With the emergence of technology that automates knowledge work, an entirely new part of the labor force is worried about job security. These concerns were once isolated to people who did repetitive physical labor, but today it can seem like any work at all might be replaced by AI. The 15-to-30-year forecast of the global labor market is a giant question mark. How will we navigate the transition? How can you know how susceptible you are?
If you’re a business leader with access to a technology budget, over the past decade, there are a handful of phrases that have suddenly became impossible to ignore. At this point, you have basically no choice but to act like you really understand what they mean. Here’s an inexhaustive list, in roughly the order that they blew up: Big data Predictive analytics Data science Machine learning Deep learning Artificial intelligence At every conference, you’ll find some industry leader declaring “X is dead, Y is the future”—where “X” and “Y” are both items from the list above, and where both X and Y are neither dead nor the future.
Welcome to another edition of Demystifying Overused Marketing Terms. The last edition was about Big Data, which you can find here. This time, we’re talking about “predictive analytics” and “machine learning.” The reason we’re doing this is that just the other day I was walking around the expo floor of a big sales conference in town and overheard the following: Guy A: We don’t do predictive anymore, now it’s all about machine learning.
I can’t remember the last time I made it through an airport terminal without seeing a giant abstract poster up on the wall with a vague heading like “Big Data is here: are you ready?“, or “Big Data: the new natural resource”. Often, the heading is in front of a photo of clouds, or a gazelle, or a server room, or some other such thing. So, for the weary business traveler who at this point is too afraid to ask what “Big data” refers to, here’s a quick breakdown.