An Empty Space seeks to fill the space for a unified, open reputation system and standard, and more generally a space for plotting the true interactions between humans. People will be able to use this standardized reputation platform across different web sites. It will plot their trustworthiness, transaction history, personalities, relative successes and failures.

Currently no other organization or company has come close to expanding into this space. Here’s why:


Google approaches the web as a platform, and is intent on displaying its targeted ads all over that platform. What it collects about individuals is not anything more than the intent expressed through search terms and the popularity of certain sites over others, as expressed by linking and click-throughs. Google focuses almost exclusively on precise, quantifiable data.

As a result, it would not necessarily be easy for Google to enter the reputation space, since that relies a lot on qualitative, subjective measurements and one person’s word versus another’s. Google also suffers from not seeing what people ultimately do with searches in the end — they do not see if a product is bought, for example. This is an incomplete view of human behaviors.

If Google wants to organize the world’s data, wants to organize humanity’s data.


Facebook has traditionally been almost completely focused on social connections, facilitating students’ abilities in their university networks to communicate. Valuable data is almost entirely from simply who you are “friends” with, although there is no granularity or degree of strength of bond contained within “friend”. There’s no “acquaintance” or “BFF”, and describing how you know someone is a feature that is hard to get to and essentially useless except for the most curious. From knowing who your friends are, Facebook displays a feed of the latest updates from them to you, but this becomes less effective once you get over a hundred friends, as Facebook selectively chooses which updates to inform you of.

Beacon is the way of the future for online social sites, although it has been lambasted at first. Instead of companies trying to craft messages that we might respond to, Beacon reports on what our friends buy and review, thinking that what someone buys is very strongly determined by what his more direct network thinks of that product.

This can be extended to figure out what people you trust actually use to complete core, universal tasks in their lives — however, without any degree of friendship or relationship built in to Facebook, how can it determine whether you’d really like what this “friend” would recommend?

We still live in a time when you laboriously google reviews to figure out which camera to buy or which movie to see. To a large degree, some products are just clearly the best for everyone and there should be better recommendations for us to cut down our crude searching times. My buddy and I had an idea to create a “Men’s Canon”, back in the day: it’d tell you what movie or book would be THE source for getting started in a certain topic, like surfing or playing Scrabble.

What’s missing is the hard data about what choices people have actually made and how people truly interact with each other. The subtleties of human behavior are not being captured or allowing users to express it in a measurable way, currently.


Amazon attempts to assign value to different objects based on people like you and your previous choices. But you get clumsy results as experiential things like music, books, and films don’t follow algorithms. People are affected by venue, physical and mental moods, and even misperception and fickleness. Netflix’s attempt to reduce bad recommendations by way of a contest to reduce false positives is interesting and innovative but ultimately will fail at its goal. It may, however, unlock answers to other problems and reduce the degree of customer negativity from bad purchases.


LinkedIn is doing something that it’ll never be that successful at, and is missing a golden opportunity in the meantime. It attempts to create networks of professionals based on where their “friends” (again, an unqualified term) work. So therefore you can coldcall some guy your buddy knows at Google if you pay LinkedIn to get his info. Corporate inefficiency being what it is, people will pay for this kind of useless service and so LinkedIn actually makes decent money. But who tends to get jobs by coldcalling people? That’s essentially what using LinkedIn is like. It’s said you get most jobs through your weak ties, not your strong ones, but there has to be some tie besides LinkedIn for successful exchange.

What LinkedIn IS useful for is what no one actually uses it for: a public resume system. It has a standardized format, allows you to update just one resume instead of keeping up with which companies have which version of your resume . It’s accessible to anyone and everyone. It could even be customizable across different fields. It could allow for submissions (companies pay to be listed, users pay to submit) and cover letters.

LinkedIn tells you where people have worked, but does it tell you where people got rejected from or where they turned down an offer? No, and it’s doubtful anyone would ever say. Where would people like to work the most? Which companies?

Incomplete Dataset

What exists on the web across social sites are biased platforms and systems. They are biased in the direction of a singular degree of relationship. You either are or are not connected to someone else. Everything is derived from this simple binary calculation. But this does not capture human relationships at all. It’s certainly biased towards positive relationships and not towards negative ones, which means that there is no way to evaluate someone’s trustworthiness on most sites.


eBay is an exception. It, by necessity, has a karma system to evaluate buyers and sellers based on their performance in completing transactions. Any dings you get for a bad transaction affect your rating, which means that in a highly competitive market, potential business will head to others with exactly the same good and price, but with a higher rating.

This is closer to what can do, but eBay does not have much reason to expand out of its flea market, and certainly not into human reputation systems.

An Anthropograph:  The Human Space

Perhaps it’s too limiting for to focus on an open reputation system. The larger implication to collecting all that data on people for their own purposes is that they can use it to catalog and record their lives. Journaling, autobiographical archiving, an individualized personal memory. Its technical advantage will be in its bias towards the individual and against marketing interest, as it will be either an open standard or a social business with consulting services layered over it. One’s fragmented data will be transparently absorbed and synthesized into from any source and displayed in a statistical or graphical or visual product for its users to comprehend and use easily.

Today’s web sites are innovative and useful but incomplete. Why can’t I use Amazon to pick a university? Netflix to sell and distribute my movie? Facebook to apply for a job? Everything is fractured. The future of the Internet will be bringing everything together organically…for individuals.

At the same time, these sites solve significant problems. Why compete against Facebook? Better to find one’s own competitive advantage.

So what is Capturing the essence of people and how they relate to each other, in all the subtle ways that they do. A site so sensitive to the complexities of people that it sets the standard for collecting personal data.