Today's New York Times has an article by John Markoff called On a Small Screen, Just the Salient Stuff. It argues that the design constraints of the iPhone (and of mobile devices in general) lead to an improved user experience, since site designers do a better job of focusing on the information that users will find relevant.
Of course, on a blog entitled The Noisy Channel, I can't help praising approaches that strive to improve the signal-to-noise ratio in information seeking applications. And I'm glad to see them quoting Ben Shneiderman, a colleague of mine at the University of Maryland who has spent much of his career focusing on HCIR issues.
Still, I think they could have taken the idea much further. Their discussion of more efficient or ergonomic use of real estate boils down to stripping extraneous content (a good idea, but hardly novel), and making sites vertically oriented (i.e., no horizontal scrolling). They don't consider the question of what information is best to present in the limited space--which, in my mind, is the most important question to consider as we optimize interaction. Indeed, many of the questions raised by small screens also apply to other interfaces, such as voice.
Perhaps I am asking too much to expect them to call out the extreme inefficiency of ranked lists, compared to summarization-oriented approaches. Certainly the mobile space opens great opportunities for someone to get this right on the web.
Showing posts with label Usability. Show all posts
Showing posts with label Usability. Show all posts
Sunday, July 13, 2008
Friday, July 11, 2008
Psychology of Intelligence Analysis
In the course of working with some of Endeca's more interesting clients, I started reading up on how the intelligence agencies address the challenges of making decisions, especially in the face of incomplete and contradictory evidence. I ran into a book called Psychology of Intelligence Analysis by former CIA analyst Richards Heuer. The entire book is available online, or you can hunt down a hard copy of the out-of-print book from your favorite used book seller.
Given the mixed record of the intelligence agencies over the past few decades, you might be wondering if the CIA is the best source for learning how to analyze intelligence. But this book is a gem. Even if the agencies don't always practice what they preach (and the book makes a good case as to why), the book is an excellent tour through the literature on judgment and decision making.
If you're already familiar with work by Herb Simon, Danny Kahneman, and Amos Tversky, then a lot of the ground he covers will be familiar--especially the third of the book that enumerates cognitive biases. I'm a big fan of the judgment and decision making literature myself. But I still found some great nuggets, particularly Chapter 8 on Analysis of Competing Hypotheses. Unlike most of the literature that focuses exclusively on demonstrating our systematic departures from rationality, Heuer hopes offer at least some constructive advice.
As someone who builds tools to help people make decisions using information that not only may be incomplete and contradictory, but also challenging to find in the first place, I'm very sensitive to how people's cognitive biases affect their ability to use these tools effectively. One of the HCIR '07 presentations by Jolie Martin and Michael Norton (who have worked with Max Bazerman) showed how the manner in which information was partitioned on retail web sites drove decisions, i.e., re-organizing the same information affected consumer's decision process.
It may be tempting for us on the software side to wash our hands of our users' cognitive biases. But such an approach would be short-sighted. As Heuer shows in his well-researched book, people not only have cognitive biases, but are unable to counter those biases simply by being made aware of them. Hence, if software tools are to help people make effective decisions, it is the job of us tool builders to build with those biases in mind, and to support processes like Analysis of Competing Hypotheses that try to compensate for human bias.
Given the mixed record of the intelligence agencies over the past few decades, you might be wondering if the CIA is the best source for learning how to analyze intelligence. But this book is a gem. Even if the agencies don't always practice what they preach (and the book makes a good case as to why), the book is an excellent tour through the literature on judgment and decision making.
If you're already familiar with work by Herb Simon, Danny Kahneman, and Amos Tversky, then a lot of the ground he covers will be familiar--especially the third of the book that enumerates cognitive biases. I'm a big fan of the judgment and decision making literature myself. But I still found some great nuggets, particularly Chapter 8 on Analysis of Competing Hypotheses. Unlike most of the literature that focuses exclusively on demonstrating our systematic departures from rationality, Heuer hopes offer at least some constructive advice.
As someone who builds tools to help people make decisions using information that not only may be incomplete and contradictory, but also challenging to find in the first place, I'm very sensitive to how people's cognitive biases affect their ability to use these tools effectively. One of the HCIR '07 presentations by Jolie Martin and Michael Norton (who have worked with Max Bazerman) showed how the manner in which information was partitioned on retail web sites drove decisions, i.e., re-organizing the same information affected consumer's decision process.
It may be tempting for us on the software side to wash our hands of our users' cognitive biases. But such an approach would be short-sighted. As Heuer shows in his well-researched book, people not only have cognitive biases, but are unable to counter those biases simply by being made aware of them. Hence, if software tools are to help people make effective decisions, it is the job of us tool builders to build with those biases in mind, and to support processes like Analysis of Competing Hypotheses that try to compensate for human bias.
Thursday, April 24, 2008
Database Usability
Just as I was digesting Jeff Naughton's presentation at DB/IR day, a colleague at Endeca emailed me the keynote that H. V. Jagadish (University of Michigan) presented at SIGMOD '07 on making database systems usable. He enumerates the familiar pain points of today's database systems: confusing schemas, too many choices to make, unexpected--and unexplained--system behavior, and too high a cost for initial creation. He proposes "systems that reflect the user's model of the data, rather than forcing the data to fit a particular model."
As with Jeff's presentation, the main take-away here is a framework (though both he and Jeff have taken initial steps to address the problems they describe). As a practitioner, I'm most encouraged by the fact that database researchers, like information retrieval researchers, are increasingly recognizing the importance of users.
As with Jeff's presentation, the main take-away here is a framework (though both he and Jeff have taken initial steps to address the problems they describe). As a practitioner, I'm most encouraged by the fact that database researchers, like information retrieval researchers, are increasingly recognizing the importance of users.
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Showing posts with label Usability. Show all posts
Showing posts with label Usability. Show all posts
Sunday, July 13, 2008
Small is Beautiful
Today's New York Times has an article by John Markoff called On a Small Screen, Just the Salient Stuff. It argues that the design constraints of the iPhone (and of mobile devices in general) lead to an improved user experience, since site designers do a better job of focusing on the information that users will find relevant.
Of course, on a blog entitled The Noisy Channel, I can't help praising approaches that strive to improve the signal-to-noise ratio in information seeking applications. And I'm glad to see them quoting Ben Shneiderman, a colleague of mine at the University of Maryland who has spent much of his career focusing on HCIR issues.
Still, I think they could have taken the idea much further. Their discussion of more efficient or ergonomic use of real estate boils down to stripping extraneous content (a good idea, but hardly novel), and making sites vertically oriented (i.e., no horizontal scrolling). They don't consider the question of what information is best to present in the limited space--which, in my mind, is the most important question to consider as we optimize interaction. Indeed, many of the questions raised by small screens also apply to other interfaces, such as voice.
Perhaps I am asking too much to expect them to call out the extreme inefficiency of ranked lists, compared to summarization-oriented approaches. Certainly the mobile space opens great opportunities for someone to get this right on the web.
Of course, on a blog entitled The Noisy Channel, I can't help praising approaches that strive to improve the signal-to-noise ratio in information seeking applications. And I'm glad to see them quoting Ben Shneiderman, a colleague of mine at the University of Maryland who has spent much of his career focusing on HCIR issues.
Still, I think they could have taken the idea much further. Their discussion of more efficient or ergonomic use of real estate boils down to stripping extraneous content (a good idea, but hardly novel), and making sites vertically oriented (i.e., no horizontal scrolling). They don't consider the question of what information is best to present in the limited space--which, in my mind, is the most important question to consider as we optimize interaction. Indeed, many of the questions raised by small screens also apply to other interfaces, such as voice.
Perhaps I am asking too much to expect them to call out the extreme inefficiency of ranked lists, compared to summarization-oriented approaches. Certainly the mobile space opens great opportunities for someone to get this right on the web.
Friday, July 11, 2008
Psychology of Intelligence Analysis
In the course of working with some of Endeca's more interesting clients, I started reading up on how the intelligence agencies address the challenges of making decisions, especially in the face of incomplete and contradictory evidence. I ran into a book called Psychology of Intelligence Analysis by former CIA analyst Richards Heuer. The entire book is available online, or you can hunt down a hard copy of the out-of-print book from your favorite used book seller.
Given the mixed record of the intelligence agencies over the past few decades, you might be wondering if the CIA is the best source for learning how to analyze intelligence. But this book is a gem. Even if the agencies don't always practice what they preach (and the book makes a good case as to why), the book is an excellent tour through the literature on judgment and decision making.
If you're already familiar with work by Herb Simon, Danny Kahneman, and Amos Tversky, then a lot of the ground he covers will be familiar--especially the third of the book that enumerates cognitive biases. I'm a big fan of the judgment and decision making literature myself. But I still found some great nuggets, particularly Chapter 8 on Analysis of Competing Hypotheses. Unlike most of the literature that focuses exclusively on demonstrating our systematic departures from rationality, Heuer hopes offer at least some constructive advice.
As someone who builds tools to help people make decisions using information that not only may be incomplete and contradictory, but also challenging to find in the first place, I'm very sensitive to how people's cognitive biases affect their ability to use these tools effectively. One of the HCIR '07 presentations by Jolie Martin and Michael Norton (who have worked with Max Bazerman) showed how the manner in which information was partitioned on retail web sites drove decisions, i.e., re-organizing the same information affected consumer's decision process.
It may be tempting for us on the software side to wash our hands of our users' cognitive biases. But such an approach would be short-sighted. As Heuer shows in his well-researched book, people not only have cognitive biases, but are unable to counter those biases simply by being made aware of them. Hence, if software tools are to help people make effective decisions, it is the job of us tool builders to build with those biases in mind, and to support processes like Analysis of Competing Hypotheses that try to compensate for human bias.
Given the mixed record of the intelligence agencies over the past few decades, you might be wondering if the CIA is the best source for learning how to analyze intelligence. But this book is a gem. Even if the agencies don't always practice what they preach (and the book makes a good case as to why), the book is an excellent tour through the literature on judgment and decision making.
If you're already familiar with work by Herb Simon, Danny Kahneman, and Amos Tversky, then a lot of the ground he covers will be familiar--especially the third of the book that enumerates cognitive biases. I'm a big fan of the judgment and decision making literature myself. But I still found some great nuggets, particularly Chapter 8 on Analysis of Competing Hypotheses. Unlike most of the literature that focuses exclusively on demonstrating our systematic departures from rationality, Heuer hopes offer at least some constructive advice.
As someone who builds tools to help people make decisions using information that not only may be incomplete and contradictory, but also challenging to find in the first place, I'm very sensitive to how people's cognitive biases affect their ability to use these tools effectively. One of the HCIR '07 presentations by Jolie Martin and Michael Norton (who have worked with Max Bazerman) showed how the manner in which information was partitioned on retail web sites drove decisions, i.e., re-organizing the same information affected consumer's decision process.
It may be tempting for us on the software side to wash our hands of our users' cognitive biases. But such an approach would be short-sighted. As Heuer shows in his well-researched book, people not only have cognitive biases, but are unable to counter those biases simply by being made aware of them. Hence, if software tools are to help people make effective decisions, it is the job of us tool builders to build with those biases in mind, and to support processes like Analysis of Competing Hypotheses that try to compensate for human bias.
Thursday, April 24, 2008
Database Usability
Just as I was digesting Jeff Naughton's presentation at DB/IR day, a colleague at Endeca emailed me the keynote that H. V. Jagadish (University of Michigan) presented at SIGMOD '07 on making database systems usable. He enumerates the familiar pain points of today's database systems: confusing schemas, too many choices to make, unexpected--and unexplained--system behavior, and too high a cost for initial creation. He proposes "systems that reflect the user's model of the data, rather than forcing the data to fit a particular model."
As with Jeff's presentation, the main take-away here is a framework (though both he and Jeff have taken initial steps to address the problems they describe). As a practitioner, I'm most encouraged by the fact that database researchers, like information retrieval researchers, are increasingly recognizing the importance of users.
As with Jeff's presentation, the main take-away here is a framework (though both he and Jeff have taken initial steps to address the problems they describe). As a practitioner, I'm most encouraged by the fact that database researchers, like information retrieval researchers, are increasingly recognizing the importance of users.
Subscribe to:
Posts (Atom)
Showing posts with label Usability. Show all posts
Showing posts with label Usability. Show all posts
Sunday, July 13, 2008
Small is Beautiful
Today's New York Times has an article by John Markoff called On a Small Screen, Just the Salient Stuff. It argues that the design constraints of the iPhone (and of mobile devices in general) lead to an improved user experience, since site designers do a better job of focusing on the information that users will find relevant.
Of course, on a blog entitled The Noisy Channel, I can't help praising approaches that strive to improve the signal-to-noise ratio in information seeking applications. And I'm glad to see them quoting Ben Shneiderman, a colleague of mine at the University of Maryland who has spent much of his career focusing on HCIR issues.
Still, I think they could have taken the idea much further. Their discussion of more efficient or ergonomic use of real estate boils down to stripping extraneous content (a good idea, but hardly novel), and making sites vertically oriented (i.e., no horizontal scrolling). They don't consider the question of what information is best to present in the limited space--which, in my mind, is the most important question to consider as we optimize interaction. Indeed, many of the questions raised by small screens also apply to other interfaces, such as voice.
Perhaps I am asking too much to expect them to call out the extreme inefficiency of ranked lists, compared to summarization-oriented approaches. Certainly the mobile space opens great opportunities for someone to get this right on the web.
Of course, on a blog entitled The Noisy Channel, I can't help praising approaches that strive to improve the signal-to-noise ratio in information seeking applications. And I'm glad to see them quoting Ben Shneiderman, a colleague of mine at the University of Maryland who has spent much of his career focusing on HCIR issues.
Still, I think they could have taken the idea much further. Their discussion of more efficient or ergonomic use of real estate boils down to stripping extraneous content (a good idea, but hardly novel), and making sites vertically oriented (i.e., no horizontal scrolling). They don't consider the question of what information is best to present in the limited space--which, in my mind, is the most important question to consider as we optimize interaction. Indeed, many of the questions raised by small screens also apply to other interfaces, such as voice.
Perhaps I am asking too much to expect them to call out the extreme inefficiency of ranked lists, compared to summarization-oriented approaches. Certainly the mobile space opens great opportunities for someone to get this right on the web.
Friday, July 11, 2008
Psychology of Intelligence Analysis
In the course of working with some of Endeca's more interesting clients, I started reading up on how the intelligence agencies address the challenges of making decisions, especially in the face of incomplete and contradictory evidence. I ran into a book called Psychology of Intelligence Analysis by former CIA analyst Richards Heuer. The entire book is available online, or you can hunt down a hard copy of the out-of-print book from your favorite used book seller.
Given the mixed record of the intelligence agencies over the past few decades, you might be wondering if the CIA is the best source for learning how to analyze intelligence. But this book is a gem. Even if the agencies don't always practice what they preach (and the book makes a good case as to why), the book is an excellent tour through the literature on judgment and decision making.
If you're already familiar with work by Herb Simon, Danny Kahneman, and Amos Tversky, then a lot of the ground he covers will be familiar--especially the third of the book that enumerates cognitive biases. I'm a big fan of the judgment and decision making literature myself. But I still found some great nuggets, particularly Chapter 8 on Analysis of Competing Hypotheses. Unlike most of the literature that focuses exclusively on demonstrating our systematic departures from rationality, Heuer hopes offer at least some constructive advice.
As someone who builds tools to help people make decisions using information that not only may be incomplete and contradictory, but also challenging to find in the first place, I'm very sensitive to how people's cognitive biases affect their ability to use these tools effectively. One of the HCIR '07 presentations by Jolie Martin and Michael Norton (who have worked with Max Bazerman) showed how the manner in which information was partitioned on retail web sites drove decisions, i.e., re-organizing the same information affected consumer's decision process.
It may be tempting for us on the software side to wash our hands of our users' cognitive biases. But such an approach would be short-sighted. As Heuer shows in his well-researched book, people not only have cognitive biases, but are unable to counter those biases simply by being made aware of them. Hence, if software tools are to help people make effective decisions, it is the job of us tool builders to build with those biases in mind, and to support processes like Analysis of Competing Hypotheses that try to compensate for human bias.
Given the mixed record of the intelligence agencies over the past few decades, you might be wondering if the CIA is the best source for learning how to analyze intelligence. But this book is a gem. Even if the agencies don't always practice what they preach (and the book makes a good case as to why), the book is an excellent tour through the literature on judgment and decision making.
If you're already familiar with work by Herb Simon, Danny Kahneman, and Amos Tversky, then a lot of the ground he covers will be familiar--especially the third of the book that enumerates cognitive biases. I'm a big fan of the judgment and decision making literature myself. But I still found some great nuggets, particularly Chapter 8 on Analysis of Competing Hypotheses. Unlike most of the literature that focuses exclusively on demonstrating our systematic departures from rationality, Heuer hopes offer at least some constructive advice.
As someone who builds tools to help people make decisions using information that not only may be incomplete and contradictory, but also challenging to find in the first place, I'm very sensitive to how people's cognitive biases affect their ability to use these tools effectively. One of the HCIR '07 presentations by Jolie Martin and Michael Norton (who have worked with Max Bazerman) showed how the manner in which information was partitioned on retail web sites drove decisions, i.e., re-organizing the same information affected consumer's decision process.
It may be tempting for us on the software side to wash our hands of our users' cognitive biases. But such an approach would be short-sighted. As Heuer shows in his well-researched book, people not only have cognitive biases, but are unable to counter those biases simply by being made aware of them. Hence, if software tools are to help people make effective decisions, it is the job of us tool builders to build with those biases in mind, and to support processes like Analysis of Competing Hypotheses that try to compensate for human bias.
Thursday, April 24, 2008
Database Usability
Just as I was digesting Jeff Naughton's presentation at DB/IR day, a colleague at Endeca emailed me the keynote that H. V. Jagadish (University of Michigan) presented at SIGMOD '07 on making database systems usable. He enumerates the familiar pain points of today's database systems: confusing schemas, too many choices to make, unexpected--and unexplained--system behavior, and too high a cost for initial creation. He proposes "systems that reflect the user's model of the data, rather than forcing the data to fit a particular model."
As with Jeff's presentation, the main take-away here is a framework (though both he and Jeff have taken initial steps to address the problems they describe). As a practitioner, I'm most encouraged by the fact that database researchers, like information retrieval researchers, are increasingly recognizing the importance of users.
As with Jeff's presentation, the main take-away here is a framework (though both he and Jeff have taken initial steps to address the problems they describe). As a practitioner, I'm most encouraged by the fact that database researchers, like information retrieval researchers, are increasingly recognizing the importance of users.
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