Author Archives: riedl

I saw an article on Read/WriteWeb today about cofundus.org, a web site where people can chip in $ to get open source software they’d like developed.  The idea is that a bunch of people chip in money, and then together spec out a pieces of software.  Then programmers offer proposals for developing the software.  The funders vote on a programmer to take on the job.  The programmer the gets paid if the funders agree he’s developed the right software, which must be open source licensed.

So far the $ are pretty small, but it would be interesting to see this idea scale up …

John 

One of the interesting arms races is between google and all the services that seek to increase page rank.  (I found particularly fascinating on this page the comment from a seo ("search engine optimizer") that "Google created this market and now they try to destroy it".)  Basically, lots of people are offering to adjust pagerank scores for web sites for money.  They work in different ways, but one of the easiest is to have farms of link pages, and work hard to get other people to link to your link farm.  Then, anyone who pays to get on one of your link pages gets a nice boost in pagerank. 

It will be interesting to see how this plays out over the long term.  Has anyone seen research that describes the relative strengths and weaknesses of the two positions in this arms race?

 John

There’s an interesting blog entry in the datamining blog about the extent to which free sites are motivated to offer good customer service.  The heart of the argument is that if you’re a freeloader on a site on which the bills are being paid by a small percentage of subscribers, you’re likely to see your service suffer.

The deeper argument, though, is that  sites that are sticky are likely to be able to get away with treating their freeloading customers worse over time than sites that are not sticky.  For instance, if part of the reason that you like to shop at Amazon is the recommendations they give you, you can’t switch to a different store easily, because they won’t be able to provide recommendations that are as good.  There are two reasons for this: first of all, they won’t have a personal profile for you, and second, they won’t have as much data about other customers’ behavior.  Because of this stickiness, Amazon should eventually be able to collect higher rents than other online stores.

One interesting solution to both of these problems would be portable profiles.  Consumers could demand that the businesses they buy from accept a profile in a standard format, and export useful information to that standard format.  (Check out the P3P proposal for an example of what such a profile might look like.) Then, customers could easily take their data with them to whatever business they wish to shop at.  For instance, at MovieLens we often get Netflix customers who ask us to import their Netflix profile, so they can use our recommendation engine on their Netflix data.  (We currently don’t support this, because we’re pretty sure doing so would be against Netflix’ terms of use.  We’d love for them to give us permission, though!)

There’s also an aside about the risk of news aggregators being in charge of what we see. The idea is that a news aggregator might refuse to broadly disseminate news that would oppose its interests.  This possibility returns us to an interesting recommender systems problem: how can the user of a recommendation system know that the system is making decisions that are in his or her best interests?  Is there a zero knowledge proof that might help?

John 

Here’s one of many articles on the battle between Apple and iPhone hackers over the ability to run their applications on the iPhone. Apple seems to be badly misreading the current state of the world.  Hello!  We’re in Web 2.0 here!  The breakthrough is Facebook fielding a full-fledged API for its fans to develop their wild and crazy applications — and to share them with everyone else.  Yet, Apple is playing Microsoft, trying to lock down and protect their ability to deliver proprietary applications that their customers cannot build themselves, extend, or improve. 

Personally, I’m committed to the power of community-maintained resources; I won’t consider buying a device that is locked down like the iPhone and the ITunes Touch.  There’s something about knowing that the machine in your pocket is programmable that makes it more fun to carry — even if you end up not programming it yourself. 

John

http://www.engadget.com/2007/10/10/iphone-and-ipod-touch-v1-1-1-full-jailbreak-tested-confirmed/

Interesting Computer World article on the future of computer science.  A wide range of views.  The ones that impressed me the most were John Canny’s thoughts on what it is that has made computer science uninteresting to so many people.  He argues in several comments that computer science has chosen the path of not caring about social relevance, and that that is now costing us in how interesting we are as a discipline of study, and how much impact we are having on the world.  He points out that much of computer science is just working hard to be a hand-maiden to other sciences.  

I found his arguments compelling.  The suggested fix of moving towards understanding how computers can provide applications that deeply fit what people want to do in their lives is critical.  Right now most computer science programs don’t want to think about users and their problems.  Why is that?  How can it be fixed?

In a New York Times article on the same topic, Jon Kleinberg is quoted about the vast opportunity computer networks are creating for measuring social networks.  Of course, he’s right about the value of the social networks, but I think focusing on the measuring misses the big picture: computers are making possible radical new notions of community that are altering or replacing our traditional geography-bound notions of community.

In a Nature issue devoted to the future of computing, Stephen H. Muggleton, one commentator, discusses the use of computers for advancing biology research.  He
discusses many examples of the use of computer algorithms to improve
the ability of scientists to form and test hypotheses.  He argues that
interfaces to these algorithms will eventually enable human scientists
to perform in a way that will demonstrate "Exceeding human limits".

What do you think the future of computing will bring?

John