Month: December 2008

Note: this post is cross-posted at the Panjiva blog, which discusses issues affecting the global trade community. I’ve recently joined Panjiva’s advisory board (alongside Panjiva investor and reknowned economist Larry Summers), and I’m proud to be helping this new venture transform global trade by providing an unprecedented level of transparency about the strengths and weaknesses of companies engaged in it. Learn more about Panjiva at their web site or blog.

While I’m a neophyte on matters of global trade (fortunately fellow MIT alum and Panjiva investor Larry Summers is a bit more qualified on those matters), I do know a thing or to about how people interact with information. So it’s my delight to share a short series of posts on the macroeconomics of information and attention.

In Brief Principles of Macroeconomics, Greg Mankiw lists ten principles of economics that he divides into three groups:

How People Make Decisions

• People Face Tradeoffs.
• The Cost of Something is What You Give Up to Get It.
• Rational People Think at the Margin.
• People Respond to Incentives.

How the Economy Works as A Whole

• Trade Can Make Everyone Better Off.
• Markets Are Usually a Good Way to Organize Economic Activity.
• Governments Can Sometimes Improve Market Outcomes.

How People Interact

• A Country’s Standard of Living Depends on Its Ability to Produce Goods and Services.
• Prices Rise When the Government Prints Too Much Money.
• Society Faces a Short-Run Tradeoff Between Inflation and Unemployment.
  

Nobel Laureate Herb Simon articulated the concept of an attention economy in his 1971 article, “Designing Organizations for an Information-Rich World”:

in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.

In the next few posts, I’ll try to apply Mankiw’s principles to Simon’s conception of an attention economy to establish a macroeconomics of information and attention.

Continue: How People Make Decisions

Today I delivered an internal presentation at Endeca entitled “What You Need To Know About Social Media” with the goal of setting a baseline of what every technologist should know about this brave new world.

As proof that I drink my own kool-aid / eat my own dog food, I’m offering it here for public consumption. I suspect that a lot of it will be familiar to readers here, but you never know. I also encourage you to re-use this presentation in your own organizations to convince skeptics that social media are not just a bunch of hype.

Enjoy!

A co-worker tipped me off to a public, non-profit service that deserves all the publicity it can get. It’s called Public.Resource.Org, run by technologist and public domain advocate Carl Malamud, and devoted to “making [U.S.] government information more accessible”.

Not sold on the value of this service yet? Consider this example of their good deeds.

Public Access to Court Electronic Records (PACER) is an electronic public access service that allows users to obtain case and docket information from Federal Appellate, District and Bankruptcy courts, and the U.S. Party/Case Index via the Internet. These documents are works of the United States government and are in the public domain. But, for reasons that have no place in a 21st century democratic government, PACER charges $0.08 / page to download copies of these records–more than most of us pay for analog photocopying!

Enter the PACER recycling program, run by Public.Resource.Org:

Just upload all your PACER Documents to our recycling bin. Click on the recycle bin and you’ll be presented with a dialogue to choose files to upload. Then, just hit the “Start Upload” button and you’ll hear the sounds of progress as your documents get reinjected into the public domain.

We’ll take the documents, look at them, and then put them onto bulk.resource.org/courts.gov/pacer for future distribution. This is a manual process and you won’t see your documents show up right away. But, over time, we hope to accumulate a significant database of PACER Documents.

They claim to have saved $9,104.08 so far. That’s hardly enough to, say, bail out the auto industry, but it’s a step in the right direction. More importantly, efforts like this instill a culture I wish we could take for granted–namely, that public government documents should be generally available to the citizenry. Like most technologists, I have a libertarian streak, and I’m the first to defend the private sector. But this is a case where the goods themselves belong to the public. No one should profit at the expense of an informed citizenry.

p.s. Perhaps this effort will interest people trying to assemble corpora for information retreival research.

I recently blogged about sofware agents, mostly musing about how to reconcile their inherent rationality with our lack thereof as human beings.

But today I noticed an article by John Markoff in the New York Times entitled “A Software Secretary That Takes Charge “, which considers some companies trying to build services based on such agents. The article called my attention to the recent death of AI pioneer Oliver Selfridge, who coined the term “intelligent agents” and devoted much of his career to trying to make them a reality.

Markoff notes that “efforts to build useful computerized assistants have consistently ended in failure”, which raises the question of why any student of history is still investing in this area. Markoff quotes an answer from Rearden Commerce founder / CEO Patrick Grady:

The promise of the Web 2.0 era of the Internet has been the interconnection of Web services. Mr. Grady says he has a far easier task today because the heavy lifting has been done by others.

“This is the connective tissue that sits on top of the Web and brings you more than the sum of the parts,” he said. “I set out to deliver on the longstanding ‘holy grail of user-centric computing,’ a ‘personal Internet assistant.’”

In other words, intelligent agents are possible now because of Web 2.0 and service-oriented architecture. An interesting theory–and I can certainly accept it in theory. But I’m curious how it plays out in practice. It seems to me that there’s a lot of “heavy lifting” still waiting to be done.

In a post today entitled “The joke of advertising on social media“, Steve Hodson goes through some familiar territory in the challenges social media companies faces in coming up with a viable business model:

• Social media is built around the idyllic concept that content should be free.
• Social media companies insist to advertisers that they have a willing flock to make their millions off of.
• But early adopters of social media behave like a swarm of pissed off wasps at the mere mention of advertising.
• Case in point: many people (myself included) rejected Google’s Chrome browser because it didn’t support an ad blocking plug-in.

So far his argument is–or should be–uncontroversial. And I agree with his prediction that “Social media in all its goodness will only survive if people like you and me can contribute but know that we can pay our bills at the same time.” There’s no such thing as a free lunch, and bloggers cannot live by page views alone.

But then he continues: “users of social media…have to stop being so greedy with their attention span.” This is a slightly different take on the “no free lunch” argument than I expected. If I understand him correctly, he is suggesting that we click on ads out of a sense of obligation, to make up for the fact that we are receiving content for free.

If my understanding is accurate, then I have to part ways with Hodson. If bloggers want to put out a tip jar and encourage readers to leave tips, that’s fine. And if they want to make it clear that clicking on an ad is, from their perspective, equivalent to leaving a few pennies as a tip, that’s fine too. There’s nothing wrong with asking users to be generous. 

But the whole point of tipping is that it isn’t out of a sense of obligation. Tips are supposed to be on top of paying a fair market value for services rendered. I know that isn’t always the case; in the United States, the minimum wage law calls out the existence of occupations where tips customarily represent a substantial portion of an employee’s income. But that doesn’t make it a good idea, let alone an example for new markets.

I realize that individual bloggers are hardly in a position to unilaterally change the prevailing business model accepted by a culture where people expect information to be free. And so we run through the sequence Hodson describes, and everyone is frustrated: underpaid writers, advertising-inundated readers, and profitless investors. But at least reality is finally sinking in, and I am personally optimistic that the days are numbered for the dominance of the advertising-supported model. Call it an audacity of hope.

As regular readers know, I am strong advocate for transparency in any system where people interact with machines. In fact, such transparency is a core HCIR value, since communication depends on the clarity with which a message traverses the noisy channel of human-computer interaction.

So I was a bit taken aback by a recent blog post in which Stephen Arnold seemed to attach the notion that an effective search engine could be transparent. But a more careful reading led me to believe that he’s reacting, perhaps a bit too cynically, to the increased currency that the word “transparency” has in marketing literature.

Let me try to cut through the marketing hype. Transparency is more than a buzzword to sell software. It is a core value than imposes significant constraints on how a system can act. If a system is not bound by transparency, then it is free to respond to user inputs arbitrarily, unconstrained by any requirement to offer users insight into the basis for its response. In contrast, a transparent system must produce user-consumable explanations of its output. A transparent system can’t get away with saying “if I told you, I’d have to kill you.”

In fact, a transparent system might have to reject a possible response to a user because it can’t present an explanation for the response that the user will understand. For this reason, some machine learning purists reject transparency as overly constraining, and prefer approaches that simply optimize an objective function that, in all likelihood, is completely opaque to the user–and possibly even to the system developer.

Why is transparency so important in systems that support information seeking, i.e., search and information retrieval systems? Because any systems that requires people to interact non-trivially with machines are fraught with communication challenges. Best-effort attempts to extrapolate user intent from a query–often a query comprised of only a couple of words–are beyond AI-hard; they’re ESP-hard. While all systems have to accept that they’ll misread users’ intention a significant fraction of the time, transparent systems at least offer users the opportunity to worth with the system to get back on track.

To be clear, implementing transparency isn’t simple. It’s like Mark Twain said: short letters are often harder to write than long ones. In a related vein, the world’s greatest minds aren’t always the world’s greatest communicators. And what holds true for people holds even more so for machines (or the people for program them): it’s hard to develop algorithms that deliver useful results and provide human-consumable explanations for them.

I understand Arnold’s frustration with vendors. And I won’t claim that Endeca always gets it right, though I think (and have been told) that we do better than many in communicating how our technology works. But there is no question in my mind that information seeking support systems have to become more transparent if we want them to work in the real world.