Socrates, Social Media and the New Dialectic

“If I tell you that this is the greatest good for a human being, to engage every day in arguments about virtue and the other things you have heard me talk about, examining both myself and others, and if I tell you the unexamined life is not worth living for a human being, you will be even less likely to believe what I am saying. But that’s the way it is.”
– Passage from Socrates’ famous speech at his trial.

Many have heard Socrates’ famous quote about the unexamined life, but you may not have heard an interesting bit of philosophical history that I’ve run across on multiple occasions recently: Socrates was distrustful of the written word.

I guess our elders are always going to be distrustful of the new media. 

Of course, it’s one of the ultimate ironies that we only know his name and his work because his student Plato was the first student to take written notes on the dialogues. Writing and the Greek Alphabet were relatively new technologies then.

I’ve run across this curious fact about Socrates’ distrust of text on three separate occasions in the last month:

1. The Information, by James Gleick.
2. Proust and the Squid, The Story and Science of the Reading Brain, by Maryanne Wolf
3. @DonaldClark brought up Plato’s (Socrates’ student) distrust of unchallenged narrative in a response to a great post on context, storytelling and narratives by John Hagel

For the sake of getting to the point I won’t go deep into any of these, but I’d recommend the for anyone interested in how we assimilate knowledge and how it’s changing.

It’s not an accident that smart people are talking about Socrates and his distrust of writing. Our modes of consuming and synthesizing information are perhaps changing faster than they have since Socrates’ time. His objections to writing seem prescient and worth another look.

What were the objections Socrates had to reading and the written word?

Maryanne Wolf highlights each of the following:
1. Inflexibility – Socrates thought the only truth could come through expressing knowledge (synthesis) and actively questioning (analysis) of that knowledge. For him the written word was too static, too inflexible.  Words in oratory come and go in an instant, yet the traces lingered. Our minds would hold the essence of the logic, and continually refine it. In this way, words received via oratory were like a clay, the written word like an uncarvable stone.
2. Loss of Memory – we would become lazy if we didn’t have to memorize our ideas and understanding. When the word is written, Socrates felt that  the page holds it, not the mind. You can just read it and forget it. So for Socrates, external word permanence led to mental impermanence.
3. Loss of Control of Language – knowledge would not come with the requisite understanding and might lose context. There wouldn’t be enough feedback during our consumption of thought and knowledge. The context of oratory was king, and for Socrates, the context was lost on the written word. As Dr. Wolf writes in Proust and the Squid, ” Ultimately, Socrates did not fear reading. He feared the superfluidity of knowledge and it’s corrollary — superficial understanding.”  

To sum it up, Socrates thought we would lead less examined lives if we relied on writing over oration. Oration allowed for iteratiion, ever-changing structures getting closer of truth. Living in stasis of belief is the unexamined life. To learn, we need ongoing and consistent feedback on our ideas, a consistent context perhaps?

In Socrates belief in oration and dialectic we find the the foundations of many of the institutions we now hold dear, including: higher education, scientific research and the scientific method, our political process and the courts (to name just a few). They each have their roots in the Socrates’ dialectical method, in testing our knowledge and our models against our peers and the outside reality we are trying to model.

A hallmark of the Socratic method is the the union of analysis and synthesis, and this, perhaps is a key clue to where we’re heading. Socrates distrusted the written word because it separated analysis from synthesis, reader from author. In the social sphere, this is no longer true.

Another important change (I believe) is that dialectics are moving in parallel. The story of an idea can now live in several parallel universes, so we have a societal dialectic and a societal narrative moving in parrallel. And that’s why Hagel’s post on narrative and context is so important. It seems we’ve moved from an individual, one to one dialectic to a societal dialectic, a broader story. If an idea doesn’t make sense in one domain, it may have a life in another. Ideas can get feedback in a variety of contexts and find its niche.

The New Dialectic:

Social media, in a sense, is a new form of massive peer to peer oratory and a new spin on a new dialectic, continually evolving with continuous feedbacd. And it matters deeply because what’s changing in multiple different directions is our process of learning, our processes for examining truth. We have many new types of dialectic systems enabled by technology and the web. We comment on blogs, we ask questions on Quora, a new type of non-real-time dialectic.

But I don’t think it ends there.

Our technology itself is becoming dialectic because it’s a more effective way to develop a new system. Open source, lean startups, UX design (based on user feedback), groupware, open standards and open anything nowadays all have their foundations in first and foremost as feedback systems, ways of organizing group learning. Importantly, each of them achieve this by reuniting analysis and synthesis.

Iteration is in vogue everywhere because the web makes it low cost everywhere. Feedback is approaching free. Feedback creates diversity of solution for new niches.

We’re just seeing the beginning of the effects in the health care industry (see #HCSMgate). For changes in healthcare see these posts by Susannah Fox and Seattle Mama Doc. Parallel societal and technological dialectics are just beginning to have an impact, just beginning to take shape, but the results so far are astounding. There will be many bumps in the road as our inflexible modes of understanding move to perpetual learning. We are beginning to see learning at scale and I believe we will benefit tremendously.

So let’s make sure these words don’t remain static and isolated in context. Tell me what you think.


Ubiquitous Evolution

I’ve been observing a pattern for the last 25 years. It’s the pattern of learning, evolution, competition and collectivism and how they work together to cultivate the amazing diversity we see in our economies, our technologies and in ecosystems of all kinds. It comes down to how networks evolve and hone their ability to create value. I’ve seen the pattern in several recent books, but never seen the elements abstracted down to what I see as the core elements and the sequence in which they happen.

Here’s how I see the evolutionary cycle: 

Along this chain, an interesting thing happens. We move to different organizational structures, different ways in which people and processes and things get organized. We from one to one, to linear or process, to networked or market-based processes for the organization of creative activities. This follow Christensen’s model of disruptive innovation, but we can see it in Hagel’s Power of Pull as well. It’s a type of “Access, Attraction and Achievement” that keeps repeating.

To me there’s also a notion of Darwin’s ideas of nature and species as a surface covered by wedges (although I’d say they were being pulled down rather than driven from above):

“Nature may be compared to a surface covered with ten thousand sharp wedges, many of the same shape, and many of different shapes representing different species, all packed closely together and all driven in by incessant blows: the blows being far severer at one time than at another; sometimes a wedge of one form and sometimes another being struck; the one driven deeply in forcing out others; with the jar and shock often transmitted very far to other wedges in many lines of direction.”

I see step 1 as the tip of the wedge, and the later steps as the wider part of the wedge as a new system enables the use of the resource discovered in step 1. Here to, we see a similarity to what David Brooks discussed in last week’s NY Times, “Nice Guys Finished First”. In fact, Brooks and Darwin are both right, the unit of the wedge could be a person, group or company, so there’s a constant interplay between cooperation, exchange and competition.

I’m going to try not to give too much detail here, but rather in future posts, give some examples of how each of these step play out in a variety of contexts. Let me know what you think of this initial iteration and let’s go from there.

Update: I just added the part about Darwin and Brooks.

Liquid data and the health information economy: Is 2011 finally the year?

Honored to have my old post reposted today on Post was originally posted on I'll post it here, too, for the record. Would love to hear your thoughts:

What a difference three years makes. It seems quaint now that in the 2008 NEJM there were concerns raised about the flow of health information onto the web. Back then there was but a faint trickle of what could be entered, mostly by hand, and accessed on the web. Before HITECH and health care reform, exchanging health data online seemed blasphemous to many hospitals, patients, and physicians alike.

Fast forward to today and where we are now:

  • Around 75% of physicians have smart phones (the web in their pocket), and will reach 80% in 2012.
  • Major vendors have opened or are preparing to open their APIs in some fashion.
  • Almost every major EHR vendor has or is working on an iPad application (a web tool).
  • HealthVault has already begun to receive info via The Direct Project for the Care360 EHR.
  • Connectivity and interoperability are quasi-law.
  • Web-based EHRs have come to the forefront for many practices.

It’s great progress, and this is an amazing jump from where we were, but it’s far from an economy of health information. The problem is that there is still little patient data to pull from. None of the top 20 iPad health care applications even have connections to EHRs.

If health information is a sort of currency, then what we are seeing is that physicians are beginning to recognize its value. Physicians (and patients, too) are pulling for new functionality and opportunities to use health data, but for the data that really matters, patient data, they’re coming up empty.

What we need to achieve a health information economy

In 2009, in a follow-up to the NEJM article, Mandle and Kohanne (the same authors that wrote the 2008 NEJM paper) describe what they believe is required to develop a robust health information economy:

  1. Liquidity of data (access and exchange)
  2. Substitutability of applications
  3. Open standards
  4. Competition and diversity of applications over functionality, not data.

I like this, and it’s similar to what I’ve found over the years. As a personal mission, I’ve been researching information economies for almost a decade, and it’s clear that there is a repeated pattern in their development:

Information economies must be put into a single system where information can be found, accessed, trusted, exchanged, and then recombined. These elements, together, allow information to flow to where it’s needed in a form where it can be easily acted upon that fits the job to be done (Christensen's cornerstone of value creation and disruptive innovation) at that moment.

Similar to Mandle and Kohanne, my definition begins with what is essentially data liquidity, which happens via access and exchange (but also requires systemic trust). Once we have access and exchange, competition will drive better, more innovative products to deliver information where and when it’s needed.

Why we’re not there

It’s certainly no surpise to anyone reading this that data liquidity is sorely lacking in health care. Too long, competition among those providing and consuming health care information has been driven by restricting access (via data lock-in) to information. It’s the major reason we have big, monolithic EMRs that are poorly designed, confusing, difficult to use, and rarely (if ever) customized to the needs of that doctor and that patient at that time. Without access to data, there is no basis for competition to drive better designed software. You simply can’t compete without the data.

Holding back the power of 2.0 and collaboration

For all the talk of Health 2.0, lack of data liquidity is significantly preventing collaboration. Several companies have built great physician networks, but without any way to exchange the health information that matters: information about real, current cases. These networks have had to rely on reentry of data or, in many cases, limiting content discussions out of fear of HIPAA or FDA violations. So there’s still no way to collaborate effectively around the jobs they have at the moment: treating patients. Successful collaborative tools in medicine simply must:

  • allow physicians to collaborate on actual cases in at trusted environment of peers
  • do so without requiring data reentry
  • have systemic trust (no fear of sharing for security or regulatory reasons)
  • be worked into their current workflow

HIPAA, for better or for worse, has given providers cover for locking in data, and that’s only led to high-friction (not liquid) exchange of data via fax, email, and phone. A combination of fear and mistrust has driven valuable data into places where it has little use beyond where it’s called from: paper charts, monolithic systems, the minds of patients, or within one clinic on the far side of town. In order to gain access, much less exchange information, you have to know what data is available, where it is, and you have to ask for it. So mostly physicians work on their own without relevant data, or worse, recreate it through additonal testing at enormous costs.

Systems that have open exchange, such as Kaiser, even $5 billion of investment in HIT, are reaping rewards. When all providers can compete in an open network of information, they can compete on how they use the information rather than on hoarding information.

Things are changing

Fortunately, meaningful use is providing the incentive for many institutions that previously had none for digitizing and freeing health info, while the Direct Project or others may be a significant step in providing the means for all to exchange health info.

Stage I of Meaningful Use was largely focused on capture and exchange of health data. Stages II and III are focused on using that information in a meaningful way in clinical workflows. While I’m sure that stage II and III will have the desired effects of speeding industry adoption of Meaningful Use of EHRs (even if there’s debate on the directions), but I also wonder how much stages II and III are needed once data is liberated. We’ve seen in many instances before that once data is liberated, it will find its way to where it’s needed.

And that’s the real benefit I see with the Direct Project: it may allow for new companies and new business models for managing health data. Although designed for point-to-point transmissions to replace fax and phone, it may also make data easier to consolidate. Business models for technology companies may arise for making sense of the data, possibly on a population level and personalized level, then delivering it where and when it’s needed.

The floodgates of health information capital may be starting to open–it’ll be interesting to see what forces now pull at the data.

Meanwhile, health care reform may start to reduce the amount of mistrust and fear that exists around health data. If you can’t lose your insurance (the part that both parties like), will you still be as afraid that your health data gets out? Will people feel like it’s just data again, akin to financial statements? It’s still too early to measure the impact, but if PatientsLikeMe is already working, and people are sharing data with drug companies and anyone else who wants to know, then the potential that will exist when people are no longer fearful of losing insurance will be even greater. Trust is easier when what you share can’t be used against you.

Where are we headed?

To get to a true health information economy, health info has to travel from its vast untapped repositories to where it’s needed. Once it’s liberated, data will flow to help patients and physicians make better choices and continue learning while technologists use that data to provide better solutions.

In The Power of Pull, John Hagel III, John Seely Brown and Lang Davison at Deloiitte’s Center for the Edge describe how access, trust, and collaboration enabled through Web 2.0 are quickly accelerating advances in many companies and in many fields. The first step is access. Through access come the connection, exchange, and trust that drive the emergence of higher order innovations. One of the key points highlighted by the Power of Pull authors and others is that sharing information drives Pull. Pull in a connected world lets solutions find you. Once physicians and patients can exchange health information in a meaningful way online, they will. The benefits in outcomes are just too big to ignore.

Of course, in true counterintuitive fashion, health data will have a chance to experience the Power of Pull, but enabled via Push technologies in the Direct Project, but it’s a big step forward.

PatientsLikeMe is a prime example. Sharing becomes a small price to pay for better decision-making ability. Even though PatientsLikeMe is very openly funded by pharma, patients share openly. Part of that is the sense of community, but more of it is surprisingly and refreshingly data-centric. People share because they want results. They recognize they can increase the knowledge researchers, physicians, and fellow patients have of disease. Data liquidity will make it even more so, and better outcomes will result. It’s like an investment and spending of currency in a thriving economy. You spend it because you trust that you or someone you love will get more in return.

Better outcomes find us when we can find better information to make decisions without managing that information. That, in essence, is what a true health information economy will look like. I have high hopes that we’ll remember 2011, through health care reform, meaningful use and new chances for interoperability, as the year that health data became truly liquid.