One of the great benefits of practicing, as Daniel Lemire calls it, open scholarship is that I have many opportunities to see how ideas translate across the research / practice divide. In particular, I obtain invaluable feedback on the accuracy and effectiveness of that translation process.
A few days ago, I was exchanging email with serial entrepreneur Chris Dixon about human-computer information retrieval (HCIR). He’d just looked through the accepted submissions list for HCIR 2009 and said, if I may paraphrase: this is great stuff, but it needs to be better communicated for broader consumption. I quickly shot back a reaction that I’ll excerpt here (when in doubt, make it public!):
At some level it’s blindingly obvious: to err is human, to really screw up takes a computer. The HealthBase fiasco isn’t a shocker: lots of people are skeptical of pure AI approaches.
What people don’t get is that you can work to optimize the division of labor. I’m evangelizing it in places like Technology Review – a bit more mainstream than my blog. But ultimately the message has to resonate with entrepreneurs and investors who will make that vision a reality. Endeca is all about HCIR. Bing is a …
One of the great benefits of practicing, as Daniel Lemire calls it, open scholarship is that I have many opportunities to see how ideas translate across the research / practice divide. In particular, I obtain invaluable feedback on the accuracy and effectiveness of that translation process.
A few days ago, I was exchanging email with serial entrepreneur Chris Dixon about human-computer information retrieval (HCIR). He’d just looked through the accepted submissions list for HCIR 2009 and said, if I may paraphrase: this is great stuff, but it needs to be better communicated for broader consumption. I quickly shot back a reaction that I’ll excerpt here (when in doubt, make it public!):
At some level it’s blindingly obvious: to err is human, to really screw up takes a computer. The HealthBase fiasco isn’t a shocker: lots of people are skeptical of pure AI approaches.
What people don’t get is that you can work to optimize the division of labor. I’m evangelizing it in places like Technology Review – a bit more mainstream than my blog. But ultimately the message has to resonate with entrepreneurs and investors who will make that vision a reality. Endeca is all about HCIR. Bing is a step in the right direction for the open web. But there’s a long way to go.
His response: that’s a lot more consumable that any other description of HCIR he’d seen to date (and he’s a regular reader here!). Having just finished reading Steve Blank’s Four Steps to the Epiphany, I appreciate his point: in a new market, the most critical priority is educating the potential customers.
As a number of us prepare for the HCIR 2009 workshop, that’s something to keep in mind. There’s a natural tension between rigorous scholarship and mass communication, but some have the greatest scholars (e.g., Richard Feynman and Linus Pauling) have shown the way for us mere mortals. Indeed, in a field as cross-disciplinary as HCIR, we would do well to make our work and vision as broadly consumable as possible, albeit without oversimplifying it to the point that it is vapid or even misleading.
Generally speaking, I blog in order to convince people that some of the esoteric ideas I encounter – and the occasional ideas I am fortunate enough to conceive – are worthy of broader consideration. I started blogging in order to bring greater visibility to HCIR – to convince people that the choice between human and machine responsibility is a false dichotomy in almost every aspect of the information seeking process.
In grade school, I learned that division of labor is the cornerstone of civilization – and perhaps our adaptive process of allocating effort our greatest achievement as a species. As machines play an increasingly important role in our lives – and serve as the lenses through which seek and consume almost all information – it is key that we not forget our roots. Let us be neither Luddites nor passive participants, but rather let us help computers help us.
