Who 2.0: Tagging People in the Real World

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Related Topic: Self-Aware e-Society

This post has been updated to include the concept of Standardized Tags.

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The Idea

This post presents an ubiquitous, passive method for tagging people in the real world with attributes that describe them (e.g. good, fun, smart, interesting, psycho, unreliable, untrustworthy, etc.. you get the idea) such that people can see how someone they’ve just met has been defined (or categorized) by others.

People will be able to make better choices about whom to associate with and whom to trust, in a real world setting. It allows the Web 2.0 “social networking” paradigm, which is currently confined to the Web, to be experienced in the real world.

From Conception to Production

The “Who 2.0” idea was suggested by a fellow WordPress blogger who goes by “farlane” in his comment to the “Hunter Gatherer” post, which he made about 3 hours ago [note that this post has been updated since.] The idea is also sort of related to what I had previously wrote in a post on “GWorld (beta)” regarding how objects (or people) within a virtual world may be tracked and identified with the virtual equivalent of the RFID tag. Links to those posts, farlane’s comment and farlane’s “about” page are provided at the end of this post.

The Design

It’s really very simple.

Today, we have camera phones that can take photos with 8 mega pixel resolution. Such camera phones can produce a pretty detailed image of people’s faces (8 mega pixels actually produce a large-sized image with more than enough details.) Simply add facial recognition software which exists today and you have your tagging mechanism. Take a shot of someone’s face, add their name (optional) and tag them with words that describe them. Click send and the image and tags will be sent to a central database. When you you meet someone and you want to find out how others think of them simply take a shot of their face and send that as a query to the central database. The answer you get back would show each word/tag that has been used to define that person and how many people used each given tag. For example, 400 people think I’m funny and fun to be around while 3 think I’m a mutant ninja turtle. Who do you trust? Obviously, you can safely conclude based on the statistics that I’m not a turtle. The tag statistics in this context will help you make a good bet about the character and personality of someone you’ve just met, but it’s you (not the system) that makes the bet.

For example, if you look up my name (or look up my face) with your phone and find out that 10 people thought I was so very boring then you probably wouldn’t want to hang out with me. However, if at the same time 1000 thought I was a fun lovin’ guy then you may want to take your chances and hang out with me. But what you can do to people people can do to you, so I can look up your face or name and hedge my bet based on the tags I get back and the associated tag statistics.

This reminds me of that famous quote by Abraham Lincoln: “You can fool all of the people some of the time, and you can even fool some of the people all the time, but you cannot fool all of the people all of the time.” So while I may not be fun all of the time (e.g. 1%) I’m still fun most of the time (or 99%), so then you can make a safe bet that I’m fun to hang out with. But that’s just a simple example.

It gets more complicated as people describe the 20 or more possible personality and character attributes, some using different words than others. However, it cannot be any worse than following a link on del.icio.us or digg that has been tagged as funny by 1000 other people.

Standardized Tags

Several readers complained that tags are relative, not absolute, so they should not be used to judge people in an absolute way. Well, I never said the system should be used as an absolute measure of people’s personality and character, but since it could be potentially misused in that way, I figured that the tags, which form the basis of the system, should reflect the difference between people’s judgment and what one could statistically define as the “standard” judgment.

Instead of using regular tags the system would allow users to use weighed tags. For example, what I think is funny may be boring to 70% of the people. So my “funny” tag should count less than another person’s “funny” tag if that person has a much more mainstream humor. To teach that to the system, users would go through an online feedback test where random scenes are shown and each user has to tell the system what he/she think of each scene by picking one of the available tags that describe the scene. Once that test has been done with a large enough population of users, those who come out in the middle of the curve for a given tag, e.g. funny, would have the most weight assigned to their use of that tag to describe others (i.e. 1.0) and those on either side of the curve (within the reference range) will have the least weight assigned to their use of that tag to describe others (i.e. 0.0), with each user in between (on both sides of the curve) having his/her use of that tag assigned a weight that is in between the maximum weight and the minimum weight depending on how far they are from the median. This way when 1000 people think that someone is funny the system will add the total weight of their “funny” tags so that if their sense of humor (plural) is tightly distributed around the median then the total score for their combined judgment will be closer to 1000 but if they mostly have odd humor the total score would be much less, e.g. 100. This way if you discover that someone you’ve just met has been described with a “funny” score of 1000 then you can think of it as if 1000 people with “standard” judgment thought that person was funny. In other words, the total score would be given in units of standard judgment.

The statistical technique described here is very simple and it can be more elaborate, e.g. having additional user-behavior-based weighing factors.

A system like the one suggested here will allow us to make good choices (about whom we pick as our friends or business partners) quickly and reliably.

This could lead to a safer, happier and more productive society (Well, at least in theory.)

Links

1. About farlane (the reader who suggested the idea.)
2. Farlane’s comment where this idea was suggested.
3. The “Hunter Gatherer” post that lured farlane to this blog.
4. The post where tagging of objects (and people) in the [virtual] world was mentioned.

Tags:

Web 2.0, Web 2.0, Where 2.0, Where 2.0, social networking, Trends, Who 2.0, facial recognition, tagging, Startup