Tech

Podcast: What is AI? We did it to help.

Determining what is and isn’t artificial intelligence can be tricky (or tricky). So much so that even experts are sometimes wrong. That’s why MIT Technology Review’s senior artificial intelligence editor Karen Hao created a flowchart to explain it all. In this bonus content, our host and her team have reimagined Hao’s original storyline into a radio drama.

Credits:

The episode was reported by Karen Hao. It was adapted for audio and produced by Jennifer Strong and Emma Silllekens. You hear the voices of Emma Sillekens, as well as Eric Mongeon and Kyle Thomas Hemingway from our team of artists. We were edited by Michael Reilly and Niall Firth.

Full transcript:

[:15 pre-roll] [TR ID]

Jennifer: Hello everyone. I’m Jennifer Strong … presenter In machines we trust

Determining what is and isn’t artificial intelligence can be tricky. So much so that even experts are sometimes wrong. That’s why Tech Review’s senior AI editor Karen Hao created a flowchart to explain it … and together we moved on to the next episode … This is silly. It’s fun. And we hope this helps.

I also want to tell you about something really special that we have been working on for over a year. It is called The extortion economy… This is a short ransomware epidemic podcast series produced in partnership with ProPublica. And now it’s available wherever you want to listen.

[Show ID]

Emma Silicens: Ladies and gentlemen … Welcome to “This is AI” …

Players will ask questions that will get to the bottom of … or not … AI … And … I took a “helper” with me to help with the answers …

Voice Assistant: Hi.

Emma Silicens: Hi Alexa.

Emma Silicens: And that’s why we’re all on the same page … Artificial intelligence … in its broadest sense refers to machines that can learn, reason and act on their own. They can make their own decisions in new situations, like humans and animals.

Emma Silicens: Now this bell … [SOT: ding] … means a correctly identified AI … and this buzzer … [SOT: buzzer, crowd sigh] Well … not really.

Emma Silicens: Ok. So let’s put your knowledge to the test .. Done … Install … Player One, Go! ..

Eric Monjon: Can “it” see …

Voice Assistant: Yes.

Eric Monjon: Can he identify what he sees …

Voice Assistant: No …[SOT: buzzer]

Emma Silicens: Ok, this is just a camera …

Eric Monjon: ok ok … but what if it’s can determine what he sees?

[SOT: ding, ding, ding]

Emma Silicens: Yep is computer vision and image processing. Second player!

Kyle Thomas Hemingway: He hears …

Voice Assistant: Yes

Kyle Thomas Hemingway: Does he respond in a useful and intelligent way to what he hears?

Voice Assistant: Yes

[SOT: DING DING DING]

Emma Silicens: So this is NLP – natural language processing.

The goal of this kind of AI is to help computers understand human language in the most useful way.

But what if it is not respond in a helpful and reasonable manner to what he hears. Maybe this is also AI?

Kyle Thomas Hemingway: If he deciphers what you say …

[SOT: bell ding, ding, ding]

Emma Silicens: Yes! This is also AI – this is speech recognition, which is similar, but works on the spoken word, not on the text. New round of questions! Player 1.

Eric Monjon: Can you read it?

Voice Assistant: Yes

Eric Monjon: Does he read what you type?

Voice Assistant: No

Eric Monjon: Is this reading passages of text?

Voice Assistant: Yes

Eric Monjon: Analyzing text for patterns?

Voice Assistant: Yes

[SOT: ding, ding, ding]

Emma Silicens: Yes, again, this is NLP – natural language processing. Great job!

Kyle Thomas Hemingway: I’ll answer the same question again – can he read?

Voice Assistant: Yes

Kyle Thomas Hemingway: Reads what you are typing?

Voice Assistant:: Yes

Kyle Thomas Hemingway: Does he respond in an intelligent and helpful manner?

Voice Assistant: Yes

[SOT: ding, ding, ding]

Emma Silicens: This is also NLP – natural language processing. New question please, player 1.

Eric Monjon: Can this reason?

Voice Assistant: Yes

Eric Monjon: Looking for patterns in huge amounts of data?

Voice Assistant: Yes

Eric Monjon: Does he use these patterns to make decisions?

Emma Silicens: Well, if not, it sounds like math …

Eric Monjon: But if he uses patterns to make decisions?

Voice Assistant: Yes

[SOT: ding, ding, ding]

Emma Silicens: Then this is machine learning – when the machine learns from its own experience. Ok. Last round!

Kyle Thomas Hemingway: Can he move?

Voice Assistant: Yes.

[SOT: ding, ding, ding]

Kyle Thomas Hemingway: Needless to say, without outside help?

Voice Assistant: Yes.

[SOT: ding, ding, ding]

Kyle Thomas Hemingway: Does he move depending on what he sees and hears?

Voice Assistant: Yes.

[SOT: ding, ding, ding]

Kyle Thomas Hemingway: Are you sure this is not just a pre-programmed path?

Voice Assistant: [Alexa] HM. I’m not sure.

Emma Silicens: Very funny … but if so, then this is just a bot.

[SOT: buzzer, crowd sigh]

Kyle Thomas Hemingway: Okay, let’s try again. Is he following a preprogrammed path?

Voice Assistant: No.

[SOT: ding, ding, ding]

Emma Silicens: So, this is a smart robot, that is, one that uses AI to make some of its own decisions.

Big….

Here comes the game.

Thanks for playing!

[Music up full]

Jennifer: We’ll be back – right after that.

[MIDROLL] [MUSIC]

Jennifer: Many thanks to the talented voices in this episode, including our Producer Emma Sillekens, Eric Mongeon, and Kyle Thomas Hemingway. Editors – Michael Reilly and Niall Firth.

Thanks for reading … I’m Jennifer Strong.

[Post Roll: TR ID]


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