Past Performance is Not Indicative of Future Results (2020)

Post by foobiekr » Sat, Jul 31, 2021, 5:25 PM UTC

3gg wrote: post #50

foobiekr wrote: post #46

Earlier quoted context omitted.

There are three entirely different groups at work here. The deepmind team etc type of group who actually know what they’re doing and the boundaries of what they are working with the “AI-washing” startups, corporate groups who know they are faking it and that what they’re doing is extremely limited the corporate project team types who are just doing random tool play and honestly don’t understand what they are doing or…

Where does Google Vision Cloud sit in your categorization? https://algorithmwatch.org/en/google-vision-racism/

Post by xnyan » Sat, Jul 31, 2021, 5:27 PM UTC

nkozyra wrote: post #43

> It’s not sorcery, it’s “magic” – in the sense of being a parlor trick, something that seems baffling until you learn the underlying method, whereupon it becomes banal. I think part of the problem is the belief that human or animal intelligence is somehow more mystical. People who think like this will see an ML implementation solve a problem better and/or faster than a human and counter "well, it's just using statis…

Post by 3gg » Sat, Jul 31, 2021, 5:31 PM UTC

foobiekr wrote: post #52

3gg wrote: post #50

Earlier quoted context omitted.

Where does Google Vision Cloud sit in your categorization? https://algorithmwatch.org/en/google-vision-racism/

First group. You’re observing that they aren’t doing a perfect job, which is true, but my grouping isn’t related to perfection of results.

Post by tw04 » Sat, Jul 31, 2021, 5:31 PM UTC

coddle-hark wrote: post #42

shreyshnaccount wrote: post #33

Earlier quoted context omitted.

I'm in favor of changing the terminology from AI and ML to something along the lines of 'prediction model' so that the idea of machines 'thinking' is replaced with them 'predicting'. it's just easier for our mushy meat brains to think that AI and ML means that it'll lead to general AI or as I like to call it 'general purpose decision maker'. it's all about the language!

I like the term “data driven algorithm“. It makes it clear to everyone involved that what we’re doing is just adjusting an algorithm based on the data we have. No-one in their right minds would confuse that with building a true “A.I.”.

Post by bhntr3 » Sat, Jul 31, 2021, 5:36 PM UTC

3gg wrote: post #10

version_five wrote: post #9

This article is mostly a straw man, while still containing some valid ML criticism. I am a ML s(c|k)eptic too, in that popular conceptions of what ML is currently overpromise, often don't even understand what ML actually is, and are often just some layperson's imagination about what "artificial intelligence" might do. This article is the opposite. He's treating ML as basically a simple supervised architecture that do…

> But I also don't think the engineers working in this space are as out to lunch as the author seems to imply. Are you at all close to this space? It sounds you may be underestimating corporate politics and the lack of rigour and ethical thought with which these systems are applied. The example Cory puts on policing -- and the many other examples you can find in Evgeny Morozov's book or "The End of Trust" -- are soli…