How do criminals take over countries?
A few weeks ago our decade-old, serially-repaired dishwasher gave up the ghost, soaking the kitchen floor in the process. Louise found a replacement online that met her needs and fitted into the space we had, and two burly guys came out this week to install it while she stood outside with all the doors and windows open.
“It’s a smart dishwasher,” she told me, handing me the instruction manual. “Figure out how to hook it up to my cell phone so we can control it remotely.”
I dutifully read the manual and downloaded the app from the overseas company that made the dishwasher. And that’s where it got weird.
Even though the dishwasher is in my house, and would be on my in-house WiFi network along with her phone, the app required me to give them my Google or Facebook login information to access their network in another country which would, in turn, control my dishwasher.
That was the point at which I stopped, removed the app from her phone, and Louise and I concluded we’re just going to have to fire up the dishwasher the old-fashioned way. We already have too many appliances spying on us.
The thermostat in our house, for example, tells the California company that sells it all about our habits, including when we’re home or not.
Our home temperature data could tell the company if somebody is having a medical problem from pernicious anemia or using beta blockers for hypertension (and so is keeping the house abnormally warm) to menopause (popping temperatures all over the place). It could tell a company selling insulation if we need some, or a potential burglar the best time to pop a window.
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The thermostat could have been designed to have a “home WiFi-only mode” where the company doesn’t get all that info, but, like nearly all the “smart” thermostat companies, they chose not to allow for that.
Ditto for our bed, which is adjustable and tracks our sleep. When I tried to disable sending our information to the company that made it, that effort, in turn, disabled its collecting interesting information about how long and how well we sleep. If we want to know how we’re sleeping, we have to share that info with a company we already paid an absurd amount of money to for the bed itself.
Our doorbell also sends our information to its mother ship; they know pretty much everything about us, including how often we get deliveries and from whom, who visits and when, and when that thief tried to break in.
I’m typing the first draft of this article into Microsoft Word, which no longer just runs on my computer; whenever I open the program, it connects to Microsoft who can provide “suggestions” for better grammar and offers to store all my writing on their own servers. If I try to turn off Microsoft’s access to my work, they take away my ability to open a PDF file, among other features.
My Windows computer at the studio is starting to pretty much insist, every time it updates every week or three, that I create a Microsoft account so they can “help” and “protect” me by monitoring everything I do on the computer. Ditto with the Apple MacBook I’m typing this into, except that I had to give them my info years ago just to get updates and download apps.
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As I lay out in my upcoming book, The Hidden History of Big Brother in America: How the Death of Privacy and the Rise of Surveillance Threaten Us and Our Democracy, none of this is random, accidental or coincidental.
These for-profit companies are collecting all this data on us for one reason: they can sell it for money.
While Europeans have a pretty high degree of protection from being spied on by commercial interests or having their data sold, it’s commonplace in the US.
It’s so bad here, in part, because Donald Trump put former Verizon lawyer Ajit Pai in charge of the FCC.
Pai then eliminated “net neutrality,” so now the company that brings the internet into your house (your “Internet Service Provider” or ISP) can not only see every website you visit and every word or letter you type online but can even monitor your individual keystrokes.
From watching just your keystroke behavior they can predict with over 80% accuracy your level of self-confidence, hesitancy, nervousness, sadness or fatigue.
All of this is information that has value, and all of it is now available to corporations and governments for a price.
When Cambridge Analytica was aiding in the design of thousands of individually personalized Facebook and other social media ads for the Trump campaign in 2016, they claimed to have over 4000 individual “data points” on each of the millions of Americans they targeted.
A 2014 Federal Trade Commission report found that even the simplest, most basic and easily purchased profiles on you and me typically include:
Name •Previously Used Names •Address •Address History •Longitude and Latitude •Phone Numbers •Email Address •Social Security Number •Driver’s License Number •Birth Date •Birth Dates of Each Child in Household •Birth Date of Family Members in Household •Age •Height •Weight •Gender •Race and Ethnicity •Country of Origin •Religion (by Surname at the Household Level) •Language •Marital Status •Presence of Elderly Parent •Presence of Children in Household •Education Level •Occupation •Family Ties •Demographic Characteristics of Family Members in Household •Number of Surnames in Household •Veteran in Household •Grandparent in House •Spanish Speaker •Foreign Language Household (e.g., Russian, Hindi, Tagalog, Cantonese) •Households with a Householder Who Is Hispanic Origin or Latino •Employed—White Collar Occupation •Employed—Blue Collar Occupation •Work at Home •Length of Residence •Household Size •Congressional District •Single Parent with Children •Ethnic and Religious Affiliations •Court and Public Record Data •Bankruptcies •Criminal Offenses and Convictions •Judgments •Liens •Marriage Licenses •State Licenses and Registrations (e.g., Hunting, Fishing, Professional) •Voting Registration and Party •Electronics Purchases •Friend Connections •Internet Connection •Internet Provider •Level of Usage •Heavy Facebook User •Heavy Twitter User •Twitter User with 250+ Friends •Is a Member of over 5 Social Networks •Online Influence •Operating System •Software Purchases •Type of Media Posted •Uploaded Pictures •Use of Long Distance Calling Services •Presence of Computer Owner •Use of Mobile Devices •Social Media and Internet Accounts including: Digg, Facebook, Flickr, Flixster, Friendster, hi5, Hotmail, LinkedIn, Live Journal, MySpace, Twitter, Amazon, Bebo, CafeMom, DailyMotion, Match, myYearbook, NBA.com, Pandora, Photobucket, WordPress, and YahooHome and Neighborhood Data •Census Tract Data •Address Coded as Public/Government Housing •Dwelling Type •Heating and Cooling •Home Equity •Home Loan Amount and Interest Rate •Home Size •Lender Type •Length of Residence •Listing Price •Market Value •Move Date •Neighborhood Criminal, Demographic, and Business Data •Number of Baths •Number of Rooms •Number of Units •Presence of Fireplace •Presence of Garage •Presence of Home Pool •Rent Price •Type of Owner •Type of Roof •Year •Apparel Preferences •Attendance at Sporting Events •Charitable Giving •Gambling—Casinos •Gambling—State Lotteries •Thrifty Elders •Life Events (e.g., Retirement, Newlywed, Expectant Parent) •Magazine and Catalog Subscriptions •Media Channels Used •Participation in Outdoor Activities (e.g., Golf, Motorcycling, Skiing, Camping) •Participation in Sweepstakes or Contests •Pets •Political Leanings •Assimilation Code •Preferred Celebrities •Preferred Movie Genres •Preferred Music Genres •Reading and Listening Preferences •Donor (e.g., Religious, Political, Health Causes) •Financial Newsletter Subscriber •Upscale Retail Card Holder •Affluent Baby Boomer •Working-Class Moms •Working Woman •African-American Professional •Membership Clubs •Membership Clubs—Wines •Exercise—Sporty Living •Winter Activity Enthusiast •Participant—Motorcycling •Outdoor/Hunting and Shooting •Biker/Hell’s Angels •Santa Fe/Native American Lifestyle •New Age/Organic Lifestyle •Is a Member of over 5 Shopping Sites •Media Channel Usage—Daytime TV •Bible Lifestyle •Leans Left •Political Conservative •Political Liberal •Activism and Social Issues •Ability to Afford Products •Credit Card User •Presence of Gold or Platinum Card •Credit Worthiness •Recent Mortgage Borrower •Pennywise Mortgagee •Financially Challenged •Owns Stocks or Bonds •Investment Interests •Discretionary Income Level •Credit Active •Credit Relationship with Financial or Loan Company •Credit Relationship with Low-End Standalone Department Store •Number of Investment Properties Owned •Estimated Income •Life Insurance •Loans •Net Worth Indicator •Underbanked Indicator •Tax Return Transcripts •Type of Credit Cards •Vehicle Brand Preferences •Insurance Renewal •Make & Model •Vehicles Owned •Vehicle Identification Numbers •Vehicle Value Index •Propensity to Purchase a New or Used Vehicle •Propensity to Purchase a Particular Vehicle Type (e.g., SUV, Coupe, Sedan) •Motor Cycle Owner (e.g., Harley, Off-Road Trail Bike) •Motor Cycle Purchased 0–6 Months Ago •Boat Owner •Purchase Date •Purchase Information •Intend to Purchase—Vehicle •Read Books or Magazines About Travel •Travel Purchase—Highest Price Paid •Date of Last Travel Purchase •Air Services—Frequent Flyer •Vacation Property •Vacation Type (e.g., Casino, Time Share, Cruises, RV) •Cruises Booked •Preferred Vacation Destination •Preferred Airline •Amount Spent on Goods •Buying Activity •Method of Payment •Number of Orders •Buying Channel Preference (e.g., Internet, Mail, Phone) •Types of Purchases •Military Memorabilia/Weaponry •Shooting Games •Guns and Ammunition •Christian Religious Products •Jewish Holidays/Judaica Gifts •Kwanzaa/African-Americana Gifts •Type of Entertainment Purchased •Type of Food Purchased •Average Days Between Orders •Last Online Order Date •Last Offline Order Date •Online Orders $500–$999.99 Range •Offline Orders $1,000+ Range •Number of Orders—Low-Scale Catalogs •Number of Orders—High-Scale Catalogs •Retail Purchases—Most Frequent Category •Mail Order Responder—Insurance •Mailability Score •Apparel—Women’s Plus Sizes •Apparel—Men’s Big and Tall •Books—Mind and Body/Self-Help •Internet Shopper •Novelty Elvis •Ailment and Prescription Online Search Propensity •Propensity to Order Prescriptions by Mail •Smoker in Household •Tobacco Usage •Over the Counter Drug Purchases •Geriatric Supplies •Use of Corrective Lenses or Contacts •Allergy Sufferer •Have Individual Health Insurance Plan •Buy Disability Insurance •Buy Supplemental to Medicare/Medicaid Individual Insurance •Brand Name Medicine Preference •Magazines—Health •Weight Loss and Supplements •Purchase History or Reported Interest in Health Topics including: Allergies, Arthritis, Medicine Preferences, Cholesterol, Diabetes, Dieting, Body Shaping, Alternative Medicine, Beauty/Physical Enhancement, Disabilities, Homeopathic Remedies, Organic Focus, Orthopedics, and Senior Needs.
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Companies now use this kind of data about you to tell potential employers whether you’re a good bet or not (HireVue, for example, scores you on “20,000 data points we collect” that even include your “nonverbal communication”).
Ditto for giant hedge funds that run massive rental operations across America (driving up the cost of housing), which use this data to decide whether to rent to you, for how long, and at what price or with how much of a deposit.
There’s a version of this for retailers, as well. One scores consumers using “massive data” and “deep expertise” for companies from Starbucks to OpenTable, Wayfair to Instacart.
“More than 16,000 signals inform the ‘Sift score,’” wrote Christopher Mims inthe Wall Street Journal in 2019. “This score is like a credit score,” he added, “but for overall trustworthiness,” according to “a company spokeswoman.”
If Sift has flagged you as “untrustworthy” for one particular retail outlet, you may not be able to open an account, complete a transaction, or even interact with multiple other retailers.
As the consumer group #REPRESENT noted in a 2019 complaint to the Federal Trade Commission, “Like all Surveillance Scores, the Sift score is a closely-guarded secret.”
Other companies offering similar services include the Retail Equation, whose fraud score is used in 34,000 stores in the United States, including Best Buy, Home Depot, and Sephora. Once you’re flagged by them, you’ll be unable to return products to these stores regardless of how well you document your identity and the money trail to your purchase.
If you’ve been flagged by another data company, Riskified, “unlike the Retail Equation, whose scores only result in the denial of returns, Riskified’s fraud scores go even farther by not only preventing returns of merchandise but also [preventing] purchases.”
America needs a conversation about privacy, and it need not be partisan.
For example, Josh Hawley wrote a book titled The Tyranny of Big Tech that makes some surprisingly good points about our loss of privacy (albeit along with rants about liberal conspiracies to use the information for nefarious and socialist purposes).
Surveys show that Americans want to reclaim their privacy, both from “Big Government” and “Big Tech.” The European Union has already traveled a good distance down this road, and we have a lot to learn from their experience.
And it starts with us saying “No” to “smart” appliances that are, in reality, data thieves attaching themselves to us and our homes like blood-sucking parasites.
(For the “Daily Audio” of Thom reading this article, available only to paid subscribers, check the “Daily Audio” tab on HartmannReport.com.)
Originally posted at The Hartmann Report
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