5 Myths About Cognitive Computing

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Artificial intelligence (AI) is one of the most frequently discussed topics in business today, but even more than most new technologies, its promise is sometimes obscured by a set of lingering myths—particularly among those whose exposure to the technology has been limited.

Professionals with first-hand experience have a different perspective, according to the 2017 Deloitte State of Cognitive Survey, which is based on interviews with 250 business executives who have already begun adopting and using AI and cognitive technologies. The responses of these early adopters shed considerable light on the current state of cognitive technology in organizations. Along the way, they help dispel five of the most persistent myths.

Myth 1: Cognitive is all about automation

It is rare to find a media report about AI that doesn’t speculate about job losses. Much of the reason for that is the commonly held belief that the technology’s primary purpose is automating human work. But that’s hardly the full story—in fact, there are significant uses for AI that do not involve substituting machine labor for human labor.

A Deloitte analysis of hundreds of AI applications in every industry reveals that these applications tend to fall into three categories: product, process, and insight. Product applications embed cognitive technologies into products or services to help provide a better experience for the end user, whether by enabling “intelligent” behavior or a more natural interface or by automating some of the steps a user normally performs. Process applications use cognitive technology to enhance, scale, or automate business processes, while insight applications use AI such as machine learning and computer vision to analyze data to reveal patterns, make predictions, and guide better decisions. In some cases, these technologies can be used to automate human work, but often they are used to do work that no human could have done otherwise.

Survey respondents clearly believe AI is important for more than just automation. While 92 percent say it is important or very important in their internal businesses processes, 87 percent rank it comparably for the products and services they sell. Cutting jobs through automation falls at the bottom of respondents’ list of potential benefits.

Myth 2: Cognitive kills jobs

Hand in hand with the belief that AI is all about automation is the expectation that it will destroy countless jobs. While it’s impossible to know what will happen in the distant future, both the objectives and the predictions of survey respondents suggest that job loss won’t be a major outcome. Only 7 percent of respondents selected “reduce headcount through automation” as their first choice among nine potential benefits of the technology; just 22 percent chose it among their top three.

When asked about the likelihood of job loss in the near future, respondents were similarly upbeat (Figure 1). Just over half expect that augmentation—smart machines and humans working side by side—will be the most likely scenario three years from now. Only 11 percent expect substantial job displacement; a larger percentage expect job gains or no substantial impact on jobs.

Respondents are more likely to be concerned about substantial job loss in the more distant future—22 percent expect it to happen in 10 years—but even then, a larger proportion (28 percent) expect augmentation to be the most likely outcome. The same percentage anticipate brand-new jobs.

Myth 3: The financial benefits are still remote

Many people view AI as a futuristic technology dominated by a handful of tech giants making headlines with high-profile applications. They believe most companies will not be able to achieve real financial benefits anytime soon. There is some truth to this view: The tech giants are indeed at the forefront of AI R&D and have capabilities not available to everyone. On the other hand, there are ordinary companies in every industry that have deployed AI and reaped financial benefits.

Read the source article at the Wall Street Journal.