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  • Technology has brought us so much

  • The moon landing, the internet, the ability to sequence the human genome

  • but it also taps into a lot of humansfear

  • and about thirty years ago, the cultural critic Neil Postman wrote a book call the amusing ourselves to death

  • Which lay this out really brilliantly

  • And here’s what he said comparing the dystopian visions of George Orwell and Aldous Huxley

  • He saidOrwell fear that we will become a captive culture; Huxley fear that we would become a trivial culture.’

  • Orwell fear the truth would be conceal from us and Huxley fear we would be drown in the sea of irrelevance.

  • In a nut shell, it’s a choice between big brother watching you and you watching big brother.

  • But it doesn’t have to be this way, we are not passive consumer of data and technology.

  • We shape the role it place in our life and the way we made meaning from it.

  • But to do that, we have to pay as much attention to how we think as how we code

  • We have to ask question and hard question to move pass counting things to understanding them

  • Were constantly bombarded with stories about how much data there is in the world

  • But when it comes to big data, and the challenge is interpreting it

  • Size isn’t everything.

  • There’s also the speed of which it moves

  • And the many variety of data types

  • And here are just the few examples, Images

  • Texts

  • Video

  • Audio

  • And what unites these despair it types of data

  • Is that they are created by people

  • And they require context

  • Now, there’s a group of data scientists at the university of Illinos at Chicago

  • And they are called the Health Media collaboratory.

  • And they have been working with the center for disease control

  • To better understand, how people talk about quitting smoking

  • How they talk about electronic cigarets.

  • And what they can do collectively to help them quit.

  • The interesting thing is if you wanna understand how people talk about smoking

  • First you have to understand what they mean, when they say smoking

  • And on Tweeter, they are four main categories.

  • First one, smoking cigarets.

  • Number two, smoking marijuana.

  • Number three, smoking ribs.

  • And number four, smoking hot women

  • Sothen you have to think about what have the people talk about electronic cigarets?

  • And there are so many different ways that people do this

  • You can see from the slide.

  • It’s a complex kind of queery.

  • And what that reminds us is that

  • Languages created by people.

  • And people are messy and were complex and we use metaphors and slang and jargon

  • And we do this twenty-four seven and many many languages.

  • And then as soon as we figure it out, we change it up.

  • Sodid this ads that cdcs put on these television ads that feature a woman with a hole in her throat

  • And that were very graphic and very disturbing

  • Did they actually have an impact on whether people quit?

  • And helpfully, the collaboratory respect the limits of their data

  • But they were able to conclude that those advertisements and you may have seen them

  • They have the affect of jotting people into a thought process.

  • That may have an impact on future behavior.

  • Andwhat I admire, and appreciate about this project design from the fact, including the fact

  • That’s base on real human need is that

  • It’s a fantastic example of courage and the face of the sea of relevance.

  • And soit’s not just big data that causes challenge and interpretation.

  • Because let’s face it. We human-beings have a very rich stream of taking any among of data

  • No matter how small and screwing it up.

  • Somany years ago you may remember

  • That formal president Ronald Reagan was very criticize for making a statement the facts are stupid things

  • And it was a slip of the tongue. Let’s be fair.

  • He actually meant to quote John Adamsdefense British soldiers in the Boston Massacre trial

  • That facts are stubborn things.

  • But I actually think there’s a bit of accidental wisdom in what he said.

  • Because facts are stubborning things.

  • But sometimes they are stupid too.

  • When I tell you a personal story about why this matters a lot to me

  • I need to take a breath.

  • My son Isaac when he was two, he is diagnose with autism.

  • And he was happy, hilarious, loving and affectionate little guy.

  • but the metrics on his developmental evaluations, which looked at things like the number of wordsat that point, none

  • Communicate with gestures and minimum eye contact put his developmental level at that of a nine months old baby.

  • And the diagnosis fact is actually correct but it didn’t tell the whole story.

  • And about a year and a half later, he was almost four.

  • I found him in front of the computer one day.

  • Running a google search on woman

  • Spell w-i-m-e-m

  • And I did what any you knowupset parents will do

  • just immediate started hitting the back bottom to see what else he has been searching for

  • And they were in order men, school, bus and computer (cpyutr)

  • And I was stunned.

  • Because we didn’t know that he could spell much less read

  • So I ask him. Isaac, how do you do this?

  • And he looked at me very seriously and saidtype in the box

  • He was teaching himself to communicate.

  • But we were looking at the wrong place.

  • And this is what happens when assessment and analytics over value one matrix in this case verbal communication

  • And undervalue otherssuch as creating problem solving.

  • Communication was hard for Isaac.

  • And so he found a work around to find out what he needed to know.

  • And when you think about it, it makes a lot of sense.

  • Because forming a question is really complex process.

  • But he can get himself a lot of way there. By putting a word in the search box.

  • And so this little moment had a really profound impact on me.

  • In our family. Because it helps us change our reference for what’s going on for him.

  • And worry of a little bit less and appreciate his resource more.

  • Facts are stupid things.

  • And theyre vulnerable to misuse willful or otherwise.

  • I have a friend - Emily Willingham who’s a scientist.

  • And she wrote a piece for forbes not long ago.

  • Entitled the ten weirdest things ever linked to autism.

  • It’s quite a list.

  • The internet link for everything, right?

  • And of course mother. Because an actually way, there’s more others the whole bunch in the mother category here.

  • And you can see, it’s a pretty rich and interesting list.

  • I’m a big fan of you knowbeing pregnant in a free way, personally.

  • The final one is interesting because the term ofrefrigeratormother was actually the original hypothesis for the cause of autism.

  • And that meant somebody was cold and unloving.

  • And at this point, you might be thinkingokaySusan we get it.

  • You can take data. You can make it mean anything and this is true.

  • It’s absolutely true.

  • But the challenge is that

  • We have this opportunity to try make meaning out of ourselves.

  • Because frankly, data doesn’t create meaning, we do.

  • So as business people, as consumers, as patients, as citizens

  • We have our responsibility, I think.

  • To spend more time focus on our critical thinking skills.

  • Why?

  • Because at this point in our history as we heard, many times over we can process Exabyte in lightening speed.

  • And we have potential to make bad decisions far more quickly, efficiently and far greater impact than we did in the past.

  • Great, right?

  • And so what we need to do instead is spend a little bit more time on things like the humanities.

  • And sociology, and the social sciences, rhetoric, philosophy, ethics.

  • Because it gives us context that is so important for big data.

  • Because they help us become better critical thinkers.

  • Because after all, if I can spot a problem in an argument, it doesn’t much matter whether it’s express in words or numbers

  • And this means, teaching ourselves.

  • To find those conformation by thesis and false correlations.

  • And being able to spot a naked emotional appeal from thirty yards.

  • Because something that happens after something doesn’t mean it happen because of it necessarily.

  • And if you let me geek out on your first second, the Romans call thispost hoc ergo propterhoc

  • After which therefore because of which.

  • And it means questioning disciplines like demographics

  • Why? Because they're based on assumptions about who we all are based on our gender

  • and our age and where we live as opposed to data on what we actually think and do

  • And since we have this data

  • we need to treat it with appropriate privacy controls and consumer opt-in

  • and beyond that, we need to be clear about our hypotheses,

  • the methodologies that we use, and our confidence in the result

  • As my high school algebra teacher used to say

  • show your math, because if I don't know what steps you took

  • I don't know what steps you didn't take

  • and if I don't know what questions you asked, I don't know what questions you didn't ask

  • And it means asking ourselves, really, the hardest question of all

  • Did the data really show us this, or does the result make us feel more successful and more comfortable?

  • So the Health Media Collaboratory, at the end of their project

  • they were able to find that 87 percent of tweets about those very graphic and disturbing anti-smoking ads expressed fear

  • but did they conclude that they actually made people stop smoking?

  • No. It's science, not magic.

  • So if we are to unlock the power of data

  • We don't have to go blindly into Orwell's vision of a totalitarian future

  • or Huxley's vision of a trivial one, or some horrible cocktail of both.

  • What we have to do is treat critical thinking with respect and be inspired by examples like the Health Media Collaboratory

  • and as they say in the superhero movies, let's use our powers for good.

  • Thank you.

Technology has brought us so much

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B1 US TED data smoking orwell huxley big data

【TED】Susan Etlinger: What do we do with all this big data? (Susan Etlinger: What do we do with all this big data?)

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