Prediction: Retro-active quantification will be a
multi-billion dollar industry by 2015.
Information is power. Humans seek novel information because it
is a tool they can use to generate income, live longer and because
it satisfies their curiosity drives. As technology makes it easier
to mine and piece together more meaningful information, humans will
instinctively apply it to better their situation, causing much
One particularly disruptive result of the human information
mining instinct will be a booming and widespread retro-active
quantification (Retro-Quant) industry. Consuming knowledge that
millions of human agents currently expect and desire to remain
hidden from their peers, the Retro Quant market will inexorably
bring to light precious political, business, family and personal
The broader your information footprint and the more valuable
your information, the more likely it is that this market will seek
your information. Unless you can obfuscate the information that you
cast off, much like a spy agency does to establish cover, your past
behavior and statistics will be subject to Retro-Quant.
Here are ten business scenarios (just off the top of my head)
that I expect will contribute to a massive Retro-Quant industry
that wants your information:
1. DNA Mapping: Both your
current DNA, mitochondrial DNA and RNA and its history
will rise in value as biomedical and geneology companies continue
to piece together a map of mankind’s genetic information. You or
your relatives will be able to sell this info, but new companies
will try to get it on the cheap by collecting and correlating
samples freely available in the public domain.
2. Lie Detection Based on Video Recordings:
Ron Brinkmann notes that face-reading technologies will make it
possible to estimate the accuracy of a person’s previously recorded
on-video statements. (Jamais
Cascio has posted a nice reaction
piece.) This will push up the value of high-rez archived
interview footage and will allow us to estimate to a high degree of
certainty who was actually lying and when.
3. Meme Mapping: Emerging semantic and baby AI
technologies will first pull together all of your online data, then
cross-analyze it a million different ways to discover your
personality type, shopping habits, and longitudinal behavior
patterns. These will contribute to a model of your personality
genome already begun by consumer data companies.
4. Garbage Picking: Once robots or truly robust 3D
scanning and analysis systems get cheap enough, fields of human
garbage will all of a sudden turn to gold. How valuable might some
undiscovered Paris Hilton video snippets or a steroids tainted
syringe with Barry Bonds’ DNA be 10 years
5. Hi-Rez Satellite Imagery: The behavioral data
contained in hi-rez aerial photographs of humans is valuable to
sociologists, market researchers, product developers, etc. At some
point someone will try to sell rich human history collected by
satellites. Eventually this information could be opened to the
public in response to a quantification uproar. (cont.)
As sensors and computers continue to spread throughout the world they quantify our environment and offer the opportunity of real-time feedback. Case in point is Honda's new "Ecological Drive Assist System for Enhanced Real World Fuel Economy", a sensor/display system that learns your driving style and conditions you to become a more ecologically conscious driver.
Here's what the interface will look like:
And here's Honda's description of the new system:
TOKYO, Japan, November 20, 2008– Honda Motor Co., Ltd. announced the development of the Ecological Drive Assist System, which combines three functions to enhance fuel economy: the ECON Mode utilizes harmonized control of the continuously variable transmission (CVT) and engine to support more fuel-efficient driving; the guidance function uses speedometer color to provide real-time guidance on fuel-efficient driving; and thescoring function provides feedback about current driving practices, as well as feedback on cumulative, long-term fuel-efficient driving.
To scale and dominate as quickly as Google has, a new company will need to generate serious end-user value, monetize effecively, and take a new web-based approach to human resources. One such structure might be an organization specializing in prosumer-based quantification (structured crowd-sourced info mining) that can expand and contract quickly by paying citizen quantifiers for quality content that they input (think adsense, but more structured and directed from the outset). I imagine that this sort of company could catalyze big, fast economic growth and play an important role in generating positive-sum network value as we move further into the acceleration era.
To get the discussion of such a possibility rolling here's a speculative timeline of such a company (2011-2015) that I've cleverly dubbed "Quantification Company":
2011 - Launch: A logical outgrowth of flash mobs, open mapping parties, and steadily rising prosumerism, the Quantification Company (QC) was created in 2011 with the mission of "organizing and accelerating the comprehensive quantification of Earth's most valued systems." The for-profit organization relied on a small core of programmers, salespeople and community managers to catalyze quantification cascades, better known as Data Swarms, for a large variety of clients, but mostly municipalities and large corporations. Early efforts were kept simple and focused mostly on the rapid and/or real-time HD video mapping of U.S. cities, national parks, and other under-quantified areas of interest. Traffic-based fees were paid out to citizen quantifiers who captured and uploaded the best geographic footage and/or commentary. Though they were slightly nervous at the ambition and direction of the QC, competitors like Google, Yahoo and Wikipedia were happy to see traffic and content flow through their systems.
If the rumors prove true, Google is about to add 1.35 quintillion liters of water and 361 million square kilometers of surface area to its Earth and Maps applications with the long-awaited release of Google Ocean.
According to CNet reporter Stephen Shankland it's rather likely that Google will announce the new monster app next week at a star-studded Google Earth event:
Gore is set to join Google Chief Executive Eric Schmidt and Marissa Mayer, vice president of search products and user experience, at the on February 2 event at the California Academy of Sciences, San Francisco's newly rebuilt aquarium, planetarium, and natural history museum. But it's another speaker's name that gives the tip-off about what the event might be about.
That person is oceanographer Sylvia Earle, explorer-in-residence at the National Geographic Society and the founder of the Deep Search Foundation.
When viewed together with Google's space-based initiatives (Google Sky, Google Moon, Google Mars), the Ocean project indicates that Google is very clearly working to lay down the scaffolding (3d wiki) for Total Systems Quantification (TSQ), a very necessary strategy considering the company's mission to make all information universally accessible.
Essentially a Wikipedia-meets-Facebook for the dead, new service Footnote.com follows Google News Archive Search as the second serious business model built around retro-active quantification of social information to make waves this week.
A one-stop shop for ancestral information, Footnote aggregates, sorts and structures historical documents “relating to the Revolutionary War, Civil War, WWI, WWII, US Presidents, historical newspapers, naturalization documents, etc”, then mixes in social networking and user feedback to create useful timelines, historical links and family trees. Basically, they’re trying to corner the market on ancestral information by taking the most comprehensive approach possible.
It’s a brilliant and inevitable idea. As Facebook, MySpace, Orkut, LinkedIn, Google, and Wikipedia dominate the social networking and information pie, other companies looking to strike it rich are forced to carve out more focused value niches outside the direct scope of the big boys. From a macro perspective, it’s clear that these companies need to mix a monetizable model with novel/valuable content and a good user experience. And that’s exactly what Footnote is trying to pull off here.
By focusing on historical information, Footnote is avoiding major head-on competition (though Google certainly will make a big dent, but – then again – is also a likely acquirer) as it tries to rapidly grow community and data value. As a result, it has become yet another force behind the relatively nascent Retro-Quant trend, essentially making it a smarter historian thanks to it’s unique techno-social approach.
The fact that such a business model makes perfect economic sense reinforces the notion that Retro-Quant will grow to become a multi-billion $ industry sometime over the next several years. There’s simply too much value to be unearthed: human behavioral data, hidden crime (on many levels), genetic/evolutionary patterns, cognitive patterns, etc.