Over the last few weeks, a lot of enthusiasm about the state of “Artificial Intelligence” (AI) radiated from the popular press as a result of AlphaGo’s win over the current world champion in Go, Lee Sedol. I remember a similar spark in the AI hype gauge when DeepBlue won against Garry Kasparov. The reality, however, is that we are very far from building truly intelligent software. Many experts agree and have tried to manage down the generated hype.
“However, we’re still a long way from a machine that can learn to flexibly perform the full range of intellectual tasks a human can—the hallmark of true artificial general intelligence.”
Few days ago we were treated with an “intelligent” chat bot called “Tay” from Microsoft. “Twitter taught [it] to be a racist asshole in less than a day“. A coordinated attack demonstrated how easy it is for Machine Learning-based software to fall over. This is because we are still lacking the ability to teach computers how to reason over basic philosophical concepts. That’s not to say that we can’t have a bot with racist personality. If that’s how it’s “brought up”, if those are the “values” that is given, then that’s fine.
We still have lots of work to do in order to put such concepts in place. I applaud Microsoft for trying. Yes, they had an issue with their system which allowed attackers to move the focus away from the real goal of the experiment. I hope Microsoft returns to the experiment once a fix is in place. Building self-evolving, self-learning systems is an important step towards the advancement of such “intelligent” experiences.
The situation reminded me of a slide I have been using for 6-7 years now in some of my presentations. Here’s a copy of it from my 2013 QCon presentation on “A Platform for all that we know”. (Variations of this spectrum have been used extensively in the literature. I am not the one who came up with it.)
We are far away from building truly intelligent experiences.
Perhaps the “A” in “AI” should stand for “Aspirational”, at least for few more years :-)