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Comment by robot197 | Hacker News Reader

I still think there is too much hype around AI with all the doomsday prediction. Yeah, data processing will get automated away, but most jobs that require thinking within an ill defined framework will be fine for at least the next 20 years. The human brain is vastly superior to any machine learning algorithm we currently have.

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Forecasts are being pushed in the mainstream media that tout that 50% of all existing US jobs will be wiped out in the next 10 to 15 years. It has reached manic levels.

35-50 years, probably still wildly over the top. 10-15? Zero chance. If you had the perfect solution in a lab that could, for example, replace truck drivers today, you couldn't even get that fully implemented & distributed such that it cleared out 50% of all trucking jobs in 10-15 years. The entire economy? It'd be laughable if there weren't so much fear mongering involved in pushing these bogus forecasts.

It's another example of people over-estimating change in the near-term. In 1999, ecommerce was going to immediately threaten all physical retail with extinction. If you didn't get on that hype train, you were toast. 23 years post founding, with year after year of incredible growth, Amazon is still just 1/4 the size of Walmart. As it turns out, it more often takes a long time to change the world.

Firstly, the human brain is not vastly superior. There are already tasks such that a reasonably competent developer can build and train a deep learning model that beats human perception on commodity hardware with open source software.

Secondly, the number of jobs requiring thinking in an ill-defined framework these days is shrinking rapidly.

This is not specifically caused by machine learning, but rather by the desire for predictable timelines / cost savings / metrics gathering. But it has set the stage for AI automation.

Take law and health care, for example:

* Law firms are consolidating, and lawyers can now spend their entire career working on one small, specialized aspect of a field.

* Primary care physicians barely are allotted just enough time to refer you to a specialist. The specialist has just enough time to order tests.

Yeah, on the ImageNet data set, where all the images are pretty unclear, low res and cropped weirdly leaving out context, deep learning "beats" human vision system.

Human brain beats everything for now. It is a much more generic system.

I don't know enough about the specific fields you talked about to comment.

Deep learning is an incredibly powerful tool, but we should differentiate between its actual merit and the huge hype around it, mostly done for PR and misleading investors/financial analyst.

You are moving the goalposts.

If we're talking about doing a specific task within a well-defined framework, computers are already proving to be superhuman. That includes image recognition beyond ImageNet, as well as games like Go.

But yes, if we're talking about a generic system, then humans are better. And I think they will be for a long time.

And yes, I agree, there is a lot of noise and sizzle around AI (but there is also quite a bit of steak there too.)

I think a big factor that people are failing to take into account is time to market and deployment. Imagine we had amazing AI that could do a lot of office jobs now. We’d still need to make useful software out of it, distribute and sell that software, customize it for different needs. That, by itself, could take years.

Forget the human brain, we are a long way away from doing what an ant does with it's spec of dust size mind. And that still requires acres of racks.

But the hype does help with funding. Which is a good thing.

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