Tuesday, May 11, 2010

Prosumer-Centric Capitalism

Irving Wladawsky-Berger has posted an illuminating piece titled Customer-centric Capitalism in which he convincingly argues the now dominant profit-driven businesses M.O. is in fact detrimental to society:
For the last thirty years, maximizing shareholder value has replaced customer value as the key objective of many companies.  But, a number of experts are now raising questions about this widespread business practice and the extreme preoccupation with short term profits that inevitably results from putting shareholders over customers. 
It is clear that our system of profit-driven capitalism must be modernized with a greater emphasis placed on the customer.  This is already happening.  A handful of companies, like Google, have adopted positive-sum or triple-bottom-line business models.  Many more are using data more effectively to improve customer service wherever it impacts profit.  Customer-centric capitalism is making a slow but steady comeback.

Now consider the spread of modern day analytics.

Thanks to the web information explosion and the social sharing boom it's become possible to track more complex behavior.  Among other things, we're compulsively piecing together this data into a more accurate picture of knowledge creation, sharing and value, and can now determine which members of a given network are more valuable than others.

So rather than advocating and rallying behind customer-centric capitalism as the next logical developmental economic step, perhaps we should expand or shift the concept to include this now visible network behavior.  We could call this "prosumer-centric capitalism".

What's a Prosumer?:  A prosumer is defined as a hybrid of a consumer and a producer.  Generally speaking, the vast majority of humans are not pure consumers, but rather prosumers that contribute more or less value to the companies and social systems they interact with.

You think Google is free?  Nope.  Google relies on all of the search queries we type in and then react to to generate its core value.  Same goes for Facebook, Yahoo, Aol, and other social media companies.  These companies all depend on prosumers for their bread and butter.

Other interesting prosumer-centric business models include iphone apps that turn street mapping into a reward-driven game, online stock markets that predict box office scores more accurately than experts, and social health networks capable of determining the effectiveness of new drugs years before clinical trials can accomplish the same thing.  The list goes on and on, largely due to the spread of modern social media.

It's not much of a stretch to imagine that these companies, and other traditional companies that undergo requisite webification, will be financially incentivized to return increasingly more value to their prosumers.  Those that can more effectively pinpoint, reward and tweak the conditions for value creation will have a distinct advantage. At the same time, keep in mind that the prosumers too will gain access to this data.  With quantitative data to point to, the tension between the prosumers and funders should create a healthy market for very specific micro behavior that could not have existed at any previous point in history (well, at least not without enormous expense).

Prosumer-Centric Capitalism: There is a gradient between consumer and producer called the prosumer.  As emerging systems get better at quantifying prosumer behavior, we will be required to adjust our consumer- and customer-oriented economic models and Excel spreadsheets (or Google Spreadsheets) accordingly.  Many companies are already doing this.  Defining customers as prosumers that add value in specific ways can help upgrade and bring more clarity to our understanding of our info-economic system and lead to more fair, balanced and/or efficient economic development.  When robust and foolproof prosumer accounting spreads to the masses we'll get Prosumer-Centric Capitalism, baby.

The Rise of Social Data Mining (as a Business Model)

Companies are discovering how to monetize social network data.  This is driving Big Open Science.  Is that a good thing?

A social network for sharing illness data, patientslikeme.com, has demonstrated that it can tap the information in its user network to predict the outcome of clinical drug trials.  The service, which is populated by a large number of ALS sufferers, determined that lithium use had no effect on the late-stage decline in ALS patients.  Why is this significant? Because it took 18 months before a formal study was able to confirm exactly the same thing.

While clearly not yet a replacement for the clinical trial process, the findings do reinforce the concept of Big Open Science - the use of large data sets to conduct a rougher, more rapid form of science.

The financial model is clever and solid:
We take the information patients share about their experience with the disease, and sell it in a de-identified, aggregated and individual format to our partners (i.e., companies that are developing or selling products to patients). These products may include drugs, devices, equipment, insurance, and medical services.  We do not rent, sell or share personally identifiable information for marketing purposes or without explicit consent.  Because we believe in transparency, we tell our members exactly what we do and do not do with their data. 
So long as the data remains totally secure, it sure reads like a win-win to me.  I can see many quantified health start-ups adopting or moving towards this model.

But, aside from the health data, it's not really all that new.

Focus groups and stock markets have been around for hundreds of years.  More recently, Hollywood Stock Exchange (HSX), a movie performance predictor site oft cited by collective intelligence researchers,  has clearly demonstrated its ability to forecast box office revenues via crowdsourcing.  And, of course, don't forget the banks, credit card companies and info aggregators that can already "predict with 95% certainty that you will get a divorce, two years before it happens, based on your purchases", as Google's Marissa Mayer famously pointed out on Charlie Rose.

In the coming years we can expect this sort of model to proliferate.  Trends like cheaper data storage, smaller sensing devices, widening bandwidth, exponentially faster computing and emergent social behavior suggest that more companies will be able to mine more valuable data from more willing participants and sell it to more interested parties.  Barring an all-out privacy backlash, it's a relatively safe bet that the broader market will create the conditions necessary for more similar social data mining startups and operations.

The new opportunities are seemingly endless:
  • health & medicine sites - like patientslikeme or curetogether (shout out to Alexandra Carmichael)
  • location video - streaming and stored on youtube
  • driving information-  gathered through your car
  • smartphone apps - more complex data capture, reality mining
  • genome - companies like 23andme
  • etcetera!
At the same time, consider how certain large companies can leverage Big Open Science (they're already doing it for market research, but could easily broaden these efforts):
  • Search: Google, Bing, Yahoo Search
  • Social: Facebook, MySpace, Twitter
  • Gaming: Sony, XBox, Nintendo, Apple
  • Smartphones: Apple, Microsoft, HTC
Privacy concerns aside (for the moment), there's such an abundance of untapped informational value that it's easy to envision a world in which total productivity grows by leaps and bounds - as a square to acceleration in the technology, data and comm space -  a sentiment echoed by Wired writer and Quantified Self blogger Gary Wolf at a recent Stanford MediaX seminar. (When I asked him whether or not he believed that Quantification was directly related to Kurzweil's Law of Accelerating Returns he thought about it for a moment then said "yes".)

Now, will these quantification driven economic gains gains trickle down to the average person?  Yes, I do think they will.  First in the form of accelerated science.  Then, second, it seems likely that the increasingly abundant services and social networks in the space will be forced by the market to return more and more value to the users, or prosumers, that are contributing this data - an effect that I have playfully nicknamed The Mandate of Kevin.

But will these gains come online fast enough to offset the disruptive forces of globalization, production automation, a large-scale privacy backlash or the resulting social turmoil?  That's hard to say, because we humans have never experienced such convergence before.  However, it is becoming more and more clear that traditional economics will drive Big Open Science and that this behavior is a thread interwoven with other accelerators.  Hopefully that will turn out to be a good thing.

Monday, May 10, 2010

Which Big Company Will Launch the Private Facebook Alternative?

Loren Feldman at 1938media makes the case for a large-scale Facebook alternative that caters to users looking for PRIVACY.   He suggests that Aol is best positioned to go that route.

Sounds pretty developmentally inevitable to me.  There will be open social networks and closed social networks.  The open play makes sense for Facebook at this time, but I expect that at least one large-scale CLOSED social network and many more gated niche players will soon emerge.  Google, Microsoft, Apple, Aol, IBM, Yahoo or even MySpace are companies that could make big gains by branding themselves as stewards of your privacy.

The Gradual Transhuman

According to transhumanist thinkers, a posthuman is a hypothetical future being "whose basic capacities so radically exceed those of present humans as to be no longer unambiguously human by our current standards."

Futurist Jamais Cascio tells io9 he thinks this word is "a term with more weight than meaning".
Posthumanity ... will always be just over the horizon. Always in The Future. When the systems and augmentations we now consider to be posthuman hit the real world, they will have become simply human in scale.

That's because augmentation - the development of systems and technologies to allow us to do and to be more than what our natural biology would allow - is intrinsic to what it means to be human.
Jamais points out in the article and in this NYC Future Salon video that the human species has already greatly augmented itself with technology (this includes words and complex abstractions, like science and math), so it's hard to pin down a static definition of "human" when we're actually evolving dynamically.

I agree and salute you, Jamais.

Our genes have changed to better take advantage of linguistics, numbers, and tools.  The cloud is an extension of our thought processes.  We're already significantly "post" and "trans" to what we were 100,000, 10,000,  1,000, and 100 years ago.

Yes,  technology, information and perhaps even intelligence are growing at an accelerating rate, but the prospect of accelerating near-term change, even a digitization scenario, does not erase that which has already occurred.

So let's achieve consensus on the term "human" to inform our concept of that which is not human, or more than human.  (This should also help clarify things in regard to that pesky "Singularity" term, another concept house built on shaky definitional foundations.)

Saturday, May 8, 2010


The similarities between Mark Zuckerberg and Genghis Khan are uncanny:

  1. Genghis Khan was born in the Mongolian plains in 1162 - not far from the current capital Ulaanbaatar.  Mark Zuckerberg was born in White Plains in 1984 - not far from world media capital New York City.  
  2. Genghis Khan became leader of his tribe at the age of 12 and began plotting world domination. Mark Zuckerberg became leader of his middle school Coders Club at the age of 12 and began planning world domination. 
  3. Genghis Khan committed a questionable act by killing his half-brother, Bekhter, during a fight which resulted from a dispute over hunting spoils. This incident cemented his position as head of the household.  Mark Zuckerberg committed a questionable act of killing Facebook predecessor ConnectU by mimicking its features and took all the spoils.  This incident cemented Facebook as the leading social network at Harvard.
  4. Genghis Khan used his cunning to unite the warring Naimans, Merkits, Uyghurs, Tatars, Mongols, and Keraits. Mark Zuckerberg used his cunning to unite college kids, parents, businesses across national borders, many of whom had been experiencing culture wars.
  5. Employing ruthless tactics, Genghis Khan conquered a vast geographic empire that stretched from Asia to Africa.  Employing ruthless tactics, Mark Zuckerberg conquered a vast prosumer empire that includes millions of Asians and Africans.
  6. Genghis Khan was tolerant of the varying religious views of the people he ruled.  Mark Zuckerberg is tolerant of the varying religious views of people that follow Facebook's rules.
  7. Genghis Khan decreed the adoption of the Uyghur script as the Mongol Empire's writing system.  Mark Zuckerberg decreed the adoption of Facebook Connect and then Open Graph as the web's sharing system.
  8. The Mongol Empire was governed by a civilian code, called the Yassa, created by Genghis Khan.  The Facebook Empire is governed by a civilian code called Facebook's Terms of Service, written by Mark Zuckerberg.
  9. In Iraq and Iran, Genghis Khan is almost universally viewed as a destructive and genocidal warlord who caused enormous damage to the population of these areas.  In Iraq and Iran, Mark Zuckerberg is viewed as a destructive and genocidal proponent of secularism and transparency who caused many awkward family dinner parties in these areas.
  10. Despite his personality flaws (extreme violence and ego), Genghis Khan was VERY popular with the ladies of the 1100's.  Despite his personality flaws (extreme nerdiness and ego), Mark Zuckerberg is VERY popular with the ladies of the 2000's. - Some things just never change.
Mark Zuckerberg should take a DNA test because all of the evidence points to him being a direct descendant of Genghis Khan, the world conqueror.

Thursday, May 6, 2010

Twitter is a Full-Fledged Media Outlet, Not Purely a Social Network

The first "quantitative study on the entire Twittersphere and information diffusion on it" conducted by the Department of Computer Science at KAIST University in Korea confirms that Twitter functions more as a broadcast news arena and less as a discrete social network.

One particularly interesting nugget is the estimation that "any retweeted tweet is to reach an average of 1,000 users no matter what the number of followers is of the original tweet. Once retweeted, a tweet gets retweeted almost instantly on next hops, signifying fast diffusion of information after the 1st retweet. "  This seems to reinforce that Twitter network behavior is more about the content and less about the people.

Wednesday, May 5, 2010

IBM Previews CityOne - Think Google Earth + Sim City = Educational Software that Supports IBM's Smart Planet Push

IBM is taking the notion of serious games to the next level with CityOne (think Google Earth + Sim City), a rich game designed to bring about awareness of the foresighted company's Smart Planet and Smart Infrastructure initiatives.

CityOne is already in use at over 1,000 universities for free as part of IBM's academic initiatives and makes sense as a branding and awareness play to support the company's Smart Planet and Smart Town initiatives.