Making machines think like humans
For decades, we
have been trying to get the machine to think like a human. In order to make this happen, we need to understand
how humans think in the first place. How do we understand the nature of human
thinking? One way to do this would be to note down how we respond to things.
But this quickly becomes intractable, because there are too many things to note
down. Another way to do this is to conduct an experiment based on a predefined
format. We develop a certain number of questions to encompass a wide variety of
human topics, and then see how people respond to it.
Once we gather enough data, we can create
a model to simulate the human process. This model can be used to create
software that can think like humans. Of course this is easier said than done!
All we care about is the output of the program given a particular input. If the
program behaves in a way that matches human behavior, then we can say that
humans have a similar thinking mechanism.
The following diagram shows different
levels of thinking and how our brain prioritizes things:
Within computer science, there is a field
of study called Cognitive
Modeling
that
deals with simulating the human thinking process. It tries to understand how
humans solve problems. It takes the mental processes that go into this problem
solving process and turns it into a software model. This model can then be used
to simulate human behavior.
Cognitive modeling is used in a variety of
AI applications such as deep learning, expert systems, Natural Language Processing,
robotics, and so on.
