How AI Is Making Prediction Cheaper

HBR IdeaCast

Harvard Business Review

Leadership, Entrepreneurship, Communication, Marketing, Business, Business/management, Management, Business/marketing, Business/entrepreneurship, Innovation, Hbr, Strategy, Economics, Finance, Teams, Harvard

4.4 • 1.9K Ratings

🗓️ 22 May 2018

⏱️ 23 minutes

🔗️ Recording | iTunes | RSS

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Summary

Avi Goldfarb, a professor at the University of Toronto’s Rotman School of Management, explains the economics of machine learning, a branch of artificial intelligence that makes predictions. He says as prediction gets cheaper and better, machines are going to be doing more of it. That means businesses — and individual workers — need to figure out how to take advantage of the technology to stay competitive. Goldfarb is the coauthor of the book “Prediction Machines: The Simple Economics of Artificial Intelligence.”

Transcript

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0:00.0	Hey everyone it's Kurt we need your help with our annual survey this is your last chance to help us get to know you so we can make idea cast even better for you
0:09.8	it's easy just go to HBR.org
0:13.0	podcast survey.
0:15.0	Again, that's HBR.org.
0:17.0	And thanks for listening. Welcome to the HBR IDEA cast from Harvard Business Review. I'm Kurt Nickish and for Sarah Green Carmichael.
0:43.6	We've got this all tabbed up.
0:47.0	Yep, it's all tabbed up.
0:51.0	Okay. dialing.
0:54.0	There's a YouTube video with millions of views.
0:59.0	In it, a couple of young women use Google Translate to order food in Hindi from an Indian restaurant.
1:06.3	They copy and paste their order in English into the computer and it translates items like
1:11.3	Somosas and reads them aloud in the foreign language.
1:17.0	At one point the women give their address for the delivery and the worker asks in Hindi if they want anything else.
1:24.0	They don't know what he's saying so they just give their address again.
1:30.0	Despite the momentary miscommunication when the quarter shows up, it's correct.
1:39.0	We got two of Basamati rice, three semoses. What's remarkable about this video is that it Smut
1:47.1	and 3 Somoas? What's remarkable about this video is that it's 8 years old. And since then, Google Translate has gone
1:49.1	from translating word by word to processing more at the sentence level. Pretty soon you won't have to
1:55.6	copy and paste into a search box anymore. And you'll be able to put something in
2:00.3	your ear or have something on your phone and get instant translations for
2:04.4	whatever language anywhere in the world and understand what people are talking about.
2:08.1	That's our guest today of E. Goldfarb. For him, one of the most mind-blowing uses of artificial intelligence technology is machine
	...

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