Computer science and AI – Stop the madness

Everyday we read some news article about the great strides made in designing things that make use of “artificial intelligence” (AI). For some it brings the fear of “rise of the machines”, so aptly portrayed in the “Terminator” movies. The big question of course is: Do we need artificial intelligence? The sad reality is that we can barely understand our own intelligence, so why would we want to create an artificial one. Okay, so a machine called Watson, built by IBM is capable of winning Jeopardy! by answering questions posed in natural language – just like humans would. The crux is of course that Watson had access to 200 million pages of structured and unstructured content – including the ENTIRE contents of wikipedia. So considering how fast machines are at finding data, it’s not incredibly hard to see a machine being able to decipher a question using speech recognitions algorithms, and find an answer. Very few humans can match the machines ability to find data. But is it AI? The quick answer is no.

Let’s see a machine evolve the same way humans do. Build a machine. Give it an operating system, and access to sensor feeds, but nothing else. Don’t write any software for it. Turn it on. If it is true intelligence it will evolve, build its own programs, become self-aware, build it’s own repertoire of data, learn. Evolve, just like humans and other animals do. The truth is that this will never lead to artificial intelligence. We create AI though algorithms and data. This “AI” will get better as we write better algorithms. But will the AI be able to feel? Be creative? Perceive as we do? The answer is no. In fact AI seems to be one of those fields that we could likely do without. Will it help make a smarter, “intelligent” thermostat? Maybe. But then maybe we don’t need intelligent thermostats. Maybe we need better insulation in our houses.

All this research may lead to some breakthrough somewhere down the road, and that’s great. Problem is, the planet we call home needs solutions to its problems now. In 50-100 years, it will likely be too late.

 

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