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Spring 2020 Buffalo Business 21 How artificial intelligence will impact self-employment People who are self-employed in sev- eral popular, lower- paying jobs are at the greatest risk of being displaced by artificial intelligence (AI), according to new School of Management research. Published by the Center for Research on Self-Employment, the study found that with both self-employment and AI invest- ment on the rise, independent salespeople, drivers, and agriculture and construction workers face the greatest danger from computerization, because the work is routine and low in technical expertise. "Those who are self-employed just don't have the same access to AI resources that corporate employees do, which makes it difficult for them to keep up with technological advancements," says Kate Bezrukova, associate professor of organization and human resources. The researchers reviewed every study to date on AI and the self-employed, and compared those findings to their own research on teams (more than 20 published studies across many work settings). They found that while certain jobs are at risk, not every profession is in jeopardy. In general, occupations that require employees to work together, negotiate and make decisions are less likely to be elimi- nated because these attributes are harder for AI to imitate. These careers typically have higher pay, such as lawyers, managers, and business and medical professionals. The study also found that technical jobs, such as maintenance for robots and hardware distribution for AI, may see significant growth. "It's like when the computer revolu- tion hit decades ago—there was great fear that computers would replace people," says Bezrukova. "But work just shied and IT positions grew because we needed more support for our computers and networking." Looking ahead, the study recommends creating public awareness programs about the opportunities and risks of AI, updat- ing education curriculums to integrate shiing skills, and conducting more research on AI at work, specifically for the self-employed. Bezrukova collaborated on the study with Terri L. Griffith, Keith Beedie Chair in Innovation and Entrepreneurship at Simon Fraser University's Beedie School of Business, and Chester Spell, professor of management at Rutgers University School of Business–Camden. Bezrukova managers for cloud computing products and services, and engineers for cloud computing technology. "Cloud resource management is a complex issue, with multiple perfor- mance metrics to consider," says Ramesh. "Administrators in cloud data centers can use these algorithms to develop efficient service-level agreements and cost-effectively manage the computing resources involved in those agreements." Ramesh collaborated on the study with Zhiling Guo, associate professor of information systems at Singapore Management University, and Jin Li, assistant professor at Xidian University School of Economics and Management.