The Future of Work

Shelly Palmer talks about the technology required for WestWorld to be real with Teresa Priolo and Antwan Lewin on Fox 5 NY. Original Airdate: December 6, 2016 Continue Reading →

Everyone was tweeting their #firstsevenjobs the other day. As I thought back on my job number 7, I remembered a traumatic lesson in the power of trust and truth. I named it "The Honesty Paradox." Continue Reading →

Here's what's going to happen. You are going to read this post up to the point where you agree with me or you don't. Then, either you will find something else to do or, if I have your attention, you will write a comment or an email that espouses your world view. This sounds great. Except it isn't. Continue Reading →

When I asked a long-standing business acquaintance of mine why he was interested in data literacy, he said, "Data is all anyone is talking about. I don't know anything about it at all. I thought you guys would be a good place to start." In some cases, this would have been a totally reasonable exchange – a mid-level executive seeking continuing professional education. But in this case, the man's title was SVP Marketing. I say "was" because he just updated his LinkedIn profile. Not surprisingly, after three years at his present job, this 18-year corporate marketing veteran is looking for work. Sadly, he is unemployable. While he's under 40 and looks like a Millennial, he has been "inside" too long and lacks the skills to be competitive in this job market. So, in his honor, here are six things he could have done to future-proof his job ... Continue Reading →

We just used a few overeducated millennials and some open-source code to get a bunch of cognitive nonrepetitive workers fired. Which sucks! Incredibly, we didn’t use AI or machine learning to do it, just imagination and some free stuff. The bad news is that unless these people learn to do higher-value cognitive nonrepetitive work, they are not going to be employable. And the really bad news is that even if they do learn to do higher-value cognitive nonrepetitive work, when we start using machine learning and AI tools to do their jobs, they will actually be unemployable. Continue Reading →

Generally speaking, there are two kinds of companies in the world: data rich and data poor. The richest of the data rich (Google, Facebook, Amazon, Apple, etc.) are easy to name. But you don't need to be at the top of this list to use data to create value. You need to have the tools in place to turn information (data) into action -- that's what the data rich do that the data poor and the data middle class do not. Continue Reading →

Because the velocity of data is increasing and will always increase, the need for data literacy is increasing and will always increase. This does not mean that to be successful executive you have to become a data scientist -- quite the contrary. It means that in order to be a successful executive, you need to understand how data is turned into action, be familiar with the methods of data science and data scientific research, and be able to think strategically about how to use data to create value for your business. All other things being equal, there is a significant difference between being literate and being fluent. Continue Reading →

Tay is a combination chatbot and AI system designed by Microsoft to "engage and entertain people where they connect with each other online through casual and playful conversation." It was specifically "targeted at 18 to 24 year olds in the U.S., the dominant users of mobile social chat services in the U.S." If the words "designed" and "targeted" are off-putting, then you're really not going to care for one of the system's recent, now infamous, tweets ... but, there is much, much more to learn from Microsoft's mistake. Continue Reading →

Technological advancements always empower people to behave differently – what makes today different is that the rate of technological advancement is accelerating beyond our capacity, perhaps even our ability, to react – and this... is new. Continue Reading →