Wisdom of the Crowd
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In Ancient Greek, the word “doxa” refers to a generally accepted belief or opinion within a particular group.
This term is often used as a counterbalance to the concept of “epistêmê” or “knowledge”—one of the Ancient Greek root words for “epistemology” which refers to a facet of philosophical study related to knowing things.
While it may seem superficially correct that these two concepts should always be in opposition to each other, the assumption that popular opinion and the theory of, validation of, and pursuit of actual knowledge are in conflict with each other is not as much of a certainty as Plato and his intellectual descendants often implied.
Consider that much of the information we soak up about our environment is derived not from focused research, study, or dialectic investigation, but rather from consciously and subconsciously watching others—including, in some cases, other species, but especially others of our own perceived kind—for signals about how to behave, what is worthy of concern, and so on.
An understanding entirely predicated on this sort of group-reading will be flat, lacking in context, and limited by the collective understanding—the epistemic knowledge—of the group.
Thus, it’s not optimal in all situations for all purposes. But it is far better than nothing, and in many circumstances this superficial grasp tells us everything we need to know according to the priorities of the moment.
Said another way: we could deeply research every single detail of every single situation in which we find ourselves, but doing so would severely limit our range of options, our response-time, and our ability to dynamically operate in the world—and probably survive in it, as well.
Quickly taking the temperature of the room, then, and adopting a watered-down version of groupthink, can in some cases be superior to actually knowing and understanding the entirety of something that’s happening—in terms of survival and functioning despite unclear variables and unfamiliar scenarios, at least.
That said, relying on democratic judgement to the exclusion of hard data, can leave us enthralled by superstition, ignorance, and well-meaning ineptitude.
Yes, it’s possible to get remarkably useful insights from a large enough population of non-experts. But you’ll often achieve superior results by asking one skilled electrician how to repair faulty wiring in your house, compared to asking 100 friends who have never used a wire-stripper or changed a lightbulb.
The implication of some research is that we can use the tools we have available to create more connections, and thus, better our collective technologies—device-based social networks, but also systems like democratic governments and open economies—benefitting from our increase in person-to-person and person-to-crowd connectivity, as a consequence.
More connections and more capacity to leverage the interconnected collective leads to more wisdom, in other words.
Unfortunately, in some cases the trend seems to move in the other direction: more people on a network influencing the collective wisdom can nudge the common understanding toward nonsense, misunderstanding, and even ideas that are harmful to the collective—or to those outside the collective.
One theory as to why this may be the case is that some types of information and understanding are better suited to crowdsourcing than others.
Research has indicated that observational, creative, and estimation-based solutions derived from groups are more likely to outperform those generated by individuals, while those that ask for specific answers to concrete questions and which necessitate expertise-based knowledge are less-likely to be successfully generated from a network of non-expert minds.
One common theory about why crowd-based answers are sometimes superior is that averaging the provided answers in this way allows for the reduction of what’s sometimes called individual noise: the statistical likelihood that any single person will get a specific question wrong is countered by the likelihood that at least some people will get it right.
It’s also been posited that certain types of cognitive task, like creativity and problem-solving, benefit from the increased range of perspectives and experiences crowd-thinking provides, while others seem to benefit from raw numbers: if you get a wide enough range of answers, you will almost always get closer to a functional answer than an average individual would because of how probability distribution works.
Much of this research and these theories have been predicated on a lack of cultural feedback, however, which is not something that should necessarily be assumed.
There’s reason to believe that an awareness of some types of data—published election polling results, for instance—can influence opinion.
In practice, this means that an individual’s awareness of how the crowd seems to be feeling can influence their own feelings, which then, on scale, can change the crowd’s feelings: the sentiments measured by a poll can be changed as a consequence of having published those poll results.
This implies that there’s a knowledge-based feedback loop that can shift everything from elections to fashion trend cycles, with one outcome emerging if the public isn’t given access to data about how they and their peers are intending to vote or feeling about a new type of garment, and another outcome entirely if they’re provided that information.
The distinction between doxa and epistêmê, then, may at times be blurrier than assumed.
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