It is no doubt that everyone has come in contact with Machine Learning (ML) algorithms, perhaps without knowing that they have or what those algorithms are. For example when you are making a purchase online and some items are 'suggested for you,' this an instance where a type of ML algorithm is used, another example is when a dating app tries to 'match' you based on previous matches you have selected. Social media platforms, such as Facebook and Instagram, use ML algorithms to determine which sponsored content to show you. These are just a few examples of how an ML algorithm is used. In today's landscape, ML is a powerful tool that many start-ups and more mature corporations are now adopting to derive more value.
So what is ML? ML is a type of computer algorithm which relies on a large amount of input data to make a future decision about a new data point. Basically, it is a type of algorithm that when it is fed data, it 'learns' and with more and more data that it processes, it becomes better at selecting the data points which best match the data set it was fed. The only thing ML can make decisions about is the data which was fed to it. For example, if you are shopping online for a black bag, the algorithm will suggest various black bags for you to chose from, but it will not suggest a blue or silver bag unless you look at some items which are black or silver.
When we think about our mind, it is much like an ML algorithm. We feed our mind certain data, in the form of stories we tell ourselves, the experiences we have, beliefs, things we read or watch, the music we listen to and the ideas we get from the people we interact with. In feeding our mind this data, we form a belief system and pick the next data point which best matches the belief system we have formed based on the information that our mind has received from us. So for example, if we have a series of positive experiences with working out, our brain develops a neural pathway which associates pleasure with physical exercise. The same is true if we have a series of negative experiences associated with a certain task, for example cleaning, our brain then develops a neural pathway that does not associate pleasure with that experience. Thus, the next time we want to feel happy, we may choose to work out but not clean. Much like an ML algorithm, we train our brain to make decisions based on the input we give it and our emotional reaction to it. While ML algorithms do not have an emotional component, our psychological makeup is such that we do and it is stored in the brain, and accessed via a neural pathway.
Our perception of life and the events we gravitate toward is largely defined by the signals our brain receives from us in the form of data it receives, both in terms of concrete events and the emotions we associate with them. Consequently, if we want to make changes, we have to start feeding our mind with different data. If we do not feed it certain data, just like in the example of shopping for a black bag above, our mind will not go searching for the blue or silver bag, we must first give our mind the possibility that the blue or silver bag exists. This explains why imagination is so crucial for lasting change. So start imagining the future you want in 2018!
Dr. Anna Powers is an entrepreneur, adviser and an award winning scientist. Her passion is sharing the beauty of science and encouraging women to enter STEM fields