Beverley Skeggs gave the public lecture You Are Being Tracked, Evaluated and Sold: an analysis of digital inequalities, hosted by LSE's International Inequalities Institute.

Wake up, machine learning algorithms have been trawling your phone whilst you slept. If you did. If you had a long sleep your health profile will record positive. Your health data is one signal that will be built into a profile of all your behaviour. It will be used to inform decisions about credit ratings and health provision. Unhealthy subjects may be less likely to consume so they are less tradable on a data auction. Data brokers can get a better price for you if you are healthy. But beware they also sell information about you to insurance companies, which will increase your premium if you have a range of health data points suggesting future risk.

Let’s hope you didn’t use a flashlight app on your phone during the night or all your data on your device will have been sent to a range of data brokers to assess whether they are willing to pay for anything that can increase their knowledge about your trading potential.

But don’t worry. By the time you’re fully awake you will already have a whole crowd of data trackers following you. The instance you open your browser you will have been traded — in a millisecond. If you are looking at anything that may directly signal your interest in a product (say a holiday) the trackers will use their machine learning algorithms to assess your potential to buy the product, going through multiple data points, e.g., when you last took a holiday, your location, credit rating, cash transactions, family purchases, health, and rate you as a likely purchaser. They will offer your potential to a data auction, and an algorithmic match will be made with a holiday company. The algos will assess your potential in relation to their product, looking for a match and bid accordingly. And that’s before your eyes are fully open.

Your web browsing history is the most lucrative piece of information that can be traded as it enables a behavioural profile to be developed. Each time you open a web page algorithmic trackers search for data points that may be of use to them for profile building, matching and trading.

Ghosterly, a company that tracks the trackers, lists over 3,000 companies that are interested in your data. The first line are the big data brokers (Axicom, Experian), which can build up the most extensive profile of who you are by combining online, off-line, sensor and social media data together and then ranking. “Lead generators” will be scouring your real-time communications to see if they can identify anything of interest that they can sell on. For instance, they will compile lists of those who are interested in college courses and offer the list to colleges. Then specific companies (such as insurance, finance, advertisers, medical support) follow, if they think you may be of interest.

These companies compete against each other. Some have long histories of collecting data on population. They have usually been amalgamated into a big data company, so historical, offline and behavioural data can be combined. The most powerful have the most information and the best analysis.

The race for the most extensive data, with the fastest capacity to analyse and trade it, leads to a trend towards monopolisation. Just follow the acquisitions of Google or Facebook to see how, and also look at how they are continually buying and building capacity to access and analyse new data such as facial recognition, messaging and sensory movement. They are constantly expanding their ability to access and analyse.

Google (Alphabet) is doing very well as it has information on every search you have made (if you use google search), it has a powerful analytic tracker with powerful machine learning capacity.

Facebook has the edge on your social habits such as how you communicate with friends, your network and (through Instagram) your relationships. Google has a behavioural and spatial map of most things you do. Their unique selling point to advertisers is that they know us and can predict our likely behaviour in order that we can be targeted more effectively.

What did you eat for breakfast? All shopping habits are logged through credit cards, loyalty cards or in the future sensors in product packing. If you ate a sausage sandwich you could be in trouble. Your health insurance or life insurance policy costs in the future are going to be high. You should have had low fat yogurt with fruit. You are signalling to the trackers that you do not take care of yourself. They will add the sausage data point to the 3,400 other data points they have about you. Equifax will run through the 17 key diseases that are likely to affect your life expectancy and medical costs and see if you are to be put on their high-risk pile. High risk usually means more costs to access the care you need.

What other apps have you opened this morning? Forty-seven of the 100 most popular apps will have transferred the phone’s location not only to the developer, but also to third parties. Location data can be used to predict what they can target you with today. Have you checked train times? Can they target you with products or activities near the station? If you’ve opened your email, there is a 73 per cent chance that your android phone will have sent your email addresses and contacts to a third party developer. It’s only a 43 per cent chance for iPhone users.

All your education results, doctor’s appointments, medication, leisure activities, purchases made by you and your parents, and possibly the rest of your family and friend network will be on your data profile. Many data brokers operate through stealth: Take 5 Solutions, a US data broker, runs 17 websites like GoodParentingToday.com and T5 HealthyLiving.com where people can share stories about their families and health. The purpose of these “sharing” websites is to compile, analyse and sell information to advertisers.

All your off-line demographic data will have been matched against your social media data. Those pictures that you posted when 13, of wrecking your parent’s house, are no longer funny. Unless of course you are a member of the Bullingdon Club studying PPE at Oxford, then your cultural capital will likely protect you. After all you may become the next prime-minister. Not on Facebook anymore, have closed down your account? It’s too late, those pictures will have become part of your profile and may or may not be used against you.

Did you plug in your battery? Do you recharge every night? Apparently it’s a sign of a responsible person, even if less good for your phone. Your responsibility index gains a point amongst the 3k +. Phone use is constantly tracked.

If you forget to behave responsibly towards your phone and it records chaotic behaviour you may head towards the remainder pile if your irresponsible behaviour maps with other data signals, such as irresponsible family, network, etc. All of these data points will be aggregated and categorised, such as into a credit rating, and as high-risk should they apply for anything that requires regularity and responsibility such as paying back a loan it is likely they will be targeted by those companies who feed off the those whose lives are irregular. They will have been identified as “low hanging fruit” (a marketing categorisation) and will be sold all the sub-prime products available. They won’t know why.

Which web sites did you log into? A quick look at the weather. The app will send location signals to the trackers. Did you look up weather in Ibiza. The data brokers log this and offer it up as a “lead”, most likely to holiday companies, obviously.

You leave the house, going to work….well that’s if you’ve managed to get a job after having all your data trawled through, your CV checked, educational qualifications recorded, and your behaviour identified. Have you ever taken an online personality test? A gift for data brokers.

But how do you get to work? In the UK you may know that Oyster cards are trackers but did you know the data on your movement is sold? Any signal about you is sold. To whom we do not know. But we do know (because this is how these companies market their unique selling point) it is collected, collated with other data before its packaged. Transport for London is a client for a major UK data broker.

So you go to work, let’s hope your employers don’t make you wear a Humanyze badge that records not just your movements, but your conversations (with whom, where, how and for how long) and registers the tone of your voice. Over 2 million are already in operation in the workplace, with a likely 5 million to be issued this year. Some people voluntarily give up all their data. Employers love fitbit wearers.

You are tired after work. After all you’ve just walked for an hour to earn your reduced premium health insurance (the is mainly true if you live in the US but if you have private insurance in the UK you will be similarly affected). So you turn on the TV, which bounces sensors off you from its commercial ads to let the TV viewing brokers know what you are watching. Eyeball recognition is one of the premium technologies in development. If advertisers know exactly what captures your attention, they think they can target you more effectively. But do they know why you are looking? It could be horror and repulsion.

You’re not interested in TV, but have been on Gaydar and located some interesting chaps? In so doing your data has been sent to over 3 different brokers. A Connecticut data broker called “Statlistics” advertises lists of gay and lesbian adults for “sale” to advertisers. Lifestyle is social data that, along with locational data, can enable a real-time bid to take place. You’ve ventured out after sex; you might be hungry. Your location data will have been auctioned to brokers who represent local restaurants who will be posted to your phone. If you decide to take up the eating offer, your consumption will be logged and added to your profile. More sausages. Oh dear. Health score points plummet again.

Now let’s hope you didn’t get an Uber. Uber handed over information on trips, trip requests, pick up and drop off areas, fares, vehicles and drivers to US regulators, state and federal agencies between July and December 2015 on 12 million riders. This is where we move beyond advertisers and into the dark realm of state surveillance. Follow Wikileaks to see who is being sold by state to state (eg the recent Indian Aadhar scandal).

You finally get home, tired but need to book a flight and hotel. Don’t do it on your Mac laptop as you are likely to be charged 20 per cent more for flights and hotels, as Orbitz found. Try and find your old PC, but oh no, it doesn’t make any difference your whole booking history has been logged and the fact that you paid over-the-odds price in an emergency over five years ago sent the signal that you buy high-priced flights. Don’t log out and start again. They know you’re interested so they’ll just keep upping the price.

Seven of the nine major data brokers will be trading your data between themselves. We don’t know for what reasons. We will never know for, as the Federal Trades Commisssion reported, it is impossible to find out. The data brokers didn’t bother turning up to FTC when called. You can’t even find out how these data brokers collected all the data they have on you. And you can’t find out what they have. You may never know. Or you may find out when you realise something has gone badly wrong. People with ‘common” names beware. They are often getting confused and rated accordingly. As Cathy O’Neil shows, it’s remarkably difficult to challenge this even if you have been tagged as an ex serial killer.

But whatever you do, remember to plug in your phone to recharge tonight.

♣♣♣

Notes:

This blog post was co-published with LSE’s Equity, Diversity and Inclusion blog.

The post gives the views of its author, not the position of LSE Business Review or the London School of Economics.

Featured image credit: Smartphone and bedtime, by m01229, under a CC-BY-2.0 licence

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Beverley Skeggs is the new Academic Director of the Atlantic Fellows programme at LSE’s International Inequalities Institute. Beverley is one of the foremost feminist sociologists in the world, and brings to the post a wealth of experience addressing the multi-dimensional nature of inequality. Her book Formations of Class and Gender (1997) has been profoundly significant in drawing attention to the intersections between class and gender inequality, as experienced by young working class women dealing with the vulnerabilities of daily life in harsh conditions.