Reminds me when X-rays first were discovered, everyone claimed their product contained them, including X-ray headache tablets, golf balls, stove polish, razor blades. <a href="https://pubs.rsna.org/doi/full/10.1148/rg.242035157" rel="nofollow">https://pubs.rsna.org/doi/full/10.1148/rg.242035157</a> for some fun pictures.<p>I won't be surprised when AI toothbrushes come out.
The rebuttal to this view is "provide a principled definition of intelligence". Doesn't seem like the article does this.<p>A hint appears partway through: "computers will not be able to match humans in their ability to reason abstractly about real-world situations". Does human intelligence distinguish itself by its "abstractness" and by its application to "the real world"? There's also "the systems do not form the kinds of semantic representations and inferences that humans are capable of". Seems like a promising direction for some definition of intelligence.<p>For my money, we will never consider any machine intelligent as long as we mass produce it. The only way we'll accept machines as intelligent is if, as the singularity theorists say, the machines build themselves. Then we aren't really mass producing them, we're just kicking off a process that we don't totally understand, a bit like gestation.
I really liked the definition of AI (back in 2015) by Seth Godin - a marketer!<p>><i>One common insightful definition of AI: Artificial Intelligence is everything a computer can't do yet. As soon as it can, we call it obvious.</i><p>If the term is used like that it does make sense to me.<p><a href="https://seths.blog/2015/04/the-noise-in-our-head-and-artificial-intelligence/" rel="nofollow">https://seths.blog/2015/04/the-noise-in-our-head-and-artific...</a>
"Computers have not become intelligent per se, but they have provided capabilities that augment human intelligence, he writes. Moreover, they have excelled at low-level pattern-recognition capabilities that could be performed in principle by humans but at great cost. "<p>It's odd how under-appreciated this is. There is no "intelligence" here as we know it, not even a hint. There are algorithms operating on data for very prescribed use cases. When you break it down its pretty primitive stuff really. Clever sure, but don't think we're building a mind here, that language just confuses things. So much of the public conversation around this stuff is polluted with this sort of sci fi nonsense claiming all sorts of properties for AI and implying some sort of singularity is around the corner. Pure fantasy.
I tried convincing the business developers and marketing for years that what we did was machine learning, applied statistics or gulp “data-driven” functionality - but no, only thing that worked was “<Company> AI Engine”... hurray for throwing my PhD at the wind...
AI isn't really a thing per se and it adds a kind of patina of false mystique to computation that is essentially no different than any other computation (which itself is also not really "a thing" out there in the world as a phenomenon). The only way AI really means anything is because the person in question has decided to frame something as AI. He is choosing to append to something meaning that it itself does not possess. Take a the linear regression type stuff lots of AI today uses. You put that in another context and it ceases to be AI. Why? Because it's not AI per se! If it were a real thing or real phenomenon, it would be mind-independent and the mental context wouldn't determine its identity.<p>Basically, it seems that whenever someone mechanizes something that previous only a thinking person could do, then its viewed as AI.
When machine learning was a buzz word then companies started using it to describe almost everything they do. Recently I have also noticed that more companies (and PMs) are using AI in its place, at least in their marketing speak.<p>Often the AI or machine learning that is being sold to their customers (or if it’s a startup, to their investors) is in fact a team or a group of teams creating static rules. If it is image recognition the they will often have a large team of manual reviewers. Yes there maybe some AI or machine learning models that are assisting in the decision making, but they are usually much less effective than people realize.<p>Today whenever I hear AI or machine learning, my default is to assume it is marketing speak.<p>I don’t doubt there are models, I just doubt their effectiveness. But saying “we use AI to do X”, sounds much better than saying, “we have a team of experts who help us do X really well”<p>With that said I have worked and continue to work with some amazing data scientist who really are pushing the limits of what can be done with machine learning.
While I mostly agree with Michael Jordan, I think that he overstates his argument a small bit. I feel comfortable applying the "AI" label to projects if they: 1) achieve human level of performance or better. 2) They use any or all of standard techniques like deep learning, NLP, knowledge representation, reinforcement learning, etc.<p>I am just about to hit my 40 year anniversary for getting paid to be doing "AI" related work, with a lenient definition of AI.<p>On the other hand, Artificial General Intelligence is a much stronger term, and is something that I don't expect to see in my lifetime.
I appreciate this notion. It seems as though AI has become a fancy marketing term for stats. I also think there are times when knowing which types of models are used would be really helpful. Having built models with neural nets and glms on the same data sets, there are pros and cons to a variety of approaches and oftentimes the simple ones win, even after a 6 month detailed analysis of all the predictors.
AI these days can be seen as nothing more than a bunch of code used to offload human manual labor to machines, and nothing more. Strong AI[0] is the real sought after gem we all want, but also the one that could cause problems (since it could 'run away' from the inventors and end up controlling humanity in some form).<p>I imagine if we really wanted to build our final invention[1] then we would have to be under some existential pressure to do so. In other words: we would build a 'run away' AI if it could potentially save humanity. Also worth reading this: <a href="https://en.wikipedia.org/wiki/Ethics_of_artificial_intelligence" rel="nofollow">https://en.wikipedia.org/wiki/Ethics_of_artificial_intellige...</a><p>[0] <a href="https://en.wikipedia.org/wiki/Strong_AI" rel="nofollow">https://en.wikipedia.org/wiki/Strong_AI</a><p>[1] <a href="https://en.wikipedia.org/wiki/Our_Final_Invention" rel="nofollow">https://en.wikipedia.org/wiki/Our_Final_Invention</a>
Sadly our marketing tests show that when we say our product uses ML we get far less engagement than when we say AI. I don't know that net-conversion is better with AI but ML sure doesn't capture people's imagination. Sigh.<p>Btw, reminds me of the old joke that goes something like this:
AI for marketing, ML for recruiting, Regression for design, multiplication for implementation.
I think IEEE has had it right for several decades now - Computational Intelligence. I’ll never forget when my undergrad research adviser in Artificial Neural Networks and Self Organising Maps (circa 2003) corrected me - “we call it computational intelligence as artificial intelligence is science fiction”.
Having grown up with 8 and 16 bit games systems and the term AI being used to describe the computer opponents (eg in beat em ups) I’ve long since learned not to take the term AI literally.<p>The problem is the term never had a technical definition. It was always just a hand waving marketing phrase for “clever algorithms”.
There's a rule of thumb literally for years. If it's Python - we are seeng a ML. If it's PowerPoint - ladies and gentlemen, let me present to you an AI.
The last time I was at a start up (~2 years ago), it was a running joke that the easiest way to raise money was to say your product had something to do with AI. We saw so many companies that were branding everything as AI simply to raise a round.<p>One of the funniest cases was a start up that claimed to be using AI to process their customers' requests but was actually just farming out the work to contractors who were doing everything by hand.
It annoyed me at first but I don't think it matters.<p>The technical people involved have since moved on to using AGI as the term for "actual AI" for years now.
> “People are getting confused about the meaning of AI in discussions of technology trends—that there is some kind of intelligent thought in computers that is responsible for the progress and which is competing with humans,” he says. “We don’t have that, but people are talking as if we do.”<p>How much more am I as a human really than the machine learning algorithms are?
Hey, would somebody mind breaking down the different not-necessarily-AI things? Like is machine learning the same as neural nets or a subset? This would be tremendously useful! I would assume "expert systems" falls somewhere at the bottom of the list, right above "good old vanilla programming". Dunno how linear regression fits in.
If a rule-based system can get as good of results as a deep neural net, why is the deep neural net "AI" but the rule-based system is "dumb and hard-coded"?<p>AI is not a precise term. If you can make a product that feels intelligent to the user, why does the implementation matter?
I agree with the article. I think calling machine learning as it is today AI is just plain wrong, it started as pure marketing about 5 years ago & now it's almost like people are believing it, even in the industry.
What would be a better way to call 'AI' then for the general public?<p>pattern recognition? matrix multiplication? fancy statistics? or maybe enhanced statistics?<p>gah, might as well just say 'algorithm' and just be done with it.
When I read the title, I thought of Mike J Jordan immediately.<p>And then I clicked on the article.<p>HAHAHA.<p>I learned Bayesian inference models from him.
But I heard the florist across the street telling me they are just now getting into the 'deep learning AI' (what they said) just to pick the right flowers for my mother for mothers day several weeks ago. Since they are 'going to use' deep learning soon, they must be turning into an AI company. /s<p>Every time I see a new company preaching endlessly about 'AI' to address a non issue at this point is straight-up begging to VCs to fund their $0 revenue so-called 'tech startup'.
Off topic: This website needs me to 'accept & close' cookies before i read the article.<p>I had people respond to me in a gdpr thread saying that they never accept cookies<p>example : <a href="https://news.ycombinator.com/item?id=26360345" rel="nofollow">https://news.ycombinator.com/item?id=26360345</a><p>What do such ppl do here? just not read the article?
Whew boy, this guy reminds me of Frank Grimes: mad that he can't control the world. I don't really think it matters, "computers" originally meant the women computed ballistics tables for the military in the early 40's... language changes, one person can't change that.
What is considered "AI" changes over time. At any point in history, if a machine appears to do a task that only a human brain used to be able to do, then that's considered "AI".<p>So in the mid 1900s a calculator that is able to do arithmetic was considered "AI", and in the late 1900s chess playing machines were considered "AI". Today those things are not considered "AI".<p>What is considered "AI" today will not be considered "AI" a decade or two from now.<p>More: <a href="https://ai100.stanford.edu/2016-report/section-i-what-artificial-intelligence/defining-ai" rel="nofollow">https://ai100.stanford.edu/2016-report/section-i-what-artifi...</a>