“The Social Graph” is a popular misnomer that has plagued the social networking portability conversation ever since Brad Fitzpatrick catalyzed the blogosphere with a vision about the Global Social Graph.

But in fact, “The Social Graph” has little real value outside of computer science elegance. Nobody but Big Brother, the TSA, the CIA, and [insert surveillance agency of your jurisdiction here], actually want that single, monolithic view of all the relationships in the world. That’s The Social Graph.

In contrast, my social graph is hugely valuable to me. Your social graph matters to you. And it might be interesting to discover where our graph (plural) overlap. But neither of us actually care about The Social Graph.

At the VRM Workshop 2008, here at Harvard’s Berkman Center for Internet and Society, it came out that “social graph” is actually plural.

Like fish.

The Social Graph is a misleading distraction, a handy buzzword we can all slip into our cocktail conversations. But the real value is in the personal, independent social graph we all have. Plural.

If you think about it, that’s the only way you can really make sense of it in our user-centric, user-driven world.

For a quick taste, check out the interview with Drue Kataoka on View from the Bay. It is amazing how a few simple words can have such a profound visceral impact.

Drue’s suggestions resonate with my user-centric world-view:

1. SIMPLIFY
   Focus on what’s important. Eliminate what’s not.
2. IMMEDIACY
   React to the moment — not to your fears and concerns.
3. BREAK YOUR RHYTHM
   Surprise yourself and those around you.
4. BE CALM
   Find Tranquility in Action.
5. GREEN FROM THE INSIDE OUT
   Begin with your own personal ecosystem.

Take time for yourself, reconnect and put things in perspective, and engage the world on your own terms, in the moment, sustainably.

When redefining technology in personal terms, Drue’s take on Zen packs a powerful punch.

Intelligence centers run by states across the country have access to personal information about millions of Americans, including unlisted cellphone numbers, insurance claims, driver’s license photographs and credit reports, according to a document obtained by The Washington Post.

…

Dozens of the organizations known as fusion centers were created after the Sept. 11, 2001, terrorist attacks to identify potential threats and improve the way information is shared. The centers use law enforcement analysts and sophisticated computer systems to compile, or fuse, disparate tips and clues and pass along the refined information to other agencies. They are expected to play important roles in national information-sharing networks that link local, state and federal authorities and enable them to automatically sift their storehouses of records for patterns and clues.

…

The list of information resources was part of a survey conducted last year, officials familiar with the effort said. It shows that, like most police agencies, the fusion centers have subscriptions to private information-broker services that keep records about Americans’ locations, financial holdings, associates, relatives, firearms licenses and the like.

Centers serving New York and other states also tap into a Federal Trade Commission database with information about hundreds of thousands of identity-theft reports, the document and police interviews show.

Pennsylvania buys credit reports and uses face-recognition software to examine driver’s license photos, while analysts in Rhode Island have access to car-rental databases. In Maryland, authorities rely on a little-known data broker called Entersect, which claims it maintains 12 billion records about 98 percent of Americans.

In its online promotional material, Entersect calls itself “the silent partner to municipal, county, state, and federal justice agencies who access our databases every day to locate subjects, develop background information, secure information from a cellular or unlisted number, and much more.”

…

“There is never ever enough information when it comes to terrorism” said Maj. Steven G. O’Donnell, deputy superintendent of the Rhode Island State Police. “That’s what post-9/11 is about.”

The last statement pretty much sums up current institutional thinking on individual liberty and national security: in the fight against terrorism, we have a moral obligation to do everything we can. Everything.

It’s scary how much that position echoes that of fascism. As promoted by Mussolini, fascism builds a moral framework based on the primacy of the state. Fasciste means a bundle of sticks, symbolizing that the group is stronger than any individual. Fascism extends that thinking, declaring that each individual’s rights exist only insofar as they support the state. Or to restate, in the defense of the state, there are no individual rights.

Which, if you think about it, is exactly what anti-terrorist programs assert when claiming that terrorism trumps the rights and privileges of the suspect or accused. Due process, protection from unreasonable searches, freedom of speech. All of these have rights have been trampled on in the name of the War on Terror. The fusion centers are just one more institution created by the mindset that brought us illegal wiretaps, extraordinary extradition, secret prison camps, extra-territorial detention, and torture.

I understand law enforcement’s position. It is easier to enforce laws when you know everything about everyone, just like in a police state (see The Lives of Others for an Academy Award-winning story of pre-information age East Germany’s police state). But it is impossible for a police state to generate the economic and social well-being that emerges in a free society… and it is that well-being which, ultimately, is the core of U.S. global power. Simply put, undermining freedom undermines US security.

In contrast, consider the subtle brilliance of Kim Cameron’s Laws of Identity, in particular, law 2:

2. Minimal Disclosure for a Constrained Use

The solution that discloses the least amount of identifying information and best limits its use is the most stable long-term solution.

We should build systems that employ identifying information on the basis that a breach is always possible. Such a breach represents a risk. To mitigate risk, it is best to acquire information only on a “need to know” basis, and to retain it only on a “need to retain” basis. By following these practices, we can ensure the least possible damage in the event of a breach.

At the same time, the value of identifying information decreases as the amount decreases. A system built with the principles of information minimalism is therefore a less attractive target for identity theft, reducing risk even further.

By limiting use to an explicit scenario (in conjunction with the use policy described in the Law of Control), the effectiveness of the “need to know” principle in reducing risk is further magnified. There is no longer the possibility of collecting and keeping information “just in case” it might one day be required.

The concept of “least identifying information” should be taken as meaning not only the fewest number of claims, but the information least likely to identify a given individual across multiple contexts. For example, if a scenario requires proof of being a certain age, then it is better to acquire and store the age category rather than the birth date. Date of birth is more likely, in association with other claims, to uniquely identify a subject, and so represents “more identifying information” which should be avoided if it is not needed.

In the same way, unique identifiers that can be reused in other contexts (for example, drivers’ license numbers, Social Security Numbers, and the like) represent “more identifying information” than unique special-purpose identifiers that do not cross context. In this sense, acquiring and storing a Social Security Number represents a much greater risk than assigning a randomly generated student or employee number.

Numerous identity catastrophes have occurred where this law has been broken.

We can also express the Law of Minimal Disclosure this way: aggregation of identifying information also aggregates risk. To minimize risk, minimize aggregation.

Whether or not you think the War on Terror is being handled well, it is a demonstrable fact that human systems fail. People make mistakes.
And that means we can guarantee that institutions–even when acting in our own best interest–will make mistakes, like the admitted errors of the FBI, as reported by the NYT:

F.B.I. Made ‘Blanket’ Demands for Phone Records

WASHINGTON — Senior officials of the Federal Bureau of Investigation repeatedly approved the use of “blanket” records demands to justify the improper collection of thousands of phone records, according to officials briefed on the practice.

…

Under the USA Patriot Act, the F.B.I. received broadened authority to issue the national security letters on its own authority — without the approval of a judge — to gather records like phone bills or e-mail transactions that might be considered relevant to a particular terrorism investigation. The Justice Department inspector general found in March 2007 that the F.B.I. had routinely violated the standards for using the letters and that officials often cited “exigent” or emergency situations that did not really exist in issuing them to phone providers and other private companies.

F.B.I. Says Records Demands Are Curbed

WASHINGTON — The Federal Bureau of Investigation improperly obtained personal information on Americans in numerous terrorism investigations in 2006, but internal practices put in place since then appear to have helped curtail the problems, Bush administration officials said Wednesday.

The Justice Department’s inspector general is expected to issue a report in coming weeks that updates the findings of a major investigation last year into the F.B.I.’s use of so-called national security letters, which allow investigators to obtain telephone, e-mail and financial information on people involved in investigations without a court warrant.

Last year’s report caused an uproar in Congress when it was disclosed that the F.B.I., under powers granted by the USA Patriot Act, had misused its authority to gather records in thousands of instances from 2003 to 2005. The new report from the inspector general will examine the bureau’s use of the records demands in 2006.

At the end of the day, this isn’t about any particular individual, nor even any particular violation of our constitutional rights.

It’s about addressing the systemic problems of the information age. There will always be threats to national security. There will always be the drive to get as much data as possible into the hands of a few, elite law enforcement agencies, capable of acting in the “public good”. And there will always be those individuals who break the rules, whether for good intent or malicious device. We don’t need conspiracy theories to point out the dangers of centralizing all the information about everybody.

What we need is an open-eyed approach to building information systems on user-centric principles, such as Cameron’s seven Laws of Identity. Do that and a vast number of systemic risks of the information age go away.

• Natural Language Understanding
  • No longer a need for cryptic “Googlese” to get the computer to give you want you want.
• The Genie in the Bottle
  • The magically perfect assistant who can answer any question or satisfy any need you might have.
• Semantic Knowledge Bases
  • Structured databases that have deep understanding of the meaning behind the data, rather than just the characters and numbers used to represent the data. Think Freebase and Twine.
• Semantic Search
  • Natural language understanding driving search results, so you can ask questions like “What clubs does Tiger use?” rather than Googleses keyword queries. Hakia, Powerset, and Cognition are all in this space.
• Social Graph
  • The pan-Internet interconnection of you and all your friends, associates, family, etc. LinkedIn, Plaxo, MySpace, FaceBook.
• Shortcuts
  • Intra-page shortcuts that augment a web page’s content to enhance a user’s browsing experience. This includes SnapShots from Snap, BlueOrganizer and SmartLinks from Alex’s own AdaptiveBlue, Shortcuts from Yahoo!, and In-text search from Lingospot.

It’s nice walk through the space and particularly interesting how Alex responds to the current state-of-the-art in each. I’ll summarize here, so I can respond in turn (check out the full article for Alex’s actual statements):

• Natural Language Understanding
  • Huge, hairy problem. No solution in site.
• The Genie in the Bottle
  • Even harder. Needs magic that isn’t even conceptually well understood.
• Semantic Knowledge Bases
  • More detailed data is good, but does it really help users? Not emotionally catalytic enough for people to actually get excited and jump on board.
• Semantic Search
  • Doesn’t look like the killer app so far, because none of the “semantic” approaches seem to improve much on Google.
• Social Graph
  • This is just a subset of the semantic web and therefore not its killer app.
• Shortcuts
  • An up and coming category, these embedded shortcuts remove search as the killer navigation online. However, it is still young, misunderstood, and also lacks emotional umph.

First, the most intriguing item is that Alex is candid enough to be critical of the category in which he places his own company’s flagship product. Perhaps AdaptiveBlue has turned the corner on their conceptualization of the market and are rapidly, fiercely developing their next innovation, their next rev, the thing that just might become the killer app of the Semanic Web. That makes me curious, indeed.

Second, I like the break down, but naturally have some slightly different opinions. SwitchBook is still largely in stealth mode–we have yet to publish much on what we are doing even though we are relatively open in face-to-face meetings. However, from my posts here you can guess that it involves search, user-centrism, and particularly the principles underlying VRM.

So let’s look at Alex’s breakdown again:

Natural Language Understanding

Definitely a huge problem. Not only do you have to deal with the incredible elasticity of language, once you’ve mapped the natural language into some sort of internal representation, you still have to figure out what the heck you are going to do with it.

In other words, “understanding” is context specific not just in terms of words having different meaning in different places–Jaguar could mean a car, a cat, or an operating system depending on whose brochure or website you find it on–but it also has different meaning based on what you (as a system, as a service) are going to do with that understanding.

• Are you going to return web pages that contain Jaguar with the same meaning?
• Are you going to offer alternatives to the term Jaguar, like a thesaurus?
• Are you going to translate Jaguar into other languages?
• Are you going to sell Jaguar compatible products?
• Are you going to reason over the threats and opportunities of Jaguars?

All of these require fundamentally different internal representations of the “understanding” of the natural language from the user.

As Jaron Lanier will tell you, language is an interface by which people remotely control the world outside their mind. We use it to communicate with others to get what we want and to understand how to respond to others (which is basically figuring out how to eventually get others to give us what we want). As such, its primary use, its raison-d’etre, is to influence the world around us. So, what we really want isn’t to understand the language, but to understand (1) what a speaker wants and (2) how to influence the world.

It turns out, people are incredibly adaptive at both of these tasks. Language is just one of the interfaces we use and we are capable of learning entirely new tools quickly when they demonstrate a more efficient, more effective way to get what we want. The humble spreadsheet is one of my favorite examples of this. I believe that more people “program” in MS Excel than in any classic programming language: we write mini-programs using functions like sum() and average() and put data in and look at the results. Who would’ve thought that entry-level clerical workers, accountants, and soccer moms around the world would’ve learned to program? And yet, they do. In my opinion, Excel is probably the most widely used programming environment in the corporate world.

Could you imagine trying to replace that with Natural Language? I can only imagine that a natural language version of Excel would be more convoluted and harder to use, but maybe that’s just because I lack imagination.

The Genie in the Bottle

This is more interesting. I agree that this goal is arbitrarily far away–no one will crack this nut entirely until we have both omniscience and omnipotence programmed into our software (and that is essentially never). However, by understanding clearly exactly what the Genie would do if he or she could, then you have a starting point for building innovative solutions.

Consider the development of online virtual worlds. Many people also said that the fictional Star Trek holodeck is arbitrarily far into the future, that, like the Genie, it requires so much advanced technology as to effectively be magic. And yet, Janet Murray’s Hamlet on the Holodeck gave us a realistic assessment of the current state of the art and how we might eventually get there. Sure, we are still arbitrarily far away from the uber virtual experience of the Holodeck. But Second Life, World of Warcraft, and Grand Theft Auto have all broken incredible ground in making a simpler, more feasible version of that experience available today to tens of millions of people.

So, what we can learn from the Genie is how to think about the “perfect” Search service. Imagine for a moment the absolutely perfect search service. Think bigger than natural language search. Think bigger than talking to your computer and getting what you want.

The perfect Search is when you only just barely have to indicate your intention and your search result appears. Somehow, magically, the system just knows what you want and when you are ready to actually act on that desire, the system has already brought your desire to you. No more running to the vending machine to get a soda from an arbitrarily limited selection in fixed volume and vendor-mandated packaging. The system knows you are getting thirsty, knows what you want (not just from history information but even from sensing your current blood-sugar and taste craving) and how you want it, and the moment you commit to getting that soda, it appears at your desk–perhaps even without you knowing exactly which soda you wanted today. All of this done discretely, unobtrusively, privately, and with the utmost discretion so neighbors or co-workers don’t see what you’d rather they don’t. The action, ultimately, is always driven by your committed intention. Not your attention, not some statistically predicted estimate of your desire, but your actual, expressed commitment to realize a particular desire. Express an intention and magically, it is fulfilled.

That’s the Genie.

While it isn’t yet available, bits and pieces of it are becoming available, just as online text MUDs and World of Warcraft are bits and pieces of 30 years working towards the ultimate virtual reality. By placing the committed intention of the user at the core of value creation, at the heart of the system design, I believe the Genie provides an almost the ideal model for conceptualizing the Holy Grail of Search.

Semantic Knowledge Bases

Essentially, I agree with Alex, this is a technology looking for a problem. “Better” data and more “powerful” ways to interact with and reason over that data should provide better results and is, therefore, a Good thing–assuming there are no other costs. Unfortunately, the semantic web has significant transitional and ongoing costs to turn the free-form, anyone-can-post-anything World Wide Web, into a system where participating as a first class of citizen requires using RDF or microformats or some other arcane technology to transform formerly arbitrary scribblings–and marketing and online stores and customer service and media outlets and whatever–into semantically structured information. It requires an imposition of structure that is inherently limiting and counter to the user-centric architecture of the open web.

Nobody wants to pay that cost unless the immediate value to them is obviously much greater. And so far, the value is uncertain and far into the future.

Semantic Search

Alex suggests that because none of the semantic search companies is better than Google that semantic search isn’t the killer app. Well, Google uses a lot of semantics in its Search. Most users just don’t know it. They’ve used Latent Semantic Indexing for years and AdSense is all about wicked smart semantic analysis of web page content for matching ads from the Google ad universe. In fact, one of the more interesting semantic tricks Google does is one you can see for yourself. Try typing “jaguar” (or some other ambiguous term) into Google’s query box.

You’ll find that alternative meanings of “jaguar” all show up in the early results. Jaguar as a car. Jaguar as the cat. Even the Jaguar quantum chemistry package from Schrodinger, which has no reason being in the top ten at Google. Google does this because it knows that from the limited query box, it can’t figure out which Jaguar you really mean. But it also knows that users will filter out the misses and get excited about the hits. They design for the “Ah-hah” moment. As long as one in ten (or so) results matches the user’s intended meaning of Jaguar, then Google gets credit for finding the “right” jaguar. Brilliant.

So, I argue that any search that isn’t semantic is a dinosaur waiting for the undertaker. Maybe it isn’t a killer app as a distinct service, but it is already an integral part of the #1 killer app of the Web, Search.

Social Graph

On this one, Alex fails to explain clearly enough why he doesn’t like it. Any killer app is going to be a “subset” of the entire market. Email isn’t the totality of the Internet, but it is the killer app that first broke down the isolated IT networks and marched like Sherman all the way through to the consumer market to give the sexier World Wide Web a fighting chance at establishing the Internet as much a fundamental part of the civilized world as electricity, running water, and paved roads.

Actually, I think the social graph might be the killer app of the Semantic Web. It doesn’t deliver the full value of the Semantic Web, but it provides such immediate, obvious value for so many people that once the privacy controls are worked out, many many people are going to be surfing the Semantic Web without knowing it as they seamlessly mingle across their social internetwork through the former silos of Facebook, MySpace, Plaxo, and others. If it can be a killer app without people giving it credit, then the Social Graph is definitely a contender.

Shortcuts

This is absolutely illuminating. I like AdaptiveBlue’s product a lot, and others in this category have potential. However, I usually find the disjoint interactions confusing. Shortcuts, by nature, interfere with the “normal” web experience and are inherently intrusive. I happen to have Snap installed on my machine and I’m still surprised and often annoyed when it pops-up “previews” of links I’m doodling my cursor on.

I do that… I doodle mouse and doodle click. I have the same problem at the New York Times’ website, actually. They allow you to look up the meaning of any word on a page just by double-clicking on the word. Problem is, I doodle-click meaninglessly, sort of a virtual twiddling of my thumbs as I browse. And -whoops- I just triggered a new page download I don’t really want. It is a mess.

So, shortcuts have a long way to go to be less intrusive and to find the right “intuitive” connection with the user. Ultimately, I am a huge fan of augmenting the traditional “browse”-based experience of the web, rather than replacing it wholesale. People like the web. They like their services. They like the freedom of going anywhere that supports http and html. And yet, many of those websites don’t have the technical wherewithal to get “semantic”.

BlueOrganizer does a nice job, for example, of connecting IMDB listings of movies with NetFlix so it is easy for you to go from the Internet’s unofficial authority on movies to the leading movie-on-demand service. All without NetFlix or IMDB needing to do anything. That sort of user centrism is critical to the next evolution of the web and it’s the semantics of what is already on the web pages that make that possible. Shortcuts are just one effort to do something with that semantic data. Perhaps as they grow up, they will become more useful to more people.

Closing

Again, despite my initial hopes, I have written WAY too much, which is a pathological flaw I seem to have. Thanks for hanging in there.

My point in responding to Alex’s post is simply this: any killer app needs to start and end with the User. This is so true it has become a software development truism that everybody knows is important, but few know how to translate into their feature development schedule. Technology alone–like Natural Language Understanding–will never be a killer app. Only when someone figures out how to make it electric for users–exciting and immediate and so obviously valuable–can any innovation become a killer app.

With all due respect to the folks who love this term, the Semantic Web is one of those bundling concepts that is about as useful as the term “Electric Appliance.” It is useful in describing a category of product, but completely useless in helping retailers make decisions about what products people are going to buy this season. Until companies move beyond that catch all descriptor into product discussions that connect with what users already understand and want… none of the “semantic” offerings can possibly breakthrough to being a true killer app.