Tell me what you think! And why this is so difficult to do.

The human brain is excellent in analyzing, drawing conclusions and evaluating information. Scientists try to replicate these capabilities to enable machines to take over tasks. This is not the easiest mission as human decision processes are highly complex. What is behind this complexity? Let’s group the reasons in three categories:

First of all, each of our decisions is based on a multitude of experiences which we make in our lives and from which we learn from one to the next decision.

Second, large parts of human decision making happen subconscious. This is the reason why one person is often not able to fully explain to another person why he or she decided something in a certain way.

And third, even if such a knowledge transfer succeeded, there is a high degree of complexity within the „receiving system“ and the problem of subconsciousness arises again.

So, if we are hardly able to explain our thoughts to others of our species, it is clear, that replicating our decision-making process to machines is quite challenging too. Translating the complete process in programming code would demand an immense amount of time and resources.

Machine Learning solves part of this problem: Instead of programming each and every component of a decision process, it provides the framework in which the exact decision making is derived from the provided data. Thus, a general definition of Machine Learning summarizes: A computer solves a problem although it was not programmed to solve this particular problem.

Machine Learning is the most promising starting point for replicating the complex human decision-making process and to enable machines to support our daily life. Why do we want to get there? Because of three convincing capabilities offered by machines:

First of all, machines do not get tired by doing repetitive tasks.

Second, they are able to handle very long columns of figures.

And third machines were not trained to get used to a three-dimensional world like humans were from their early childhood on and the problem of handling high-dimensional data does not arise.

These three reasons explain why we carry on cracking the tough nut of bringing intelligence to machines although we struggle with explaining our thoughts to other humans.