IRBs are composed of academics versed in the research and the ethics around the acquisition and use of information. In academia, data acquisition from human subjects is usually supervised by an in-house institutional review board (IRB) whose approval researchers must have to obtain access to the people involved, research funds, or permission to publish. But first we’ll offer a brief overview of the organizational requirements for a robust ethical-review process. In the following pages we’ll discuss each of them and look at how AI technologies increase the risk of data abuse. We call these issues the five Ps (see the exhibit “The Five Ps of Ethical Data Handling”). ![]() A Bing chatbot even stated in an exchange that it would prioritize its own survival over that of the human it was engaging with.Īs they examine new projects that will involve human-provided data or leverage existing databases, companies need to focus on five critical issues: the provenance of the data, the purpose for which it will be used, how it is protected, how the privacy of the data providers is ensured, and how the data is prepared for use. What they do with that intelligence can be scary. Those fears will only intensify with the use of chatbots such as ChatGPT, Bing AI, and GPT-4, which acquire their “intelligence” from data fed them by their creators and users. And stories abound about how AI-driven decisions discriminate against women and minority members in job recruitment, credit approval, health care diagnoses, and even criminal sentencing, stoking unease about the way data is collected, used, and analyzed. In 2018 the Cambridge Analytica scandal alone wiped $36 billion off Facebook’s market value and resulted in fines of nearly $6 billion for Meta, Facebook’s parent company. ![]() Over the past few years the EU has fined companies more than 1,400 times, for a total of nearly €3 billion, for violations of the General Data Protection Regulation (GDPR). Which customers are likely to buy what products and when? Which competitors are likely to move ahead or fall behind? How will markets and whole economies create commercial advantages-or threats? Data and analytics give companies better-informed and higher-probability answers to those and many other questions.īut the need for data opens the door to abuse. The ability to encode, store, analyze, and share data creates huge opportunities for companies, which is why they are enthusiastically investing in artificial intelligence even at a time of economic uncertainty.
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