AI, Machine Learning (ML) and Deep Learning (DL) are all the hype these days, and for good reason. By now we know progress in AI accelerated over the past decade thanks to a convergence of factors including Big Data and compute power. And results are impressive as a recent Economist article highlights:
In February 2015 DeepMind published a paper in Nature describing a reinforcement-learning system capable of learning to play 49 classic Atari video games, using just the on-screen pixels and the game score as inputs, with its output connected to a virtual controller. The system learned to play them all from scratch and achieved human-level performance or better in 29 of them.
Over the next two years, many businesses will continue ramping up their ML/DL initiatives with the hope of improving every aspect of their business performance. These companies will follow a path similar to Major League Baseball’s pursuit of sabermetrics, or Wall Street’s appetite for algorithmic trading.
I think at some point in 2018, the latest wave of AI hype will peak and begin receding thereafter. Ongoing issues with model accuracy, as well as high costs required to operate less-than-stellar model performance will be two of the primary reasons behind this. I also believe decision-makers will feel increasingly vulnerable as AI effectively detaches them from understanding and refining the theories underlying their business performance.
This will usher in a new period of enlightenment where companies adjust their be-all-end-all expectations of AI in favor of empowering their people to effectively coexist with AI. This will be good news for workers too as Tyler Cowen suggests in Average is Over:
As intelligent-analysis machines become more powerful and more commonplace, the most obvious and direct beneficiaries will be the humans who are adept at working with computers and with related devices for communications and information processing. If a laborer can augment the value of a major tech improvement by even a small bit, she will likely earn well. This imbalance in technological growth will have some surprising implications. The key questions will be: Are you good at working with intelligent machines or not? If the answer is yes, then your wage and labor market prospects are likely to be cheery. If the answer is no, but you have an unusual ability to spot, recruit, and direct those who work well with computers, then the contemporary world will make you rich.