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Kate Compton @GalaxyKate
, 7 tweets, 2 min read Read on Twitter
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AI is a theatrical term with no technical meaning

AI is a theatrical term with no technical meaning

AI is a theatrical term with no technical meaning

AI is a theatrical term with no technical meaning, hey!
💃
Nothing but love for my original AI agents.

(note: there are some descriptions dating to ancient Greek and Arabic too)
AI has two definitions:
"It's too complex for you to understand because it's a big pile of barely working hacks"
"It's too complex for you to understand, because if you knew that it's really a poorly paid guy turning a crank and talking through a box the magic would go away"
AI that starts as the first can graduate from AI to algorithm as we trust it more (pathfinding, 3d graphics)

AI that starts as the second either eventually switches out the back end (rare), runs out of money/patience trying to do that (common) or is exposed.
"Secretly run by a poorly paid worker" and "big pile of barely-functioning hacks" can be synonymous, except that we more often underestimate the complexity of the worker, and overestimate the potential of our not-quite-there hacks
"just a little more domain modelling and knowledge representation and we'll have it for sure!" - every AI scientist in 1970
Citation: en.m.wikipedia.org/wiki/Commonsen…
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More from @GalaxyKate see all

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Do you know this book (grapefruit, by Yoko Ono)? I've been reading it and profoundly affecting my bot-making.

Art appreciation and bot-making thread follows:
I've been trying to identify a peculiar tendency of bots (and other algorithmically generative text):

When the pleasure of the "artwork" is getting people to ~imagine~ what is being described.
One cause:
generative text is very good at accidental juxtaposition. Give it a bag of things to use, and it will put two next to each other without considering the implications. (humans are bad at this, btw, we have a lot of baggage that makes us overthink juxtapositions)
Read 16 tweets
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Was thinking about this again, and it's important to recognize:

WE CONFLATE THING BEING DIFFICULT FOR HUMANS
WITH THINGS BEING DIFFICULT FOR COMPUTERS

and this colors everything we do in AI.
On reflection, maybe it's "things smart people enjoy stuggling with". Chess, modernist music/art/poetry, Go.

"My AI is smart so it should have smart people hobbies"

But those hobbies are...not representative of challenges for machines.
For example, modernist music is difficult because it requires composers to think outside the patterns they have been trained on. For a small child, this is easy, for very-trained composer Brian Eno, he had to make a deck of cards o help him do this.

lifehacker.com/brian-enos-obl…
Read 12 tweets

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THREAD: I ask Amazon Alexa’s #AI #chatbot about Republicans, Democrats, Trump, Obama, even Rush & @seanhannity The answers are funny, bizarre, and yes, biased against conservatives. For perspective, please read thoughts at end. Here, Alexa suggests Rs are SNL characters 1/12
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President poised to sign bill creating quantum computing initiative

(When combined with self-learning AI, this technology can be wonderful... or downright terrifying.) engadget.com/2018/12/20/pre…
#AI #QuantumComputing
Think INTEL.

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Alan Marco: high quality patent has to adhere to patentability standards and claim an appropriate scope.
(Turns out defining a high quality patent isn’t that hard after all.)
Marco: does allowing amendments post-grant create an incentive for applicants to care less about getting a valid patent up front?
Read 73 tweets
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If you have an interest in #AI, #HealthTech or #PatientSafety - then please read this evidence based thread which tells the story of @DrMurphy11 & an #eHealth #AI #Chatbot.

Read on, or see single tweet summary here👇0/44
is not a 'nerd'; he's a pretty typical NHS consultant with an interest in #PatientSafety.

On 6th Jan 2017 a tweet about an #eHealth #AI #Chatbot in #NHS trials caught his attention, so he thought he'd take a look. 1/44

Evidence here 👇
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As evidenced by👇 2/44
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More hype around AI, mHealth, wearables. @AliveCor devices can use #AI to find LQTS:

prnewswire.com/news-releases/…
From the press release:

AUC 0.83, specificity 81%, sensitivity 73%, accuracy 79%

Prevalence of LQTS 160,000 out of US population of 325.7 million (0.049%)
Do we need to do a tweetatorial about how this is grossly insufficient accuracy and will almost certainly lead to more harm than good?
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