Artificial intelligence (AI) and machine learning are being used for all kinds of things, including making financial decisions like building investment portfolios. Although they can be handy, they often work behind an opaque glass, known as a black box model. Read on to learn more about black box models and why they should matter to investors.
What is a black box model?
In complex systems like AI and machine learning tools, there's a lot of programming involved, with many, many processes taking place, often simultaneously. This is great, but because of the complexity, it can also make it very difficult to know why decisions are made.
This lack of transparency is the main characteristic of a black box model. In a black box model, complex decisions are made by a computer, but we don't necessarily know why. Laypeople and even programmers and operators themselves are also in the dark.
How do black box models work?
That is the mystery, isn't it? Black box models are such complex programs that no one really knows what's going on under the hood, and the computer itself can't tell us, either. They're not built with transparency in mind; they're designed for speed and power.
Despite the lack of transparency, we still use them in engineering, finance, and a wide range of other complicated disciplines. As long as you check their output and make sure it makes sense, then how the sausage gets made is a lot less important than that it gets made.
Black box model versus white box model
If you're wondering to yourself why we let something like a black box model happen -- well, it kind of happened accidentally, and then programmers decided that since experts were working with these machines, it might not much matter how they came to their conclusions. That's the black box model: it's answers without transparency.
A white box model is very different. It's instead built with transparency in mind, as well as restraints at each step in the process to force the machine to slow down and explain itself as it goes. A white box model tells you not only the answer, but how it got there, in case there are legal or ethical implications that need to be considered. They run slower due to these additional checks, but not necessarily slow enough to matter.
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Why do black box models matter to investors?
Black box models matter to investors who use artificial intelligence or other machine learning processes to make buying and selling decisions. If that's you, you should really be very careful before investing blindly using these tools, since you don't have any way to understand the logic behind the calls that your computer friend is making on your behalf.
Black box models are not only logically opaque, they also lack legal and ethical transparency, which can leave you on the hook for some calls that might be good in one sphere but terrible in another. You should be able to sleep at night with decisions you've made when it comes to your financial life -- not simply leave it to a complicated algorithm.
For a portfolio with a long-term time horizon, being sure you know if you're facing a black box model or a white box model and checking its work carefully can go a long way. After all, you may have different goals than the model assumes, which could seriously derail your plans. If it wants to plan for five years and you're looking for growth over decades, those might be very different stock picks, for example.
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