Does QS techonologies end up creating norms (that could generate ethical issues)?

Hi everyone,

There is an ethical issue related to QS that I would like to raise. There is an ever-growing amout of data collected and shared by QS technologies. Don’t you think these technologies and this data end up creating medical / well-being norms ?

Are these norms relevant and trustworthy or is it hazardous to pay attention and follow them ?

What do you guys think ?


There are already norms for almost everything, but they’re often biased towards people with specific health issues, or based on small populations, and may therefore not be appropriate for everyone. See e.g. the controversy around vitamin D.

Thanks to the “ever-growing amount of data” we may be able to replace one-size-fits-all norms with recommendations that are relevant to the individual, and therefore hopefully less “hazardous” to follow…


One norm that comes to mind is 10,000 steps as an activity goal. It’s pretty clear that was just a round number that happened to be just outside the realm of many people’s everyday activity. So reaching it was an achievable stretch. But it wasn’t clear what hitting that goal was supposed to mean.

I remember seeing a flurry of articles earlier this year suggesting that the benefits (cardiovascular, I assume) dropped off after 7,500 or 8,000 steps. But that’s population level and doesn’t incorporate cadence.

These targets can be a challenge for some people with chronic conditions. At QS13, Jackie Wheelwright had a talk on figuring out what a good step target would be for her, that wouldn’t leave her with days of fatigue. I believe she landed on a number around 4,000.


That, plus the Japanese character for 10,000 resembles a walking person (万), which might have helped market a step counter in Japan the 60s :upside_down_face:

One concern is that people might not even try to get a little bit of exercise because they feel they can’t reach the “goal”, even though 90% of the benefit may be in the “little bit”!


I think the concern is not in the data, but in its interpretation.

“Bad interpretations” is an ongoing concern with data – and I think we can imagine (and have seen) various ideas and approaches to try to avoid them, and the potential risk vs. benefit in performing interpretation.

Relatedly… I think the potential for someone performing bad interpretation is, in my humble opinion, a poor argument against having access to the data. Indeed, I think more ready access and abilities to interpret data in different ways helps counter the risks of monolithically disseminated “bad interpretation” (by illustrating that other interpretations are available, and hopefully encouraging caution regarding faith in any particular interpretation).


I don’t think that QS technologies in themselves CREATE norms, but they CARRY them. Indeed, these norms already exist and are well established in our current society, the QS only reinforce them by giving them a regular aspect (daily, weekly, monthly).
In another hand I agree with you and I think norms created by data sharing may be a bigger problem. These are very subjective, depending on the individual’s data. The standardization of this data is less relevant and paying attention to these “norms” created by this data might be hazardous.

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