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Mind the gap

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The list of issues to address as a neophyte AI developer or AI data scientist is daunting.

The students at MIT will certainly be exposed to those issues top of mind in the machine learning community, but by the end of the course, will they be masters of the emerging discipline of XAI, or explainable AI, which posits that all AI programs should be able to explain themselves automatically to their human designers? The list of issues to address as a neophyte AI developer or AI data scientist is daunting.

So, one reason that progress toward broad-based adoption of cognitive computing is slow across many industries is simply the “gap,” the shortfall in trained people. But another perhaps equally key reason is that the talent that has been coming into the market is unevenly distributed.

The companies that have already bet their businesses on machine learning systems are hiring and acquiring as many talented people as they can find, in both research and applied technology. They are not only the top internet firms—Amazon, Google, Facebook—but also the likes of Microsoft and Apple, Intel and Salesforce, and beyond those giants are the many specialized consumer-facing sites like TripAdvisor, Netflix, Uber and more. What all of those firms share is that they are making extraordinary profits with that technology, and they can therefore afford to pay outsized wages to the scarce people they can find with the requisite skills. This effect raises a high barrier to most “normal” industrial firms that are not benefitting as directly from the new attention-driven business models.

For most of industry, the calls of the conductor are coming through loud and clear: “Mind the gap.” In many cases, firms face the kind of existential risk once experienced by the buggy whip manufacturers. But in virtually all cases, finding strategies to partner or acquire or develop the talent to compete in cognitive computing is an imperative. Coming to an accurate understanding of the competence and work profiles that will lead teams to successful AI outcomes is becoming a foundation for the next generation of the business. And getting the enterprise feet and luggage across the gap could be a big part of the legacy accomplishments for today’s executives.

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