At the current stage, we are trying to make machines understand our world by setting specific rules. That is how humans are empowering machine learning. The technology is currently being developed under human supervision. In the future, however, unsupervised machine learning may become the dominating method when it comes to developing machine learning algorithms.
When people are frustrated and worrying about a future of AI and automation taking jobs away from humans, the AI industry itself is having a severe skills gap. There are not so many people who really master and are able to leverage deep learning and AI. Moreover, it is very complicated and challenging to teach a computer the simplest idea, like how to identify a critter.
For the time being, we are training machine learning algorithms by feeding them curated training data. And we are not talking about some small amount of data, we are talking about big data. Human capabilities can’t really match the data needs of AI algorithms; therefore, the progress in machine learning and AI hasn’t reached its maximum potential yet.
Unsupervised deep learning, on the other hand, allows algorithms to absorb data from the internet. Humans will never be able to digest and read the mammoth amount of data we have created but machines can. Unsupervised deep learning models can process the data, learn from it, understand it to ultimately generate their understanding of our world. We can then harvest huge benefits from those models.
Unsupervised machine learning in particular and technologies, in general, will gradually shift the roles of humans and machines. Machines will take over the manual works and research because they are better than human at those tasks. Humans will focus on developing strategies and tasks that are related to emotions, relationships, and creativity, at which we are much more excellent than machines.
If we can leverage unsupervised machine learning to create more AI tools faster and more easily, we will be able to engage AI in more aspects of life, increasing efficiency, and productivity. The cost of developing AI tools using unsupervised machine learning is cheaper than that when using supervised machine learning models. The lower expense will encourage AI adoption across industries and daily activities. Over time, unsupervised deep learning will boost the development and growth of other technologies and industries.
There are some popular concerns regarding what the machine learning algorithms will learn without supervision and how AI will affect the job market. The threat of unsupervised machine learning creating biased or twisted AI tools is real. However, unsupervised deep learning is inevitably the future of AI. Therefore, instead of hindering the progress, we should make sure that the unsupervised deep learning technology is mature before we set it free and don’t rush into the technology without proper preparation. Humans also need to shift their job preferences to adapt to the future scenario where AI is everywhere. Otherwise, we will find ourselves lost in the world of AI.