{"title":"为人工智能机器人建议的伦理道德打分:为什么我们需要网关和评级","authors":"Paul Kofman","doi":"10.1007/s10551-024-05753-5","DOIUrl":null,"url":null,"abstract":"<p>Unlike the many services already transformed by artificial intelligence (<i>AI</i>), the financial advice sector remains committed to a human interface. That is surprising as an AI-powered financial advisor (a <i>robo-advisor</i>) can offer personalised financial advice at much lower cost than traditional human advice. This is particularly important for those who need but cannot afford or access traditional financial advice. Robo-advice is easily accessible, available on-demand, and pools all relevant information in finding and implementing an optimal financial plan. In a perfectly competitive market for financial advice, robo-advice should prevail. Unfortunately, this market is imperfect with asymmetric information causing generalised advice aversion with a disproportionate lack of trust in robo-advice. Initial distrust makes advice clients reluctant to use, or switch to, robo-advice. This paper investigates the ethical concerns specific to robo-advice underpinning this lack of trust. We propose a regulatory framework addressing these concerns to ensure robo-advice can be an ethical resource for good, resolving the increasing complexity of financial decision-making. Fit for purpose regulation augments initial trust in robo-advice and supports advice clients in discriminating between high-trust and low-trust robo-advisors. Aspiring robo-advisors need to clear four licensing gateways to qualify for an AI Robo-Advice License (AIRAL). Licensed robo-advisors should then be monitored for ethical compliance. Using a balanced score card for ethical performance generates an ethics rating. This <i>gateways-and-ratings</i> methodology builds trust in the robo-advisory market through improved transparency, reduced information asymmetry, and lower risk of adverse selection.</p>","PeriodicalId":15279,"journal":{"name":"Journal of Business Ethics","volume":"89 1","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scoring the Ethics of AI Robo-Advice: Why We Need Gateways and Ratings\",\"authors\":\"Paul Kofman\",\"doi\":\"10.1007/s10551-024-05753-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Unlike the many services already transformed by artificial intelligence (<i>AI</i>), the financial advice sector remains committed to a human interface. That is surprising as an AI-powered financial advisor (a <i>robo-advisor</i>) can offer personalised financial advice at much lower cost than traditional human advice. This is particularly important for those who need but cannot afford or access traditional financial advice. Robo-advice is easily accessible, available on-demand, and pools all relevant information in finding and implementing an optimal financial plan. In a perfectly competitive market for financial advice, robo-advice should prevail. Unfortunately, this market is imperfect with asymmetric information causing generalised advice aversion with a disproportionate lack of trust in robo-advice. Initial distrust makes advice clients reluctant to use, or switch to, robo-advice. This paper investigates the ethical concerns specific to robo-advice underpinning this lack of trust. We propose a regulatory framework addressing these concerns to ensure robo-advice can be an ethical resource for good, resolving the increasing complexity of financial decision-making. Fit for purpose regulation augments initial trust in robo-advice and supports advice clients in discriminating between high-trust and low-trust robo-advisors. Aspiring robo-advisors need to clear four licensing gateways to qualify for an AI Robo-Advice License (AIRAL). Licensed robo-advisors should then be monitored for ethical compliance. Using a balanced score card for ethical performance generates an ethics rating. This <i>gateways-and-ratings</i> methodology builds trust in the robo-advisory market through improved transparency, reduced information asymmetry, and lower risk of adverse selection.</p>\",\"PeriodicalId\":15279,\"journal\":{\"name\":\"Journal of Business Ethics\",\"volume\":\"89 1\",\"pages\":\"\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Business Ethics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s10551-024-05753-5\",\"RegionNum\":1,\"RegionCategory\":\"哲学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Ethics","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s10551-024-05753-5","RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
Scoring the Ethics of AI Robo-Advice: Why We Need Gateways and Ratings
Unlike the many services already transformed by artificial intelligence (AI), the financial advice sector remains committed to a human interface. That is surprising as an AI-powered financial advisor (a robo-advisor) can offer personalised financial advice at much lower cost than traditional human advice. This is particularly important for those who need but cannot afford or access traditional financial advice. Robo-advice is easily accessible, available on-demand, and pools all relevant information in finding and implementing an optimal financial plan. In a perfectly competitive market for financial advice, robo-advice should prevail. Unfortunately, this market is imperfect with asymmetric information causing generalised advice aversion with a disproportionate lack of trust in robo-advice. Initial distrust makes advice clients reluctant to use, or switch to, robo-advice. This paper investigates the ethical concerns specific to robo-advice underpinning this lack of trust. We propose a regulatory framework addressing these concerns to ensure robo-advice can be an ethical resource for good, resolving the increasing complexity of financial decision-making. Fit for purpose regulation augments initial trust in robo-advice and supports advice clients in discriminating between high-trust and low-trust robo-advisors. Aspiring robo-advisors need to clear four licensing gateways to qualify for an AI Robo-Advice License (AIRAL). Licensed robo-advisors should then be monitored for ethical compliance. Using a balanced score card for ethical performance generates an ethics rating. This gateways-and-ratings methodology builds trust in the robo-advisory market through improved transparency, reduced information asymmetry, and lower risk of adverse selection.
期刊介绍:
The Journal of Business Ethics publishes only original articles from a wide variety of methodological and disciplinary perspectives concerning ethical issues related to business that bring something new or unique to the discourse in their field. Since its initiation in 1980, the editors have encouraged the broadest possible scope. The term `business'' is understood in a wide sense to include all systems involved in the exchange of goods and services, while `ethics'' is circumscribed as all human action aimed at securing a good life. Systems of production, consumption, marketing, advertising, social and economic accounting, labour relations, public relations and organisational behaviour are analysed from a moral viewpoint. The style and level of dialogue involve all who are interested in business ethics - the business community, universities, government agencies and consumer groups. Speculative philosophy as well as reports of empirical research are welcomed. In order to promote a dialogue between the various interested groups as much as possible, papers are presented in a style relatively free of specialist jargon.