“One of the best things about predictions is that they tell you how often they will be wrong. If there is only a 10% chance of rain, you probably won’t take an umbrella. But one in ten times, you will still get wet. You will be surprised since there was a 90% chance of sun. But the prediction was correct.” - Heather Bussing
“Beyond the claim on the package, it is difficult to understand what an intelligent tool does. It’s even harder to understand what more it might do and how to improve it.” - John Sumser
Over the next two to five years HR’s most important asset will be its data. So, what percent of organizations already have a Data Governance policy? We surveyed 542 HR executives to find out.
We surveyed 542 HR executives and subject matter experts to find out what they really think about machines replacing people (and how they are evaluating new HR Tech).
We surveyed 542 HR executives and subject matter experts to find out what AI and intelligent tools were passing or failing in real-world deployments.
Recognizing AI means trying to remember, in the onslaught of machine opinion, that by accepting the machine’s opinion you are making a decision. ‘The machine suggests but the fault is yours’ will necessarily replace ‘The machine told me to do it.’ - John Sumser
“Bias related technical tools fall into two categories. The tech group assumes that things work better when humans are not involved. The human group assumes that people should be the decision-makers when lives and careers are affected.” – John Sumser
John Sumser’s video talk on where we are now with Intelligent Tools (AI and Data) in the HR and Recruiting space during the coronavirus pandemic. John covers the key points companies need to understand about AI and other intelligent tools to successfully implement systems and gain their full benefits.
“The number of tools available in Talent Acquisition outnumbers other tools by almost 10 to 1. New intelligent tool initiatives are most likely to start in the Recruiting silo or as a part of a larger suite initiative.” - John Sumser
“The nature of algorithmic decision-making is that the machine seeks hard lines for solutions. Most Human Resource questions involve subtle distinctions, case specifics, or other bits of context. When even a little compassion or conscience is required, machines can only assist.” - John Sumser
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