How Machines Learn: Big Brother Is Watching

The ubiquity of Machine Learning algorithms remains a topic of interest because we, as a society, still haven't come to terms with what "acceptable" use looks like, and what privacy looks like in the post-AI world. 

Algorithms are helping you pick out your next gift on Amazon, controlling what you find on Google, they're suggesting new music for you on Spotify, and they're doing their best to keep you on their website.

They're following you in stores, on the streets, and many would argue they're tracking your phone calls, text messages, and more. 

With all that being said, I do think it's important to have a cursory knowledge of the things that impact our lives ... so, even if you're not an AI-aficionado, I think it's important to somewhat understand how machines learn, and how powerful they're becoming. 

The video is a bit simple in its explanations, but it describes some important concepts.

 

CGP Grey via Youtube

The video focuses on Genetic Algorithms, which is one type of machine learning – and neglects some of the other more complicated approaches.

As machine learning gets more complicated and evolved, it gets harder for a human to understand what makes it good … and that's okay. Understanding the direction AI is heading is more important than truly understanding the intricacies. 

It's human nature to feel safer when we understand something. It's human nature to envision machines as making human-like decisions, just faster.

Of course, just because it suits human nature to believe something, that doesn't make it true. 

Part of what makes machine learning exciting is that it can do a lot of things well that humans are really bad at. 

In reality, it doesn't matter why a bot is making a decision, or what inputs the bot is making the decision on. What matters is the performance and level of decision-making in relation to itself and to other options (and whether the bot is biased).

With respect to trading, focusing on the markets is a distraction.

For the most part, I don't care how markets are doing.

I care how our systems are doing and I care how the portfolio is doing.

It's a brave new world, and not only is big brother watching, but algorithms are too.

Live long and prosper!