2019-06-17-hrexaminer-article-john-sumser-Its-Not-AI-but-it-is-a-Wonderland-of-Experimentation-photo-img-cc0-via-pexels-by-rawpixel-acrylic-art-artistic-1083617-full-544x635px.jpg

“What I’ve found instead was an amazing wonderland of experimentation. The companies I’ve covered in our reports are all charting unique paths through technology in pursuit of demonstrable value. It is a new flavor of Research and Development.”


In the process of conducting the research for our AI reports over the last couple of years I’ve visited with experts in AI from Stanford, Berkeley, MIT, Harvard, and the University of Toronto. When we asked these experts what AI was, they painted a picture of a conversational consciousness. In that conversation, the intelligent machine would be able to innovate on the topic and interpret/respond to nuance and inference. Academics have a pretty consistent definition of AI.

That’s not happening in the halls of HR Technology. The most advanced tools are extremely mechanistic and limited when compared to a dynamic conversational intelligence. Companies that lay a strong claim to having AI functions look silly for the most part (although there are a few exceptions).

What I’ve found instead was an amazing wonderland of experimentation. The companies I’ve covered in our reports are all charting unique paths through technology in pursuit of demonstrable value. It is a new flavor of Research and Development.

In the 20th century, R&D laboratories were huge environments with extensive teams of really smart people. The conventional wisdom was that if you handled the environment well enough, someone would produce something interesting. It was a model pioneered by Thomas Edison, perfected by the telephone companies, and remains in companies like Intel, Apple, HP, Cisco, and other tech giants.

That approach doesn’t really work in an environment of industrial disruption. We learned early in the digital era that the pioneers of bulk R&D failed because they couldn’t get out of their own way. Polaroid failed to thrive, disc makers went under, music dematerialized. Investors began to distrust large-scale technical innovation initiatives.

The result is a generation of technical companies that resemble single functions on a dropdown menu more than whole companies. The new model is that software companies are not only responsible for R&D, they have to prove its value in the market. Having a good idea is not enough. Investors are more interested in good ideas that make money.

In our first report I looked at thirty companies engaged in a deep exploration of a slice of the HR continuum (some likelier to succeed than others). Even when focused on the exact same problem and solution, they are profoundly different. When a new technology emerges, the early adopters are rewarded disproportionately for investing early. At the same time, there is an enormous range of career risks associated with backing the wrong horse.

These are still early days for a very different way of interacting with software. It is not Artificial Intelligence, but it is very different from the software we are used to. There are ethical issues, new technologies, and new approaches to intractable problems.



 
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