2020-02-13 HR Examiner article prediction machine 9 trends in ai and intelligent tools that are shaping hr tech photo img cc0 by wyron a GY38n9WKjQI unsplash 544x306px part1.jpg

“Humans are not good at making decisions. And yet, the proliferation of intelligent tools will give every decision-maker at every level a range of conflicting inputs from which a decision must be made.” - John Sumser

Part I


Predictions Everywhere, Sensors Everywhere, Predictive Models Everywhere, Conflicting Predictions Everywhere


Catch Up on the Series

Haven’t read parts 1 or 2? Catch up on the series by clicking on the links to each article at the bottom of this post. Click here to navigate to the links.

There will be a prediction everywhere it is possible to have a prediction. There will be a sensor everywhere it’s possible to install a sensor. There will be a predictive model everywhere one is possible.

It won’t be very long before enterprise intelligent tools start to look outmoded when compared to the tools employees already have. Both Google and Microsoft are ‘intelligencing’ their various products and applications. Any employee can set up an Azure account and build their own intelligent tools.

In this series we’ll be taking a look at nine trends that are shaping AI and intelligent tools in HR Tech.

I. It’s Not AI (most of the time), It’s Intelligent Tools
(What to Call This Next Step in Technology)

2017-04-21 HRExaminer photo img sumser john bio pic IMG 3046 black and white full 200px.jpg

John Sumser is a Principal Analyst for HRExaminer.

Our expectations for this emerging technology (regardless of what we call it) will continue to change for the foreseeable future. It isn’t really AI most of the time, just as it wasn’t Big Data, People Analytics, or Predictive Analytics. The trend is driven by nearly free processing and storage applied to fundamental business problems. We’ve been calling it ‘intelligent tools.’

II. Millions of Data Models Usher In a New Kind of Management

Currently, each proposed intelligent tool is viewed as a transactional phenomenon with little or no relationship to other intelligent tools. In the medium term (five years), the real question will be what to do with all the models. The care, feeding, maintenance, improvement, and repair of data models en masse will be the dominant concern of HR’s data professionals. A class of employees devoted to HR Data as Infrastructure is quickly emerging.

III. Employees Learn to Deal With Conflicting Predictions and Conflicting Consequences (The Next Layer of Bias)

Humans are not good at making decisions. And yet, the proliferation of intelligent tools will give every decision maker at every level a range of conflicting inputs from which a decision must be made. Machines cannot forecast the consequences of their recommendations. The human use of machine recommendations will be guided by the human capacity to imagine the consequences of a given decision in the ‘real’ world.

IV. Skills Shortages Understated

Hierarchical organizations are responsible for training generations of workers to see their jobs as following specific orders. Because intelligent tools seem to deliver answers (unless the interface is sufficiently modernized), companies will suffer when their employees fail to question the machine’s output. Learning to take the machine’s suggestions, recommendations, forecasts, and insights as ‘just one opinion’ is the foundation of next generation skills. As simple as it sounds, the workforce is ill equipped to out-think its tools. Workers need to learn how to manage their new digital counterparts.

V. Job Loss Expectations Overstated

While mindlessly repetitive tasks are already being automated, their volume in a contemporary economy is limited. Many of the jobs that could be executed by machine have a capital investment hurdle that precludes their elimination. While it is certain that intelligent tools will bring great waves of change with their emergence, it is unlikely that job losses will be significant. Further complicating job loss forecasts are the inherent limitations of machine intelligence and the need for humans to manage them.

Stop by next week for the next chapter in this series on the trends that are shaping intelligent tools and AI in HR Technology.

Catch Up on the Series

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