Scientists beginning to tap the research potential of the quantified self

Big Data Evangelist, IBM

Real-world experiments don't get more real than when you apply them to yourself.

It always blows my mind to read of biomedical and other life sciences researchers who primarily experimented on themselves, while still being able to collect objective measurements. Such was the case with the recently departed Alexander "Sasha" Shulgin, who synthesized many psychopharmacological potions, including the compound best known as Ecstasy.

As his Wikipedia entry states, Shulgrin expanded his (legal) self-experiments to his social group: "After judicious self-experiments, Shulgin enlisted a small group of friends with whom he regularly tested his creations, starting in 1960. They developed a systematic way of ranking the effects of the various drugs, known as the Shulgin Rating Scale, with a vocabulary to describe the visual, auditory and physical sensations. He personally tested hundreds of drugs.....There are a seemingly infinite number of slight chemical variations, which can produce variations in effect—some pleasant and some unpleasant, depending on the person, substance, and situation—all of which are meticulously recorded in Shulgin's lab notebooks. Shulgin published many of these objective and subjective reports in his books and papers."

Real-world experimentation of a very personal and hyper-analytical nature is what the quantified-self (QS) movement is all about. It would be a stretch to call Shulgrin a QS pioneer, given that his focus was more on gaining objective scientific knowledge than on pushing his own mind and body to the limits. By contrast, the focus of most QS practitioners is largely on self-tracking for self-centered reasons (for example: boosting their own personal health, wellness, fitness, athleticism, sexual performance and so forth). In a sense, most QS, as practiced today, is a bit closer to the Timothy Leary brand of pharmacological self-experimentation than to Sasha Shulgrin's.

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Image courtesy of Openclipart and used with permission

But, self-indulgent as most QS is, it still skirts the edges of scientific discovery. That's because QS practitioners are playing with approaches that behavioral scientists have traditionally applied to third-party subjects within controlled laboratory experiments. By that I'm referring to real-time sensors, biofeedback mechanisms and behavioral-modification tools. Or, as this recent article puts it, QS is "a systemic monitoring approach where an individual's continuous personal information climate provides real-time performance optimization suggestions." You might even think of it as a personal application of "next best action." 

However, the scientific establishment is beginning to realize the potential of quantified self tools for gaining primary data directly from human subjects in a way that is organic to the biological, behavioral and psychological phenomena being studied. As the cited article notes, professional scientists in many fields (biology, sociology, genomics and so on) are starting to take an interest in QS, both in controlled experiments and in crowdsourcing initiatives, to provide a new source of data that they may have been unable to collect heretofore.

People will choose to participate in these QS-aided scientific studies for a variety of reasons. Some of the reasons will be entirely self-centered: they're being paid to self-track. But some will be more altruistic: they want to contribute their self-data to a research project that addresses some burning scientific issue, such as whether certain lifestyles under certain circumstances have beneficial or detrimental physiological impacts.

Whatever their reasons for participating in QS-aided studies, people who do so will be pushing a new frontier in scientific research. They will be forever blurring the boundaries between laboratory and field research in the biological and behavioral sciences.

In the future, every human, in fact, every organism to which a sensor can be attached or embedded, will be capable of feeding real-time, objective performance metrics into scientific data repositories. And that, in turn, may hasten the advent of a new era of scientific discovery in a wide range of disciplines whose subjects can be equipped with the innovative new tools of QS.