Tricia Wang: The human insights missing from big data
تريسيا وانج: افتقار البيانات الضخمة إلى رؤية الإنسان
With astronaut eyes and ethnographer curiosity, Tricia Wang helps corporations grow by discovering the unknown about their customers. Full bio
Double-click the English transcript below to play the video.
poets and politicians,
وحتى الجنود والشعراء والسياسيين
on life's most important questions,
في أسئلة الحياة الهامة.
advance into this territory?"
and you would get on your knees,
she would come out of it,
what's going to happen next.
to make the right decision.
القرار الصحيح.
knowing that we can make a decision
أننا يمكننا اتخاذ قرار
or "deep learning" or "neural net."
أو"الشبكة العصبية الاصطناعية."
we ask of our oracle now,
على أوراكل،
to ship these phones
with a genetic disorder?"
we can predict for this product?"
لهذا المنتج؟"
and she hates the rain.
to untrain her.
an oracle, called Dark Sky,
أوراكل يدعى "دارك سكاي"
in the next 10 minutes.
في العشر دقائق القادمة.
our oracle is a $122 billion industry.
قطاعًا تجاريًا بحجم 122 مليار دولاراً.
aren't even profitable,
البيانات الضخمة غير مربحة.
coming up to me saying,
better decisions.
with more breakthrough ideas."
المزيد من الأفكار المبدعة."
التكنولوجية.
of how people use technology,
not helping us make better decisions,
على اتخاذ قرارات أفضل،
who have all these resources
a research position with Nokia.
cell phone companies in the world,
كبرى شركات الهاتف الخلوي في العالم،
like China, Mexico and India --
مثل: الصين والمكسيك والهند--
a lot of research
المنخفض للتكنولوجيا.
as a street vendor
in internet cafés,
so I could understand
games and mobile phones
والهواتف الخلوية
from the rural areas to the cities.
إلى المدن.
that I was gathering,
among low-income Chinese people.
بين الصينيين ذوي الدخل المنخفض.
by advertisements for luxury products
التي كانت تحاوطهم،
who wouldn't want one? --
من لا يريد امتلاك واحد؟ --
the actually enticed them the most
into this high-tech life.
من التقنية العالية.
in urban slums like this one,
بالمدينة مثل هذه،
over half of their monthly income
of iPhones and other brands.
وغيرها من الماركات.
with migrants and working with them
والعمل معهم
that they were doing,
all these data points together --
like me selling dumplings,
مثل بيع المعجنات
on their cell phone bills.
هواتفهم المحمولة.
this much more holistic picture
would want a smartphone,
to get their hands on one.
looking like iPhones.
and realistic people said,
these heavy things
and they break every time you drop them?"
وتنكسر الهواتف عندما تسقط منك"
about my insights,
to share them with Nokia.
millions of data points,
of anyone wanting to buy a smartphone,
يريد شراء هاتف ذكي
as diverse as it is, is too weak
ضعيفة للغاية بالنسبة لنا
assuming that people don't know
وتفترضون أن الناس لا تعرف
to get any data back
a smartphone in two years.
have been designed
at these emergent human dynamics
of missing something.
throwing out data all the time
it's our responsibility.
فهذه مسؤوليتنا.
very specific environments,
or delivery logistics or genetic code,
أو التسليم اللوجيستي أو الشفرة الجينية
that are more or less contained.
are as neatly contained.
and systems are more dynamic,
that involve human beings,
that we don't know how to model so well.
about human behavior,
are constantly changing.
enters the picture.
on big data alone
that we'll miss something,
that we already know everything.
أننا نعرف بالفعل كل شيء.
to see this paradox
that I call the quantification bias,
of valuing the measurable
colleagues who are like this,
company may be like this,
so fixated on that number,
outside of it,
right in front of their face.
wrong with quantifying;
from looking at an Excel spreadsheet,
عند النظر في جدول بيانات على برنامج إكسل
Everything is under control."
كل شيء على ما يرام."
to kind of keep that in check,
as a numerical value.
into silver-bullet thinking,
for any organization,
the future we need to predict --
نحتاج إلى التنبؤ بالمستقبل --
that's bearing down on us
the wrong decisions.
of ancient Greece
that shows us the path forward.
الطريق للأمام.
where the most famous oracle sat,
حيث جلست الوسيطة الروحية الأشهر،
over two earthquake faults.
these petrochemical fumes
right above these faults,
فوق الصدعين مباشرةً
of ethylene gas, these fissures.
من غاز الإيثيلين، هذان الصدعان.
babble and hallucinate
any useful advice out of her
surrounding the oracle?
المحيطين بالوسيطة الروحية؟
on your left-hand side
with the oracle.
and get on their knees,
ويركعون أمامها،
would get to work,
follow-up questions,
this prophecy? Who are you?
من أنت؟"
with this information?"
this more ethnographic,
هذا على محمل علم الأعراق البشرية.
are huffing ethylene gas,
invalid predictions.
that the oracle needed her temple guides,
and user researchers
ما أسميه البيانات الكثيفة.
that cannot be quantified.
والتفاعلات التي لا يمكن قياسها.
that I collected for Nokia
of a very small sample size,
the human narrative.
what's missing in our models.
in human questions,
أسئلة نشاطنا التجاري على أسئلة الناس.
big and thick data
والبيانات الكثيفة
insights at scale
تقديم وجهات نظرعلى قدر ما هو مطلوب
of machine intelligence,
rescue the context loss
تساعد في إنقاذ السياق المفقود
صالحة للاستعمال
of human intelligence.
that's when things get really fun,
تصبح الأمور أكثر مرحًا
just working with data
that hasn't been collected.
مع البيانات التي لم تجمعها بعد.
to transform their business.
recommendation algorithm,
for anyone who could improve it.
لمن يستطيع تحسينها.
the improvements were only incremental.
كانت تزايدية فقط.
Grant McCracken,
الأعراق البشرية، غرانت مكراكين،
that they hadn't seen initially
to binge-watch.
feel guilty about it.
"Oh. This is a new insight."
this big data insight
and validated it,
very simple but impactful.
the same show from different genres
من فئات مختلفة
from similar users,
for you to binge-watch.
viewer experience,
for whole weekends at a time,
والأصدقاء في العطلات الأسبوعية.
like "Master of None."
they not only improved their business,
البيانات الضخمة مع البيانات الكثيفة
to double in the next few years.
في السنوات القليلة القادمة.
watching more videos
مشاهدة المزيد من الفيديوهات
insights into the algorithm
في خوارزمياتهم
police departments are using big data
البيانات الضخمة
and sentencing recommendations
لدى الأمن القومي الأمريكي
of thousands of civilians in Pakistan
للجهاز الخلوي.
or to employment,
by the quantification bias.
is that we've come a long way
أننا سلكنا طريقًا طويلًا
to make predictions.
so let's just use them better.
with the thick data.
with the oracles,
in companies or nonprofits
داخل شركات أو جمعيات غير حكومية
we're collectively committed
missing that something.
ABOUT THE SPEAKER
Tricia Wang - Technology ethnographerWith astronaut eyes and ethnographer curiosity, Tricia Wang helps corporations grow by discovering the unknown about their customers.
Why you should listen
For Tricia Wang, human behavior generates some of the most perplexing questions of our times. She has taught global organizations how to identify new customers and markets hidden behind their data, amplified IDEO's design thinking practice as an expert-in-residence, researched the social evolution of the Chinese internet, and written about the "elastic self," an emergent form of interaction in a virtual world. Wang is the co-founder of Sudden Compass, a consulting firm that helps companies unlock new growth opportunities by putting customer obsession into practice.
Wang's work has been featured in The Atlantic, Al Jazeera, and The Guardian. Fast Company spotlighted her work in China: "What Twitter Can Learn From Weibo: Field Notes From Global Tech Ethnographer Tricia Wang." In her latest op-ed on Slate, she discusses how attempts to stop terrorists on social media can harm our privacy and anonymity. Her Medium post, "Why Big Data Needs Thick Data," is a frequently cited industry piece on the importance of an integrated data approach. One of her favorite essays documents her day in the life of working as a street vendor in China.
Known for her lively presentations that are grounded in her research and observations about human behavior and data, Wang has spoken at organizations such as Proctor & Gamble, Nike, Wrigley, 21st Century Fox and Tumblr. Her most recent talk at Enterprise UX delved into why corporate innovation usually doesn’t work and what to do about it. She delivered the opening keynote at The Conference to a crowd of marketers and creatives, delving into the wild history of linear perspective and its influence on how we think and form organizations.
Wang holds affiliate positions at Data & Society, Harvard University's Berkman Klein Center for Internet Studies and New York University's Interactive Telecommunication Program. She oversees Ethnography Matters, a site that publishes articles about applied ethnography and technology. She co-started a Slack community for anyone who uses ethnographic methods in industry.
Wang began her career as a documentary filmmaker at NASA, an HIV/AIDS activist, and an educator specializing in culturally responsive pedagogy. She is also proud to have co-founded the first national hip-hop education initiative, which turned into the Hip Hop Education Center at New York University, and to have built after-school technology and arts programs for low-income youth at New York City public schools and the Queens Museum of Arts. Her life philosophy is that you have to go to the edge to discover what’s really happening. She's the proud companion of her internet famous dog, #ellethedog.
Tricia Wang | Speaker | TED.com