THE COMMON RECORD IS FORMED:

“Science has provided the swiftest communication between individuals; it has provided a record of ideas and has enabled man to manipulate and to make extracts from that record so that knowledge evolves and endures throughout the life of a race rather than that of an individual.

There is a growing mountain of research. But there is increased evidence that we are being bogged down today as specialization extends.”

Dr. Vannevar Bush

The quote above is taken out of context. By itself, it is a bit banal. What is extraordinary is that it was written in 1945, and goes on to articulate what sounds very much like the internet (in addition to many other inventions). His essay — similar to Schmidt’s — was a call to action. In Bush’s case it was for all scientists, with a few World War’s just behind them, to pivot their efforts away from developing tools for destruction and coercion to tools for expanding the mind and human knowledge. To create new tools to harness the ammassing “mountain of research”. He suggests a machine called the “memex”, pictured below. He hypothesized storing data and images would only become more efficient, and a new profession for filtering through the data would appear:

“There is a new profession of trail blazers, those who find delight in the task of establishing useful trails through the enormous mass of the common record. The inheritance from the master becomes, not only his additions to the world’s record, but for his disciples the entire scaffolding by which they were erected.”

Who are these “trail blazers”? Who is sorting through our “common record” — our data culture — and revealing insights, drawing conclusions, and advancing the human capacity for processing data into meaningful transferable information? What are the incentives behind the filters? How is this influx of data working us over, and how are we working it? As Schmidt begins to outline in his essay, but was not explicitly disclosed by Bush, the answers to these questions are mixed.

Data is not a static repository stored at a person’s desk, but collected in a ‘cloud’ (my all-time favorite mental model), connected to billions of mobile people via smart phones and other devices — each adding to a churning dynamic dialog. All of the data is not scholarly either. It can take the form of gossip bits and photo bragging, in addition to works of scientific inquiry. Many types of individuals contribute to the form and content of ‘the common record’ with varied intentions as well. Some want to follow and track your data for security or sales purposes. Each respectively targeting and defining a ‘consumer’ or a ‘risk’ — both orchestrating a form of digital espionage from data traces.

Such tactics create privacy and anxiety issues alike. With tools constructed for such purposes, they offer personal gains to the user to gather more data, but can have mixed side-effects due to their ulterior motives. The most pervasive example being Facebook, which makes it very easy for users to keep in touch and share with many, but ironically has created situations where people are always on their devices. Users are then less present in a current moment, rather stuck between a world of digital space and the actual physical space they inhabit — a mixed reality — disrupting the practice of Zen-like mindfulness and opportunities for meaningful human connections. The data they collect is then used to created targeted adds to sell and create feedings of need in individuals. A visious and bleak example for sure.

“All media are extensions of some human faculty- psychic or physical.”

Marshall McLuhan

In its more virtuous manifestations, data culture has been very helpful in creating new ways of sharing, creating insights to knowing one’s self, and opening opportunities for the democratization of conversation and education. As McLuhan is constantly reminding us; all this data pushed into media channels, all these ways of collecting data, all these ways of using the data, all these trailblazers making connections and creating tools for consumption from the data, are extensions of ourselves. And we are an emotional conflicted beautiful varied bunch — with different needs, desires, and motivations.

WHAT KINDS OF MENTAL MODELS ARE BEING PUT INTO PLACE, WHAT ARE THE FILTERS?

“The next great awakening of human intellect may well produce a method of understanding the qualitative content of equations. Today we cannot. Today we cannot see that the water flow equations contain such things as the barber pole structure of turbulence that one sees between rotating cylinders. Today we cannot see whether Schödinger’s equation contains frogs, musical composers, or mortality — or weather it does not.”

Richard P. Feyman

As Feyman notes, our brains structure the very methods for understanding that make the ‘common record’ comprehensible. That we have made gains to in our human intellect to see much, but there is room for improvement. That we cannot necessarily see the qualitative in the quantitative with our current methods for understanding. I think this is an important point to consider. That our common grasp of the world around us can only be as good as the methods, theories, and mental models that exist to process it. That our collective knowledge and the ability for our brains to comprehend it are intertwined. That there is a symbiotic relationship in place with all this compounding data and our methods to harness it into beneficial tools.

And this is why I think that Schmidt choosing art as method for talking about data culture was on point. We know that only more data is coming, and that it will have varied motives, and varied cultural effects. We also know that science, technology, government and engineering sectors — the ones generating and using the majority of big data — are largely being overseen and run by men. I am sure the racial and cultural profile is also limited, establishing particular practices of working with narrow mental models in place.

Personally, I believe that the tremendous success of humanity has relied, and will rely on, our variation. On our diverse skills and perspectives coming together as social animals to advance collective knowledge. Our ability to collaborate across disciplines and perspectives is therefore useful, if not imperative. I am not alone on this, Joi Ito, director of the MIT Media Lab (in addition to many other iconoclast roles) notes that “Right now, the three areas I’d say we are primarily working on are the Future of Science, the Future of Design, and the Future of Learning. And they’re all related.” Because he believes that the way research is being conducted is flawed, and sees the future in anti-disciplinary creative labs where ways of working push new and creative disruptive technologies.

There are is an array of evidence to point to the success of creative disciplines pushing more technical ones — and visa versa. Take Albrecht Dürer — arguably the greatest German artist of the Northern Renaissance. In addition to many other scientific woodcuts, in 1515 he created the first printed maps of the northern and southern celestial hemispheres shown as polar projections. His mental model of the hemispheres helped visualize and therefore explain changing conceptions of the universe.

The specific technical issues that arise when addressing an ever evolving mixed reality of ‘data culture’ — a reality compounding physical spaces and interactions with virtual data and its many manifestations — include defining correspondence between real-world and virtual objects, sensory perceptions (including vision processing, video tracking of objects, plan recognition, and integration of multiple forms of sensory data), spatial reasoning, and learning and adaptation. Therefore, designing and constructing mixed-reality devices that are functional, useful, interesting, and desirable present not only technical challenges, but artistic and practical ones. That is, it can be complex. Therefore the more types of brains we have thinking about data, the generation of data, and the filters of data, the better. All this new data has no inherent value, it is what we bring to it that matters.

PERSONALLY. REALLY WHAT CAN I (AND YOU) DO ABOUT IT?

As this is a sort-of call to action response, I feel compelled to end with what I want to do about it. The first being obvious, to conduct a critical inquiry (check), and second to apply the insights to myself and my work. Read, ask questions, and form an opinion. Lastly, do not let fears or insecurities get in the way of imposing a vision on the world. The emerging world will always be coming, no need to shy away from what it brings. No matter how big the data or cutting edge the technology, we need a range of people willing to interpret in their own ways and be open to sharing it.