""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
Science (https://courses.csail.mit.edu/18.337/2015/docs/50YearsDataScience.pdf).

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).

Best,
Péter
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.
>
> Chris
>
> 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. [1] 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.
> >
> > [1] travelogue - https://sites.nd.edu/emorgan/2018/12/fantastic-futures/
> >
> > [2] ai4lib – https://groups.google.com/forum/#!forum/ai4lib
> >
> > --
> > Eric Lease Morgan
> > University of Notre Dame



-- 
Péter Király
software developer
GWDG, Göttingen - Europeana - eXtensible Catalog - The Code4Lib Journal
http://linkedin.com/in/peterkiraly