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It can be difficult (or difficult) to define what AI is or isn’t. So much so that even experts sometimes get it wrong. That’s why Karen Hao, Senior Artificial Intelligence Editor at MIT Technology Review, created a flowchart to explain it all. In this bonus content, our host and his team redesigned Hao’s. original reporting, by gamifying it into a radio play.
Credit:
This episode was reported by Karen Hao. Adapted for voice and produced by Jennifer Strong and Emma Cillekens. The voices you hear are Emma Cillekens from our art team, as well as Eric Mongeon and Kyle Thomas Hemingway. Edited by Michael Reilly and Niall Firth.
Full transcript:
[:15 pre-roll]
[TR ID]
Jennifer: Hello there. I’m Jennifer Strong… presenter Machines We Trust.
Defining what AI is or isn’t can be a little tricky. So much so that even experts sometimes get it wrong. That’s why Tech Review’s senior AI editor Karen Hao created a flowchart to explain this… and together, we got to the next section… It’s ridiculous. Comic. And we hope it helps.
I also want to tell you something really special that we’ve been working on for over a year. called Extortion Economy. A short podcast series about the ransomware epidemic produced in collaboration with ProPublica. And now it’s available wherever you want to listen.
[Show ID]
Emma Cilikens: Ladies and gentlemen… ‘Welcome to this Artificial Intelligence…
Players, what is what… or not… AI… and… and… I brought an “assistant” to help with the answers…
Voice assistant: Hello there.
Emma Cilikens: Hello Alex.
Emma Cilikens: And we’re all on the same page… Artificial Intelligence… in its broadest sense refers to machines that can learn, reason and act for themselves. Like people and animals, they can make their own decisions when faced with new situations.
Emma Cilikens: Now this bell… [SOT: ding] …means correctly defined AI… and this buzzer… [SOT: buzzer, crowd sigh] Not really.
Emma Cilikens: OK. So, let’s test your knowledge.. Ready… set… player one, go! ..
Eric Mongeon: Can ‘he’ see…
Voice assistant: Yeah.
Eric Mongeon: Can he describe what he saw…
Voice assistant: Number …[SOT: buzzer]
Emma Cilikens: Ok, so it’s just a camera…
Eric Mongeon: okay okay… but what if to be able to describe what you see?
[SOT: ding, ding, ding]
Emma Cilikens: Yes – this is computer vision and image processing. Player two!
Kyle Thomas Hemingway can you hear…
Voice assistant: Yeah
Kyle Thomas Hemingway Does he respond in a helpful and logical way to what he hears?
Voice assistant: Yeah
[SOT: DING DING DING]
Emma Cilikens: So, this is NLP—natural language processing.
The purpose of this type of artificial intelligence is to help computers usefully make sense of human languages.
But what if do not do responds to what he hears in a helpful and logical way. Could this be AI too?
Kyle Thomas Hemingway If he’s copying what you’re saying…
[SOT: bell ding, ding, ding]
Emma Cilikens: Yeah! This is also AI – speech recognition, which is similar but works from spoken word instead of text. New question round! Player 1.
Eric Mongeon: can he read
Voice assistant: Yeah
Eric Mongeon: Does he read what you write?
Voice assistant: Number
Eric Mongeon: Does it read text passages?
Voice assistant: Yeah
Eric Mongeon: Does it analyze the text for patterns?
Voice assistant: Yeah
[SOT: ding, ding, ding]
Emma Cilikens: Yes, this is NLP once again—natural language processing. Congratulations!
Kyle Thomas Hemingway I’ll get the same question again – Is it readable?
Voice assistant: Yeah
Kyle Thomas Hemingway Does he read what you write?
Voice assistant:: Yeah
Kyle Thomas Hemingway Does it respond in a logical and helpful way?
Voice assistant: Yeah
[SOT: ding, ding, ding]
Emma Cilikens: This is also NLP—natural language processing. New question please player 1.
Eric Mongeon: could it cause?
Voice assistant: Yeah
Eric Mongeon: Looking for patterns in large amounts of data?
Voice assistant: Yeah
Eric Mongeon: Does he use these patterns to make decisions?
Emma Cilikens: If not, it sounds like math….
Eric Mongeon: But what if he uses patterns to make decisions?
Voice assistant: Yeah
[SOT: ding, ding, ding]
Emma Cilikens: Then this is machine learning; this is when a machine learns through experience. OK. Last lap!
Kyle Thomas Hemingway Can it move?
Voice assistant: Yeah.
[SOT: ding, ding, ding]
Kyle Thomas Hemingway On your own, without help?
Voice assistant: Yeah.
[SOT: ding, ding, ding]
Kyle Thomas Hemingway Does he act on what he sees and hears?
Voice assistant: Yeah.
[SOT: ding, ding, ding]
Kyle Thomas Hemingway Are you sure you’re not just following a pre-programmed path?
Voice assistant: [Alexa] Hmm. I’m not sure.
Emma Cilikens: It’s hilarious… but if it is, it’s just a bot.
[SOT: buzzer, crowd sigh]
Kyle Thomas Hemingway OK, let’s try again. Is it moving along a pre-programmed path?
Voice assistant: Number.
[SOT: ding, ding, ding]
Emma Cilikens: Okay, this is an intelligent robot, meaning a robot that uses artificial intelligence to make some of its own decisions.
Wonderful….
And that’s the game.
Thanks for playing!
[Music up full]
Jennifer: We’ll be back – soon after that.
[MIDROLL]
[MUSIC]
Jennifer: A big thank you to the talented voices in this episode, including our producers Emma Cillekens, Eric Mongeon and Kyle Thomas Hemingway. Editors Michael Reilly and Niall Firth.
Thanks for listening… I’m Jennifer Strong.
[Post Roll: TR ID]
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