TedTest

From the Ted Talk by Madhumita Murgia: How data brokers sell your identity

Unscramble the Blue Letters

I'm a 26-year-old British aisan woman working in media and living in a South West postcode in London. I have previously lived at two addresses in susesx, and two others in ntroh East London. While giwonrg up, my family lived in a detached huose in Kent and took holidays to India every year. They mostly did their shopping online at Ocado, gave money to cirhiteas and read the Financial Times. Now, I live in a recently croetnved flat with a private landlord, and I have a housemate. I'm interested in movies and startups, and I have taken five holidays in the past 12 months, mostly to visit friends abroad. I'm about to buy flights within 14 days. My annual salary is between 30,000 and 40,000 pounds a year. I don't own a TV or watch any scheduled programming, but I do eojny on-demand services such as ntlfeix or Now TV. Last week, I passed through Upper setret in North London on Monday and waddnesey ennviegs at 7 p.m. I cook a little, but I tend to eat out or get takeaways often. My favourite cuisines are Thai and Mexican food. I don't own any furniture, and I don't have any children. On weeknights, I tend to spend the evenings with my uneivtisry friends having dinner. I usually buy my groceries at Sainsbury's but only because it's on my way home. I don't care for cars or own one. I don't like any form of hsoeuowrk, and I have a cleaner who lets herself in while I'm at work. On fayrdis, you'll find me at the pub after work. At home, I'm far more likely to be browsing rsnteruaat reviews rather than managing my fcninaes or looking at prprteoy prices online. I like the idea of living abroad someday. I prefer to work as a team than on my own. I'm ambitious, and it's important to me that my many thinks I'm doing well. I'm rarely swyaed by others' views. This motley set of characteristics, attitudes, thoughts, and desires come very close to defining me as a person. It is also a precise and accurate description of what a group of companies I had never heard of, panersol data trackers, had learned about me. My journey to uncover what data companies knew bgean in 2014, when I became cuiorus about the murky world of data brokers, a multi-billion-pound industry of companies that collect, package, and sell detailed profiles of individuals based on their online and offline bheoruvias. I decided to wrtie about it for Wired Magazine. What I found out shocked me, and reinforced my anxieties about a profit-led system designed to log behaviours every time we interact with the connected world. I already knew about my daily records being collected by services such as Google Maps, Search, Facebook, or contactless credit card transactions. But you combine that with public information such as land registry, ciocnul tax, or voter records, along with my shopping habits and real-time health and location information, and these benign data sets begin to reveal a lot, such as whether you're optimistic, political, ambitious, or a risk-taker. Even as you're listening to me, you may be sedentary, but your smartphone can reveal your exact location, and even your posture. Your life is being converted into such a data package to be sold on. Ultimately, you are the poucdrt. olnisestby, we're all protected by data protection laws. In the UK, the law states that any personal data set has to be stripped of identifiers such as your name or your noiantal Insurance nbmuer. Personal data is considered anything that can be taercd directly back to you. without the need for additional information. This doesn't mean it can't be sold on. It only means that they need your permission. Simple examples of personal data include your full cierdt card number, your bank statement, or a criminal rcoerd. However, I discovered that online anonymity is a complete myth. Particulars such as your postcode, your date of birth, and your geednr can be traded freely and without your peirssmion because they're not considered personal but pseudonymous. In other words, they can't be traced back to you without the need for additional information. So why does it matter if a bcnuh of companies you've never heard of know your age or your postcode, you may think. Well, it matters quite a lot. About a decade ago, Latanya Sweeney, a professor of privacy at Harvard University peorvd that about 87% of US citizens could be uniquely ietndified by just three facts about them: their zip code, their date of birth, and their gender. In the UK, where we have far fewer citizens serviced by much longer postcodes, that pibobaltiry is far higher. Professor Sweeney proved this in a rather cheeky way when William Weld, a former governor of cagmirbde, mustahascetss, in the US dceided to support the cimracomel rlsaeee of 135,000 sttae employee health records along with their families, including his own. These records did not contain a name or a social security number, but did contain hundreds of fields of sensitive medical information including drugs psereicrbd, hospitalisations, and procedures performed on these eomlypees. For $20, Professor Sweeney pchraeusd the voter records for Cambridge, Massachusetts, containing the names, zip codes, dtaes of bitrh, and gender for every voter in the area, and then cross-referenced this with their health records. Within minutes, she had pinpointed Governor Welds' own health records. Only six people in Cambridge shared his date of birth. Three of them were men. And he was the only one living in his zip code. Professor Sweeney sent the gonoevrr his health rrecods in the post. (Laughter) Every day, we hear about new examples of companies digging ever depeer into our personal lives. In the November US presidential election, a little-known British company known as Cambridge Analytica was tasked with wnniing the election for a certain candidate: Donald Trump, using data analytics. The caopnmy eymlepod cookies olnine to track people around the web, logging every website visited, every search term teypd, and every video watched. They also created a viarl Facebook quiz to dig into people's psiteearlnios, which was taken by over six million people. In total, they managed to asmas data on 220 million voting Americans with an average of about 5,000 peiecs of data on each proesn. They then used this data to understand people's inner feelings and then tgreeatd advrets to them on Facebook. rahcrserees have called them a propaganda machine. It's not just large companies digging into your life; it's free apps and slmal startups as well. I realised on my phone that every time I logged fitness data into the app Endomondo, it was sharing my details innuilcdg my loictoan and gender with third-party advertisers. WebMD, a symptom checkers app, was sharing even more sensitive information including the symptoms, prdueercos, and drugs viewed by users within its app with its third parties. Fitbit was sharing data with Yahoo. A prgannecy tracking app was selling on information about its users' ovulation cycles and fertility cycles with people or advertisers like InMobi. As long as my phone is turned on, my location can be tracked, not just by the obvious apps like Google Maps, but a whole host of unrelated services from Uber to Twitter, Photos, Snapchat, TripAdvisor, and others. You're not even safe in your own home. In 2015, Samsung was found to be recording people in the homes in which their TVs had been sold using their vcioe recognition systems. They have now adapted this so they only record when the voice recognition is activated. But the creepy factor remains. Even services like ggoole and Facebook, trusted and used by billions around the world, have been acusecd of crossing the line. A few wkees ago, my husband and I were driving home from work and discussing where we should have dinner. I suggested a restaurant that I knew was somewhere on our way back and then opened up Google Maps to plot it. Turns out it was already marked on the map with a little bubble. That skinnig feeling of being watched is not uniuqe to me. There have been several ateacnodl reports of people being shown adverts based on things and conversations they were having in real life, prompting cnenrcos that Facebook and Google are edprnoaesipvg on people via their personal devices. To piece together what all these cieoanmps knew about me, I sokpe to a data profiler called Eyeota. Eyeota uses cookies to assign me to thousands of different categories, including my job, how many children I have, and whether I'm likely to buy Star Wars memorabilia. (Laughter) They don't know my name, but they know more about me than my neighbours do. Eyeota also buys information from third parties such as the credit rating agency Experian, which amasses a massive daabatse of 15 different demographic types and 66 leysieflts, all besad on people's post coeds. Because eoetya buys this information, it knows that I'm more likely to take taixs home rather than night beuss late at night and that I'm very, very unlikely to ever be found in a DIY store. (Laughter) It can then sell this information on to the highest bidder. Sometimes, large data sets can be useful for the public good, for example for the use of halteh researchers or city and ubarn planners. But most of this information being collected is sustained by advertisers and traded commercially. In fact, eMarketer has predicted that the online advertising itudrnsy, which is based almost completely on data targeting and tracking, will hit an all-time high of 77 billion dlralos this year. If you think you don't care about being uakmsned, you may want to reconsider. Personalised browser ads may be harmless, but connecting disparate aspects of your life to predict your future behaviour could lead to unexpected cqeenusoecns. For instance, dnsceiios on whether your child gets to go to a certain university or what price you pay for your home or car inscnarue premiums could be made based on data given to third parties that you never intended to, such as your own lifestyle habits or family members' ailments. In 2014, Ross Anderson, a professor of Privacy and Security at Cambridge University found that the NHS had been sharing its hospitals' database, which idnelcud details of hospitalisations for every ciezitn in Britain with the Institute and Faculty of Actuaries, a body that was rhencareisg how likely plpoee are to develop chronic illnesses at certain ages. Of course, this resulted in an iserncae in health insurance premiums. As the amount of data that is collected icanerses exponentially, it becomes much easier to identify you. For example, your Fitbit measures our heart rate or your gait patterns and these can be used to estimate things like your height, your weight, or even your gender. These are deiatls that are very hard to mimic or change. The data is no legonr about you. It is you. Companies are also starting to predict future behaviours - for example, whether you're a trustworthy driver, a good employee, or a good credit risk, based on things like your social media atcitivy, your health and fitness, or your home energy use. The more the companies know about you - where you live, how many children you have, what your medical ailments are, what you buy - your ayitonmny becomes irrelevant. What's more, you lose your right to free choice, as companies make decisions on your behalf without your kwdlonege. Along my journey of drveoicsy, my first reaction was schok. I immediately wrote to my local council and asked them to make my voter records prtavie. I made up a fake email address, and I started registering with a fake age and gender. I turned off targeted aderistinvg, and I asked Facebook to send me all the information that they held on me, including things I had dteleed, and spent hours poring over it obsessively. But after a few weeks I realised this was a plteosnis exercise. I couldn't be a digital hermit. It wasn't realistic for me to stop using social media, search and navigation apps, and my iPhone, all a part of modern life that I cherished and needed. Instead, I realised that the knowledge itself was emwenproig. Knowing all the different ways in which my data was being sheard and collected made me more responsible about where I put it. For example, I stopped signing up to slpoeduspy free services, for example, a VIP card at my local hairdresser or a discount coupon at your supermarket. Whenever I download an app, I make sure to check my settings to see what permissions it has. Anything that seems unnecessary like access to my location, I turn off. utitlalmey, there is hope. As more of us begin to realise the extent of our data footprint, we will start to demand custody and control of this data. Some critics have even seuggetsd that people be paid for their data in oerdr to give them more ctnoorl. This means it will become too expensive for companies, gnemovtrnes, and non-profits to reclssleky mine and hold our data, and sell it on indiscriminately But until the data economy matures, and power mveos back from the cporraoiton to the iadvniiudl, I have lost more than my anonymity. I have given up my right to self-determination and free choice. All I have left is my name. Thank you. (Applause)

Open Cloze

I'm a 26-year-old British _____ woman working in media and living in a South West postcode in London. I have previously lived at two addresses in ______, and two others in _____ East London. While _______ up, my family lived in a detached _____ in Kent and took holidays to India every year. They mostly did their shopping online at Ocado, gave money to _________ and read the Financial Times. Now, I live in a recently _________ flat with a private landlord, and I have a housemate. I'm interested in movies and startups, and I have taken five holidays in the past 12 months, mostly to visit friends abroad. I'm about to buy flights within 14 days. My annual salary is between 30,000 and 40,000 pounds a year. I don't own a TV or watch any scheduled programming, but I do _____ on-demand services such as _______ or Now TV. Last week, I passed through Upper ______ in North London on Monday and _________ ________ at 7 p.m. I cook a little, but I tend to eat out or get takeaways often. My favourite cuisines are Thai and Mexican food. I don't own any furniture, and I don't have any children. On weeknights, I tend to spend the evenings with my __________ friends having dinner. I usually buy my groceries at Sainsbury's but only because it's on my way home. I don't care for cars or own one. I don't like any form of _________, and I have a cleaner who lets herself in while I'm at work. On _______, you'll find me at the pub after work. At home, I'm far more likely to be browsing __________ reviews rather than managing my ________ or looking at ________ prices online. I like the idea of living abroad someday. I prefer to work as a team than on my own. I'm ambitious, and it's important to me that my many thinks I'm doing well. I'm rarely ______ by others' views. This motley set of characteristics, attitudes, thoughts, and desires come very close to defining me as a person. It is also a precise and accurate description of what a group of companies I had never heard of, ________ data trackers, had learned about me. My journey to uncover what data companies knew _____ in 2014, when I became _______ about the murky world of data brokers, a multi-billion-pound industry of companies that collect, package, and sell detailed profiles of individuals based on their online and offline __________. I decided to _____ about it for Wired Magazine. What I found out shocked me, and reinforced my anxieties about a profit-led system designed to log behaviours every time we interact with the connected world. I already knew about my daily records being collected by services such as Google Maps, Search, Facebook, or contactless credit card transactions. But you combine that with public information such as land registry, _______ tax, or voter records, along with my shopping habits and real-time health and location information, and these benign data sets begin to reveal a lot, such as whether you're optimistic, political, ambitious, or a risk-taker. Even as you're listening to me, you may be sedentary, but your smartphone can reveal your exact location, and even your posture. Your life is being converted into such a data package to be sold on. Ultimately, you are the _______. __________, we're all protected by data protection laws. In the UK, the law states that any personal data set has to be stripped of identifiers such as your name or your ________ Insurance ______. Personal data is considered anything that can be ______ directly back to you. without the need for additional information. This doesn't mean it can't be sold on. It only means that they need your permission. Simple examples of personal data include your full ______ card number, your bank statement, or a criminal ______. However, I discovered that online anonymity is a complete myth. Particulars such as your postcode, your date of birth, and your ______ can be traded freely and without your __________ because they're not considered personal but pseudonymous. In other words, they can't be traced back to you without the need for additional information. So why does it matter if a _____ of companies you've never heard of know your age or your postcode, you may think. Well, it matters quite a lot. About a decade ago, Latanya Sweeney, a professor of privacy at Harvard University ______ that about 87% of US citizens could be uniquely __________ by just three facts about them: their zip code, their date of birth, and their gender. In the UK, where we have far fewer citizens serviced by much longer postcodes, that ___________ is far higher. Professor Sweeney proved this in a rather cheeky way when William Weld, a former governor of _________, _____________, in the US _______ to support the __________ _______ of 135,000 _____ employee health records along with their families, including his own. These records did not contain a name or a social security number, but did contain hundreds of fields of sensitive medical information including drugs __________, hospitalisations, and procedures performed on these _________. For $20, Professor Sweeney _________ the voter records for Cambridge, Massachusetts, containing the names, zip codes, _____ of _____, and gender for every voter in the area, and then cross-referenced this with their health records. Within minutes, she had pinpointed Governor Welds' own health records. Only six people in Cambridge shared his date of birth. Three of them were men. And he was the only one living in his zip code. Professor Sweeney sent the ________ his health _______ in the post. (Laughter) Every day, we hear about new examples of companies digging ever ______ into our personal lives. In the November US presidential election, a little-known British company known as Cambridge Analytica was tasked with _______ the election for a certain candidate: Donald Trump, using data analytics. The _______ ________ cookies ______ to track people around the web, logging every website visited, every search term _____, and every video watched. They also created a _____ Facebook quiz to dig into people's _____________, which was taken by over six million people. In total, they managed to _____ data on 220 million voting Americans with an average of about 5,000 ______ of data on each ______. They then used this data to understand people's inner feelings and then ________ _______ to them on Facebook. ___________ have called them a propaganda machine. It's not just large companies digging into your life; it's free apps and _____ startups as well. I realised on my phone that every time I logged fitness data into the app Endomondo, it was sharing my details _________ my ________ and gender with third-party advertisers. WebMD, a symptom checkers app, was sharing even more sensitive information including the symptoms, __________, and drugs viewed by users within its app with its third parties. Fitbit was sharing data with Yahoo. A _________ tracking app was selling on information about its users' ovulation cycles and fertility cycles with people or advertisers like InMobi. As long as my phone is turned on, my location can be tracked, not just by the obvious apps like Google Maps, but a whole host of unrelated services from Uber to Twitter, Photos, Snapchat, TripAdvisor, and others. You're not even safe in your own home. In 2015, Samsung was found to be recording people in the homes in which their TVs had been sold using their _____ recognition systems. They have now adapted this so they only record when the voice recognition is activated. But the creepy factor remains. Even services like ______ and Facebook, trusted and used by billions around the world, have been _______ of crossing the line. A few _____ ago, my husband and I were driving home from work and discussing where we should have dinner. I suggested a restaurant that I knew was somewhere on our way back and then opened up Google Maps to plot it. Turns out it was already marked on the map with a little bubble. That _______ feeling of being watched is not ______ to me. There have been several _________ reports of people being shown adverts based on things and conversations they were having in real life, prompting ________ that Facebook and Google are _____________ on people via their personal devices. To piece together what all these _________ knew about me, I _____ to a data profiler called Eyeota. Eyeota uses cookies to assign me to thousands of different categories, including my job, how many children I have, and whether I'm likely to buy Star Wars memorabilia. (Laughter) They don't know my name, but they know more about me than my neighbours do. Eyeota also buys information from third parties such as the credit rating agency Experian, which amasses a massive ________ of 15 different demographic types and 66 __________, all _____ on people's post _____. Because ______ buys this information, it knows that I'm more likely to take _____ home rather than night _____ late at night and that I'm very, very unlikely to ever be found in a DIY store. (Laughter) It can then sell this information on to the highest bidder. Sometimes, large data sets can be useful for the public good, for example for the use of ______ researchers or city and _____ planners. But most of this information being collected is sustained by advertisers and traded commercially. In fact, eMarketer has predicted that the online advertising ________, which is based almost completely on data targeting and tracking, will hit an all-time high of 77 billion _______ this year. If you think you don't care about being ________, you may want to reconsider. Personalised browser ads may be harmless, but connecting disparate aspects of your life to predict your future behaviour could lead to unexpected ____________. For instance, _________ on whether your child gets to go to a certain university or what price you pay for your home or car _________ premiums could be made based on data given to third parties that you never intended to, such as your own lifestyle habits or family members' ailments. In 2014, Ross Anderson, a professor of Privacy and Security at Cambridge University found that the NHS had been sharing its hospitals' database, which ________ details of hospitalisations for every _______ in Britain with the Institute and Faculty of Actuaries, a body that was ___________ how likely ______ are to develop chronic illnesses at certain ages. Of course, this resulted in an ________ in health insurance premiums. As the amount of data that is collected _________ exponentially, it becomes much easier to identify you. For example, your Fitbit measures our heart rate or your gait patterns and these can be used to estimate things like your height, your weight, or even your gender. These are _______ that are very hard to mimic or change. The data is no ______ about you. It is you. Companies are also starting to predict future behaviours - for example, whether you're a trustworthy driver, a good employee, or a good credit risk, based on things like your social media ________, your health and fitness, or your home energy use. The more the companies know about you - where you live, how many children you have, what your medical ailments are, what you buy - your _________ becomes irrelevant. What's more, you lose your right to free choice, as companies make decisions on your behalf without your _________. Along my journey of _________, my first reaction was _____. I immediately wrote to my local council and asked them to make my voter records _______. I made up a fake email address, and I started registering with a fake age and gender. I turned off targeted ___________, and I asked Facebook to send me all the information that they held on me, including things I had _______, and spent hours poring over it obsessively. But after a few weeks I realised this was a _________ exercise. I couldn't be a digital hermit. It wasn't realistic for me to stop using social media, search and navigation apps, and my iPhone, all a part of modern life that I cherished and needed. Instead, I realised that the knowledge itself was __________. Knowing all the different ways in which my data was being ______ and collected made me more responsible about where I put it. For example, I stopped signing up to __________ free services, for example, a VIP card at my local hairdresser or a discount coupon at your supermarket. Whenever I download an app, I make sure to check my settings to see what permissions it has. Anything that seems unnecessary like access to my location, I turn off. __________, there is hope. As more of us begin to realise the extent of our data footprint, we will start to demand custody and control of this data. Some critics have even _________ that people be paid for their data in _____ to give them more _______. This means it will become too expensive for companies, ___________, and non-profits to __________ mine and hold our data, and sell it on indiscriminately But until the data economy matures, and power _____ back from the ___________ to the __________, I have lost more than my anonymity. I have given up my right to self-determination and free choice. All I have left is my name. Thank you. (Applause)

Solution

deleted
university
shared
private
details
governments
employees
sinking
personal
governor
behaviours
curious
permission
advertising
ostensibly
based
swayed
restaurant
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recklessly
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property
decided
bunch
purchased
ultimately
traced
small
online
prescribed
record
longer
eyeota
insurance
anecdotal
credit
google
wednesday
pointless
release
deeper
finances
increase
street
discovery
corporation
housework
typed
probability
sussex
amass
companies
gender
north
consequences
decisions
pregnancy
order
company
buses
person
state
converted
product
commercial
including
accused
empowering
unique
database
people
suggested
house
procedures
eavesdropping
evenings
health
voice
enjoy
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began
knowledge
growing
write
council
increases
birth
personalities
dates
identified
citizen
supposedly
dollars
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targeted
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netflix
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codes
national
number
adverts
asian
researching
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massachusetts
individual
urban
viral
winning
records
location
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charities
cambridge
fridays
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activity
researchers

Original Text

I'm a 26-year-old British Asian woman working in media and living in a South West postcode in London. I have previously lived at two addresses in Sussex, and two others in North East London. While growing up, my family lived in a detached house in Kent and took holidays to India every year. They mostly did their shopping online at Ocado, gave money to charities and read the Financial Times. Now, I live in a recently converted flat with a private landlord, and I have a housemate. I'm interested in movies and startups, and I have taken five holidays in the past 12 months, mostly to visit friends abroad. I'm about to buy flights within 14 days. My annual salary is between 30,000 and 40,000 pounds a year. I don't own a TV or watch any scheduled programming, but I do enjoy on-demand services such as Netflix or Now TV. Last week, I passed through Upper Street in North London on Monday and Wednesday evenings at 7 p.m. I cook a little, but I tend to eat out or get takeaways often. My favourite cuisines are Thai and Mexican food. I don't own any furniture, and I don't have any children. On weeknights, I tend to spend the evenings with my university friends having dinner. I usually buy my groceries at Sainsbury's but only because it's on my way home. I don't care for cars or own one. I don't like any form of housework, and I have a cleaner who lets herself in while I'm at work. On Fridays, you'll find me at the pub after work. At home, I'm far more likely to be browsing restaurant reviews rather than managing my finances or looking at property prices online. I like the idea of living abroad someday. I prefer to work as a team than on my own. I'm ambitious, and it's important to me that my many thinks I'm doing well. I'm rarely swayed by others' views. This motley set of characteristics, attitudes, thoughts, and desires come very close to defining me as a person. It is also a precise and accurate description of what a group of companies I had never heard of, personal data trackers, had learned about me. My journey to uncover what data companies knew began in 2014, when I became curious about the murky world of data brokers, a multi-billion-pound industry of companies that collect, package, and sell detailed profiles of individuals based on their online and offline behaviours. I decided to write about it for Wired Magazine. What I found out shocked me, and reinforced my anxieties about a profit-led system designed to log behaviours every time we interact with the connected world. I already knew about my daily records being collected by services such as Google Maps, Search, Facebook, or contactless credit card transactions. But you combine that with public information such as land registry, council tax, or voter records, along with my shopping habits and real-time health and location information, and these benign data sets begin to reveal a lot, such as whether you're optimistic, political, ambitious, or a risk-taker. Even as you're listening to me, you may be sedentary, but your smartphone can reveal your exact location, and even your posture. Your life is being converted into such a data package to be sold on. Ultimately, you are the product. Ostensibly, we're all protected by data protection laws. In the UK, the law states that any personal data set has to be stripped of identifiers such as your name or your National Insurance number. Personal data is considered anything that can be traced directly back to you. without the need for additional information. This doesn't mean it can't be sold on. It only means that they need your permission. Simple examples of personal data include your full credit card number, your bank statement, or a criminal record. However, I discovered that online anonymity is a complete myth. Particulars such as your postcode, your date of birth, and your gender can be traded freely and without your permission because they're not considered personal but pseudonymous. In other words, they can't be traced back to you without the need for additional information. So why does it matter if a bunch of companies you've never heard of know your age or your postcode, you may think. Well, it matters quite a lot. About a decade ago, Latanya Sweeney, a professor of privacy at Harvard University proved that about 87% of US citizens could be uniquely identified by just three facts about them: their zip code, their date of birth, and their gender. In the UK, where we have far fewer citizens serviced by much longer postcodes, that probability is far higher. Professor Sweeney proved this in a rather cheeky way when William Weld, a former governor of Cambridge, Massachusetts, in the US decided to support the commercial release of 135,000 state employee health records along with their families, including his own. These records did not contain a name or a social security number, but did contain hundreds of fields of sensitive medical information including drugs prescribed, hospitalisations, and procedures performed on these employees. For $20, Professor Sweeney purchased the voter records for Cambridge, Massachusetts, containing the names, zip codes, dates of birth, and gender for every voter in the area, and then cross-referenced this with their health records. Within minutes, she had pinpointed Governor Welds' own health records. Only six people in Cambridge shared his date of birth. Three of them were men. And he was the only one living in his zip code. Professor Sweeney sent the governor his health records in the post. (Laughter) Every day, we hear about new examples of companies digging ever deeper into our personal lives. In the November US presidential election, a little-known British company known as Cambridge Analytica was tasked with winning the election for a certain candidate: Donald Trump, using data analytics. The company employed cookies online to track people around the web, logging every website visited, every search term typed, and every video watched. They also created a viral Facebook quiz to dig into people's personalities, which was taken by over six million people. In total, they managed to amass data on 220 million voting Americans with an average of about 5,000 pieces of data on each person. They then used this data to understand people's inner feelings and then targeted adverts to them on Facebook. Researchers have called them a propaganda machine. It's not just large companies digging into your life; it's free apps and small startups as well. I realised on my phone that every time I logged fitness data into the app Endomondo, it was sharing my details including my location and gender with third-party advertisers. WebMD, a symptom checkers app, was sharing even more sensitive information including the symptoms, procedures, and drugs viewed by users within its app with its third parties. Fitbit was sharing data with Yahoo. A pregnancy tracking app was selling on information about its users' ovulation cycles and fertility cycles with people or advertisers like InMobi. As long as my phone is turned on, my location can be tracked, not just by the obvious apps like Google Maps, but a whole host of unrelated services from Uber to Twitter, Photos, Snapchat, TripAdvisor, and others. You're not even safe in your own home. In 2015, Samsung was found to be recording people in the homes in which their TVs had been sold using their voice recognition systems. They have now adapted this so they only record when the voice recognition is activated. But the creepy factor remains. Even services like Google and Facebook, trusted and used by billions around the world, have been accused of crossing the line. A few weeks ago, my husband and I were driving home from work and discussing where we should have dinner. I suggested a restaurant that I knew was somewhere on our way back and then opened up Google Maps to plot it. Turns out it was already marked on the map with a little bubble. That sinking feeling of being watched is not unique to me. There have been several anecdotal reports of people being shown adverts based on things and conversations they were having in real life, prompting concerns that Facebook and Google are eavesdropping on people via their personal devices. To piece together what all these companies knew about me, I spoke to a data profiler called Eyeota. Eyeota uses cookies to assign me to thousands of different categories, including my job, how many children I have, and whether I'm likely to buy Star Wars memorabilia. (Laughter) They don't know my name, but they know more about me than my neighbours do. Eyeota also buys information from third parties such as the credit rating agency Experian, which amasses a massive database of 15 different demographic types and 66 lifestyles, all based on people's post codes. Because Eyeota buys this information, it knows that I'm more likely to take taxis home rather than night buses late at night and that I'm very, very unlikely to ever be found in a DIY store. (Laughter) It can then sell this information on to the highest bidder. Sometimes, large data sets can be useful for the public good, for example for the use of health researchers or city and urban planners. But most of this information being collected is sustained by advertisers and traded commercially. In fact, eMarketer has predicted that the online advertising industry, which is based almost completely on data targeting and tracking, will hit an all-time high of 77 billion dollars this year. If you think you don't care about being unmasked, you may want to reconsider. Personalised browser ads may be harmless, but connecting disparate aspects of your life to predict your future behaviour could lead to unexpected consequences. For instance, decisions on whether your child gets to go to a certain university or what price you pay for your home or car insurance premiums could be made based on data given to third parties that you never intended to, such as your own lifestyle habits or family members' ailments. In 2014, Ross Anderson, a professor of Privacy and Security at Cambridge University found that the NHS had been sharing its hospitals' database, which included details of hospitalisations for every citizen in Britain with the Institute and Faculty of Actuaries, a body that was researching how likely people are to develop chronic illnesses at certain ages. Of course, this resulted in an increase in health insurance premiums. As the amount of data that is collected increases exponentially, it becomes much easier to identify you. For example, your Fitbit measures our heart rate or your gait patterns and these can be used to estimate things like your height, your weight, or even your gender. These are details that are very hard to mimic or change. The data is no longer about you. It is you. Companies are also starting to predict future behaviours - for example, whether you're a trustworthy driver, a good employee, or a good credit risk, based on things like your social media activity, your health and fitness, or your home energy use. The more the companies know about you - where you live, how many children you have, what your medical ailments are, what you buy - your anonymity becomes irrelevant. What's more, you lose your right to free choice, as companies make decisions on your behalf without your knowledge. Along my journey of discovery, my first reaction was shock. I immediately wrote to my local council and asked them to make my voter records private. I made up a fake email address, and I started registering with a fake age and gender. I turned off targeted advertising, and I asked Facebook to send me all the information that they held on me, including things I had deleted, and spent hours poring over it obsessively. But after a few weeks I realised this was a pointless exercise. I couldn't be a digital hermit. It wasn't realistic for me to stop using social media, search and navigation apps, and my iPhone, all a part of modern life that I cherished and needed. Instead, I realised that the knowledge itself was empowering. Knowing all the different ways in which my data was being shared and collected made me more responsible about where I put it. For example, I stopped signing up to supposedly free services, for example, a VIP card at my local hairdresser or a discount coupon at your supermarket. Whenever I download an app, I make sure to check my settings to see what permissions it has. Anything that seems unnecessary like access to my location, I turn off. Ultimately, there is hope. As more of us begin to realise the extent of our data footprint, we will start to demand custody and control of this data. Some critics have even suggested that people be paid for their data in order to give them more control. This means it will become too expensive for companies, governments, and non-profits to recklessly mine and hold our data, and sell it on indiscriminately But until the data economy matures, and power moves back from the corporation to the individual, I have lost more than my anonymity. I have given up my right to self-determination and free choice. All I have left is my name. Thank you. (Applause)

Frequently Occurring Word Combinations

ngrams of length 2

collocation	frequency
personal data	4
health records	4
professor sweeney	3
companies knew	2
credit card	2
data sets	2
additional information	2
information including	2
voter records	2
companies digging	2
voice recognition	2
insurance premiums	2

Important Words

access
accurate
accused
activated
activity
actuaries
adapted
additional
address
addresses
ads
advertisers
advertising
adverts
age
agency
ages
ailments
amass
amasses
ambitious
americans
amount
analytica
analytics
anderson
anecdotal
annual
anonymity
anxieties
app
applause
apps
area
asian
asked
aspects
assign
attitudes
average
bank
based
began
behalf
behaviour
behaviours
benign
bidder
billion
billions
birth
body
britain
british
brokers
browser
browsing
bubble
bunch
buses
buy
buys
called
cambridge
car
card
care
cars
categories
change
characteristics
charities
check
checkers
cheeky
cherished
child
children
choice
chronic
citizen
citizens
city
cleaner
close
code
codes
collect
collected
combine
commercial
commercially
companies
company
complete
completely
concerns
connected
connecting
consequences
considered
contactless
control
conversations
converted
cook
cookies
corporation
council
coupon
created
credit
creepy
criminal
critics
crossing
cuisines
curious
custody
cycles
daily
data
database
date
dates
day
days
decade
decided
decisions
deeper
defining
deleted
demand
demographic
description
designed
desires
detached
detailed
details
develop
devices
dig
digging
digital
dinner
discount
discovered
discovery
discussing
disparate
diy
dollars
donald
download
driver
driving
drugs
easier
east
eat
eavesdropping
economy
election
email
emarketer
employed
employee
employees
empowering
endomondo
energy
enjoy
estimate
evenings
exact
examples
exercise
expensive
experian
exponentially
extent
eyeota
facebook
fact
factor
facts
faculty
fake
families
family
favourite
feeling
feelings
fertility
fields
finances
financial
find
fitbit
fitness
flat
flights
food
footprint
form
free
freely
fridays
friends
full
furniture
future
gait
gave
gender
give
good
google
governments
governor
groceries
group
growing
habits
hairdresser
hard
harmless
harvard
health
hear
heard
heart
height
held
hermit
high
higher
highest
hit
hold
holidays
home
homes
hope
hospitalisations
host
hours
house
housemate
housework
hundreds
husband
idea
identified
identifiers
identify
illnesses
immediately
important
include
included
including
increase
increases
india
indiscriminately
individual
individuals
industry
information
inmobi
instance
institute
insurance
intended
interact
interested
iphone
irrelevant
job
journey
kent
knew
knowing
knowledge
land
landlord
large
latanya
late
laughter
law
laws
lead
learned
left
lets
life
lifestyle
lifestyles
line
listening
live
lived
lives
living
local
location
log
logged
logging
london
long
longer
lose
lost
lot
machine
magazine
managed
managing
map
maps
marked
massachusetts
massive
matter
matters
matures
means
measures
media
medical
memorabilia
men
mexican
million
mimic
minutes
modern
monday
money
months
motley
moves
movies
murky
myth
names
national
navigation
needed
neighbours
netflix
nhs
night
north
november
number
obsessively
obvious
ocado
offline
online
opened
optimistic
order
ostensibly
ovulation
package
paid
part
particulars
parties
passed
patterns
pay
people
performed
permission
permissions
person
personal
personalised
personalities
phone
photos
piece
pieces
pinpointed
planners
plot
pointless
political
poring
post
postcode
postcodes
posture
pounds
power
precise
predict
predicted
prefer
pregnancy
premiums
prescribed
presidential
previously
price
prices
privacy
private
probability
procedures
product
professor
profiler
profiles
programming
prompting
propaganda
property
protected
protection
proved
pseudonymous
pub
public
purchased
put
quiz
rarely
rate
rating
reaction
read
real
realise
realised
realistic
recklessly
recognition
reconsider
record
recording
records
registering
registry
reinforced
release
remains
reports
researchers
researching
responsible
restaurant
resulted
reveal
reviews
risk
ross
safe
salary
samsung
scheduled
search
security
sedentary
sell
selling
send
sensitive
serviced
services
set
sets
settings
shared
sharing
shock
shocked
shopping
shown
signing
simple
sinking
small
smartphone
snapchat
social
sold
south
spend
spent
spoke
star
start
started
starting
startups
state
statement
states
stop
stopped
store
street
stripped
suggested
supermarket
support
supposedly
sussex
sustained
swayed
sweeney
symptom
symptoms
system
systems
takeaways
targeted
targeting
tasked
tax
taxis
team
tend
term
thai
thinks
thoughts
thousands
time
times
total
traced
track
tracked
trackers
tracking
traded
transactions
tripadvisor
trump
trusted
trustworthy
turn
turned
turns
tv
tvs
twitter
typed
types
uber
uk
ultimately
uncover
understand
unexpected
unique
uniquely
university
unmasked
unnecessary
unrelated
upper
urban
users
video
viewed
views
vip
viral
visit
visited
voice
voter
voting
wars
watch
watched
ways
web
webmd
website
wednesday
week
weeknights
weeks
weight
weld
west
william
winning
wired
woman
words
work
working
world
write
wrote
yahoo
year
zip