Forget problem-solving. In the age of AI, it’s problem-finding that counts

• The global conversation around artificial intelligence (AI) has rapidly shifted from optimism to pessimism.But that fear is misplaced — AI tools will always require humans to develop and direct them to where they’re most useful.And the most essential human skill is going to shift from problem-solving to problem-finding, which demands cognitive diversity.

The global conversation about artificial intelligence (AI) has come full circle. It has shifted from widespread curiosity (what can AI do?) to boundless optimimism (AI will save the world) to sweeping pessimism (AI will destroy the world).AI undoubtedly raises a range of serious policy issues that we are only beginning to understand. But the tenor of the current discussion is unreasonably skeptical. AI will take away some of today’s jobs; we know this because every major technology advance has done so. But we also know that AI will create significantly more new jobs and potentially at higher wages. Rather than stifling humans, this technology will enable us to expand our knowledge, skills and productivity far beyond what most of us previously thought possible.The employees and companies that will thrive in this new era are those that embrace the technology and accept the inevitable disruption — rather than those reflexively opposing it. This will require a profound change in mindset, one that has little precedent in previous waves of technology.

The most essential human skill is going to shift from problem-solving to problem-finding.This contrasts with how workplaces have functioned since the Industrial Revolution. For decades, the emphasis has been on taking an obvious problem and finding an unobvious solution. But AI — when combined with human ingenuity — has unprecedented problem-solving power, so much so that it may free humans to spend more time in creative pursuits. The real challenge of applying AI productively is going to be “use case” discovery: identifying cross-disciplinary urgent problems that are best suited to AI technology. One good illustration of a surprising application of AI is boosting the productivity of salmon farming — a crucial step towards promoting sustainable aquaculture. Fish farmers are now using AI and machine perception tools (that can take in and process sensory information) to automate feeding time in accordance with the hunger levels of the fish. This reduces wasted feed, trimming a significant carbon emissions source, while improving salmon growth metrics. A recent collaboration between Tidal AI (a project inside X, Alphabet’s Moonshot Factory) and Cognizant will build on the initial success and expand to other sectors of what’s known as the Blue Economy, including shipping via sea transport. Already, companies can use machine learning models to analyze micro-weather systems, current speeds and port data traffic to optimize shipping route and port arrival times for lower fuel usage.

Problem-finding, unlike problem-solving, is going to demand cognitive diversity. To navigate this landscape successfully, businesses will require a more diversely skilled workforce — one that understands human behavior (sociology, psychology, anthropology), can create and optimize different processes (design thinking, six sigma, industry-specific knowledge) and engage audiences intellectually and emotionally through storytelling and design. Liberal arts majors will play as big of a role as STEM graduates. They will help humanize AI and give it more nuanced judgment. In the face of an increasingly complex and unpredictable world, organizations need to embrace the mantra that “great minds think different — not alike.” Homogeneous cultures tend to stifle cognitive diversity because of the pressure to conform. We can’t tackle 21^st century problems purely through top-down analysis and the application of big data. We need people who can ask great questions, see around corners, think outside the mainstream, understand context, tell us not only what’s happening but why it’s happening and look at the world through their customers’ eyes. That’s why cognitive diversity is so important to maintaining a business’s relevance to its customers and employees. The prevalence of immigrant founders, researchers and leaders in the US AI industry is a testament to the importance of different perspectives and backgrounds to ensure the country maintains its leadership position as the industry grows. According to one recent study, 28 of 43 (65%) of the top AI companies in the US were founded or co-founded by immigrants.It is clear that even as generative AI advances towards human-like capabilities, there is no near-term prospect that it will replace human work. Human imagination and ingenuity will be the source of human work indefinitely. People are still going to be essential to solving the