It’s the same Achilles heel of any predictive model. What to do with something completely new? ““While analytics has helped many businesses to navigate the crisis, it has also shown fallibility,” said Saleh. “As a technology that relies on the details of past patterns and behaviors to predict what will happen next and what action…
If I had to guess, I think most people, when asked about “deepfakes”, if they are concerned at all, are concerned about elections, political fakes, or famous people being taken down by fake videos. We aren’t thinking about phishing, and yet, in a time when many companies are struggling with employees who can’t seem tor…
I think this is really interesting, because the more information about you there is, the more reasons someone can find to either rule against you, or to do more investigation into you. Which leads to more information about you being available, and round and round we go. “That is in part because algorithms are made…
The Perfect Preservation Letter: A New Guide
Is Flexible Work the New Normal? Survey Says It Is Good For Mental Health
The coming wave of Covid-related age discrimination lawsuits
– Employers need to be vigilant in laying off older workers. “High risk for Covid” and “highly compensated” might by proxies for age discrimination.
Amid COVID-19, people under 30 may finally kill email
Will lawyers be replaced by GPT-3? Yes, and here’s when
Fake LinkedIn Accounts – What to Do and What LinkedIn is Doing
One Ethics Rule Leads to Another: Technology Competence and the Duty of Supervision
Remote Networking as a Person of Color
Burnout Of The Remote Employees And How Can They Counter It
Algorithms are Black Boxes, That is Why We Need Explainable AI
I’ve asked you before if you would be able to tell if I walked away from this blog years ago and simply left AI to write it. Maybe we aren’t there yet, but consider the article below. This is how it came to be: “This article was written by GPT-3, OpenAI’s language generator. GPT-3 is…
And this really brings me back to my point, that we do a poor job of truly understanding science, statistics and cause and effect. We believe that algorithms have all been well-thought out, and produce a “true” result, even when they are trying to predict something as unpredictable as what traffic will look like 20 years from now. We assume social science studies are giving us the “right” answer for how to educate people, or train them for the best outcomes, without considering what we are teaching them about the larger world. We assume that we can tweak one belief, or one thing, without human beings reacting to those changes in unpredictable ways, all the while thinking our one change will cause the reaction we DO predict.
We assume a lot that should never be assumed. We over-simplify a world that actually has more influences than we can possibly account for, and assume that what is really a small statistical difference represents a universal truth.
It doesn’t. There are no simple answers. It takes hard work, hard discussions, and lots of listening to figure out the best way forward. Don’t wait for AI to tell you what to do, it may be missing quite a bit.