I’ve been thinking about the actual mechanics underneath a system of limitless personal data inputs. What relevance do different data fields in your life have with each other? Take, for instance, the number of hours you’ve spent playing a guitar, and then comparing that against the number of women you’ve dated. What is the common factor? Would there ever be any correlation between the two? Perhaps women like a man who can play a guitar, so therefore you might want to play a guitar in order to get more chicks. Or perhaps there’s something about the culture of playing a guitar (i.e. being in small groups of friends) that facilitates emotional relationships.
These are interesting (but perhaps statistically untestable) hypotheses that I am more than happy to let Galapag.users play with, experiment upon, and debate with each other about. While I am interested in providing the tools to let Galapag.users interpret their own data however they want, I also know there must be a ubiquitous economic formula or standardized measure within each of the formulae that Galapag.users will create.
It will include some function of attention and time. That is, peoples’ attention given towards a certain activity, or towards tracking that activity online (a statistical bias in itself, perhaps), is paramount towards determining what value someone places upon an activity or a subject, but it is not the ONLY measure. Time perhaps is a more neutral unit of measure. Despite our very different lives, varying deeply not only from person to person but also from tribe to tribe and country to country , we are all dealt with a hard-coded limit of 24 hours in the day.
A large part of that day is spent sleeping (we cannot track quality of sleep yet, but I’d love to have the ability to), but unlimited permutations of how other activities are mixed into the rest of the day reflect our individual uniqueness and personal interests. As an example, the average hours of sleep per night in the US seems to be about 6-7 hours, while it is recommended that they get 7-8. Some people may sleep on average more, around 9-10, while others who have a lot of work to do may get as little as 5-6. Coders certainly may go on long stints without any sleep at all if they’re in the middle of the coding zone on something they’re engaged in.
But you can extract some fairly accurate time-value pictures of people based on how they compose the activities in their days relative to how long that activity takes. So therefore if you spend 5 hours a day in the gym and working out, probably because you are an athlete, it goes to say that you exceed the average and value that aspect of your life quite a bit. It’s also likely that you spend a lot of time also on your eating habits and diet. But not necessarily. It could be a symptom of some self-image problem. Or maybe it’s a short-term program, not indicative of your life-long patterns. It might be that you spend much of your day doing the wrong thing for you (addiction, bad job, family problems), so in that case your numbers will not represent themselves the same way they would for someone else who doesn’t have those issues. It might be that the summation of activities you do in a day exceeds 24 hours, because you’re capable of multi-tasking.
Thus this gets complex quickly. But expecting the amount of time you take versus the average, per day, on certain activities is a rough way to gauge the value you place on those things. Time, not just over a day, but over years and paying specific attention to how different key events (marriage, divorce, children being born, graduations) affect your patterns would become even more fascinating.
Attention and time belong in a function together. You might be fully engaged into a hobby, relative to others, but it might be that that doesn’t really eat up a lot of your time. This would be akin to Malcolm Gladwell’s positing that his 10,000 hours need to be active, fully-focused practice and not just 10,000 hours of hanging out at the tennis court chatting while playing a little bit.
These two data points (attention being harder to quantify) will provide the grounding for the rest of the data within Galapag.us formulae.
I think ultimately that these time-value formulae are akin to productivity calculations, which seem interesting when compared across nations. Western Europe seems to take a lot of vacation time, while Americans take little at all. Relatively speaking (compared to, perhaps, GDP/capita), who is more productive? While we can look at our own personal productivities relative to each other, what will it look like when we compare across nations using the Galapag.us dataset? Can we tug out interesting observations about the value of time and attention? Can we employ such data towards strategies for increasing human capital and youth development in developing nations?
Do you have any ideas about how to proceed with these measures of value?