Artificial Intelligence is and continues to change the way we see things and the way we do things. For much of our lives there has been conventional wisdom, there are strong elements why conventional wisdom has lasted, but is it the best approach? In a recent book written by Nick Polson and James Scott titled AIQ published by St. Martin’s Press, NY, 2018, the authors examine artificial intelligence – what it is, how it works, where it comes from and how to harness its power for a better world. Note the optimism in the authors expectation, AI can help make the world a better place.

It is not unusual for 2 different published research findings to look at different data sets and find different answers to the same questions. This is often how science works. Only overtime does the evidence accumulate convincingly in a single direction.

AI has limitations, one can use the same data and come up with different conclusions and reports have done that. The lesson is simple, algorithms do exactly what they are told, there are biases or assumptions in the program. In reviewing data, find out about the assumptions to see if you agree or not. The assumptions are made more important because the consequences of a bad one can be amplified over and over again. What do you look for:

Rage to conclude

Model rust

Bias in, bias out.

Most calculations in data science require assumptions of one kind or another. The first was constant probability and the second is independence. Why are they related?

Data scientists have a favorite saying: all models are wrong, but some models are more useful. No model is perfect.

Linking to dividend paying stocks, over the course of investing you will see many projections. Some are right and some are wrong, learn from the ones that are wrong. What was the assumptions and why did it go wrong that you can easily notice. Start with the basics and build on them, why was a projection rate used? why are people going to buy the goods and services? by approaching the reports with a bit of cynicism you will save money, which means you will earn more.

There are more questions than answers, till the next time – to raising questions.