{"title":"守护智能企业:确保人工智能在商业决策中的应用","authors":"P. Bhattacharya","doi":"10.1109/ICIM49319.2020.244704","DOIUrl":null,"url":null,"abstract":"Artificial Intelligence (AI) is increasingly permeating into the commercial world, and the consequences have raised concerns about the security of these technologies. This paper explores the use of AI technologies in business organizations and the security implications for such organizations, especially when they are used for making business decisions. The contribution of this paper is that it presents a new systematic model that discusses the security implications of AI-enabled business decision making, based on a synthesis of the literature on security concerns of AI technologies and business decision making. The paper also presents an opportunity to empirically test this new model using diverse case studies.","PeriodicalId":129517,"journal":{"name":"2020 6th International Conference on Information Management (ICIM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Guarding the Intelligent Enterprise: Securing Artificial Intelligence in Making Business Decisions\",\"authors\":\"P. Bhattacharya\",\"doi\":\"10.1109/ICIM49319.2020.244704\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial Intelligence (AI) is increasingly permeating into the commercial world, and the consequences have raised concerns about the security of these technologies. This paper explores the use of AI technologies in business organizations and the security implications for such organizations, especially when they are used for making business decisions. The contribution of this paper is that it presents a new systematic model that discusses the security implications of AI-enabled business decision making, based on a synthesis of the literature on security concerns of AI technologies and business decision making. The paper also presents an opportunity to empirically test this new model using diverse case studies.\",\"PeriodicalId\":129517,\"journal\":{\"name\":\"2020 6th International Conference on Information Management (ICIM)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 6th International Conference on Information Management (ICIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIM49319.2020.244704\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 6th International Conference on Information Management (ICIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIM49319.2020.244704","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Guarding the Intelligent Enterprise: Securing Artificial Intelligence in Making Business Decisions
Artificial Intelligence (AI) is increasingly permeating into the commercial world, and the consequences have raised concerns about the security of these technologies. This paper explores the use of AI technologies in business organizations and the security implications for such organizations, especially when they are used for making business decisions. The contribution of this paper is that it presents a new systematic model that discusses the security implications of AI-enabled business decision making, based on a synthesis of the literature on security concerns of AI technologies and business decision making. The paper also presents an opportunity to empirically test this new model using diverse case studies.