""AI" now is just another name for statistics and statistics
(especially in disguise) is very dangerous given that untrained human
beings are very bad at statistics."
I agree with the second part of this sentence, but I don't think that
AI is just relabelling statistics. There are lots of discussion about
it, my favorite paper on this is David Donoho's 50 years of Data
Regarding to metadata: I think there might be lots of cases, where we
could use metadata as labels in supervised learning or as a gold
standard in information extraction experiments, however I never run
any real test, so I can imagine different scenarios where it may or
may not be misleading (I hope that properly curated metadata would
more often be proved to be unbiased than not).
Chris Gray <[log in to unmask]> ezt írta (időpont: 2018. dec. 11., K, 17:34):
> 1. I would add that what is called "AI" nowadays is not what was meant
> when the term was invented. "AI" now is just another name for
> statistics and statistics (especially in disguise) is very dangerous
> given that untrained human beings are very bad at statistics. I would
> rather that people spent less time promoting "AI" and more time becoming
> aware of cognitive biases and how they infect everything we think. I
> love the book title "Don't believe everything you think".
> 2. We are not even close and most of that technology should be
> classified as torturing the data until it confesses. I was very
> disappointed when I started to read a book on deep learning with Python
> and discovered it was just about choosing canned statistical analyses to
> get what you were already looking for. I recommend googling for tests
> that show that Alexa, Siri, and Hey, Google aren't as good as the
> commercials might lead you to believe, or why self-driving cars are not
> coming any time soon.
> 3. Technology is no substitute for serious human thought. Metadata will
> not save us. On this Cory Doctorow's Metacrap is my touchstone. Also
> Fred Brooks's "No Silver Bullet" was right in 1986 and it is still right.
> I'm not saying that techniques that come out of AI research aren't worth
> using, but that we should use them instead of being used by them and
> those that hype them.
> On 2018-12-10 4:52 p.m., Eric Lease Morgan wrote:
> > Last week I attended an artificial intelligence (AI) in libraries conference, and I've written the briefest of travelogues.  Some of my take-aways include:
> > 1. Machine learning is simply the latest incarnation of AI, and
> > machine learning algorithms are only as unbiased as the data used
> > to create them. Be forewarned.
> > 2. We can do this. We have the technology.
> > 3. There is too much content to process, and AI in libraries can
> > used to do some of the more mechanical tasks. The creation and
> > maintenance of metadata is a good example. But again, be
> > forewarned. We were told this same thing with the advent of word
> > processors, and in the end, we didn’t go home early because we
> > got our work done. Instead we output more letters.
> > 4. Metadata is not necessary. Well, that was sort of a debate,
> > and (more or less) deemed untrue.
> > If you want to participate in AI for libraries-like discussions, then consider subscribing to ai4lib.
> >  travelogue - https://sites.nd.edu/emorgan/2018/12/fantastic-futures/
> >  ai4lib – https://groups.google.com/forum/#!forum/ai4lib
> > --
> > Eric Lease Morgan
> > University of Notre Dame
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