Life Optimization Theory and Quantified Self

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self improvement and self optimization via self-tracking personal analytics and quantified selfAfter becoming fascinated by the Quantified Self movement a couple of years ago, I have immersed myself in self-tracking, and have been using this blog to document my personal experiences and thoughts, and review different tools and measures that I tried. When I started this blog, the scope of topics was limited to physical and mental health and fitness, but this list has been growing since then. The objective of the Measured Me project has evolved and become more ambitious than ever. I am now searching for the best ways to measure and track as many aspects of my everyday life as possible. But what is it exactly that I am trying to achieve? What is the ultimate goal of this ongoing experiment? In this post, I will discuss the new raison d’être behind the Measured Me experiment –  theory of life optimization.

I believe that for the most of us, everyday life consists of the same routines and activities, and thus is pretty much repetitive and structured. As a result, it can be described in terms of structural elements which come from the finite ranges, and are often defined by the context of the situation in which we find ourselves at that particular moment. The most basic elements in this “constructor set” are behaviors and states, and anything else can be defined using them: goals (behavior or state, short-term or long-term), modes of operation to achieve those goals (behaviors and states, short-term and long-term), and even outcomes (behavior or state, short-term and long-term). For instance, situation {breakfast} can be described in terms of goals {state = satiety; state = optimal fat %; state = increased focus, etc.}, modes of operation {skip/eat breakfast; eat breakfast with certain caloric value; drink coffee, etc.}, and outcomes {state = satiety; state = 10% body fat; state = concentration 2X average, etc}. I also believe that only a finite number of these behaviors and states really matter. In other words, our everyday life can be reduced to a sum of most important life behaviors and states Yi.

Further, there are numerous internal (e.g., physiological, mental, or psychological states and traits, skills, habits) and external (e.g., social relationships, weather) factors that affect our everyday life by influencing those situational behaviors and states. Your current mood and weather may influence your productivity at work, and your social skills (including relationship with your boss) – your chances to get that promotion. While there are potentially thousands, if not gazillions of such factors, I also believe that only a limited number of factors actually have a significant and consistent impact. In other words, out of those gazillions of factors, only a small bunch of Xi actually matter. So ultimately, we can define life as a set of important variables Yi, and a set of factors Xi that influence those Yi. Theoretically, if I could determine what those Xi and Yi are, and how they are related to each other, by manipulating or at least accounting for Xi, I could potentially influence and optimize my Yi.

Now, I am not claiming this theory to be exclusively mine. What I just described has been known in philosophy and social sciences as a deterministic model: our behavior is driven and shaped by some predetermined factors, as opposed to free will. I won’t exaggerate if I say that social scientists have proposed thousands of causal models of internal or environmental determinants of human behavior. While I may not agree with most of these models, I do find the deterministic theory plausible, and would like to build and test a model of my own. Unlike most of the scientists, however, I think that the Xi and Yi, as well as the pattern of relationships among them vary considerably across individuals, and thus, cannot be generalized. It is possible that while MY life can be defined in terms of 46 Ys, each or some of them affected by 189 Xs, and none of these Y or X has any significant meaning or impact in YOUR life.

And this is where Quantified Self and self-tracking come in. The only way to find out which Xs and Ys define your life, and how they are related is by observing and tracking yourself. Sounds crazy? Ambitious? Impossible? Perhaps. For now, I know of only way to test this theory: using self-tracking, self-experimentation and personal analytics. And so Measured Me experiment continues. Stay tuned!

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10 Responses to Life Optimization Theory and Quantified Self

  1. David says:

    Extremely interesting!

  2. Rajiv says:

    I wonder whether you really want to “optimize” your life, or whether you’d be better off focusing on “resiliency”? If you want to try and ensure that your life goes on pretty well, coping well with a constantly changing environment, than you should emphasize resiliency (think of a Land Rover — works really well almost everywhere). If you want to have absolutely the best life given your current circumstance, than optimization would seem to be the goal, though you’re setting yourself up for a dramatic fall if conditions change significantly (think of a Ferrari — fantastic if all the conditions are just so). Given the vagaries of life, I think resilience is a better goal than optimization.

  3. Measured Me says:

    Hello Rajiv,
    Great point! You are absolutely right, increasing my inner strength would allow me to be independent of any changes in the external factors and the environment. I guess it depends on the “objective function”, or what i am trying to optimize, or maximize. I am thinking about shifting the focus away from the smaller things (e.g., productivity) to more fundamental like happiness and life satisfaction. And resiliency has been shown to be an important predictor and antecedent of the happiness.

  4. Eric Jain says:

    Small and unexpected things can have large impacts on happiness and quality of life in the long run (e.g. by reducing the risk of disease), and sometimes also in the short run (e.g. by mitigating existing medical conditions).
    Then again you might be happier if you stopped all the measuring and optimizing, and spent the time meditating instead. Of course you’d have to measure something to know for sure that you’re happier now :-)

  5. Jay says:

    This is ambitious – and it’s exactly the sort of higher level, conceptual thinking QS needs.
    The most valuable use of such a framework for me would be learning which Xs matter the most. Building a causal model is extraordinarily challenging though – even for social scientists who have large populations to observe.
    On the question of resiliency versus optimization – I think that’s a very good point. It reminds me of Nassim Nicholas Taleb’s idea of the “antifragile.” However, I think it can be resolved by incorporating “resiliency” as one of the Ys.
    I hope to see more exploration of this topic. Great blog.

  6. Measured Me says:

    Thank you, Eric and Jay,
    I am considering starting with just a few Ys. Perhaps, health (different dimensions) and happiness (different dimensions) will do for a start :)

  7. Miguel Elox says:

    Hey there Rajiv,
    as someone who thinks in terms of optimization most of the day, I completely get your point. For instance, when I can make the best meal choice at some given time I get excited and take pictures of it. If, however, my meal is suboptimal for any reason, I usually think obsessively about how I could have made it better. In this regard, a wise quote I once read has been very helpful: “Be content with making the best choice you canat any given moment”. Because indeed, when I’ve made poor choices, it’s been mostly because of enviromental constraints rather than internal/mental factors.
    The coolest thing would be to strive to be optimal WHILE accepting that some factors will always be out of our control (aka being resilient).

  8. Ruppel says:

    Not sure if you can control everything in this life. There are always random events can ruin your predictive models. But the concept is interesting, and I see how quantifiedSelf fits. would love to see formulas when you are done!

  9. Measured Me says:

    hi Ruppel,

    My theory is that even some random events can be predicted. I am currently tracking “entropy” -how chaotic and unpredictable was my day. Hopefully, there will be some interesting patterns!

  10. Anne Deuchar says:

    Interesting theory, that can definitely be empirically backed and tested by your own data.

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