I vividly remember the first day of my first class in algebra: it was awesome. Solve for ‘x’! Scientific notation! Absolute values! (Wait a minute, you mean values can be not absolute?) I felt like I was learning the stuff of geniuses and was thrilled to be following in their footsteps. Well, maybe not, but I was a mathlete so more math was never a bad thing.
Fast forward a year or two and then there was Algebra 2 with its dreaded ‘algebraic proof.’ Don’t get me wrong, I still loved the new concepts and learning, but to say that I wasn’t a fan of ‘showing your work’ is a significant understatement. I already knew the answer! Why do I need to show you what the ‘yellow brick road’ looks like--we both know I’m right! Right? I am right, right?
It’s been a few years (or decades) since my initial struggle with proofs but when I saw this article the other day, the necessity of this practice ‘clicked’ in a new way. As the two semesters of pain (and the subsequent need for proofs in calculus, differential equations, and even physics down the road) came rushing back, I realized that maybe those poor teachers who had to put up with my recalcitrant (admittedly, about half the rest of the class as well) point of view on the subject, the need to ‘understand how we got here’ is more important than ever.
Why is DARPA, the organization that’s birthed ideas from the internet to online interactive maps and even GPS, seeking the ability to understand the algebraic proof of Artificial Intelligence (AI)? If we look at John Launchbury’s (and DARPA’s) perspective on ‘3rd wave’ AI in greater depth, it makes an enormous amount of sense: if decisions are contextual, then how do we make sure that these solutions are able to leverage the appropriate contexts? At the same time, how do we identify if we’re lacking context and need to go get it? If the 3rd wave is all about context, the key to success is being able to show your work.
For more information, check out DARPA’s presentation and video:
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