When the renowned computer scientist Jim Gray went missing at sea last week, the internet community rose up to help in the search in any way that they could. One of the more ingenious, although unfortunately not successful, methods employed was to upload thousands of satellite photos of the area where he disappeared to the Web and ask volunteers to examine them for objects that might be his sail boat.

This massive online manhunt was enabled by Amazon.com’s Mechanical Turk service.

Mechanical Turk, named after the chess-playing mannequin illusion of the 18th century, is a web application that enables “artificial artificial intellgence” by dividing up large jobs such as photographic analysis or data entry into chunks that can be performed by people over the Internet. The basic idea is that certain types of jobs, such as jobs involving pattern recognition or identification of objects in photographs, are more easily and accurately performed by humans than computers. If these types of jobs also involve working with large amounts of data, splitting the work up among large numbers of humans can be a more efficient (read: cheaper) method of doing the work than writing or utilizing specialized artificial intelligence software.

Services such as Mechanical Turk are being touted by some as an important development in harnessing the “collective intelligence.” Some have gone so far as to suggest that such human-powered Web applications represent a new paradigm and possibly a new version number of the Web and a new way of doing business on the Web. Frankly, I love the idea of being able to employ volunteers to search photographs for a missing person, but I’m disturbed by the idea of using random Web surfers to boost your corporate profits.

Mechanical Turk allows anyone to create a job that they’d like other people to complete on the Web. The creator of the job can specify the amount they’ll pay for each HIT (Human Intelligence Task). Typical tasks involve looking at photos and identifying certain objects in them, or transcribing podcasts. Typical payments range from 1 cent to $1 per HIT. You don’t get paid for your work unless it’s accepted by the creator of the task.

At first glance, these rates and types of tasks looked to me like the digital equivalent of sweatshop labor. Companies are farming out jobs that are too boring, or that would be too costly to have someone on payroll do, to be done by the ‘collective intelligence’ for very low wages. I decided to try out a few tasks in order to try to get a better feeling for whether it was possible to actually make a living off of this type of work, or if it is really just exploitation and the first step towards “The Matrix.”

At 10:00 AM, I sat down with my laptop and a cup of coffee and started in on my first workday at Mechanical Turk.

I began by going to the list of available HITs and sorting them highest paying first. I’m not cheap. The first HIT said it paid 96 cents, with a bonus of up to twice that for accuracy, and there was a qualification test. The ‘test’ turned out to be just clicking a checkbox and hitting a submit button. So far so good.

The task was to transcribe a 9 minute podcast. I’m a fairly fast typer, but I guessed that transcribing a podcast would take at least 3 times as long as the length of the podcast, and there was a style guide to follow too. In theory, if I were to complete the task perfectly, I could earn $2.88 [I actually ended up making $1.92].

In the interest of making the best possible use of my time, I started listening to the podcast – something about making money on eBay – while looking over the style guide.

At 10:15, I started my work.

At 11:20, after typing 1570 words, I finished my first job. I had grossly underestimated the amount of work it would take to transcribe 9 minutes of audio. So far, the best case scenario was that I was making slightly under $3/hour. I decided to move on to my next HIT.

The next task I found was a simple Google bombing job. I was to search for a certain phrase on Google and then click on a certain company’s link. The idea (not spoken in the HIT description, of course) is that the cumulative effect of hundreds of people doing this same search will improve that company’s rank in Google. I refused this one on ethical grounds.

Several other jobs involved registering on different sites, various search engine scams, Google Adword fraud, and a lot of people looking for creative people to give them ideas or write content for their sites for 25 cents. At 11:30, I became so repulsed by the nature of the majority of the jobs, and by the piddly amounts people were willing to pay for my writing talents that I decided to quit my job as a human CPU.

Yelling “Take this job and shove it!” to my laptop wasn’t very satisfying, but it was actually the first time I had ever spoken those words when quitting a job, so that was one positive aspect of the experience.

Jim Gray is known for his work with databases, and several very large databases in particular, including, ironically, Microsoft’s database of satellite images, Teraserver. He also was the recipient of a Turing Award, which is named after Alan Turing, who famously created the Turing Test of artificial intelligence.

I never met him, but I suspect that Dr. Gray would agree with me that the future of the Internet should not be one in which human intelligence is devalued simply because we now have the technology to give 10 cents to anyone who’s willing to do our most menial tasks for that amount.

Tragically, as of this writing, it seems very unlikely that Jim Gray will return. The amazing volunteer effort to find him, however, stands as a testament to the power of the Internet community and of the Web to bring people together. My experience today with the for-profit uses of the same technology, however, reminds me that the collective intelligence aspect of Web 2.0 also enables less noble endeavors.

While searching the Web recently to find out what other pundits believe Web 3.0 will come to mean, I found a blog post by Stephen Baker on BusinessWeek.com in which he says that his “assignment in Monaco was to lead a panel in defining Web 3.0.” After summarizing the ideas that his panel came up with, he ends his post by asking readers what they think. My favorite comment on this post (from ‘bob’) simply says “I think you all wasted your time.”

While it’s very doubtful that a trip to Monaco could be considered a waste of time (especially if it’s paid for by someone else), I certainly agree that serious discussions of questions as meaningless as “What features will the next version of the Web include?” are largely a waste of time concocted by marketers and conference-planners. The people who will build what will come to be called ‘Web 3.0’ don’t have these sorts of discussions. So, here I go again.

The fact of the matter is that most people define Web 3.0 in terms of what they’d like to see happen. Some say it will be defined by the widespread adoption of SVG, some say the key concept is “software as a service,” some say Web 3.0 will be when we fix the bugs in Web 2.0.

Personally, I believe that one of the biggest unsolved issues faced by the Web right now involves trust. Wikipedia, Google, Yahoo! Answers, and hundreds of other sites that are heralded as models of Web 2.0-ness all rely on user-contributed content. The theory goes that a crowd of people is smarter than the old-style “gurus.” Whether or not that’s true is a topic for another article (and maybe an experiment). The relevant issue that I think Web 3.0 will deal with is “Who do you sue when the Web 2.0 community gives you bad information?”

Traditional media companies have rules governing things like fact-checking, use of anonymous sources, printing rumors, and separating advertising from editorial. At some point in the past, they even followed these rules.

Today, this isn’t the case, and the media likes to blame it on the free-wheeling ways of the Internet. The logic goes like this: “Someone published this irresponsible or wrong information on the Internet, and so we in the mainstream media can report on the fact that someone reported this information on the Internet. If this information later turns out to be false, don’t blame us, blame the Web 2.0 bloggers.”

However, because many of these bloggers are anonymous or just repeating things they heard on some other blog, there’s no one in particular for mainstream media outlets to point a finger to when they get in trouble for reporting something they read on the Internet. They want this situation remedied pronto!

Clarifying who should be blamed will be the driving force behind Web 3.0. Just like Web 2.0 has it’s signature technologies (AJAX, RSS, Mash-ups), Web 3.0 will have its darling protocols and acronyms. The hot technologies in Web 3.0 will be RFID, biometric identification, and digital certificates. Logging into a Web site using your fingerprint will be marketed as a handy way to not have to remember passwords, but it will also provide solid proof that you were the person who posted that damaging information about that multinational corporation.

Web 3.0 identification technologies will also be used to reduce or eliminate spam. By blocking all email that isn’t signed with a digital signature, you could eliminate 100% of the spam you get. Unfortunately, it would also block all of your legitimate mail, because almost no one uses digital signatures today.

In Web 3.0, more people will start to use digital signatures, which will make everyone start using digital signatures for fear that if they don’t then their emails to or from their old high school sweethearts will get blocked.

Real Web ID will enable new forms of e-commerce, eliminate certain types of e-crime and piracy of electronic media, and reduce the number of fake Myspace profiles. Online privacy advocates will redouble their efforts in response.

Several years into the Web 3.0 revolution, the general population will begin to look for something else…some sort of improvement to Web 3.0. Right at about the point when Web 3.0 has outlived its usefulness, the conference planners, pundits, and marketers will get together somewhere beautiful and start to think of a name for what will come after Web 3.0. I’ll reveal my theories on what this thing might be called and what it might look like in a future column.