## Artificial Intelligence Is Making Job Descriptions Obsolete, Executives Say

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A recent study suggests that seeing tasks taken away by machines has a demoralizing effect on human workers. The study, conducted by researchers at Cornell and Hebrew University of Jerusalem, details how humans were pitted against machines in a series of games. (Dan Robitzski provides a nice summary of the results in Futurism.)

As one (human) study participant put it: “I felt very stressed competing with the robot. In some rounds, I kept seeing the robot’s score increasing out of the corner of my eye, which was extremely nerve-racking.”

The Accenture  survey found close to three quarters of executives (74 percent) plan to use AI to automate tasks to a “large” or a “very large extent” in the next three years. At the same time, almost all (97 percent) also say its purpose is to enhance worker capabilities. They envision their people productively collaborating with intelligent machines.

At the same time, executives underestimate the willingness of employees to acquire the relevant skills,  according to the report’s authors, Ellyn Shook and Mark Knickrehm, both with Accenture. On average, executives deem only about a quarter (26 percent) of their workforce as “ready for AI adoption,” and cite resistance by the workforce as

a key obstacle. However, from the workers’ perspective, 68 percent of highly skilled workers and nearly half (48 percent) of their lower-skilled peers are positive about AI’s impact on their work. Overall, 67 percent of workers consider it important to develop their own skills to work with intelligent machines.

So, executives are optimistic that AI will enhance jobs, but don’t seem to quite grasp that their employees want to begin learning how to work with AI. To address this disconnect, Shook and Knickrehm provide the following advice to “reimagine work” and pivot the workforce in the coming age of AI:

Continually assess tasks and skills, not jobs.  “Companies need to identify the new kinds of tasks that must be performed,” and “allocate those tasks to people or machines.” Such an effort is ongoing and requires constant re-evaluation, ”some companies are finding that they need to correct their initial allocation of work to machines. After all, many AI systems are not fully autonomous and require considerable input and adjustment from humans.”

Create new roles. This is essential, as “AI enables people to take on higher-value work,” Shook and Knickrehm state. “Operational jobs will become more insight-driven and strategic, while mono-skilled roles will become multiskilled.” For example, “consumer brands will become increasingly dependent on AI chatbots to represent them in the mass market. Personality trainers will be required to develop the appropriate tone, humor and level of empathy needed for different situations. A health care AI agent must appreciate the sensitivity of patients in a different way than a supermarket AI agent would need to appreciate the mood and mindset of a groceries customer.”

Map skills to new roles. In many cases, employees  whose roles have been automated can take on higher-value work, “using AI and other technologies to provide more informed services to clients,” the Accenture authors state. “Take order processing and accounts payable collections. One Accenture client has produced a human–AI hybrid workforce where algorithms predict which orders have issues, such as a risk of cancellation or payment disputes. Employees can therefore spend more time paying attention to high-risk situations and be more proactive in mitigating negative outcomes. This approach has required training people to help them develop a range of expertise and capabilities — from industry sector knowledge to analytics and data interpretation, to the soft skills required to work with customers in new ways.”

Prioritize skills for development.  In the Accenture survey, the most important skills for effective AI deployments include resource management, leadership, communication, complex problem-solving and judgment/decision-making. “Among the most valuable human skills required to collaborate with AI will be the judgment skills needed to intervene and make or correct decisions when machines struggle to make them,” Shook and Knickrehm state.

Employ digital learning experiences. ”Digital learning methods, such as virtual reality and augmented reality technologies, can provide realistic simulations to help workers master new manual tasks so they can work with smart machinery,” the authors state.

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