To the best of our knowledge, humans are the only species capable of thinking about thinking, even though most of us don’t do it very often. We use the Greek word “meta” to talk about this ability. Basically, “meta” refers to a concept which is an abstraction of another concept –an instruction sheet for whatever the original thing is.
Because humans can grasp this concept, it can be a powerful way to overcome the limits of our genetic programming. Daniel Kahneman’s book, Thinking Fast and Slow, is essentially a meta-guide to the act of thinking – an owner’s guide for our minds. In it, he catalogs evolutions extensive list of cognitive “gotch-yas” that can way lay our rational reasoning.
In our digital world, we use the word “metadata” a lot. Essentially, metadata is a guide to the subject data. It sits above the data in question, providing essential information about it, such as sources, structure, indexing guides, etc. Increasingly, as we get data from more and more disparate sources, metadata will be required to use it. Ideally, it will provide universally understood implementation guide. This, of course, requires a common schema for metadata; something that organizations like schema.org is currently working on.
Meta is a relatively new concept that has exploded in the last few decades. It’s one of those words we throw around, but we probably don’t stop to think about. It’s power lies in its ability to both “mark up” the complexity of real world, giving us another functional layer in which to operate. But it also allows us to examine ourselves and overcome some of the mental foibles we’re subject to.
According to Wikipedia, there are over 160 cognitive biases that can impact our ability to rationally choose the optimal path. They include such biases as the Cheerleader Effect, where individuals are more attractive in a group, the IKEA Effect, where we overvalue something we assemble ourselves, and the Google Effect, where we tend to forget information we know we can look up on Google. These are like little bugs in our operating software and most times, they impact our rational performance without us even being aware of them. But if we have a meta-awareness of them, we can mitigate them to a large degree. We can step back from our decision process and see where biases may be clouding our judgment.
Meta also allows us to model and categorize complexity. It allows us to append data to data, exponentially increasing the value of the aggregated data set. This becomes increasingly important in the new era of Big Data. The challenge with Big Data is that it’s not only more data, because in this case, more is different. Big Data typically comes from multiple structured sources and when it’s removed from the guidance of it’s native contextual schema, it becomes unwieldy. A metadata layer gives us a Rosetta’s Stone with which we can integrate these various data sources. And it’s in the combining of data in new combinations that the value of Big Data can be found.
Perhaps the most interesting potential of meta is in how we might create a meta-model of ourselves. I’ve talked about this before in the context of social media. Increasingly, our interactions with technology will gain value from personalization. Each of us will be generating reams of personal data. There needs to be an efficient connection between the two. We can’t invest the time required to train all these platforms, tools and apps to know us better. It makes sense to consolidate the most universally applicable data about us into a meta-profile of our goals, preferences and requirements. In effect, it will be a technologically friendly abstraction of who we are. If we can agree on a common schema for these meta-profiles, the developers of technology can develop their various tools to recognize them and reconfigure their functionality tailor made for us.
As our world becomes more complex, the power of meta will become more and more important.