Meetings are important in your life. They take up a bunch of time, some are great and others are agonizing, but you need to have them to get work done. Search your feelings; you know it to be true.¹ Both the popular press (see for a discussion Kello, 2015) and peer-reviewed outlets have a great deal of helpful meeting-optimization advice (discussed briefly below), with some caveats for cross-cultural differences (Gerpott & Lehmann-Willenbrock, 2015; Köhler & Gölz, 2015; see also van Erde & Buengeler, 2015). To the best of our knowledge, however, these recommendations are silent on the topic of using videos—not synchronous video conferencing but prerecorded videos—in the context of meetings. Silent—no pros, no cons, no evidence, no research questions. Let’s take a look at some of the existing recommendations and see how we can slot this technology into them, shall we?

This issue, we’ll be exploring another concept core to data science called natural language processing (NLP).  Many people assume that NLP is a particular analysis, as if you open up a dataset and “apply NLP” to it.  But NLP is in reality an entire field of study attempting to explore and understand how humans interpret language and, in turn, how computers can mimic that interpretation.  Once a computer “understands” language, you can run a lot of targeted analyses on that language to address your research questions—or in the language of data science, you can apply a variety of different algorithms to develop insights. 

I’ve been thinking about automation and artificial intelligence lately. In the news this week, a marketing company called Cambridge Analytica is being credited with affecting the outcome of the presidential election, by using AI to target Facebook users based on their personalities and expose them to personalized advertising. Also in the news, swaths of high-skill, professional jobs like radiology technicians are being replaced by robots. Also, legislators are suggesting that universities are biased and that professors tell students what to think and that they should be replaced by Ken Burns documentaries. All of this makes me wonder: How long until I-O psychologists are automated out of our jobs? Is it really so crazy to think that day might not be so far away?

Once again time has moved rapidly by, and I find myself preparing the last of my presidential TIP columns.  A lot has happened over the last few months, and I can’t begin to discuss all of it, but here are a few of the exciting things going on with SIOP.