AI needs people.
Despite all the panicky warnings seen in the mainstream media, AI will not be taking over and automating peoples’ jobs. AI will be replacing manual tasks, not job categories. However, something very important is missing from the picture: the involvement of the employees who will be charged with making AI and data-driven enterprises work. AI is only ramping up demand for the human talent needed to guide AI systems to engage in tasks relevant to the business, monitor and maintain the fairness and actionability of AI decisions, and to build, program, update, and ultimately retire these systems.
That’s one of the takeaways of Deloitte’s latest research on the state of AI, which finds a lack of employee input into the ways AI will be deployed and what it will deliver.
“Assembling the technology and talent required to build, scale and innovate with enterprise AI is an evolving challenge,” the study’s authors, Nitin Mittal, Irfan Saif, and Beena Ammanath, all with Deloitte, point out. “Over the last few years, many successful AI models and training sets have made their way into commercially available software and open-source offerings that can help jumpstart efforts and mitigate effects of the talent shortage. However, the ability for an organization to achieve differentiated tools and applications with AI still hinges in large part on the talent it is able to bring in-house.”
AI will amplify human capabilities in the workplace, and employees appear to be onboard with this addition to their organizations. Most survey respondents, 82%, indicate their employees believe that working with AI technologies will enhance their performance and job satisfaction.
However, there remain gaps in harnessing increased workforce optimism, the study’s authors add. There is awareness of the dual role humans and machines play in advancing data-driven enterprises. A sizeable segment of respondents, 43%, report their organization has appointed a leader responsible for helping workers collaborate better with intelligent machines. Also, 44% of all respondents reported using AI to assist in decision-making at senior-most levels.
There is also a significant gap in further actions needed to enable the hybrid human-machine workforce. Only 21% of all respondents reported actively educating workers on when to apply AI most effectively, the Deloitte study shows. In addition, only 25% reported providing access of user-friendly AI systems to nontechnical/nonspecialized workers, 30% reported including workers in participative design of AI, and 36% reported redesigning organizational practices in light of a mixed human and machine workforce.
Even among the organizations leading the way with AI, only a minority (32%) reported taking significant action needed to bring workers into greater collaboration with AI systems using innovation rewards or incentives for AI pilots.
“One of the biggest challenges to enabling stronger human and machine collaboration may be that leading practices around the talent models most likely to generate results are still emerging,” the Deloitte co-authors state. “That doesn’t mean all is unknown. An important element that has emerged in establishing positive working relationships with intelligent machines is to focus on fostering trust in algorithms by involving business specialists and frontline employees to help design them.”
AI needs people.