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  • [MUSIC PLAYING]

  • I'm Prasad Setty.

  • I lead, among other groups and people operations

  • at Google, our people analytics and communications groups

  • as well.

  • Now that we're back from lunch, I

  • know exactly what's going on in all your minds.

  • You're thinking, there are those napping parts

  • that we hear are all over Google?

  • We've hidden them away.

  • But I am going to indulge you for a little minute.

  • Close your eyes, everyone.

  • We're going to do a little bit of a thought experiment

  • to begin with.

  • I want you to think about your most favorite piece of artwork.

  • Some of you might think about a masterpiece

  • from one of your most favorite post-impressionist artists.

  • Others might think about the dinosaur

  • their kid drew in first grade and is still

  • on their refrigerator.

  • Mine is this charcoal piece of work

  • that my wife did and was her very first present to me.

  • What emotions come into your mind

  • when you think about this artwork?

  • What meaning does it have in your life?

  • Keep your eyes closed this a little longer.

  • Now I want you to think about something different.

  • I want you to think about the most compelling piece

  • of science or analytical work that registers in your life;

  • again, something that has a deep, personal meaning.

  • And for all the academics in the audience,

  • you can't think about your own research.

  • That's would be too easy.

  • No thinking about your own research.

  • Give it a couple more seconds and now open your eyes.

  • Wasn't the second exercise much, much more difficult?

  • I see a lot of heads nodding.

  • We spend an inordinate amount of time

  • doing hardcode science and analytics.

  • But how do we ensure that it's memorable?

  • How do we ensure that we can communicate

  • better so that our messages resonate and stick?

  • Over the next 30 minutes, that's exactly what

  • we're going to explore.

  • The speakers that follow me Michelle Gielan and Christine

  • O'Connell, have the answers.

  • I, on the other hand, get to play executive.

  • So I'm going to vent-- there's going to be a lot of venting.

  • And I'm just going to leave you with a lot of problems

  • to solve.

  • Tim Chatwin, who leads communications and public

  • relations for Google in our Asia Pacific region,

  • and who used to be the speechwriter for David

  • Cameron, the prime minister of the UK

  • before he joined Google-- that is Tim joined Google, not

  • David Cameron-- when you ask him what he thinks

  • about as good communications he says there are three things,

  • It all boils down to three things--

  • what do you want your audience to know,

  • how do you want them to feel, and what do you

  • want them to do.

  • And when it comes to communicating science

  • and analytics, we typically fall short on all three questions.

  • Instead of telling people what they should know,

  • we like to tell them what we did.

  • We like to use a lot of highfalutin jargon

  • in all of our work.

  • It takes a PhD typically to understand the work

  • that another PhD does.

  • Of course there's the age-old question

  • of if a tree falls in a forest does it make a sound.

  • The philosophers can duke that one out.

  • But I have a follow-on question for you.

  • If a tree falls in a forest and we use the pulp up the print

  • and publish a prestigious academic journal,

  • did we suck out even one more sound out of it?

  • [LAUGHTER]

  • And I think we know the answer to that one.

  • So I'm really glad that Christine

  • is going to come up on stage soon and tell us

  • how to communicate science in the comprehensible manner.

  • Tim's second question is even more of a problem.

  • We don't even think about emotions

  • when we communicate science and analytics.

  • It's as if in our quest for objectivity

  • and rational thinking we try to strip away

  • all emotion from our speech.

  • And that becomes less memorable.

  • So personally, for instance, I've

  • been at Google for a few years now.

  • And I have a pretty vivid memory of everything

  • that we've done in analytics here.

  • I spent five years at my previous employer.

  • And if you ask me what I recollect from that time,

  • I can really think of one vivid analytical example.

  • The organization was going through a troubled phase

  • and we needed to lay off a significant fraction

  • of the workforce.

  • And we had develop the right severance packages

  • for these people.

  • The analytical team developed a simple visual

  • that showed what happens under the existing severance policy.

  • Executives were going to make much, much more money

  • than your typical rank and file employee.

  • And we shared that with the CEO, who

  • also happened to be the founder of the organization

  • and though of every employee as a family member.

  • He had such a visceral reaction to seeing that visual,

  • and immediately made the decision

  • to double the severance for all rank

  • and file employees, while keeping executives

  • exactly where they were.

  • It was going to cost a ton of money, but in his mind

  • it was absolutely the right thing to do.

  • Going into this piece of work, I just

  • treated it as just another piece of analysis.

  • But coming out of the meeting with the CEO,

  • I could see the difference that it was going

  • to make in people's lives.

  • And as I think about what we did there,

  • it was quite by accident that we were

  • able to induce that emotion.

  • I'm really glad Michelle is going

  • to tell us soon about what it means to induce

  • an emotion intentionally.

  • That gets us to Tim's third question

  • about how we get people to act on information.

  • And we have a long way to go there as well.

  • But this is an area that Google has

  • invested a tremendous amount of effort in to try and improve.

  • We experiment a lot with all the communications

  • that we do to see what influences behavior.

  • And just to look at one particular example,

  • we've been thinking about all the advances in the literature

  • around framing.

  • As you know, how you frame a message

  • has an impact on what happens.

  • To summarize from some of the prominent researchers

  • on the framing field, here's what they're saying.

  • There's an understandable but misguided tendency

  • to try to mobilize action against socially disapproved

  • conduct by depicting it as regrettably frequent,

  • thereby inadvertently installing a counterproductive descriptive

  • norm in the minds of their audiences.

  • You got that?

  • I put into to Google Translate.

  • [LAUGHTER]

  • And our machine learning algorithms

  • have still not caught up.

  • So I asked Jessie Wisdom, who is one of the PhD's in our team,

  • and speaks all this research juju,

  • and she told me what this actually means.

  • She said basically if you frame something in a positive light

  • it leads to better outcomes.

  • So what is an example of that?

  • So let's say you're talking about ground beef--

  • pretend you were.

  • If you framed it in a positive light

  • and said that it was 75% lean instead of negative light

  • saying it was 25% fat, apparently it

  • tastes less greasy and it's going to be registering better.

  • It's going to sell better.

  • The only people this kind of framing doesn't work on

  • is the vegetarians, like me, but who cares about them.

  • So we've done similar types of randomized controlled trials

  • at Google as well.

  • And what we've found is that when

  • you use social norms to nudge people

  • we actually do find changes in behavior.

  • We have fewer people cancel interviews

  • that they're scheduled for, fewer people cancel training

  • sessions that they're registered for.

  • Behavior change is possible.

  • And later this afternoon, we're going

  • to hear about a lot of nudges that are good.

  • So in summary, what am I saying?

  • Just in case I haven't been here so far all,

  • let me go meta and tell you the answers to Tim's three

  • questions in my own talk.

  • What I want to know is that we are

  • pretty terrible at communicating science and analytics.

  • And I want us to feel-- how do I put it gently--

  • I want us to feel really crappy about it.

  • But fear not-- all the evidence suggests

  • that 100% of people who listen to Michelle and Christine

  • walk away as better communicators.

  • So let's pay attention to them, OK?

  • All right, thank you.

  • [APPLAUSE]

  • [MUSIC PLAYING]

[MUSIC PLAYING]

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ストーリーテリングの科学|プラサド・セッティ、Google People Analytics (The science of storytelling | Prasad Setty, Google People Analytics)

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    John に公開 2021 年 01 月 14 日
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