Current Issues and Scientific Progress put Pressure on Technology and Human Pride
Just over a week ago on October 3rd there was a Connecticut Forum meeting at the Bushnell theatre to discuss the next big things on the horizon of science. This discussion focused on more than the next big technological advancement, it also addressed up and coming problems and concepts that scientists are trying to come to terms with. These problems included climate change, education reform, and much more. In accordance with the problems just listed, the rest of the discussion revolved around coming to grips with the limitations that prevent the scientific community from solving them. Inevitably the conversation always approached the question of how can we use science and technology to find solutions?
Think about the implications of that question, it’s not even a question that humans will turn to computer technology in order to address the problems of the future. Humans have become reliant on computers to process the huge amounts of data we generate. Science in turn has become inexorably linked to large data that is generated and analyzed by computers. While humans are currently a necessary component of data collection and analysis, the threshold for self-sufficient computers is ever approaching. One example of computers approaching self-sufficiency is Google’s driverless car, which appears to be very close to hitting public roads. However, as driverless cars and artificial intelligence continue to draw closer to reality there is one important factor to consider.
This important factor is the method in which we are teaching computers to collect and process data. Unlike humans, computers cannot analyze data beyond the parameters set in their code. That is to say they cannot apply salience to discrete observations they make that have not been made important to them by their code. This limitation is why humans are still a necessary cog in the data analysis that many supercomputers conduct today. Since humans are the ones programming/teaching these computers, an obvious syllogism can then be made. Given the fact that we still do not have a complete understanding of our own central nervous system, then we cannot program another entity to have something comparable to the human mind. At this point some may make references to recent work showing computers with the amazing potential to learn. However, while we continue to make great strides in computer programming and learning, we are also approaching the limit of our own human understanding.
How then do we address our shortfall of understanding regarding our own mind? To date most technological advances have come from humanity’s ability to observe, adapt, and overcome. The inspiration for much of today’s most advanced technology can be traced back to some source found in the natural world. The combustion engine has a 4 chambered design used to power a machine, which is analogous to the human heart. The internet and computers run on a feedback system that emulates the human brain. More examples could be made, but the point is we draw inspiration from our surroundings, and innovate it to suit our purposes. This process has been largely successful, as proved by the current luxuries that people today enjoy as a result of our ingenuity.
I think the solution to the conundrum of modeling an artificial intelligence lies in long term research of the human brain. We are advancing in our knowledge of the brain and technological capability almost daily. These advancements are working in tandem with each to further our understanding of the mechanisms that drive us and the world around us. In a way the process by which we conduct our research is becoming a feedback system itself. Once we have a question we get an answer, which then propagates another question. Sometimes the solutions we find to our questions may be unexpected, like potentially storing information in cellular DNA rather than flash drives to improve data storage. However, as I’ve already stated, many of humanity’s best ideas and inventions haven’t been intuitively thought up by someone. Therefore, we shouldn’t look to draw upon human intellect to solve our problems, but look at pre-existing systems in nature that we can innovate upon.