Introducing Record Time

Status

Dropped

Area

Personal

Imagine the story of someone’s life told not with words, like a novel, or video, like a movie — but with records.

Our lives can be seen as a catalogue of records. Records that we create, and records that are created about us. Told in this way, a story could start with a birth certificate. Or before that, the purchase receipt for a car seat. Or even further back, a text inviting someone to a party.

That’s why I’m starting a new project, called Record Time. It’s about creating a new way to tell stories — one that also tells us about the time we live in.

💽 Living in a time of records

The number of records we generate now reaches thousands a day, even if we’re not aware of it. Timestamps of when we pick up our phone, how long we use it for. Histories of the websites we visit, and the people we call. Emails we write at work, emails and messages we receive from our family.

And other creepier records. Our location, tracked 24/7. The porn we watch, stashed on some server on the other side of the world, the secret fears we type into Google. The articles we choose to read, which reveal the way we think.

Creating a story from these records will show how linked our lives are with the digital realm while we’re alive, and what will remain of us in bytes after we die.

👓 What this looks like

Record Time will start as a series of blog articles here on louis.work/blog, where each article will consist of a bunch of infographics and data visualisations (charts, etc.) that represent the kind of things you could find out about a person if you were a data scientist with God-level access to every database on earth.

It’ll all be fictional, because we don’t have that God-level access, but we can imagine what we’d find if we did, based on what we know about the data we’re giving out. It’s not so much about imagining raw data, but imagining the analysis and insights that you could come up with if you had access to all that raw data.

So: analysis and insights, in the form of infographics and data visualisations, will combine to tell a story about a person.

⁉️ Why I’m doing this

For three reasons:

First, to show how creepy the world of data that we live in is, and to bring data to life. We struggle to imagine the vastness of the data that exists about us, and even more crucially, to take the next mental leap, which is to realize the profound and disturbing facts and stories that any good data scientist could infer about us from our data.

Second, to show the strange beauty of data, as a trace that each of us is leaving in the world, whether we realize it or not. This is a new facet to human existence that has only recently come into being; an additional layer of marks we make on the universe. Think about it: right now, in data centers and on devices scattered across the world, exists a whole side of you.

Third, to showcase a new form of storytelling fit for the digital age. And I hope that this form of storytelling will evolve. The first two projects I’ll work on for this form of storytelling will be relatively straightforward (described above), but after those, I’ll start thinking about dynamic Record Time formats; for instance collaborative games that people can play with each other, taking the role of data science detectives going through data to piece together a narrative themselves, or even creating data for each other to try to understand.

🏕️ Where I’ll start

With a story about Tinder. Here’s what the first short story, based on the Tinder data of someone called Josh, will show.

Personality

❌ How Josh tries to delete Tinder every few weeks but keeps coming back

⏱️ The hours Josh spends on Tinder, and how he uses it late at night in particular, as well as (probably) when he is sitting on the toilet

🔥 How his probability of swiping right tends to increase late at night, perhaps because he is lonelier

And how he often tweaks the age range of women he gets shown

🗨️ A breakdown of his most successful Tinder conversations

Which shows which ‘converted’ to phone numbers being exchanged and which didn’t
And which are the most frequent words used in successful (’converted’) conversations

🔡 The way his bio evolves over time as he changes his outward personality to try and do better on the app

🖊️ The way his opening lines also evolve over time, sometimes in depressing ways

We see how he deploys the same carefully crafted opening line again, and again, and again

Story

💔 We see that there is an 11 month break in his usage of Tinder after one particularly long conversation which did convert to phone numbers being exchanged, and infer from this that he ended up in a relationship with this particular woman. But it presumably ended, because he comes back to Tinder

🔦 We see that his Tinder tactics change for a short while after he comes back to Tinder. He’s swiping right more indiscriminately, putting out more generic opening lines

👥 We see problematic facts about Josh’s racial dating preferences, and we see how these evolve over time e.g. he stops dating women of a certain race after what we can guess was a failed relationship with a woman also of that race

💳 We see him eventually pay for Tinder Premium, which hugely affects the time he spends on Tinder. Now that he can see profiles of women who have already swiped right on him, the power dynamic is changed and he in fact connects with far fewer women, but with higher quality interactions