February, 2009

A little Twitter game: What’s the 4th Word?

February 23rd, 2009

Every day or so, I’m going to post to the @enjoymentland Twitter account a set of three words that hint at a fourth word (described in the post from a few days ago, Dress, dial, flower).  In the case of “dress, dial, flower” you would dm me back “sun”.

In the case of “sleeping, bean, trash” you would dm me with (hover for answer).

In the case of “loser, throat, spot” you would dm be with (hover for answer).

And the tough one from that previous entry was “man, glue, star” (hover for answer).

I’m thinking of building a quick iPhone app around this idea, but sort of want to gauge interest in the game first.  Also, I want to see if the accuracy (or number of correct answers) fluctuates much from set to set.

I will think about posting the winners, stats, and maybe any close answers right before the next set gets sent out.  Not sure yet.

So, if you’re interested, friend @enjoymentland if you haven’t already, and wait for the first game (or see if there have been any previous sets to play).

Locavore version 1.0 submitted to the App Store

February 21st, 2009

Just submitted my Locavore app to the iPhone App Store.  It will most likely be available in the next week or two.  To be notified of when exactly, follow @enjoy_locavore on Twitter.

So, as you most likely know, it’s an app that determines where you are, and then shows you what fruits and vegetables are in season where you are. And around that idea are a couple other interesting ideas:

  • Sorts fruits and vegetables by how much longer they’re in season, so you can appreciate the carrots, or whatever, now, before you spend the rest of the year without access to super fresh carrots.
  • Shows you farmers markets near you, thanks to the lovely cooperation of LocalHarvest.  They were kind enough to let me access their data, and I look forward to finding more things to do with it.
  • See a map of all the states a given food is currently in season in, thanks to Google’s awesome Chart API.
  • Browse by food (I have 237 different kinds in the database).
  • Browse by state to see what’s in season in other parts of the country (right now, we’re limited to US-only data).
  • Find out more information about any food with a direct link to the mobile Wikipedia page.
  • Find out what recipes are popular for a given item with a direct link to epicurious.com’s search results page (I do wish there was a more iPhone-friendly source for this).

All expertly designed by the very talented Matt Hickey.

Here are a few screenshots:

photo photo2

photo3

photo4

The interesting thing in my development of this app was that sometime last week I realized that the way I was building the interfaces wasn’t going to scale.  I was using Interface Builder to designe the table cells for various screens, and it turns out that this method of design doesn’t scale to tables that have a lot of rows.  And so my app became sluggish as a slug.

But after some internet research, I found an entry by the creator of Tweetie that explained in nice detail about how to speed up table scrolling.   A couple other entries that were useful were this one from stackoverflow and this one from rudis.net.  Most likely, if you aren’t an iPhone developer, you’ll have no idea what they’re talking about so there’s no need to click.  But in my slowly developing studies, I find articulate developers like these people invaluable.

Patterns of iPhone apps that I enjoy

I love collaboration. And this app in particular has been a great act of collaboration.  From Tattfoo who gave me permission to use the collection of colors that he collected from different fruits and vegetables.  To LocalHarvest (a wonderful site that’s 10+ years old and has the most comprehensive database of farmers’ markets in the US, and so much more) who opened up their data to be used in the spirit of increasing awareness of how to find locally grown foods.  To Google’s generous creation of map-making APIs and reverse geo-coding web services.  To the various sites and sources that gleaned data about what’s in season when and where.  To the stock photography websites that allow, in many cases, free use of beautiful images.  To Wikipedia for creating a beautiful mobile version of their site.  To the creators of iphoneonrails.com.  The only true contribution I brought to the table was glue.

I love simplicity. iPhone apps lend themselves to simplicity.  Do something simple, do it well, and do it in an aesthetically-pleasing way.  From the iPhone app itself, to the Objective-C programming language, to integration of Xcode, the iPhone Simulator, and Interface Builder, to the simple constraints of screen size, computing power, and human interest, everything about iPhone app development rewards the beauty of simplicity.

I love small projects. I love that one or two people can create an app.  It doesn’t take a team, or a company, to take on an interesting idea and make it happen.  $99 is all you need to get all the tools to build an app.  You don’t have to host the code, or find a way to charge for it, or find a way to sell it, or anything, really.  You build it, you upload it, you choose a price (or free), you wait for the reviews and feedback to come in and you continue to improve upon it.  It’s really truly amazing.

I created a new twitter account (@enjoy_locavore) to talk about news, updates, and whatever else Locavore related.  Add it if you want.  The twitter account is also built into the app so that users of it can always see what the latest developments are.

It’s such a tiny little world all to itself, and I hope that my little contribution to the idea of learning to enjoy food that is local is at least a little bit useful.

What could you do if access to space was as cheap and accessible as the Web is today?

February 19th, 2009

This is the premise of a genius massively multi-player thought experiment game invented by my idol Jane McGonigal, amongst others who I can’t quite determine, is to contemplate the answer to the above question.  We are in the future, we have technology that allows us to put cheap open personal satellites into orbit for $100, and we now need to figure out how this will change the world.

You get points for creating a forecast.  A forecast can be for a best case scenario or a worst case scenario.  For any given scenario, you can add on to it with further comments, a disagreement, an alternate forecast, or a question.  If your scenario leads to 10+ responses, you get more points, and if you get selected as a favorite forecast by the game designers, you also get more points.

It’s a very well-designed game, and has an interesting premise, and has true applicability to real life.  It’s awesome.

Here’s my profile badge:

And here are some of my favorite forecasts:

Okay, some of them are a little silly, but I actually think the time-capsule and weather decider ideas are pretty good. Overall, thinking about this on my walk home tonight, I realized that having a satellite is actually not that different from having an iPhone, or a website, these days. We have ridiculous amounts of information available to us cheaply and smartly, it’s just a matter of thinking big and figuring out what to do with it, right? Satellites, in this scenario, represent something that seems to be in the future, but actually being up in the sky isn’t going to give you a whole lot of advantage that we don’t already have. Google is in the sky for us, and they give us almost all of their data. What more do we need?

The great thing about this game is that it has a beautiful spirit and a beautiful execution. I honestly want to give it some forecasts that justify the effort that went into it. Thinking about the future is the first step in making the future, and I hope that the positive forecasts win out in the end. We need to remain optimists about the future.

Matt Webb re-publishing Carl Steadman’s 99 Secrets

February 18th, 2009

Matt Webb, another guy I’ve admired and followed for years, is always up to something new and interesting…

Carl Steadman opened my eyes to the possibility of narrative in new media with two pieces: Two Solitudes (1995), in which you would eavesdrop by email on a conversation between two lovers?, friends? becoming distant, over 30 days, and 99 Secrets which I first encountered in 2000.

You can read Two Solitudes online, though without the slow delivery and intimacy of the inbox, it loses much of its poignancy and involvement.

99 Secrets has similarly decayed. 99secrets.com, where you could click through 99 short snippets of conversation between an anonymous he and she, has been snagged by a domain squatter and is consequently no longer available in the Wayback Machine. (I’ve attempted to buy the domain to enable access to the cache again, but haven’t had a response to my emails.) It’s sad.

[...]

I’m posting Carl Steadman’s 99 Secrets to Twitter instead, randomly, roughly once a day: follow @to_no_one.

I’m definitely following, straight to the phone even.

We learn through our senses

February 18th, 2009

Is it possible that one of the reasons we have such difficulty with knowing our own minds is that we are visual learners, auditory learners, and tactile learners?  The sightless, soundless, textureless nature of our own personalities and brains makes it difficult for our sensory-driven form of learning to find anything to grasp on to.

From an educator’s perspective, which learning style would be best suited for introspection in a sensory-deprived learning environment?

Pattern #1 – Study your mistakes

February 18th, 2009

Merlin Mann has me thinking about patterns for creativity. Then, the other night at Jonah Lehrer‘s talk, someone from the audience asked him if he had applied any of his learning about decision-making towards influencing his own life. The joke was whether he had begun to give his hypothetical 3-year old child random rewards, since we know those are most likely to trigger our dopamine reward buttons the most effectively. Hypothetical child aside, he said that the main new practice he had begun in his life, which is only tangentially related to decision-making and creativity, is to study his own mistakes.

He mentioned how some of the most skilled and productive people he knew were diligent studiers of their own mistakes… from football players to public speakers to people in any area of performance or skill-based work.

Fast-forwards the learning process

If random rewards are known for their ability to give us little jolts of enjoyment, like candy for the brain, random punishments are even more powerful.  Most of us have very strong loss aversion (wikipedia) and feel more pain at losing $10 than winning $10.  This helps keep most of us out of the casinos and out of other risky situations.

Studying mistakes is like self-surgery — a delicate procedure

However, most of us don’t use this to its full advantage, knowing also that making mistakes is a frustrating and sometimes humiliating feeling.  The key is to find that balance between acknowledging your mistake and taking it as a personal hit against your own self-worth.  The touchiness of this exercise probably explains why this pattern isn’t used very much.  Assuming you can find your own way into this tangle, the value will more than pay back for the effort.

Balances the ego

The ego has no problem seeking out ways to make itself stronger.  And yet, a balanced ego that has love for itself as well as love for others is the healthier route to take.  Finding healthy ego-weakening exercises isn’t an easy task though… studying your own mistakes, without broadcasting or glorifying them, could do the trick.  On the other hand, if your ego is down in the dumps and can barely look itself in the eye without feeling contempt for itself, this pattern is probably not the first pattern you should adopt.

How to practice this pattern

1 – The first task is to become more attentive and accepting of mistakes.  Our tendency is to spend so much time hiding our mistakes that we can often trick even ourselves into thinking that a mistake isn’t a mistake.  This is perhaps the most difficult step in the pattern… becoming mindful of your mistakes without leveling harsh judgment on yourself is a pretty powerful skill.

2 – Assuming you can discover, acknowledge and accept a particular mistake, the next step is to figure out why the mistake happened.  Was it an error in intention (did you have the wrong intention?) or an error in execution (did you choose the wrong way to bring the intention to fruition?) or an error in results (did something unexpected turn good intentions and good actions into the wrong result?).

3 – Depending on where the mistake has occured in the anatomy of the full event, you can then determine if there’s anything to learn from it.  Often, there may be nothing to learn from it, especially if it was an error of innocence where a previously unknown element surfaced and produced unpredictable results.

Caveat: Don’t try to learn too much about your mistake simply for the sake of creating new rules.

Note that this pattern isn’t about learning from your mistakes, but simply studying them.  Becoming aware of them, accepting them, shifting them in your hands like a hot coal until it cools down, and setting it on the ground.

Dress, dial, flower

February 16th, 2009

The poorly named, but well-acronymed, “compound remote associate problem” tests were coined by some dude in the 60s. They were sets of three words that have some fourth word in common, like:

sleeping

bean

trash

They flashed on the screen for 2 seconds, 7 seconds, or 15 seconds, unless you could hit the space bar and say “bag” before time ran out.

These problems are interesting because they aren’t that difficult, and yet the optimal play strategy is to get your mind into a loosey goosey state, where it’s open to insight and creativity. To go about it rigidly and in an analytical manner will almost always take longer than 2 seconds, and often times longer than 15 seconds, but the subconscious, when primed and ready, can be a lot quicker than that.

Looking around the Internet, I found a few old articles in Google’s cache (because the originals have long since fallen off the web for some reason), that have hundreds of these three-word sets with their answers and results from various studies on how long each set took to complete on average.

loser

throat

spot

I really like sets of words like this. They capture the creative spirit to me, and are like little bits of enjoyment candy since the brain loves finding loose connections.

If I have some free couple hours in the next week, I’ll think about creating a tiny website to host all of these tests for people to take, timing their answers, etc.

It’s a good way to start the day, by loosening up the mind.

man

glue

star

Measuring moods might make the moods being measured even richer

February 13th, 2009

circumplex

If you have the time, and are interested in the idea of self-tracking, in particular the tracking of your own moods, I highly recommend this latest post from Quantified Self: “Measuring Mood – Current Research and New Ideas“.

Can you be happy and sad at the same time?

The first half of the article talks about one of the controversies in monitoring mood… can you have more than one mood at a time?  Do moods have opposites?  If you watched the TED talk by Matthieu Ricard that I mentioned a few days ago, you’ll hear him mention what I believe to be a core tenet of Buddhist thought… that you are able to balance emotions, that opposite emotions can’t co-exist.  That, by practicing compassion, emotions like anger, fear, and insecurity are by definition expunged from your brain.

The article mentions a few conflicting reports, but settles on the conclusion that of course you can be both happy and sad at the same time.  The end of a wonderful visit with long-time friends, for example.  Or, the feeling of pain in your legs at the end of a race that you just won.  It seems that pleasure and pain can not only intermingle, but enhance one another.

In my own personal life, the closing of McLeod Residence was bittersweet… to realize that so many new friends had been made, and yet also feeling like the ground was shifting under our feet and that things would never be exactly the same.  But that’s okay.

What happens when you measure moods?

The end of the article makes a great point, which I’ve never explicitly thought about before:

Barrett’s theory of emotion opens the door for another type of self-tracking than is permitted by the circumplex, tracking that asks questions like: How many emotions do I have? What is the range of my emotions? Do I meet various experiences with well tuned emotional responses, or have my feelings become rigid and stereotyped? Her paper suggests that we can improve our emotional structure, increasing the  granularity of emotional experiences by enriching our vocabulary and learning to apply it to previously unnoticed patterns in affect and context. (I am assuming for the moment that a more complex structure of emotion is a good thing. This could be questioned. But the first step in any case is mapping our emotional architecture.)

Perhaps simply by measuring mood, and delving deeper and deeper into our understanding of our own emotions, we can cultivate richer emotional experiences.  The same way that by studying wines, or beers, you begin to appreciate the more subtle characteristics, and love them all the more, by studying mood and emotions we can appreciate even the tiniest shifts in mood, and become experts in our own palatte of emotions.

A new goal

The new goal in my own self-tracking experiements is going to focus not on measuring moods, but in how to make them richer.  Not in suppressing or canceling out moods, but in experiencing them for all that they are, and appreciating them for the complicated ways of thinking that they represent.

Google Chart API enjoyment

February 12th, 2009

There’s this little pie graph I want in my app that looks sorta like this:

chart

Basically, it’s gonna be a stopwatch-like graph that tells you how much time is left for a particular food in a particular location.  In this case, the pie would represent 1 month left.  It’s convenient because there are 12 months in a year, 12 hours on a clock, etc.  I can color the pie slice differently when it’s nearing its “out of season” time (as is the case here, so the slice should be a red-ish color in the final deal).

Easy enough, right?  I told Matt, the guy who’s generously helping me design this, that I could make the pie charts with Google’s chart API.

The chart API takes data, like (1,11) to represent the amount that’s colored one color versus colored another.  But, unfortunately, the chart’s default orientation is at 3 o’clock.  To rotate the chart, you supply it with a number in radians.  So, after some research in radians, I determine that to rotate the slice 90 degrees clockwise, I give everything a radians of 4.712388975.

Unfortunately, that aligns the wrong side of the pie slice.  Making it look like this:

chart2

So, now I need to figure out how to rotate it to the a little bit less than the default offset.  Since I’m making one of these for each half-increment of a month, I’ll need 24 slices. So, each half month has its own correction of

1 radian * 15 (degrees) = 0.2617993875 radians

Each with a different radian correction to the offset.  Or, rather, for each increment,

(default offset) – ((half month correction from above) * (number of half months))

So now I figure this all out in a Google Docs spreadsheet.

And for some reason, I find the whole process highly enjoyable.

Why?

Also, now that I’ve got this spreadsheet open, I’m interested in using this information to help determine the colors used for each slice.  I have some colors that have been sampled from actual foods in nature and wonder how I might use math to simulate the changing colors of the season.

But I’m going to leave that for tomorrow because I want a drink right now.  I feel like I’m in that weird nerd limbo… nerdy enough to come up with a really convoluted way to get something really simple, and yet still not nerdy enough to come up with the really easy way to get something really simple.

Credit Card Roulette, my first iPhone app

February 11th, 2009

How I learned

Back in July, I decided that I needed to learn how to make iPhone apps.  I had a trip planned to NYC for about 10 days as a vacation of sorts while Kellianne worked at her salon there (Space, highly recommended).  We were staying at Rick Webb’s house, and there’s this great cafe down the street from his place called 88 Orchard.

For those 10 days, I basically worked in their little basement and learned how to make iPhone apps (which required learning a bit of Objective-C, and general app development since I’ve only ever done web development).

It was frustrating, but also great, to learn something completely new to me from a cold start.  I had the time and determination to build something simple and make it go all the way to the App Store.

What I came up with back then was an app for a game we play at the Robot Co-op every day at lunch (which we learned from Jason Fried of 37 Signals when he came to help us design the first version of 43 Things).  Literally, every day for the last 4+ years, at the end of lunch, since we learned this game, we put our credit cards in a pile, and someone holds them under the table and picks one out of the bunch.  That person pays for the whole meal.

This game is great for a couple reasons.

  1. It’s fun
  2. It simplifies the paying process
  3. Superstitions sprout up around it

Any game that has these qualities (substitute the paying process for any other social activity) is a favorite of mine.

My first iPhone app

itunes-1

Luckily, the game is simple.  You choose players from your phone’s contact list, and then randomly reveal who is paying the bill.  The suspense of displaying people who are NOT paying the bill one at a time is an essential element of the game, because you can feel possibilities and statistics shift subtley in your fingers.

The app adds the ability to keep track of who pays for lunch the most often, and also tallies who is above water and below water in the random distribution of lunch payments.  A favorite motto of ours is, “The game is fair, as long as you play an infinite number of times.”

So, after my 10 days of development (which I wrote about more extensively on my 43 Things goal), I finished off a few details back in Seattle and submitted it to the App Store.  It eventually showed up and I think I sold like 10 in the first week!

I was stoked.  Unfortunately, the App Store doesn’t really make it easy to track sales (you have to download text files for each country each month and import them into spreadsheets… just about 3 steps too many for me to care).

I just checked it again for the first time in 3 months and saw that I’m still selling a few apps every once in a while.  I’ve almost made it to the minimum payment threshold for them to actually pay me!

image

So, while I’m not gonna quit my day job anytime soon, it’s cool that somehow people keep finding this app and continue buying it.  It’s even been reviewed by a guy named “poopsack” to say that “this should be free”.

For me, I’m just glad that it’s useful enough for us to use at lunch.  Build what you want to use, right?  And anyway, holding the cards under the table is just too much of a hassle, and looks suspicious to the waiters.

It’s $0.99 if you think the game is at all interesting.  I’m planning on adding a few more features… most importantly the ability to share data on the web.

Matthieu Ricard on Sustainable Happiness

February 10th, 2009

A person at last night’s talk brought up Matthieu Ricard, a recent TED speaker, in relation to how meditation is related to decision-making and emotions.

I listened to the TED speech and wasn’t very impressed.  Certain Buddhist philosophies simply rub me the wrong way, even though I agree that they’re effective methods for learning to train the mind to be less reactive.

Before I go into what I disagree with (as that will take more preparation), here’s something I agree with from a recent article on Sustainable Happiness:

Human qualities often come in clusters. Altruism, inner peace, strength, freedom, and genuine happiness thrive together like the parts of a nourishing fruit. Likewise, selfishness, animosity, and fear grow together. So, while helping others may not always be “pleasant,” it leads the mind to a sense of inner peace, courage, and harmony with the interdependence of all things and beings.

Afflictive mental states, on the other hand, begin with self-centeredness, with an increase in the gap between self and others. These states are related to excessive self-importance and self-cherishing associated with fear or resentment towards others, and grasping for outer things as part of a hopeless pursuit of selfish happiness. A selfish pursuit of happiness is a lose-lose situation: you make yourself miserable and make others miserable as well.

This passage basically says to me that happiness is a quality of community rather than individuality.  That the non-zero sum game is the key strategy for happiness.  And I generally agree with that.  Those who take the selfish strategy in the Prisoner’s Dilemma may make short term gains, but will not outlast other more cooperative players.

Consider this as a starting point for my longer goal of exploring the differences between enjoyment, pleasure, happiness, hedonism, lack of suffering, Buddhism, cooperation, and shared experience.  They’re all tied together, and I want to meditate on their differences and subtleties in a loosey goosey manner that goes to the very inspiration for me to start this blog in the first place.

A couple friend charts

February 10th, 2009

Here’s a Venn diagram displaying the overlap of my Facebook friends, my Twitter friends, and the percentages of each that I’ve met in person:

Intersection of Facebook friends, Twitter friends, and people I've met in person

After a bit more work, I put together this rather difficult to decipher chart that shows overlap between all of the various categories.

Anyone who can figure this one out...

Each bar in the chart represents the % of group A that are in group B as well.  So, for example, on the left of the chart you can see that out of everyone on Facebook, I’ve seen about 52% of them in the last year.  However, if you look under the “Seen in last year” column, you can see that of all the people that I’ve seen in the last year, 90% of them are on Facebook.

Note: the sets of “Met” and “Seen in last year” are not comprehensive, but only include people who are also on Facebook, Twitter, Livejournal, Flickr, or in my phonebook.

In any case, I mention this because I think it makes a good argument that when you have 665 friends on Facebook that it represents a group of people that are not in any way analog to your friends in real life.  Jonah Lehrer argued that we may even have less than typical empathy with our online friends.

I think that this project, for me, is revealing that my “online friends” simply represent a broader slice of people that I know, including my baker, my lawyer, my conference friends, my highschool friends, etc.  It’s not a qualitatively different circle than the normal circle of friends, it is simply the first time we have a way of visualizing the size of all the different people we run into during life and have brief (or strong) relationships with.

Becoming sensitive to your own hands

February 10th, 2009

8:36pm Jonah Lehrer at Town Hall. Loving it!

I saw Jonah Lehrer speak last night at Seattle’s Town Hall and got to learn a bunch of new stuff about decision making, one of my favorite topics of study.

I will most likely be referring to notes I took during his talk for several posts this week, but I wanted to first comment on what I thought was the most interesting “actionable” take-away from his talk.

He referred to a study I was familiar with regarding people who were confronted with 4 decks of cards of subtley different quality.  Turning over cards in each deck would tell you to gain or lose a certain number of dollars or points.  The goal of the game was to turn over enough cards to know which deck was stacked to be the “best” in return.

On average, it took about 50 card turns for most people to determine the best card deck.  However, they were also hooked up to stress sensors on their hands, measuring the alkalinity of the surface of your palms.  It turns out, your hands became “stressed” when choosing cards from the wrong deck after an average of 8 cards had been turned over.

In other words, our hands (in this case an extention of our subconscious) is about six times faster at finding patterns than our conscious minds.

Poker players, therefore, are encouraged to become students of their hands when playing a game.

Our subconscious is great at finding patterns where patterns exist.  Especially really complicated patterns (as our conscious minds are also good at finding simple patterns, just not as good).

Something we can do

First we should know that our subconscious minds, and our hands, are only going to be able to find patterns where patterns exist.  For example, in card games.  They will NOT help you play slots, or other games of chance.  Perhaps the stock market is sufficiently complex and pattern-driven to benefit from our hands?  Perhaps studying statistics, metrics, and such are another relevant field.

Second, we should become students of our stress responses in situations of extreme complexity.  I almost think some small startup should help devise a stress-sensing ring.  A modern mood ring that responded to alkalinity on our hands.  Until then, though, simple awareness is the trick.  I’m not even sure I can tell when my hands are sweaty with any consistency… so I have a long journey ahead of me.

Any tips or tricks along these lines would be appreciated.

Distribution of friends found online

February 7th, 2009

My Friendsheet project is a part of my general self-tracking goal.  Over the last couple months, I’ve been working on collecting all of my friends on Facebook, Twitter, and Flickr, deduping them for duplicates, and then slowly going through and flagging them for various different shared qualities.

The distribution is pretty much believable, considering that I had friended about 635 people on Facebook at the time that this was begun.  It makes sense that I’ve eaten with 31% of the people but have had only about 13% of the people over to my house.

I’m going to continue adding new categories to this until I feel like I’ve covered enough to move on to the next step in the project.  A few axes I’m considering: talked to on the phone with, IMed with, met parents of, and given a present to.

The next step is going to be to come up with a couple different ways to visualize this, more as a distribution of similarities, and less as info-graphic.  I love taking data like this and abstracting it out so that the information is gone, but the patterns remain.

History of my self-tracking

February 7th, 2009

I have been interested in self-tracking ever since I started posting links to the Internet in 2002, when I attached a + or a – to each link depending on its impact on my morale.  It turns out, whatever makes me want to post a link to something also tends to impact my morale in a positive way, and so my first Morale-O-Meter almost always showed my morale as 10 (tracking the last 10 links posted).

Later, around 2005, I started a more general Morale-O-Meter that allowed me to rate my morale each day from 1-10.  In addition, I also counted the number of alcoholic drinks and caffienated drinks I had, the number of hours of sleep, and my general “health” (1-10, 10 being healthiest).  It created a graph that looked something like this:

morale

The coincidence of this graph was that all of the inputs could be displayed on the same 1-10 scale, and so it tended to make it easy to believe that the inputs could in some way be correlated.  After doing this for about 3 years though, except for minor correlations between number of alcoholic drinks and amount of sleep, there were no deep insights.

I eventually opened this up to anyone who wanted to track along these same 4 axes, which was mildly successful and interesting, but I never really wholly supported the idea because for some reason I didn’t think that these particular numbers were going to ever lead to an epiphany.

The reason I am obsessed with self-tracking is because I think there is a way to track yourself in such a way that it leads to epiphanies about yourself, about the cause and effect of things, in such a way that these numbers would eventually be able to tell you things about yourself that you didn’t already know.  This is the only reason to self-track, in my opinion.

Growing popularity

Over the last couple years, self-tracking has gotten a lot more attention and interest.  Blogs like Quantified Self have been highlighting a number of different ways that self-tracking is taking off. Sites like Daytum, Me-trics, and Happy Factor are making it easier and easier to join in the fun.

The biggest hurdle to self-tracking is motivation.  By making it fun (and in some cases social), the hurdle comes down and more people are able to enjoy the benefits.

Fitness Functions

A fitness function is, I think, the thing that self-trackers should strive for.  From Wikipedia: “An ideal fitness function correlates closely with the algorithm’s goal, and yet may be computed quickly.” In an abstract sense, fitness functions handle any number of inputs, and output a number that is correlated with the overall fitness of the inputs.  For example, a simple one might be adding (hours of sleep + morale + health – alcoholic drinks).  Some people might say that as that number goes up, so does the overall fitness of the person.  Of course, there are flaws… for example, sleeping 24 hours a day would give you a pretty high score, but would generally result in a pretty unhealthy lifestyle.

So, you’d have to perhaps grade sleep based on how close your sleep was to 8 hours a night.  And, maybe allow one or two alcoholic drinks as healthy, with a penalty for going over that.

And maybe simply grading “health” is too abstract to really rely on, maybe it should track your blood pressure, heart rate, number of times you exercised, glasses of water, etc.

You can see how the fitness function can get a little crazy.

Game-ifying life

A fitness function that was both well-designed AND within reason in terms of amount of effort required to gather the data (that’s where the “gathered quickly” part of the Wikipedia quote becomes relevant) would be highly valuable.  It would give you a score, and a score would allow you to attempt to optimize it.  The fact that the fitness function in some ways obscures the inputs is also helpful in the sense that it makes it more difficult to explicitly “game”.

My Fitness Function

I’m still balancing on that thin rope between finding the right inputs, the right tools, and the right reasons to continue self-tracking.  Right now, Happy Factor is the only publicly available tool I’m using regularly.  I am hoping that they allow export of data in the future, as it’s pretty silly to have that live on a server somewhere in a way that can’t even be shared with friends.

At the same time, I’m working on my own personal fitness function in a Google Docs spreadsheet.  I input my weight, stress levels, exercise, and completion of a number of personal goals (like hosting potlucks, working on my iPhone apps, cooking, talking with family, etc) and have each input go into a formula that outputs a 0 or a 1.  For example, if my weight is within my goal weight range, I get a 1.  If I exercise more than once a week, I get a 1.

This then all gets added up on a weekly basis and graphed into something like this:

weekly_scores

I’m still adjusting it week by week, and hope that eventually it will be possible to actually trust the output of this fitness function to relate my true fitness in life.  The goal being a well-balanced, healthy, creative life shared with family and friends.

It’s definitely a work in progress.