HRIntelligencer v2.04

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HRIntelligencer v2.04

Topics: HR Intelligencer, HRExaminer, John Sumser, by John Sumser

The HR/Recruiting marketplace is awash in blitzing jargon about the arrival of “AI” in the space. Most of what is in the market are more akin to statistics than it is to intelligence. It takes a lot of hard work to stay abreast of the concepts you need to master.

Ironically, if you were to use machine learning to forecast the effectiveness of this wave of AI, the forecast would be the momentum crests and the output disappoints….just like the last three waves. That’s the limit of the current tools. They are bound by history and can’t make innovative leaps. The tools can only forecast that what has already happened will happen again.

Once a new thing happens, it becomes increasingly predictable. Until it does, the machine will never guess it.

Current ‘AI’ is best suited for environments that operate like games (Jeopardy or Chess). It’s not so good when there are unlimited moves and the rules of the game change randomly. That’s really how our organizations (and their hiring processes) work.

This week’s articles are a breather. The tutorial section, with its bits about model robustness and expectation setting, are the gems.

Big Picture

How AI Will Define New Industries. A token bit of doom and gloom about the timing of job loss and creation as the result of AI. AI purchases are being made with cost savings and efficiency justifications. Money is flowing into the sector based on this job replacement theory. The longer bet is that AI will create the science that underlies new industries.

HR’s View

Audio Adversarial Examples: Targeted Attacks on Speech-to-Text. The largest concentration of systems with a voice interface will be in HR. That means that the Department must get savvy about hacking. Here’s a note on how to hack a voice based system.

Execution

Union heavyweight wants to ban UPS from using drones or driverless vehicles. The Teamsters want to swim against the coming high tide. Expect more labor pushback.

Tutorial

The working relationship between AIs and humans isn’t master/slave. We are being sold a vision of AI in which the machines are oracles, disagreement or agreement are the only choices in conversation.
Overfitting vs. Underfitting: A Conceptual Explanation. This is a good introduction to the questions you need to understand when evaluating a data model. ‘Overfitting’ means that the model (algorithm) perfectly regurgitates the data. ‘Underfitting’ means that the correlations are much looser. A ‘robust fit’ is somewhere between the two.

Quote of the Week

“Several years ago—shortly after Watson beat the Jeopardy champions—IBM invited me to an event where they showed off Watson’s capabilities. What impressed me at the demo wasn’t its ability to beat humans, but that fact that it could tell you why it came to a conclusion. While IBM hadn’t yet developed the user interface (which was irrelevant to Jeopardy), Watson could show probabilities that each potential answer (sorry, each potential question) was correct, based on the facts that supported each possible answer. To me, that’s really where the magic happened. Seeing the rationale behind the result raised the possibility of having an intelligent conversation with an AI.” – from The working relationship between AIs and humans isn’t master/slave.

About

Curate means a variety of things: from the work of vicar entrusted with the care of souls to that of an exhibit designer responsible for clarity and meaning. At the core, it means something about the importance of empathy in organization. HRIntelligencer is an update on the comings and goings in the Human Resource experiment with Artificial Intelligence, Digital Employees, Algorithms, Machine Learning, Big Data and all of that stuff. We present a few critical links with some explanation. The goal is to give you a way to surf the rapidly evolving field without drowning in information. We offer a timeless curation of the intersection of HR and the machines that serve it. We curate the emergence of Machine Led Decision Making in HR.

About the author

John Sumser

John Sumser is a principal analyst for HRExaminer, an independent analyst firm covering HR Technology and the intersection of people, tech, and work. John’s mix of experience over the course of his career gives him a broad and unique perspective on the industry. Like anyone trying to process a lot of information, he is two or three steps ahead in some areas and still learning about others. Sumser’s work includes deep research into the nooks and crannies of HR Technology to identify and explain rapidly evolving trends. Built on a foundation of engineering, design, and philosophy, John’s seeks to understand and advise clients on where their technology works best, for whom, and in what context. Each year, John examines the insides of hundreds of companies, their products, and ecosystems. He delivers vendor analysis by building the framework from which to deliver the critique. He is constantly connecting and making visible the front end of change. He can help you see the path of evolution and the risks on the journey. The HRExaminer is Sumser’s vehicle for understanding and explaining the inner workings of the industry. With three weekly podcasts, and written commentary, he covers emerging ideas, the state of the industry, and the executives who operate it.

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