Was Nate Silver Wrong?

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By Bram Wessel, first presented at the 2017 Information Architecture Summit. "Was Nate Silver Wrong: The Crisis of Modeling in an Era of Clickbait, Fake News, and Alternative Facts." This talk explores what election forecasting and information architecture can learn from each other and how your business can survive in our noisy information environment. Transcript: http://factorfirm.com/posts/transcript-was-nate-silver-wrong/

Internet

@bramwessel | @factorfirm | factorfirm.com

@bramwessel @factorfirm factorfirm.com
WRONG?

@bramwessel @factorfirm factorfirm.com
PLACES | THINGS
MADE OF INFO

@bramwessel @factorfirm factorfirm.com
Attention Economy

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Hidden costs?

@bramwessel @factorfirm factorfirm.com
INFLECTION POINT
IS INFLECTED

@bramwessel @factorfirm factorfirm.com
Is the public less informed?

@bramwessel @factorfirm factorfirm.com
Fake News
@bramwessel | @factorfirm | factorfirm.com

@bramwessel @factorfirm factorfirm.com
TRUTHINESS

@bramwessel @factorfirm factorfirm.com
ALTERNATIVE FACTS

@bramwessel @factorfirm factorfirm.com
STRAW POLL…

@bramwessel @factorfirm factorfirm.com
Clickbait ad image

@bramwessel @factorfirm factorfirm.com
@bramwessel | @factorfirm | factorfirm.com

@bramwessel @factorfirm factorfirm.com
CONTENT FARMS
DGAF ABOUT UR CONTENT

@bramwessel @factorfirm factorfirm.com
PRODUCT IS US
SUCH BIZ MODEL
SO ATTENTIVE

@bramwessel @factorfirm factorfirm.com
TFW human interpretation doesn’t matter
THIS IS NOT THE CRAP WE’RE LOOKING FOR

@bramwessel @factorfirm factorfirm.com
Doing more work for the machines
@bramwessel | @factorfirm | factorfirm.com

@bramwessel @factorfirm factorfirm.com
WHAT INFLUENCE DO WE REALLY HAVE?

@bramwessel @factorfirm factorfirm.com
RECURSIVE FEEDBACK LOOP IS RECURSIVE
@bramwessel | @factorfirm | factorfirm.com

@bramwessel @factorfirm factorfirm.com
Dopamine Rush
NORMAL COCAINE

@bramwessel @factorfirm factorfirm.com
Who benefits?
FOLLOW THE MONEY

@bramwessel @factorfirm factorfirm.com
NOW WITH MORE LOSSY
EFFICIENT MARKET

@bramwessel @factorfirm factorfirm.com
DDOS ON MEANING

MUGGLES DON’T HAVE TIME
NEITHER DO WIZARDS

@bramwessel @factorfirm factorfirm.com
How is Data Journalism like IA?

@bramwessel @factorfirm factorfirm.com
What’s your evidence?

@bramwessel @factorfirm factorfirm.com
Data vs. Access
Quant vs. Qual

@bramwessel @factorfirm factorfirm.com
But, getting good data is getting harder.

@bramwessel @factorfirm factorfirm.com
Downstream Effects

@bramwessel @factorfirm factorfirm.com
“So number one, and this kind of goes back to the
supply chain, but if you're working with actually trying
to manufacture something out of data, to come to
some analysis or some conclusion, you have to make
sure the data is good to begin with.”
— Nate Silver, 2011 IAS Keynote

@bramwessel @factorfirm factorfirm.com
The information supply chain.
Input Output
Noise
The Information Supply Chain

@bramwessel @factorfirm factorfirm.com
First principle: the data is wrong.

@bramwessel @factorfirm factorfirm.com
Embracing entropy.

@bramwessel @factorfirm factorfirm.com
We can’t read users’ minds.

@bramwessel @factorfirm factorfirm.com
How to correct for wrong data?

@bramwessel @factorfirm factorfirm.com
What inputs do we trust?

@bramwessel @factorfirm factorfirm.com
Prioritizing Input

@bramwessel @factorfirm factorfirm.com
User Research recruiting

@bramwessel @factorfirm factorfirm.com
How likely is someone to vote?

@bramwessel @factorfirm factorfirm.com
Likely voter models

@bramwessel @factorfirm factorfirm.com
Moving target

@bramwessel @factorfirm factorfirm.com
Changes over time
BUT HER EMAILS!

@bramwessel @factorfirm factorfirm.com
The peril of adjustments

@bramwessel @factorfirm factorfirm.com
Apples to Apples
@bramwessel @factorfirm factorfirm.com

@bramwessel @factorfirm factorfirm.com
Third parties are not created equal.

@bramwessel @factorfirm factorfirm.com
Trend Line Adjustment

@bramwessel @factorfirm factorfirm.com
House Effects Adjustment

@bramwessel @factorfirm factorfirm.com
Undecideds?

@bramwessel @factorfirm factorfirm.com
Even more stuff?
W’ELL BE RIGHT BACK…
WITH MORE STUFF

@bramwessel @factorfirm factorfirm.com
This message was approved by…

@bramwessel @factorfirm factorfirm.com
Modeling is done by humans.

@bramwessel @factorfirm factorfirm.comElection forecasting is grounded in classic information theory.

@bramwessel @factorfirm factorfirm.com
“Information is the resolution of uncertainty.”
— Claude Shannon

@bramwessel @factorfirm factorfirm.com
“Findability is at the
center of a quiet
revolution in how we
define authority, allocate
trust,
and make decisions.”
— Peter Morville,
Ambient Findability

@bramwessel @factorfirm factorfirm.com
What does this all mean for Information Architects?

@bramwessel @factorfirm factorfirm.com
What are our information supply chains?

@bramwessel @factorfirm factorfirm.com
How do we know?

@bramwessel @factorfirm factorfirm.com
Our jobs will keep getting harder.

@bramwessel @factorfirm factorfirm.com
Side doors

@bramwessel @factorfirm factorfirm.com
Re-orienting Users

@bramwessel @factorfirm factorfirm.com
We are the definers.

@bramwessel @factorfirm factorfirm.com
Changes in Page Rank align with us

@bramwessel @factorfirm factorfirm.com
What can we do
as information architects
on the ground?

@bramwessel @factorfirm factorfirm.com
As IA’s, what effect do we have
on the broader information environment?

@bramwessel @factorfirm factorfirm.com
How do we give information users
the ability determine quality?

@bramwessel @factorfirm factorfirm.com
What are the implications for organizations?

@bramwessel @factorfirm factorfirm.com
What are an organization’s information assets?

@bramwessel @factorfirm factorfirm.com
What is the aboutness of your organization?

@bramwessel @factorfirm factorfirm.com
Bring the aboutness forward.

@bramwessel @factorfirm factorfirm.com
Resist the impulse to automate for its own sake.

@bramwessel @factorfirm factorfirm.com
Automate intelligently.

@bramwessel @factorfirm factorfirm.com
Consider the question.

@bramwessel @factorfirm factorfirm.com
Prioritization = values.

@bramwessel @factorfirm factorfirm.com
What can we do as information architects as a community?
What is our responsibility as a community?

@bramwessel @factorfirm factorfirm.com
What are our goals as a society?

@bramwessel @factorfirm factorfirm.com
#DTDT
#DTDT?

@bramwessel @factorfirm factorfirm.com
Information environmentalists.

@bramwessel @factorfirm factorfirm.com
Elevating the signal to noise ratio
Restoring a healthy signal to noise ratio.

@bramwessel @factorfirm factorfirm.com
We need to be careful
about giving up human control.

@bramwessel @factorfirm factorfirm.com
What ambient entropy
do automated processes generate?

@bramwessel @factorfirm factorfirm.com
Good, Cheap, Fast?
Pick two.

@bramwessel @factorfirm factorfirm.com
Engaging the community of thought.

@bramwessel @factorfirm factorfirm.com
Human solutions for human challenges.

What the triple bottom line?
What is our
triple bottom line?

@bramwessel @factorfirm factorfirm.com
MODELING FOR TRUTH, JUSTICE,
AND THE CANADIAN WAY

@bramwessel @factorfirm factorfirm.com
Modeling from the outside in.

@bramwessel @factorfirm factorfirm.com
Modeling from the inside out.

@bramwessel @factorfirm factorfirm.com
Make information great againWhat kind of information environment
do we want to live in?

@bramwessel @factorfirm factorfirm.com
The curatorial imperative.

@bramwessel @factorfirm factorfirm.com
Chance 538 gave Trump of
winning the presidency in 2016:
28.6%
Chance a major league baseball player
would get a hit during any at-bat in 2016:
25.5%

@bramwessel @factorfirm factorfirm.com
LEAST WRONG

THANK YOU!
@bramwessel | @factorfirm | factorfirm.com

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原版仿制(uob毕业证书)英国伯明翰大学毕业证本科学历证书原版一模一样

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1比1复刻(bath毕业证书)英国巴斯大学毕业证学位证原版一模一样

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原版纸张【微信：741003700 】【(bath毕业证书)英国巴斯大学毕业证学位证】【微信：741003700 】学位证，留信认证（真实可查，永久存档）offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma 1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700 留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才

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Was Nate Silver Wrong?

1. @bramwessel | @factorfirm | factorfirm.com

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27. @bramwessel @factorfirm factorfirm.com TFW human interpretation doesn’t matter THIS IS NOT THE CRAP WE’RE LOOKING FOR

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46. @bramwessel @factorfirm factorfirm.com What’s your evidence?

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52. @bramwessel @factorfirm factorfirm.com The information supply chain. Input Output Noise The Information Supply Chain

53. @bramwessel @factorfirm factorfirm.com First principle: the data is wrong.

54. @bramwessel @factorfirm factorfirm.com Embracing entropy.

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85. @bramwessel @factorfirm factorfirm.com Modeling is done by humans.

86. @bramwessel @factorfirm factorfirm.comElection forecasting is grounded in classic information theory.

87. @bramwessel @factorfirm factorfirm.com “Information is the resolution of uncertainty.” — Claude Shannon

88. @bramwessel @factorfirm factorfirm.com “Findability is at the center of a quiet revolution in how we define authority, allocate trust, and make decisions.” — Peter Morville, Ambient Findability

89. @bramwessel @factorfirm factorfirm.com What does this all mean for Information Architects?

90. @bramwessel @factorfirm factorfirm.com What are our information supply chains?

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111. @bramwessel @factorfirm factorfirm.com Prioritization = values.

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120. @bramwessel @factorfirm factorfirm.com What ambient entropy do automated processes generate?

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124. What the triple bottom line? What is our triple bottom line?

125. @bramwessel @factorfirm factorfirm.com MODELING FOR TRUTH, JUSTICE, AND THE CANADIAN WAY

126. @bramwessel @factorfirm factorfirm.com Modeling from the outside in.

127. @bramwessel @factorfirm factorfirm.com Modeling from the inside out.

128. @bramwessel @factorfirm factorfirm.com

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132. @bramwessel @factorfirm factorfirm.com Chance 538 gave Trump of winning the presidency in 2016: 28.6% Chance a major league baseball player would get a hit during any at-bat in 2016: 25.5%

133. @bramwessel @factorfirm factorfirm.com LEAST WRONG

134. THANK YOU! @bramwessel | @factorfirm | factorfirm.com

Was Nate Silver Wrong?

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