There’s a new language forming around data. Nebulous “big data” has been on fervent tongues of the forward thinking for a few years now. This ambiguous term is now being broken down into definable parts, and futurist Chris Dancy is our linguist. He makes the distinction between “soft data” and “hard data.”
Big data, as we know it, is mostly soft. Soft, as in, formable, not as solidly truthful as what’s called hard data. Soft data includes social media activity, transaction logs’ data, and anything individual that can be manipulated by attempting to appear a certain way. Basically, there is choice involved in soft data—what you post, what you buy, what apps you use.
Soft data informs who we think we are. It contributes to the illusory working self, based as much on goals, desires, faulty memory, popular archetypes we map ourselves onto, as it is based on the internal identity we feel and try to make external.
Hard data though doesn’t lie. Hard data is made up of the constant day-to-day facts that are gathered from sensors in an individual’s environment or on his or her body. The typical human doesn’t access this data. Dancy, strapped with at least three sensors at all times, is able to track, store, and search data concerning his mood habits, health habits, work habits, social habits, etc. Someday it will be any quantifiable habit imaginable. He can search any previous day for every piece of information gathered that day.
This kind of data defies the faulty memories or false impressions we can make up for our past. Of course, all it can do is invoke memory with data as the retrieval cue—one step short of human anomalies, people who can remember almost everything, even the trivial minutia of everyday.
In fact, it can provide a narrative over a specified amount of time, rather than being fundamentally episodic evidence. Basically, technology is helping humans reach a more accurate self-identification, what futurists are calling “the quantified self” (Wired).
The accumulation of data, and ability to form it into narratives, provides a portrait of the self that is based on solid data. We are nearing the ability to actually conceive philosopher David Hume’s “Bundle Theory,” that posits that the idea of self is a collection of every single instance of a person’s existence.
Here’s where a third type of data arises. Kind data. Dancy says, “I’m obsessed with data being kind.” By kindness, he means, the art of applying data to benefit human lives. He figures that data usage will go from where it is now, soft data, skip past personally collected hard data, and move to what he calls “core data” (Ogilvy Do). Core data is data already collected and interpreted by a third party, and applied to the individual. That’s where it can become truly kind.
When data is combined to become intuitive to customer needs, an individual can make decisions based on things she or he could not normally compute, or would take too much time to do so. Kind data could be developed to inform a decision by using data on health, mood, activity, and even genetics. Dancy uses the simple example of a menu only offering options dependent on predetermined health and mood decisions made before, as well as that day’s current calorie intake. Kind data frees up time by eliminating erroneous information and options from the environment (Ogilvy Do).
How can metrics be developed to offer practical individualized information? Will IT management be able to provide the metrics businesses need to make data beneficial to consumers?
Or will data take a different path? We’ve heard of data access invading personal privacy, through hackers as well as corporations.
The future of data reminds of Kurt Vonnegut’s criticism of science in Cat’s Cradle: “There was no talk of morals.”
As data and its effect on our lives grows, it’s up to individuals in technology to make sure it is as kind as possible.