Every futurist and forecaster I have talked to is convinced the The transformative technology of the next seven years is artificial intelligence. Everyone seems to be talking about AI. Unfortunately, most of these conversations do not lead to value creation or greater understanding. And, as an IT leader, you can bet these same conversations are reverberating throughout your organization — in particular, in the C-suite.

CIOs need to jump into the conversational maelstrom, figure out which stakeholders are talking about AI, inventory what they are saying, remediate toxic misconceptions, and guide the discussion toward value-creating projects and processes.

A brief history of AI hype and impact

AI has been part of the IT conversation since the term was coined by Stanford University computer scientist John McCarthy in 1956. Conversations around AI have generally tracked alongside multiple waves of enthusiasm and valleys of disappointment for the technology. In 1983 the prevalent conversation regarding AI was “It’s coming, it’s coming!” Thanks in part to Edward Feigenbaum and Pamela McCorduck’s The Fifth Generation: Artificial Intelligence and Japan’s Computer Challenge to the World. And then just a year later, in 1984, a subset of AI startup companies in Silicon Valley collapsed, spectacularly ushering in a period known as “the AI ​​winter.” At that point, AI conversations, when they occurred, typically concluded with the determination “not yet.”

Around the turn of the century we — most of us unknowingly — entered the age of artificial narrow intelligence (ANI), sometimes referred to as “weak AI.” ANI is AI that specializes in one area. John Zerelli, writing in A Citizen’s Guide to Artificial Intelligence,contends, “Every major AI in existence today is domain-specific” — ie, ANI.

The general path forward for ANI has been that it moves into a given domain and 7 to 10 years later it becomes impossible to compete/perform that particular task/activity without AI. Executives need to have tactical conversations regarding which domains and activity areas — aka, in AI-speak, which definable problems and measurable goals — should be targeted with which ANI resources.

By 2009 we were surrounded by invisible ANI, in the form of purchase, viewing, listening recommendations; medical diagnostics; university admissions tasks; job placement; etc. Today ANI is ubiquitous, invisible, and fundamentally misunderstood. Ray Kurzweil, computer scientist, futurist, and director of engineering at Google, keeps telling people that if AI systems went on strike “our civilization would be crippled.”

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