AIES) complex and variable nature can be sufficiently characterized by the boundaries of acceptable performance. To help the DoD understand and prepare for the challenges of T&E of AIES, we convened a group of AI adoption, AI development, and policy experts to develop a future vision of T&E with respect to AI. The result is a vision of T&E that incorporates the unique requirements for AIES, encompassing policy changes, user engagement approaches, measures and metrics, data, infrastructure, and cybersecurity. This future vision is accomplishable by identifying focus for efforts across DoD, academia, Federally Funded Research and Development Centers (FFRDCs) and industry to provide processes, policy/standards, tools, data, and infrastructure. Thus, we can assure a more feasible future for the T&E of AIES.","PeriodicalId":55025,"journal":{"name":"IEEE Instrumentation & Measurement Magazine","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enabling the Department of Defense's Future to Test and Evaluate Artificial Intelligence Enabled Systems\",\"authors\":\"F. Reeder, Carol Pomales, Diane M. Kotras, James Lockett\",\"doi\":\"10.1109/MIM.2023.10208252\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While of great potential benefit, Artificial Intelligence (AI) presents new challenges and exacerbates some existing ones for the Department of Defense (DoD) Test and Evaluation (T&E) community. T&E professionals will need to work to ensure that AI-enabled systems' (AIES) complex and variable nature can be sufficiently characterized by the boundaries of acceptable performance. To help the DoD understand and prepare for the challenges of T&E of AIES, we convened a group of AI adoption, AI development, and policy experts to develop a future vision of T&E with respect to AI. The result is a vision of T&E that incorporates the unique requirements for AIES, encompassing policy changes, user engagement approaches, measures and metrics, data, infrastructure, and cybersecurity. This future vision is accomplishable by identifying focus for efforts across DoD, academia, Federally Funded Research and Development Centers (FFRDCs) and industry to provide processes, policy/standards, tools, data, and infrastructure. Thus, we can assure a more feasible future for the T&E of AIES.\",\"PeriodicalId\":55025,\"journal\":{\"name\":\"IEEE Instrumentation & Measurement Magazine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Instrumentation & Measurement Magazine\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1109/MIM.2023.10208252\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Instrumentation & Measurement Magazine","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1109/MIM.2023.10208252","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Enabling the Department of Defense's Future to Test and Evaluate Artificial Intelligence Enabled Systems
While of great potential benefit, Artificial Intelligence (AI) presents new challenges and exacerbates some existing ones for the Department of Defense (DoD) Test and Evaluation (T&E) community. T&E professionals will need to work to ensure that AI-enabled systems' (AIES) complex and variable nature can be sufficiently characterized by the boundaries of acceptable performance. To help the DoD understand and prepare for the challenges of T&E of AIES, we convened a group of AI adoption, AI development, and policy experts to develop a future vision of T&E with respect to AI. The result is a vision of T&E that incorporates the unique requirements for AIES, encompassing policy changes, user engagement approaches, measures and metrics, data, infrastructure, and cybersecurity. This future vision is accomplishable by identifying focus for efforts across DoD, academia, Federally Funded Research and Development Centers (FFRDCs) and industry to provide processes, policy/standards, tools, data, and infrastructure. Thus, we can assure a more feasible future for the T&E of AIES.
期刊介绍：
IEEE Instrumentation & Measurement Magazine is a bimonthly publication. It publishes in February, April, June, August, October, and December of each year. The magazine covers a wide variety of topics in instrumentation, measurement, and systems that measure or instrument equipment or other systems. The magazine has the goal of providing readable introductions and overviews of technology in instrumentation and measurement to a wide engineering audience. It does this through articles, tutorials, columns, and departments. Its goal is to cross disciplines to encourage further research and development in instrumentation and measurement.
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