People talk about Artificial Intelligence (AI) and Machine Learning (ML) these days a lot. I'll join the crowd as I also believe that's the future. However, the power of artificial intelligence would not be the point here. Rather, I'll focus on something natural to all human beings, our intuition, and how similar (arguably, of course) it is to neural networks (NN).
Deep neural nets are, perhaps, the most powerful predictive tools up to date, and are well known for producing highly accurate models but could be hard to interpret. You have a choice: a simpler ML model that is easily interpretable but only 90% accurate. Or, you can train a NN that makes 99% accurate predictions -- but shrug your shoulders when asked why you get certain results. Doesn’t it sound just like that “gut feeling” when you know you are right but can’t quite make it out? With a trade-off between interpretability and accuracy, the favor is often given to the former.
Deep neural nets are, perhaps, the most powerful predictive tools up to date, and are well known for producing highly accurate models but could be hard to interpret. You have a choice: a simpler ML model that is easily interpretable but only 90% accurate. Or, you can train a NN that makes 99% accurate predictions -- but shrug your shoulders when asked why you get certain results. Doesn’t it sound just like that “gut feeling” when you know you are right but can’t quite make it out? With a trade-off between interpretability and accuracy, the favor is often given to the former.
NN have been inspired by the human's brain. We still don't understand a great deal of the processes inside our heads but we do not distrust our senses. Well, except one.
We don't trust intuition. Personally, I don't trust my intuition.
Logic, our knowledge, and the five natural senses help us build judgments about the world the way most ML models produce their predictions, e.g. (Non)-Linear Regression, Decision Trees, k-means clustering, etc.
Neural nets may have the same input but are not as transparent with all their hidden layers, weights, and backpropagation. So assume that intuition works the same way: its logic is hidden, its predictions are accurate but hard to explain. That is to say, I am convinced that intuition is, in fact, uses our experience and observations but in a more subtle way. Intuition assigns its "weights" while we see something out of the corner of the eye without even realizing it; when we hear something without listening. Intuition learns without our knowledge.
As I mentioned, I am among those who think Neural Networks and Machine Learning in general will shape the future of AI. Yes, magic inside a black box is attractive but scary. However, we embraced this "scary" reality by welcoming voice assistants and face recognition technologies when we first asked Siri/Cortana/Alexa/Alice what the weather forecast was, tagged our friend on a Facebook photo, and unlocked our iPhone with the Face ID...
Maybe we should treat our intuition with more respect as well?
