Oct 29, 2016

Personal Data Literacy

At the age of 19, still pimple-faced and barely out of high school, I was hired to make decisions that would change strangers’ lives.

Day after day was filled with simple yes or no decisions. If yes, they’d get a tool that would make their lives easier. No, they’d go without and continue struggling.

I had a front-row seat to how the personal data industry started - in consumer credit. My role was reduced to running a credit score, and accepting or declining people based on a single number.

Do you remember the first time you applied for credit? Maybe it was for a mobile phone, or at a bank.

What I soon realised, was that these decisions are designed to be systematised, for companies to be able to hire inexperienced kids to make credit decisions, step by step, like making a burger at McDonald’s.

I saw how flawed the system was, because the policies it created made it so good people were rejected. A lot. This wasn’t just to be safe - it was to be systematic. Err on the side of caution.

Where I grew up, building your credit was considered a coming-of-age act, like learning to drive and getting a degree.

Then I got a backstage look at how credit really works. At age 19, I worked in a mobile phone company’s call center. At age 19, I was accepting and rejecting people based on their credit.

And this is why I want to teach you why your personal data is so important.

The same broken logic of consumer credit ratings is coming to healthcare, job applications, voting rights and more

The same broken credit system that works against people is being rebuilt for jobs, insurance and healthcare, voting registration, and is going to unfairly and negatively affect us.

There are established companies that buy your personal data, convert it into a way for large organisations - including insurance, healthcare and governments - to make decisions about you without you ever knowing.

Let me explain.

The credit score tool is designed as a filter for applications. You apply, the company pays for a credit report, gets a number, and if that score is above whatever they decided their minimum score is, you get accepted or not.

This is why when you apply for a mortgage, you end up dealing with a kid bank manager who was a teller 6 months ago.

This financial data about you – technically, you have a right to see it, but you don’t have any control over it. If your phone company makes a mistake and misses a payment from you, they report it to the credit bureau, and your score drops. It’s possible to see this, if you jump through some hoops, but almost impossible to correct.

And with financial data, it’s regulated in most places.

Let’s look at what’s emerging.

Your online activity reveals way more than you think

All of this personal stuff you share, all of the heart and like buttons you press, and all of the stuff you read online, that’s all getting recorded. Put together, it starts to tell a clear story about you.

For example, did you know that if you’re an American and you tend to read recipes with ice-berg lettuce more than arugula, you’re likely to be a Republican, and if you read recipes with arugula more than ice-berg, you’re likely to be a Democrat? Even one or two Facebook likes reveal, with high statistical accuracy, your sexual orientation, if your parents divorced while you were a child, your IQ, your emotional stability, and your health. They can even go so far as to predict changes to your health that you’re not even aware of. (Only your health records are protected by law, not accurate predictions of your health from you reading symptoms on WebMD.)

This data about you gets sold.

While these companies claim to protect your privacy, there’s a loophole they all use - they say they share the data with “trusted Third Parties.” This allows them to share the data to other companies, which de-anonymise it and package it.

Big Data means big changes

Now, it’s starting to get used in other places.

Take, for example, job applications. An easy first-pass to screen out candidates is to run them through a simple system like a credit check. “Here’s everyone that applied, score them all and give me the top 100 for interview.” Again, the hiring company here doesn’t mind missing a couple good candidates with low scores if they can be sure their time on the 100 interviews is generally better spent. That margin of error costs people opportunities.

The same type of screen is already happening with screening for health insurance, for voting eligibility, and a wider and wider range of critical services. People are being rejected for health insurance, and turned away at the polls because of the way personal data is used.

In a way, learning to understand your personal data, and keep it private, is the same as learning to manage your personal credit. It’s just as smart to invest in your “financial literacy” as it is to invest in your “personal data literacy.” There’s a system out there that’s not designed for you, but for the needs of companies that want something from you, and for you to come out ahead, you’ll need to understand it.

What am I up to these days?

I’m a new parent, and prioritising my attention on our new rhythms as a family.

Work-wise, I’m trekking along at a cozy pace, doing stuff that doesn’t require meetings :)

I have a few non-exec/advisory roles for engineering edu programs. I’m also having fun making a few apps, going deep with zero-knowledge cryptography, and have learned to be a pretty good LLM prompt engineer.

In the past, I've designed peer-learning programs for Oxford, UCL, Techstars, Microsoft Ventures, The Royal Academy Of Engineering, and Kernel, careering from startups to humanitech and engineering. I also played a role in starting the Lean Startup methodology, and the European startup ecosystem. You can read about this here.

Contact me

Books & collected practices

  • Peer Learning Is - a broad look at peer learning around the world, and how to design peer learning to outperform traditional education
  • Mentor Impact - researched the practices used by the startup mentors that really make a difference
  • DAOistry - practices and mindsets that work in blockchain communities
  • Decision Hacks - early-stage startup decisions distilled
  • Source Institute - skunkworks I founded with open peer learning formats and ops guides, and our internal guide on decentralised teams