Election 2.0
Wonder Cabinet
Wonder Cabinet Productions
4.8 • 1K Ratings
🗓️ 30 October 2016
⏱️ 52 minutes
🧾️ Download transcript
Summary
Americans head to the polls amid mounting political rhetoric, from both sides, about vote rigging and voter supression. Maybe it's time to rethink the way we do elections. In this episode, we surface some ingenious, off-the-wall, and counter-intuitive ideas about how to make voting fairer, better and more fun. You've Been Micro-Targeted; Are Americans Smart Enough To Vote? (The Answer is No); US Elections Rank Worst Among Western Democracies ; Pay To Vote? How Markets Could Fix Democracy; Should We Let Babies Vote?; How To Make Elections Fun Again.
Transcript
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| 0:00.0 | After months of campaigning and debates, months of leaks and tweets and videotapes, months of bad |
| 0:08.7 | hombres and nasty women, pussy grabbing, deleted emails, dirty money, finally, this whole ugly, |
| 0:18.6 | degrading, stressful election is about to be over. |
| 0:24.3 | I'm Anne Strange Champs, and on November 8th, finally, you and I get to walk into a polling place, |
| 0:30.4 | pick up a ballot, and cast our one and only personal and private vote. |
| 0:36.7 | Oh, did I say private? |
| 0:40.1 | The fact that you voted is public information. |
| 0:43.6 | What's not public is who you voted for. |
| 0:45.7 | That's secret. |
| 0:46.8 | But the thing is that these guys have so much information on us, our demographics, |
| 0:51.1 | like the kind of newspapers we read. |
| 0:53.4 | They can infer so much about us that they might as well know who we actually have voted for. |
| 0:58.6 | This is Kathy O'Neill. |
| 1:00.2 | She's a data scientist, and she says there's one thing about this election you might have missed. |
| 1:06.1 | You were micro-targeted. |
| 1:09.1 | So these days, political campaigns know everything about you. They know |
| 1:13.6 | your gender, your occupation, where you live, where you shop, what you buy, who your social |
| 1:18.5 | network is, and what websites you look at. So you tell me, what do you think they do with all |
| 1:25.3 | that information about you? Okay, so let's say they have a candidate. |
| 1:29.4 | And let's say that candidate has like 17 different opinions about policy. So they're going to have, |
| 1:35.3 | for any person, you, they're going to have a score of to what extent you agree with the candidate |
| 1:41.4 | on those policies. Now, they'll also have a score. To what |
... |
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