Month: November 2008

Fresh from reporting why he switched from Firefox to Chrome, CNET’s Stephen Shankland reports that Chrome has a larger market share than he expected:

For comparison, here are the stats for The Noisy Channel, based on the last 30 days (note that stats don’t reflects users reading the blog through RSS readers):

• Firefox: 58.4%
• Internet Explorer: 19.2%
• Safari: 9.9%
• Chrome: 6.8%
• Mobile (assorted): 3.0%
• Opera: 1.6%
• Mozilla 1.x: 1.1%
• Konqueror: 0.1%

Not quite the same mix as Shankland is seeing at CNET, but Chrome’s share is respectable.

Note: the Chrome market share may be slightly skewed by my using Chrome to post, since I’ve found it handles my WordPress web client better than Firefox. I still am faithful to Firefox for everything else. As someone posted recently, no Adblock = no Chrome.

Even so, I’m sure that doesn’t account for more than 1% of traffic. A noticable minority of Noisy Channel readers are giving Chrome a chance.

Bruce Schneier had a a column in the Wall Street Journal a few days ago entitled “Why Obama Should Keep His BlackBerry – But Won’t“. He uses Obama’s BlackBerry dilemma to make the broader point that, we’ve moved from an assumption of privacy to a world where everything is recorded. His argument is that, rather than trying to turn back the clock, we need to adjust our legal and cultural norms to the reality of our digital trails. (via Vincent Gable’s comment at whydoeseverythingsuck.com)

I’m reminded of these thoughts from Danah Boyd’s Master’s Thesis on managing identity in a digital world:

Although it may seem advantageous to have historical archives of social interactions, these archives take the interactions out of the situational context in which they were located. For example, by using a search engine to access Usenet, people are able to glimpse at messages removed from the conversational thread. Even with the complete archive, one is reading a historical document of a conversation without being aware of the temporal aspect of the situation. As such, archived data presents a different image to a viewer who is accessing it out of the context in which it was created.

Digital archives allow for situational context to collapse with ease. Just as people can access the information without the full context, they can search for information which, when presented, suggests that two different bits of information are related. For example, by searching for an individual’s name, a user can acquire a glimpse at the individual’s digital presentation across many different situations without seeing any of this in context. In effect, digital tools place massive details at one’s fingerprint, thereby enabling anyone to have immediate access to all libraries, public records and other such data. While advantageous for those seeking information, this provides new challenges for those producing sociable data. Although the web is inherently public, people have a notion that they are only performing to a given context at a given time. Additionally, they are accustomed to having control over the data that they provide to strangers. Thus, people must learn to adjust their presentation with the understanding that search engines can collapse any data at any period of time. 

And Danah wrote those words seven years ago, before Facebook and Twitter invented micro-blogging and inspired people to voluntarily live in virtual fishbowls. I’ve blogged about the end of privacy through difficulty, but it seems we’re heading in a direction of no privacy at all. It will be interesting to see how the next generation frames this discussion.

Thanks to Amir Michail for a tweet that alerted me to a technical report by Ingmar Weber, Stephen Robertson, and Milan Vojnovic on “Rethinking the ESP Game“.

The ESP Game is a human-based computation game designed by Luis Von Ahn to tag images. Part of the his motivation for developing the game was that image tagging was too hard for machines. Hence, he decided to make it fun for humans to volunteer their own labor to the cause.

But it turns out that, once humans have supplied some initial labels to the game, a machine can take over. Here is the abstract for the technical report:

The ESP Game was designed to harvest human intelligence to assign labels to images – a task which is still difficult for even the most advanced systems in image processing. However, the ESP Game as it is currently implemented encourages players to assign “obvious” labels, which are most likely to lead to an agreement with the partner. But these labels can often be deduced from the labels already present using an appropriate language model and such labels therefore add only little information to the system.

We present a language model which, given enough instances of labeled images as training data, can assign probabilities to the next label to be added. This model is then used in a program, which plays the ESP game without looking at the image. Even without any understanding of the actual image, the program manages to agree with the randomly assigned human partner on a label for 69% of all images, and for 81% of images which have at least one “off-limits” term assigned to them. We then show how, given any generative probabilistic model, the scoring system for the ESP game can be redesigned to encourage users to add less predictable labels, thereby leading to a collection of informative, high entropy tag sets. Finally, we discuss a number of other possible redesign options to improve the quality of the collected labels.

Daniel Lemire commented recently that spammers may help make AI a reality. It’s interesting to see how yesterday’s Turing Test has become today’s CAPTCHA, and the competition between humans and machines is making both smarter.

I’m an avid LinkedIn user and fancy myself an expert on search, so I was excited today to see that LinkedIn has officially launched its new search platform. I recommend you watch the four-minute video below to get an overview of the new features.

First, the good news. The interface is slick and streamlined as promised. Type-ahead works smoothly, though it is restricted to the names of your contacts. The in-page options for refining your query by changing the sort or adding parameters are a welcome improvement to their previous interface, which took you to another page to make query modifications. And the presentation of results is clean and effective. Finally, there is a “saved searches” feature that also acts as a running query to alert you to new results. This is a great feature for recruiters.

Now, the bad news. There is still no support for exploratory search. I get 1,198 results when I search for Endeca (your results will depend on your personal network). That’s far too many to look through if I’m trying to establish contacts at a company, and sorting by relevance or relationship strength has limited value. What I’d really like is an overview of those 1,198 people that I can explore–by location, job title, their present and past relationship to Endeca, etc. Faceted search would certainly be more helpful than the unguided parametric search they offer.

I don’t mean to damn LinkedIn with faint praise–this is a significant improvement from the experience they offered before. But I wish that they would recognize the importance of exploratory search in the context of a professional networking site. As it is, they are leaving so much on the table.