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Channel / Source:
TEDx Talks
Published: 2016-11-28
Source: https://www.youtube.com/watch?v=WaOUJa9fjXU
in ancient Greece when anyone from slaves soldiers poets and politicians needed to make a big decision on life's most important like should I get married or should we embark on this voyage I should our army advance into this territory they all consulted the oracle so this is how it worked you would bring her questioning you would get on your knees and then she would go into
this trance it would take a couple of days and then eventually she will come out of it giving you her predictions has to answer from the oracle bones of ancient China ancient Greece to mine calendars people have craved for prophecy in order to find out what's going to happen next and that's because we all wanna make the right decision we don't want to miss something the
future is scary so it's much nicer knowing that we can make a decision with some assurance of the outcome well we have a new oracle and its name is big data I hold her we call it Watson or deep learning on your own that and these are the kind of questions we ask of our oracle now like us you know what what's the most efficient way
to ship ship these phones from China to Sweden or or what are the odds of my child being born with the genetic disorder or what are the sales volume you can predict for this product I have a dog her name's al and see if the rain and I have tried everything to untrained her but because I have failed at this I also have to consult the
oracle because the dark sky Everytime before we go on a walk through very accurate weather predictions in the next ten minutes Leslie so because of all of his heart or a goal is a one hundred and twenty two billion dollar industry now despite the size of this industry the returns are surprisingly low investing in big data is easy by using it is hard over seventy three
percent of big data projects aren't even profitable this is a humongous number when I first found out I was I was really shocked and Palin here one of the largest big data companies their clients like amex coca NASA they're not renewing their contracts because of saying Hey we're not seeing enough results and I've executives coming up to me saying works rings the same thing we invested
in some big data system and our employees are making better decisions and they're certainly not coming up with more breakthrough ideas so this is all really interesting to me because I'm a technology ethnographer I study and I advise companies in the patterns of how people use technology and one of my interest areas is data data are to me what stars are to astronauts mean datus practically
its own language we communicate through data we make decisions with data that's why people say we live in the age of data driven decision making but it is pretty cool that we live in an age where we can get all the feedback from our activity trackers to affordable genetic testing so why is having more data not helping us make better decisions especially for companies who have
all these resources to invest in these big data system why isn't it getting any easier for them so I've witnessed the struggle firsthand in two thousand nine I started a research position with Nokia and at the time Nokia was one of the largest cellphone companies in the world dominating emerging markets like China Mexico and India all places or had done a lot of research on how
low income people use technology and I spent a lot of extra time in China getting to know the informal economy so I do things like working as a street vendor selling dumplings to construction workers or I did fieldwork spending nights and days in internet cafes hang out with Chinese youths like a nurse and how they were using games a mobile phones and using it between moving
from the rural areas to the cities and through all of this qualitative evidence that I was gathering I was starting to see so clearly that a big change was about to happen among low income Chinese even though they were surrounded by advertisements for luxury products like fancy toilets who wouldn't want one and apartments in cars through my conversations with them I found out that the allies
to actually enticed them the most were the ones for iPhones promising than this entry into this high tech life and even when I was living with them in urban slums like this one I saw people investing over half of their monthly income into buying a phone and increasingly there were signs I which or are affordable knock offs of iPhones and other brands this they're very usable
does the job and after years of living with migrants and working with them and just you know really doing everything that they were doing I started piecing all these data points together you know from the things that were seen my grandma might be selling dumplings to the things are more obvious like you know tracking how much you're spending on their cell phone bills and I was
able to create this much more holistic picture of what was happening and that's when I start to realize that even the poorest in China would want a smartphone and that they would do almost anything to get their hands on one you have to keep in mind Ivan iPhones had just come out with two thousand nine so this is like eight years ago and enjoys had just
started looking like iPhones in a lot of very smart and realistic people said those smartphones that's just a fad right who's wants to carry around these heavy things were battery's drained quickly in a break every time you drop them but I had a lot of data and I was very confident about my insights so I was very excited to share them with Nokia but no he
was not convinced because it wasn't big data they said we have millions of data points and we don't see any indicators of anyone wanting to buy smartphone and your data set of one hundred O. as diverse as it is is too weak for us the young take seriously I think not you're right of course you wouldn't see this because you know you're sending all surveys assuming
that people don't know what a smartphone it's so of course you're not picky immediate impact about people wanting to buy smartphone in two years your surveys are met this have a design to optimize an existing business model and I'm looking at these immersion human dynamics I haven't happened yet were in a looking out cited market dynamics that we can get ahead of it we know what
happens to Nokia their business fell off a cliff this this is the cost of missing something Nokia was so busy looking for the right data to fit their models that they never even bothered asking the right questions not everything valuable is measurable and for Nokia it was just it was inconceivable to them that people would always paid a certain price point for something could just all
sudden change their behavior it was that was unfathomable but no he is not alone I see organizations during out data all the time because it didn't come from what model or did it doesn't fit in one but it's not the greatest faults it's the way we use big data it's our responsibility big did his reputation for success comes from quantifying very specific environments like a electricity
power grids or a delivery logistics our genetic code well more quantifying in systems are more or less contains big data does a very good job by giving us a very accurate view of the world enough for a skill to make good predictions based off of it like once you know how much electricity a factory is consuming you can make projections off but not all systems are
as neatly contained when you're quantifying and systems are more dynamic X. specially systems that involve human beings forces are complex and unpredictable and these are things that we don't know how to model so well now this distinction between quantifying in contains systems versus dynamic systems is really important to understand and this new ones is captured very well in this tweet by my favorite astrophysicist writing is
everyone's favorite has a physicist Neil degrasse Tyson where he says in science when human behavior enters the equation things go nonlinear and that's why physics is easy in sociology of hard true so that's why quantification in vain and make systems creates is really super interesting paradox big data doesn't just create more knowledge it also creates more unknowns once you predict something about human behavior new factors
emerge because conditions are constantly changing that's why it's a never ending cycle you think you know something and then something unknown enters the picture and that's why just relying on big data alone increases the chance that will miss something while giving us this illusion that we already know everything and what makes it really hard to see this paradox unevenly rap farm brains around it is that
we have this thing that I call the quantification bias which is the unconscious beliefs of valuing the measurable over the immeasurable and we often new experiences at our work you know we've made you work alongside colleagues who are like this or even our whole entire company maybe like this where people become so fixated on that number that they can't see anything outside of it even when
you present them evidence right in front of her face and it becomes even harder to see the spice Hiciste reinforced by big data companies the say Hey you know we can quantify everything important for you so you could find that needle in the haystack so you can find a single source of truth your one true answer to everything and this is a metaphor that they literally
use and their sales and marketing pitch axis haystack in needle and so this is a very appealing message because there's nothing wrong with quantifying it's actually very satisfying me I get a great sense of comfort from looking at an excel spreadsheet even very simple plans it's kinda like yeah the formula works it's all okay everything's under control but the problem is that quantifying acidic and when
we forget died and when we don't have something to kind of keep that in check it's very easy to just throw data because they can't be expressed as a numerical value is very easy to slip into silver bullet thinking as if some simple solution existed because this is a great moment of danger for any organization because often times the future we need to predict it isn't
in the haystack but if that tornado that's bearing down on us outside of the barn there is no greater risk than being blind to the unknown it can cause you to make the wrong decisions it can cause you to miss something big but we don't have to go down this path turns out that the oracle of ancient Greece holds the secret key that shows us the
power no recent secure logical research has shown that the temple of Apollo where the most famous oracle sat was actually built over to earthquake faults and he spoke would release these Petro chemical fume from underneath the earth's crust and the oracle literally sat right above these faults in healing enormous amounts of ethylene gas these fish it's to it's all true and that's what made her babbling
hallucinating go insist trance like state she was a high as a kite as soon did anyone how did anyone get any useful advice out of her in this state well you see those people surrounding the oracle you see those people holding her up because you like the little movies and you see that guy in your left hand side holding the orange no book well those are
the temple guides and they work hand in hand with the oracle when inquisitors were calm and get on their knees that's in the temple guys to get to work because after they ask her questions they would observe their emotional state and then you ask them fall of questions like Hey you why do you want to know this prophecy who are you would even to do with
this information and then the temple guides would take this more effort graphic this more qualitative information and interpret the oracles bathrooms so the oracle didn't stand alone and neither should our big data systems not to be clear I'm not saying that big data systems are you know having a fling gas or that they're even giving about predictions the total opposite what I am saying his sides
and the same way that the oracle needed her temple guides are big data systems the them to they need people like ethnographers and reuse the researchers hooking gather what I call thick data this is precious data from humans like stories of motions and interactions that cannot be quantified it's the kind of data that I collected for Nokia comes in the form of a very small sample
size but delivers incredible depth of meaning and what makes it so fake and needy is the experience of understanding the human narrative and that's what helps to see what's missing and our models big data grounds are business questions in human questions and that's why integrating big and thick data forms a more complete picture big data is able to offer insights at scale and leverage of best
of machine intelligence worst big data can help us rescue the context loss that comes from making big data usable and the levers of best of human intelligence well you actually integrate the two that's when things get really fun because then you're no longer just working with data you've already collected you get to also work with data that has since been collected you get to ask questions
about why why is this happening no one Netflix did this they unlocked a whole new way to transform their business no Netflix is known for their really great recommendation algorithm and they have this one million dollar prize for anyone who could improve it and there were winners but Netflix discover that the improvements were only incremental so to really find out what was going on they hired
an ethnographer grant McCracken together think data insights and what he discovered was something that they hadn't seen initially in the quantitative data he discovered that people love to binge watching in fact people don't even feel guilty about it they enjoyed it so Netflix was like whoa this is a new insight so they went to their data science team and they were able to scale the stick
data insight into with their quantitative data and once they verified it invalidated Netflix decided to do something very simple but impassable they said instead of offering the same show from different genres or Morris to the different shows from similar users well just offer more of the same show would make it easier for you depends what's and they didn't stop there they read data that all these
things to redesign their entire viewer experience to really encourage binge watching that's why people and friends disappear for a whole weekends at a time catching up on shows like masters of nine that's where I'll be this week so Netflix by integrating big data and fix the other they not only improve their business they transform how we consume media and now their stocks are projected to double
in the next few years but this isn't just about you know watch more videos are selling more smartphones first son integrating thick data insights into the algorithm could mean life or death especially for the marginalized all around the country police departments are using big data for predictive policing to set bond amounts in sentencing recommendations and ways that reinforce existing biases and they say sky that machine
learning algorithm has possibly aided in the deaths of thousands of civilians in Pakistan for misreading cellular device metadata as all of our lives become more automated from auto mobiles a health insurance or to employment it is likely that all of us will be impacted by the quantification bias now the good news is that we've come a long way from having a fling gas to make predictions