“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
“From data quality to regulatory compliance, there are 28 key parameters to evaluate when considering a purchase of intelligent tools for HR. We’ve also provided 40 key questions to ask to evaluate an AI or Intelligent Software vendor solution.” - John Sumser
“The question is when, not whether, organizations will use intelligent tools. The future is inevitable. The sooner you get started, the easier it will be to keep up. Conversely, the longer you wait, the more competitive advantage you will lose.” - John Sumser
“AI is quickly becoming a table-stakes commodity. Since it will often be unlabeled, the question will be, ‘How do we recognize it?’ This is not the discovery of a rarity, it’s remembering to be effective in the flow of recommendations, suggestions, forecasts, probabilities, and interpretations that fill our every transaction. Recognizing AI means trying to remember, in the onslaught of machine opinion, that by accepting the machine’s opinion you are making a decision.” - John Sumser
In times of scarcity or crisis like the pandemic, the rules change. Business continuity becomes the governing question. Michael Kannisto, Ph.D. looks at MVP’s during the Pandemic: Modern Succession Planning for Operational Continuity.
In March 2020, many workers fled their offices for the safety of home. The change was hurried by necessity, but with little understanding of the consequences. Stella Lupushor has more on Zoom and a bit about the downsides of decentralized work.
Fara Rives discusses how AI can help overcome a key roadblock with outdated employee and contractor information. AI Can Improve Talent Mobility.
It’s one of the most common workplace mistakes: applying the wrong solution to a situation simply because you went with your “go to”move. Hello Hammer, Meet Nail from Dr. Todd Dewett.
In March 2020, many workers fled their offices for the safety of home. The change was hurried by necessity, but with little understanding of the consequences. Stella Lupushor has more on Zoom and a bit about the downsides of decentralized work.
Fara Rives discusses how AI can help overcome a key roadblock with outdated employee and contractor information. AI Can Improve Talent Mobility.
It’s one of the most common workplace mistakes: applying the wrong solution to a situation simply because you went with your “go to”move. Hello Hammer, Meet Nail from Dr. Todd Dewett.
Heather Bussing writes, “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.” Read Heather’s two-part series on How to Not Screw Up Predictions (when you’re working with AI and Intelligent Tools).
In part two of her series, Heather Bussing shares an exercise and analysis on How to Not Screw Up Predictions (Exercise: Consider and Decide).
John Sumser writes, “The work of synthesizing, prioritizing, and then acting on the data is increasingly what work is all about. And that’s where the new tools come in handiest.” Modern HR Data Types and Attributes (From Text to Machine Generated or Monitored Data).
“Ethical questions about how we use data and technology in organizations are growing in prominence and importance and bias is the noisiest of the ethics questions now facing HR.” John Sumser has more in, Bias in AI: Are People the Problem or the Solution?
In this combined article and podcast the topic is Open Feedback and Joyous Co-founder Mike Carden is in the driver’s seat. Open Feedback with Mike Carden (article and Podcast).
In part two of her series, Heather Bussing shares an exercise and analysis on How to Not Screw Up Predictions (Exercise: Consider and Decide).
John Sumser writes, “The work of synthesizing, prioritizing, and then acting on the data is increasingly what work is all about. And that’s where the new tools come in handiest.” Modern HR Data Types and Attributes (From Text to Machine Generated or Monitored Data).
“Ethical questions about how we use data and technology in organizations are growing in prominence and importance and bias is the noisiest of the ethics questions now facing HR.” John Sumser has more in, Bias in AI: Are People the Problem or the Solution?
In this combined article and podcast the topic is Open Feedback and Joyous Co-founder Mike Carden is in the driver’s seat. Open Feedback with Mike Carden (article and Podcast).
“All tools contain embedded biases. Bias can be introduced long before the data is examined and at other parts of the process. Meanwhile, one group says people are the problem; the other sees them as the solution.” - John Sumser
“Data has a funny property. It wants to make more data. There’s a saying, ‘data makes its own gravy.’ Using data creates data about usage. Interestingly, the metadata created by data is often more useful than the data itself.” - John Sumser
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