By now we have all probably heard the two magic letters ‘AI’. Artificial Intelligence we say, and this steers a lot of awe and fear in different people depending on what level of understanding you happen to be on the subject.
The problem is that, as with many other new things in our society, the full utility impact and danger of this technology are pretty much under or over-estimated. If you were old enough to understand the issue, during the first time microwave ovens first popped on the market, you may remember salespeople pitching the oven as a miracle able to cook pretty much anything. Today (2018) most of us would never try to cook something in a microwave oven but simply reheat food already cooked by conventional means. I feel that the same is true with today’s AI hype when we’ll look back in 10 or 20 years.
What is AA then?
AA is not Alcoholics Anonymous as it may first sound like but in the AI context, it stands for Advanced Automation. I think AA is actually what most of the current so-named AI applications are doing. Limited signal (image, sound, or other sensors) recognition, can e hardly be called ‘intelligence’.
Why AA and not AI?
- Fits better the current functionality, as in pattern search and identification in various data streams video, audio, other sensor types, or human input (old good keyboard)
- In real AI (or AGI), I mean the one Data from StarTreck or the Human Replicators in StarGate or Terminator, machines are self-aware, living noncarbon-based systems. Our current systems we call AI are far away from having enough complexity to allow consciousness to emerge.
The main problem with Real AI
Around 25 years ago (more or less) I won a praise from a radio station when (for the first and last time), I bothered to call in to comment on their show, which was about all those smart machines of the future. At that time AI was not yet what it is today.
My comment, which impressed the radio host was this:
“Any system modeled to work as the human brain does whose complexity is higher than a certain unknown level will naturally spawn a consciousness, or simply put will be a living intelligent entity like you and me!”
This is a totally different ball game than what we call today AI. Our current level of technology is much closer to regular automation but at a higher level of complexity due to the ability to process complex natural data flows generated by sensors sensing the real world by using various Machine Learning systems and variants.
Why we should not create real AI systems?
The answer is simple. If we will create real AI systems, they will by definition compete with human beings for resources and abilities sooner than later. Since we are already living in a highly competitive environment ourselves, the last thing we should do is to add high-ability competitors for human beings. This can and most likely will end in us humans being wiped out of existence. The only thing yet to be solved is a power source compact enough for the machines to use, but we’ll get there.
If not AI then what?
Advanced Automation (AA) targets enhancing existing human beings. Instead of creating new competitors for human beings as in AI’s case, with AA we simply increase the abilities to live and compete with regular humans and even other living things.
What would you choose, AI or AA?
May 9, 2018: Since publishing this article I’ve got some feedback and I’d like to add the following additional info to the article. Trying to clarify some issues pointed out to me without getting into technical details.
A hypothesis I like is that our universe uses a fractal engine whose change in the time dimension is powered by quantum mechanics (injecting random changes in the fractal structure). So, basically, it works based on algorithms (laws of nature). There are two kinds of algorithms out there, fully predictive and partially predictive. Regular (no ML/AI) programming is fully predictive. ML and AI are not. We built digital computers to BE fully predictive because we need stability in dealing with the quantum nature of reality (dealing with small random changes).
We did not yet master the classic coding, (how many defects are in our products so far?) and we are jumping head-on into more advanced cases of automatically generated algorithms used by ML which is the bases of AI. My point is simple, to succeed and avoid getting in trouble (legal?) in the future we have to make sure we know how to test ML and AI in order to minimize their errors. On the other hand, we have to educate the end user to understand the limitations, pitfalls, and dangers of the technology.
I’m afraid that the warning Carl Sagan gave us was not to put advanced tech. in the hands of technically illiterate users is near and it can impact all businesses using ML and AI very soon.
So ML and AI test automation as well as end-user schooling in limitations and pitfalls is a must.
From this perspective, I believe that AA (Advanced Automation) is a closer-to-reality acronym than AI, at least for now. Obviously, it is up to all of you out there to choose what two letters to use to label this new technology…