AI Should Put Itself Out of a Job

I read a piece on linkedin from an entrepreneur who is encouraging his employees to use AI to put themselves out of a job.

In theory an employee who follows that advice will then have the ability to move on to more interesting jobs and challenges.

Even if his intentions were good, I’m sure what many of his staff were actually hearing was “you should train your replacement before we fire you”. 1

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Could a Driver’s License for the Internet Save Humanity?

The internet is destroying our civilization. And AI, with its ability to create fake content and exploit human weakness at scale, will only accelerate the the problem. However, there is an opportunity to turn this around if we use the motivation to get online to our advantage. In fact, harnessing this motivation has the capacity to do more for humanity than most schools. But first we need to treat the internet with the respect it deserves which means creating a something akin to a drivers license.

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Emacs for Data Science

tl;dr: If you want an editor that works with R, python, SAS, Stata, SQL and almost any other data science language. If you want an editor with IDE-like features. If you want an editor that works on any platform and as well as on the terminal. If you’re a fan of literate programming. If you want an editor that is highly customizable and will be around after most editors have come and gone, then you’d be hard pressed to find anything better than emacs.

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The Impact of Media on Entrepreneurship and Startups

So there has been a lot talk about how the media hype machine is setting entrepreneurs up for failure. That is, it’s encouraging folks who may not be serious to try their hand at starting a business when they probably shouldn’t. Below are some charts on the relationship between media, legitimacy and entrepreneurship that attempt to understand media’s impact.

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Topic Models Network Analysis

In preparation for a workshop at this year’s Academy of Management conference my colleague Tim Hannigan and I gathered data on all the sessions and workshops. We then processed them using R’s topic models package to extract “themes” from the abstracts.The purpose was to identify what the divisions at Academy were discussing and to look at the overlap between them. The image below is one result from this work

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