Q&A on AI and Intelligent Tools with John Sumser

Watch this video Q&A with John Sumser on AI and Intelligent Tools in the HR and Recruiting space during the coronavirus pandemic.

User Interface Design Ethics in AI – Part II

“One area Manhattan-based Greenhouse focused on is predicting the Recruiting Department’s results. Hiring and finance managers always want to know when the new person will be hired and whether they will show up.” - John Sumser

User Interface Design Ethics in AI – Part I

“The essence of traditional interfaces is a deep emphasis on clarity (or intuitiveness). One look at the interface tells you what to do. That doesn’t work with likelihoods. Intelligent output like you’d find in machine learning requires the user to think before deciding.” - John Sumser

How to Not Screw Up Predictions (Exercise: Consider and Decide)

“Predictions don’t give you answers. They give you more questions. And it’s essential to explore those questions before you make decisions based on predictions, especially when people and their careers are involved.” - Heather Bussing

How to Not Screw Up Predictions (when you’re working with AI and Intelligent Tools)

“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

What intelligent tools are organizations using (and what’s their growth potential)?

“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

Do You Have A Data Governance Process?

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.

What Do HR Professionals Really Think About Machines Replacing People (and how are they evaluating new HR Technologies)?

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).

Abandonment of AI and Intelligent Tool Projects (and what it actually means)

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.

We Don’t Know If We Can Eliminate Bias From Tech

“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