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


Explaining what is, or is not, the creative process can be difficult (or difficult). Too often, even experts sometimes make mistakes. This is why MIT Technology Review’s Senior AI Editor Karen Hao created a flowchart to explain everything. In these bonuses we were welcomed by his team he also thought about Hao initial report, making it a radio drama.

Extras:

The story was told by Karen Hao. It was adapted to be composed by Jennifer Strong and Emma Cillekens. The voices you hear are from Emma Cillekens, as well as Eric Mongeon and Kyle Thomas Hemingway from our art team. We were replaced by Michael Reilly and Niall Firth.

All posts:

[:15 pre-roll]

[TR ID]

Jennifer: Hi there. I am Jennifer Strong… director In Machines We Trust Them.

Explaining what it is, or is not, the creative process can be difficult. So much so, that even experts make mistakes sometimes. That’s why Tech Review AI editor-in-chief Karen Hao created a descriptive chart… It’s fun. And we hope it helps.

I would also like to tell you about something very special that we have been working on for over a year. It is called The Extortion Economy. It is a short podcast series about the ransomware epidemic developed in collaboration with ProPublica. And It’s available now wherever you would like to listen.

[Show ID]

Emma Cilikens: Ladies and gentlemen … Welcome to ‘This is AI’ …

Players ask questions that reach the end of the content…

Voice Assistant: Hello.

Emma Cilikens: Hello, Alexa.

Emma Cilikens: And just because we are all on the same page… Artificial Intelligence… in its entirety means machines that can learn, think, and act on their own. They are free moral agents, as humans and animals are.

Emma Cilikens: Now this bell … [SOT: ding] … means well-known AI… [SOT: buzzer, crowd sigh] Well … not so much.

Emma Cilikens: All right. So, let’s test your knowledge .. Ready … be… player one, go! ..

Eric Mongeon: Are they ‘seeing’ …

Voice Assistant: Yes.

Eric Mongeon: It can detect what they see …

Voice Assistant: No …[SOT: buzzer]

Emma Cilikens: Well, then just a camera …

Eric Mongeon: ok ok … but if so he can to realize what he is seeing?

[SOT: ding, ding, ding]

Emma Cilikens: Yes – that’s computer vision and photo editing. Player two!

Kyle Thomas Hemingway: Can hear …

Voice Assistant: Yes

Kyle Thomas Hemingway: Does it respond in a practical, sensible way to what it is hearing?

Voice Assistant: Yes

[SOT: DING DING DING]

Emma Cilikens: The reason, then, is NLP – the development of natural languages.

The purpose of this type of AI is to help computers understand human languages ​​in a more efficient way.

But what if satero respond positively, wisely to what you have heard. Could it also be AI?

Kyle Thomas Hemingway: If it records what you are saying…

[SOT: bell ding, ding, ding]

Emma Cilikens: Yes! It is also AI — and speech recognition, which is similar but works from spoken words instead of text. New questions! Player 1.

Eric Mongeon: Can he read?

Voice Assistant: Yes

Eric Mongeon: Am I reading what you write?

Voice Assistant: No.

Eric Mongeon: Am I reading the text?

Voice Assistant: Yes

Eric Mongeon: Am I analyzing color words?

Voice Assistant: Yes

[SOT: ding, ding, ding]

Emma Cilikens: Yes, and so is NLP – natural language development. Well done!

Kyle Thomas Hemingway: I answer the same question – Can it read?

Voice Assistant: Yes

Kyle Thomas Hemingway: Am I reading what you write?

Voice Assistant:: Yes

Kyle Thomas Hemingway: Does it answer wisely, in a practical way?

Voice Assistant: Yes

[SOT: ding, ding, ding]

Emma Cilikens: It is also an NLP-based natural language development. New question please player 1.

Eric Mongeon: Can they imagine?

Voice Assistant: Yes

Eric Mongeon: Looking for more data systems?

Voice Assistant: Yes

Eric Mongeon: How to use these techniques to make plays?

Emma Cilikens: Well, if not, that sounds like math….

Eric Mongeon: But what if he is using a method to make decisions?

Voice Assistant: Yes

[SOT: ding, ding, ding]

Emma Cilikens: So that’s machine learning — that’s where machines learn through experience. All right. The finish line!

Kyle Thomas Hemingway: Can it move?

Voice Assistant: Yes.

[SOT: ding, ding, ding]

Kyle Thomas Hemingway: Individually, without help?

Voice Assistant: Yes.

[SOT: ding, ding, ding]

Kyle Thomas Hemingway: Does it move based on what you see and hear?

Voice Assistant: Yes.

[SOT: ding, ding, ding]

Kyle Thomas Hemingway: Are you sure you want to continue the process?

Voice Assistant: [Alexa] Hmmm. I do not know.

Emma Cilikens: Very funny… but if so, it’s just a bot.

[SOT: buzzer, crowd sigh]

Kyle Thomas Hemingway: All right, let’s try again. Is it moving in a predetermined direction?

Voice Assistant: No.

[SOT: ding, ding, ding]

Emma Cilikens: Well, that’s a smart robot, meaning that it uses AI to make its own decisions.

Good….

And that’s the game.

Thanks for playing!

[Music up full]

Jennifer: We’ll be back – as soon as this happens.

[MIDROLL]

[MUSIC]

Jennifer: Thank you so much for the creative voice in this episode — including our producer, Emma Cillekens, and Eric Mongeon and Kyle Thomas Hemingway. Designers by Michael Reilly and Niall Firth.

Thanks for listening… I’m Jennifer Strong.

[Post Roll: TR ID]



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