So I recently decided to leave my job as an operational analyst. This means that I am going to spend some time cultivating Galapag.us, hopefully attracting funding and mentorship with my friend Bryn, and am going to give the company a real shot. It’s an amazing feeling and something I’ve been dying to do for years now. I seem to have a lot of people supporting me, so that seems nice…but now I have to really prove myself and that’s a little daunting.
Anyway, I’ve been continuing the thinking about liquidity from my last post.
Measuring Interaction Liquidity in Jobs
Some ways of life lend themselves to more interactions with other people. In my case, I had gone from an Army experience to a grad school environment to a shift-work job. In terms of interaction liquidity, the Army is an extremely poor environment for finding suitable girlfriends (although I had a wonderful girlfriend at the time) and friends outside my team. I did meet an amazing number of people, but the other hindrance was that social networking was so stigmatized within the military still that no one would start using Facebook until they all (mostly) got out. Military folks aren’t always the most tech-savvy either.
Grad school was completely different. Before my grad program even began, I had started a Facebook group for us, and almost all of our new class had joined it before the first day even began — the rest would later join once they heard that Facebook and Google groups were how people were organizing/disseminating info. My friend count took off, since you meet so many people in school and are in the trade of ideas, partying, and conversations. I started using Twitter but even now only a limited group of my classmates have ventured onto it.
At my job, my friend count slowed down — but I think most jobs are like that. You meet your teammates and that’s it. You have to be in certain positions, like HR and executive-level and PR to be within the swirling eddies of social networking. It can be stultifying for professional growth to be in a job where you don’t meet many new people. It’s a virtual death sentence for people who are single and who want to meet potential mates in a peer environment instead of at bars or through dating sites, which work great in DC, but as Dan Ariely pointed out,
“The dating market is perhaps the only market that we moved from a centralized market to a decentralized market. You know, we used to have a yentl, your parents used to tell you what to do, all this is gone, now you have to fend for yourself. On top of that, we move a lot, right? You go to one place for undergrad, then you go to grad school, then you move to another city for a job, two years later you move again. You have no time to create a social network. We work long hours, so it’s really a system where we don’t have time to find people for ourselves. It’s taboo to date people at the work place, the social networks are weaker in the physical world. We move all the time and we don’t have a yentl or parents to tell us what to do.”
So you might be asking at this point, does it even matter how much interaction liquidity you have? I don’t think it matters for most people, but I do think it’s a valuable metric that may show larger trends.
For instance, what if you could compare companies and how much internal and external interaction liquidity they have? Would you work at a company that doesn’t seem to provide much liquidity for its employees? Could it signal dysfunction inside a company if it has fewer interactions/period than its peers? What about cities? Is it a desirable quality for a city planner to want to increase interaction liquidity? This would seem consistent with architects and designers in modern theory wanting to build spaces more conducive to public gathering, drawing people in instead of away.
Which leads us to…
Landmark Interaction Liquidity
There’s a key series of scenes in the movie Before Sunrise, that movie with Julie Delpy and Ethan Hawke which has NOT aged as well as its sequel, Before Sunset, that I think sums up landmark interaction liquidity quite well.
In short, the movie is about two people who meet up on a train in Europe and spend the rest of the evening and early morning falling in love while walking around in Paris. They visit different places in the city throughout their long date. But at the end of the movie, they part ways. It all concludes by showing all the sites they visited, as the sun comes up. The places, since it’s early, are all empty, and the scene which had previously been so intimate, private, and unique to the couple have resumed form as landmarks, placeholders, statues, squares, etc.
So it interests me that certain locations, over time, build their own interaction histories. In the same day, or even at the same time, different groups of people converge on those places and use them in different ways that are unique to the different parties. So at one moment here in DC, Dupont Circle may have a couple flirting with each other, a musician playing for on-lookers, some people meeting up after a bike ride, people playing chess, people on their way home from work, people eating a quick dinner, people reading on the lawn. This could register, say, 1,000 interactions in an hour. That space is continually transformed, re-used, and remixed over that time. This is immensely valuable for social interaction.
Certain locations take on a reputation. Dupont Circle for instance was used last month as venue to watch two World Cup games. In this case, it was being used as a shared space by many, many people to experience the same event. But each person had their own experience within it. And this is radically different than the epic snowball fight that took place in the circle this winter.
Is there a way to measure interaction liquidity for certain places? Some places do it, like measuring foot traffic at Grand Central or counting tickets at Nationals Stadium. Can we build a history for a place, which shows a list of interactions that have taken place there over time, searchable by # of people involved, observability (how many people witnessed it), importance (was it a political rally? did an interaction lead to socially-agreed positive outcomes like marriage?), etc.? I think we can. At the very least, we need the tools to develop these kinds of metrics, and the ability to define our own variables to build those metrics.
Reputation is too important in our daily lives for us to have not done more with it. Especially when it’s filled with our own individual biases and backed by little hard data and statistical analysis about what the reputations of people, places, and things actually are. When you start thinking about reputation and identity, you start to see it everywhere.