Quantified self

Quantified self (also lifelogging or just QS) is the process of systematically collecting and analyzing data about oneself in order to improve one’s life. In other words, it is self-improvement through self-knowledge through self-tracking and self-experimentation.

Quantified self is not usually discussed in the context of effective altruism, but the basic idea falls under the umbrella of self-improvement (which encompasses ideas such as Lifestyle improvements, improving rationality, etc.).

In terms of a cause, quantified self has several approaches:

  • Increasing awareness of quantified self and getting more people to record various aspects of their life for the purpose of self-improvement.
  • Improving data collection tools so that self-tracking and self-analysis is easier and encompasses more aspects of one’s life.
  • Improving data analysis tools so that collected data can more easily be visualized or so that a broader synthesis of the data is possible (e.g. through machine learning).


The arguments for the importance of the quantified self (QS) can be most generally divided into two categories: first, arguments which focus on benefits to the person quantifying themselves, and second, arguments which focus on ways in which people other than said person benefit from accessing that data. The second category can be perhaps more succinctly phrased as ‘benefits arising from open access to QS data’.

Benefits to the person quantifying themselves

  • A person’s level of alertness experiences natural variation throughout each day. QS combined with statistical analysis would facilitate the identification of habits that maximize or otherwise optimize the duration and periods of time when they are most alert. The same applies to “environmental perturbations” that affect productivity. (The importance of this increases commensurately with the productivity of any given person.)

  • Quantifying the returns on time spent on various tasks would allow people to more easily identify areas in which they have or do not have a comparative advantage, allowing them to better optimize usage of their time.

  • Possible entertainment from tracking and visualization. As Bryan Caplan says, “People may be misled by entertainment that falsely purports to be factual. But they’re not mistaken about how entertained they are.”

Benefits to others

  • Being able to correlate website browsing data with IQ has many potential applications. In particular, knowledge of which websites highly intelligent or highly accomplished people visit on a frequent basis could be of significant interest and value.

  • Openness about productivity (e.g. if people posted RescueTime logs online) could inspire people to pursue more productive paths or weigh productivity (in a general sense) more in their decisions of what paths to pursue. For people of extremely high intelligence and ability, time is the most important and crucial resource available to them, so inspiring them to focus on productivity could benefit both themselves and the population as a whole.

  • David Kirkpatrick writes in The Facebook Effect (p 199):

    “Having two identities for yourself is an example of a lack of integrity,” Zuckerberg says moralistically. But he also makes a case he sees as pragmatic—that “the level of transparency the world has now won’t support having two identities for a person.” In other words, even if you want to segregate your personal from your professional information you won’t be able to, as information about you proliferates on the Internet and elsewhere. He would say the same about any images one individual seeks to project—for example, a teenager who acts docile at home but is a drug-using reprobate with his friends.

    Zuckerberg, along with a key group of his colleagues, also believes that by openly acknowledging who we are and behaving consistently among all our friends, we will help create a healthier society. In a more “open and transparent” world, people will be held to the consequences of their actions and be more likely to behave responsibly. “To get people to this point where there’s more openness—that’s a big challenge,” says Zuckerberg. “But I think we’ll do it. I just think it will take time. The concept that the world will be better if you share more is something that’s pretty foreign to a lot of people and it runs into all these privacy concerns.”

  • Ryan Fuller, co-founder of VoloMetrix, writes for Wired about quantified self and people analytics:

    [A] report published recently by the World Economic Forum [suggests] that increased connectivity through new technologies and big data could result in $14.4 trillion of added value across global industries. These commercial gains are driven by the opportunity for improvements in employee productivity, asset utilization and innovation.


    People analytics and daily performance feedback technologies will essentially transform how organizations understand time investment and forecast performance. With data collected from these technologies, businesses can begin predicting employee performance and attrition based on their own internal data.

  • Josh Bersin for Forbes:

    Ultimately this is a very good thing. Remember that employers already have plenty of data about all of us: our job history, employment history, salary, performance evaluations, and when we clocked in and out each day. If companies start using this information to improve the workplace, we’ll see better management, better hiring, and improved workplace conditions.


    I know these tools will raise many issues about data ownership and workplace privacy. But we already give up much privacy to companies like Google and Facebook so in most cases these tools are just extensions of our consumer life every day.

  • SFGate article by Cory Weinberg:

    Ethan Bernstein, an assistant professor of leadership at Harvard Business School […] has studied the “transparency paradox,” which says that production in the workplace can slow down if employees know the bosses are watching. “It will be much harder to see if these are actually improving productivity or if, because people change when they’re watched, they produce a different outcome,” he said.

    There seems to be an online draft of the referenced study.

  • From “Unblinking Eyes Track Employees” by Steve Lohr in the New York Times:

    The payoff for well-designed workplace monitoring, Mr. Waber [of Sociometric Solutions] said, can be significant. The underlying theme of human dynamics research is that people are social learners, so arranging work to increase productive face-to-face communication yields measurable benefits.


    The researchers [paper] studied the data on all transactions and patterns suggesting theft, before and after the software was installed, at 392 restaurants, in 39 states. The savings from the theft alerts themselves were modest, at $108 a week per restaurant. More startling, revenue increased an average of $2,982 a week at each restaurant, about 7 percent, a sizable gain in the low-margin restaurant industry.

    Servers, knowing they were being monitored, pushed customers to have that dessert or a second beer, which resulted in the increased revenue for the restaurant and tips for themselves.

Privacy concerns

See also Digital rights.

From “5 Major Takeaways from the Quantified Self Conference in Amsterdam”:

As more personal data is collected, ethical questions arise. Information that is near and personal—about our health, relationships, and emotions—is now available to more and more people. Are we comfortable with large corporations mining that data to serve us ads, or insurance companies to adjust our premiums, or our employers to monitor our health?


Rudimentary self-tracking is already possible. Because QS has various approaches to it (popularizing it, developing software and hardware to make it easier or more insightful), tractability of QS depends on which approach we are considering. In addition, tractability in each approach also depends on which metric we are considering. For instance, when popularizing QS, it’s probably easier to get people to start tracking their computer use through e.g. RescueTime (since this is automatic) than it is to get people to manually record their eating habits.

From NBC News:

The problem is people often abandon, lose or break their fitness trackers pretty regularly. In fact, around one-third of wearable owners abandon them in within six months, according to a report from market research firm Endeavor Partners.


The only real numbers that seem to available on this are from Pew Internet Research, related by an article on QuantifiedSelf.com:

  • 69% of adults track a health indicator for themselves or others.
  • 34% of individuals who track use non-technological methods such as notebooks or journals.
  • 21% of individuals who track use at least one form of technology such as apps or devices.

See also