Projections of the Future

Source: Deep Learning on Medium

Projections of the Future

Based on the Past

For about the past 60 years, deep learning has been advancing and growing. With new ideas and advancements every year (it seems like), deep learning is creating a new world for us. The history of neural networks has given us an insight into where we came from, but can it also show us where we are going or, at least, give us an idea of the future?

Rosenblatt began his article that describes his invention the Perceptron, with three questions:

“ 1. How is information about the physical world sensed, or detected, by the biological system?

2. In what form is information stored, or remembered?

3. How does information contained in storage, or in memory, influence recognition and behavior?”

Rosenblatt believed that in order to understand higher organisms and how they function in the area of perception and thinking, these three questions needed to be answered.

One of today’s main focuses for deep learning is to try to find a way in which a machine can hold the key to the world of perceiving and decision making based on observation. Thus these from 1958 are key into the future that scientists want to make of deep learning — especially looking at it from a “how humans and animals observe” lens.

As we go further into the future bringing along advancements, new ideas, and discoveries how will deep learning affect our lives? What will our planet be like? Will there be major changes? Will the past effects repeat itself? We probably won’t know for sure, but we can certainly gather conclusions from the past in order to create different hypothesis’ of possibilities. Ultimately the real question becomes, how can we implement the past effects and outcomes in order to question what is the possible outcomes for deep learning in society today?

Most people fight against the growth of deep learning because of the possibility of jobs not being needed because of new technologies being able to perform those duties; therefore, throwing everyone into discourse and being the very reason many jobs are lost. Some say that, in some way, artificial intelligence was part of every industrial revolution that came about. Guess what happened during every period that was considered an industrial revolution. Certain jobs were not needed anymore, people were laid off, and everyone was thrown into discourse. Do you know what happened after that? Those who lost their jobs received new ones, and were not in discourse for long. They probably even love technology being part of their lives.

In Skynet Today’s article, Job loss due to AI — How bad is it going to be?, this exact possibility is discussed. “AI is sometimes characterized as part of the ‘Fourth Industrial Revolution’. Today, most economists agree the prior industrial revolutions ultimately benefited society as a whole, even though they did result in some losing jobs to automation in the process …Figure by World Economic Forum, seen on Fortune (above).” They go on to describe the process of how new technologies have affected the job force. Mainly stating that after the technology replaces workers and lessens the work of others, the workers are transitioned to new jobs (sometimes a job created because of the new automation). In all, it leads to higher incomes, lower work hours, creates more jobs and more space for economic growth.

Based on the past, there were small moments of hardship, including the loss of jobs that we are scared of, but in the long run it turned out to be a great idea; which created more positives than negatives. So yes, there will be a chance of harm, specifically for certain jobs, but what if, in the end, it turns out to be a great idea?

The article, noted above, states, “These technologies still require a lot of human input, and it’s very difficult to apply advances in games and pattern recognition to fully perform human jobs.” There is still so much that needs to be done before a machine is “capable” of doing what a fully functioning human, or even animal, can do. Most don’t even know if it is possible to have a machine reach that capacity. So the question now resumes as, “do we even need to worry or fear machines the idea of machines taking over?” And based on the past histories, most of the advancements, in this realm, are based on past advancements and just give a little boost to those discoveries. If we do seem to come upon a discovery where a machine is able to completely function as a human (even in thoughts), will we have a crisis on our hands? Based on the past, the advancements, in deep learning, that have occurred have only created an outcome that has become the best for society. The way deep learning is flowing, one can infer, from past observations, that if we do lose more jobs it won’t be a huge sweep across the world but only simple ideas; which could possibly, in turn, create more jobs, better economies, and higher incomes with shorter hours. The outcomes and impacts will, most likely, not be as dangerous as we fear it will be.