Worried about the rise of the machines? Like doing things yourself? Now you can address both. Build your own AI with kits from Google.
You can tell when something’s time has come. Hobbyists and tinkerers start doing it by themselves by cobbling together off-the-shelf parts. It’s hard to believe, with all the hype, but Artificial Intelligence (AI) has arrived. Get a real feel for what this is all about. Want to play with some of the neat machine learning functions like image or voice recognition?
You are in luck. Google has just released updated AIY Vision and AIY Voice kits that include what you need to get started. You buy them through Target ($89.99 for the Vision kit and $49.99 for the Voice one). Everything is included so, you won’t be going on extra shopping trips (or downloading software) just to get the ball rolling.
While you have fun building your own Skynet consider the implications of what’s really transpiring. AI’s are just tools that are increasingly seeping into our work and play. As they do so they get easier to use. You have heard it before: your smartphone has more computing muscle than what it took to get us to the moon and you don’t even notice it. Nor do you have to know how it works; you just use it. Likewise, we’ll be increasingly using AI just like that. Want proof? Look at the success of voice based digital assistants like Amazon’s Echo.
AI’s are no more different than smartphones, spreadsheets and analytical programs. But, computers seem to have always over stimulated our imagination. Exaggerated claims in the press about the intelligence of computers are not unique to our time, and in fact they go back to the very origins of computing itself. The first computer – ENIAC in 1946 – was characterized as an electronic brain. You may have mixed feelings about your smartphone but I doubt you would claim it’s an electronic brain.
That doesn’t mean that AI’s are an unalloyed good. Bad algorithms can lead to bad conclusions from the machines. IBM’s over hyped Watson has been slammed for making poor and dangerous medical recommendations. The machines are also only as smart as the people who build them and the data sets they use to train them. This leads to all sorts of unconscious biases being introduced, e.g. Google’s Photo Service labeled black people as gorillas.
So they are just tools with some extra oomph. Let’s stop focusing on the sensational and scary, and focus on the important and relevant. Zachary Lipton, an assistant professor at the machine-learning department at Carnegie Mellon University, has watched in frustration as news article after article transformed from “interesting-ish research” to “sensationalized crap”.
Now that you can see AI can come in a cardboard box and can be thrown together by your child or the kid down the street, don’t worry about doomsday scenarios. Let’s focus on just leveraging it correctly.