Understanding Exponential Versus Linear Growth
The essential thing that we need to understand is the difference between exponential and linear growth. We’re accustomed to perceiving/understanding things under the scope of the a linear lens. As with most things, this is rarely ever the case. There’s a strong case to be made that mathematics has a strong existential base in the fundamental mechanics of reality i.e. things generally grow and die exponentially in cycles and we can measure this to a fault.
Why is this Important?
Because we need to establish a baseline understanding that the reality of artificial intelligence becoming a substantial issue for human beings is a near future reality.
Elon Musk has already began developing early models of Nuerolink, a neurological integration system that integrates your neocortex and limbic system to an external artificial intelligence. ie. the external integration becomes just as much a part as you as your biological system could ever be.
Program or be Programmed: the Issue of Automation
Tesla already has self driving vehicles on the road that have been proven to be already safer than the average human driver. Elon Musk anticipates that his later models by the end of 2019 will be 100-200% safer than the average human being.
The number one occupation in the world is driver (e.g. taxi, truck driver etc). We already have self automated cars and transportation of goods (e.g. self driving trucks I’ve seen them first hand). What’s going to happen to the thousands that get replaced by automation? Not only will this have a huge impact financially worldwide, this is small relative to what A.G.I will manifest into the world. What happens when the A.G.I starts replacing low level white collar jobs?
Have you noticed that in the last several years the advertisements on your smart phone have become increasingly more accurate relative to the given variables in your life / patterns in your behavior? That’s because of something called machine learning. Machine learning gives computer systems the ability to “learn” via trial and error through statistical techniques and algorithms. It just so happens that the graph above reflects exponential increase.
The graph above demonstrates the exponential increase of attendees to the Computer Vision Foundation in Long Beach California. Pay attention to extensive increase of attendees as soon as deep learning hit the scene (and this graph only stops at 2015!).
Again we have a chart graphing the attendees of the Neural Information Processing Systems event down in Montreal. Can you see a pattern? To date this is one of the largest workshops covering machine learning and computational neuroscience.
Will A.I. do more harm than good?
There’s too many variables to give a definitive answer. Given the data we have it’s safe to assume there are serious parameters that need to be set in place as the technology progresses. People like Bill Gates and Elon Musk have been pulling out the glow sticks screaming “put a fucking law around the development of this shit!” for years.
Happy Thanksgiving 🙂