Part 1
Title: Machines and Mindlessness: Social Responses to Computers
Authors: Clifford Nass, Youngme Moon
Publisher: Journal of Social Issues, Volume 56, Issue 1
Part 2
Title: Computers Are Social Actors
Authors: Clifford Nass, Jonathan Steuer, Ellen R. Tauber
Publisher: CHI '95: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Part 3
Title: Can Computer Personalities Be Human Personalities?
Authors: Clifford Nass, Youngme Moon, B.J. Fogg, Byron Reeves, Chris Dryer
Publisher: CHI '95: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Summary
This paper talked about the social rules that get applied to computers and the expectations of the computers. Users tend to apply social categories to computers. For example, in one experiment, the testers had their users be tutored, tested and evaluated by a computer with a male/female voice. They found that people found the male voice to be friendlier. People also acted polite towards their computers. The researchers also showed how people value information given by a computer when it was identified as a "specialist". Television and news shows were given as the supporting example. The researchers explored anthromorphism, the belief that everything is human.
Part 2 describes why people act the way they do with computers. It is easy and commonplace to generate consistent responses. There were many experiments conducted to test whether a person will be polite to a computer, whether a person will apply the notion of 'self' to the computer, how a person distinguishes between 'self' and 'other', how a person distinguishes between the two and whether or not gender stereotypes are also applied. They find that the computer-human relationship is a social one.
Part 3 talks about the personality of a computer. Computers can either be dominant or submissive. They tested this to see how a user would react to each personality trait. A dominant computer used strong language and displayed high confidence. A submissive computer asked a lot of questions and made suggestions. The researchers found that when a person's personality trait matched that of the computer, a satisfying interaction occurred.
Discussion
I had never really thought that a computer could have a personality but this does make sense. It's amazing that dominance or submission has such a large impact in the way people feel about their computers. I should take note of stuff like this when I'm talking. There is a rather large difference in "Please do this" and "Would you like to do this?"
Tuesday, April 26, 2011
Monday, April 25, 2011
Full Blog: Living With Complexity
Reference Information
Title: Living With Complexity
Author: Donald A. Norman
Editors: The MIT Press (2010)
Summary
Summary
Norman begins by talking about the idea of things being complex and things being complicated. Things being complex refers to the state of the world, the tasks we do and the tools we use. Things being complicated refers to the psychological state of a person attempting to understand, use or interact with something in the world.
He then talks about how complicated systems occur as a result of poor design and different ways of coping with complexity. There are several examples however of when we like complexity as it seems to be appropriate. One of the ways that he measures complexity is by the time it takes to learn and master a task.
Norman talks about the conceptual model, the underlying belief a person holds about how something works. The conceptual model helps to simplex complexity in systems. He goes on to talk about "featuritis", adding more and more features to a product thereby increasing its complexity. Norman prefers an intermediate level of complexity as simpler looking products do not always result in simpler to use.
Donald Norman talks about how things get increasingly complicated when the number of items increases. Passwords for example, are an instance of this. He then goes on to talk about how we cope with information by putting it in the world. People will sometimes put passwords under their monitor.
"Scaling" is a problem that works well sometimes but fails as the number grows. In an ideal world, we wouldn't need signs and too much information makes things complicated. Forcing functions on items provides many benefits.
Social signifiers are indicators that an environment allows people to navigate in complex environment. These things are referred to as perceived affordances. He talks about the importance of signifiers as they provide clues to the world and how people should act.
Discussion
I thought Norman gave a lot of really good examples in this book. I particularly liked the chapter about task mastering. 10,000 is a lot of time to become an expert at a field. The part about increasingly complexity with increasing number of items hit home. I have far too many passwords.
I thought Norman gave a lot of really good examples in this book. I particularly liked the chapter about task mastering. 10,000 is a lot of time to become an expert at a field. The part about increasingly complexity with increasing number of items hit home. I have far too many passwords.
Paper Reading #25: Agent-Assisted Task Management that Reduces Email Overload
Title: Agent-Assisted Task Management that Reduces Email Overload
Author: Andrew Faulring, Brad Myers, Ken Mohnkern, Bradley Schmerl, Aaron Steinfeld, John Zimmerman, Asim Smailagic, Jeffery Hansen, and Daniel Siewiore
Publisher: IUI '10, February 7-10, 2010 Hong Kong
Summary
The researchers in this paper developed RADAR (Reflective Agents with Distributed Adaptive Reasoning). RADAR is an email management system. It uses task-based metaphore in an attempt to organize a user's inbox.
It does this through machine learning. The system analyzes incoming emails, detecting a task and groups future emails with the initial one. Emails therefore are sorted into a much more logical fashion.
Their tests showed that users using RADAR had an easier time querying emails. There were few reported false positives in the system.
Discussion
This is somewhat interesting, but I would much rather sort my own emails or use threading. Within the same conversation the topic can differ wildly. People might not remember how they got to a certain point and thus have a hard time classifying their email.
Summary
It does this through machine learning. The system analyzes incoming emails, detecting a task and groups future emails with the initial one. Emails therefore are sorted into a much more logical fashion.
Their tests showed that users using RADAR had an easier time querying emails. There were few reported false positives in the system.
Discussion
This is somewhat interesting, but I would much rather sort my own emails or use threading. Within the same conversation the topic can differ wildly. People might not remember how they got to a certain point and thus have a hard time classifying their email.
Book Reading #52: Living With Complexity Microblog
Reference Information
Title: Living With Complexity
Author: Donald A. Norman
Editors: The MIT Press (2010)
Summary
Chapter 3: How Simple Things Can Complicate Our Mind (26 pages)
Donald Norman talks about how things get increasingly complicated when the number of items increases. Passwords for example, are an instance of this. He then goes on to talk about how we cope with information by putting it in the world. People will sometimes put passwords under their monitor.
"Scaling" is a problem that works well sometimes but fails as the number grows. In an ideal world, we wouldn't need signs and too much information makes things complicated. FOrcing functions on items provides many benefits.
Chapter 4: Social Signifiers (22 pages)
Social signifiers are indicators that an environment allows people to navigate in complex environment. These things are referred to as perceived affordances. He talks about the importance of signifiers as they provide clues to the world and how people should act.
Discussion
I liked when Norman talked about traffic and how people perceive that there are accidents ahead when many times there are not. Usually the cause for the slowdown is the compounding of brake lights or people waiting for the person in front of them to go during green lights.
Chapter 3: How Simple Things Can Complicate Our Mind (26 pages)
Donald Norman talks about how things get increasingly complicated when the number of items increases. Passwords for example, are an instance of this. He then goes on to talk about how we cope with information by putting it in the world. People will sometimes put passwords under their monitor.
"Scaling" is a problem that works well sometimes but fails as the number grows. In an ideal world, we wouldn't need signs and too much information makes things complicated. FOrcing functions on items provides many benefits.
Chapter 4: Social Signifiers (22 pages)
Social signifiers are indicators that an environment allows people to navigate in complex environment. These things are referred to as perceived affordances. He talks about the importance of signifiers as they provide clues to the world and how people should act.
Discussion
I liked when Norman talked about traffic and how people perceive that there are accidents ahead when many times there are not. Usually the cause for the slowdown is the compounding of brake lights or people waiting for the person in front of them to go during green lights.
Wednesday, April 20, 2011
Paper Reading #24: Personalized Reading Support for Second-Language Web Documents by Collective Intelligence (IUI 39)
Comments
http://shennessy11.blogspot.com/2011/04/paper-reading-23.html
http://stuartjchi.blogspot.com/2011/04/paper-reading-24-personalized-reading.html
http://shennessy11.blogspot.com/2011/04/paper-reading-23.html
http://stuartjchi.blogspot.com/2011/04/paper-reading-24-personalized-reading.html
Reference Information
Title:Personalized Reading Support for Second-Language Web Documents by Collective Intelligence
Author: Yo Ehara, Nobuyuki Shimizu, Takashi Ninomiya, Hiroshi Nakagawa
Publisher: IUI '10, February 7-10, 2010 Hong Kong
Summary
The researchers in this article developed a way for Web documents to be written in the second languages of users. Today, many users browse Web pages using English word glossing systems, that is, when someone hovers over an unknown word a pop-up window comes up with the definition.
This can be useful but does not take advantage of a user's existing vocabulary. Valuable data is wasted instead of being accumulated. The researchers harnessed collective intelligence by utilizing the accumulated word click logs for many users. Their system automatically predicts unfamiliar words and glosses them with their meaning in advance. If prediction succeeds, the user does not need to consult the dictionary. If it fails, the user can correct the prediction. The predictions are personalized and estimated using a state-of-the-art language testing model that is trained in practical response time with only a small sacrifice of prediction accuracy.
Conclusion
There were a lot of complex equations that I didn't really understand. I'm still not entirely sure how this system actually works. I guess it's a good idea but it's something that I would never use. I also haven't used any English word glossing systems, mostly because I hate pop-overs so much.
Summary
This can be useful but does not take advantage of a user's existing vocabulary. Valuable data is wasted instead of being accumulated. The researchers harnessed collective intelligence by utilizing the accumulated word click logs for many users. Their system automatically predicts unfamiliar words and glosses them with their meaning in advance. If prediction succeeds, the user does not need to consult the dictionary. If it fails, the user can correct the prediction. The predictions are personalized and estimated using a state-of-the-art language testing model that is trained in practical response time with only a small sacrifice of prediction accuracy.
Conclusion
There were a lot of complex equations that I didn't really understand. I'm still not entirely sure how this system actually works. I guess it's a good idea but it's something that I would never use. I also haven't used any English word glossing systems, mostly because I hate pop-overs so much.
Full Blog: Why We Make Mistakes
Reference Information
Title: Why We Make Mistakes
Author: Joseph T. Hallinan
Editors: Broadway Books (2009)
Summary
In the introduction, Hallinan describes what mistakes are and how the world is designed as to expect us to see things clearer than than they appear. The topics to be discussed: similar mistakes that happen, what one can do to make fewer errors and understanding context.
The next chapter Hallinan talks about how we don't see things as clearly as we think we do. He gives many examples of this such such as the door experiment. He also talks about movie mistakes. Towards the end, the author goes on to explain the beer-in-the-fridge problem and how people have a threshold at which point they will quit searching for something.
In the chapter "We All Search for Meaning", Hallinan focuses on meanings we pick up on. Hallinan talks about the ones that we see and hear are more important than the details of the entire scene. He gives a lot of examples as to how details aren't stored well in memory: penny test, slip of tongue errors, recall errors, things like that. He talk about how we should come up with passwords quickly because we won't remember it in the future if we had to figure it out first. Next the author considers how we connect dots and consider things. He gives a lot of examples. One of them is how voters make quick decisions on who they're going to vote for based on how competent the candidate looks. Another example was wine tasting--people rated more expensive wine as tasting better even if it tasted exactly the same as cheap wine. The author gives a bunch ore examples to help us understand mistake sources.
Summary
The next chapter Hallinan talks about how we don't see things as clearly as we think we do. He gives many examples of this such such as the door experiment. He also talks about movie mistakes. Towards the end, the author goes on to explain the beer-in-the-fridge problem and how people have a threshold at which point they will quit searching for something.
In the chapter "We All Search for Meaning", Hallinan focuses on meanings we pick up on. Hallinan talks about the ones that we see and hear are more important than the details of the entire scene. He gives a lot of examples as to how details aren't stored well in memory: penny test, slip of tongue errors, recall errors, things like that. He talk about how we should come up with passwords quickly because we won't remember it in the future if we had to figure it out first. Next the author considers how we connect dots and consider things. He gives a lot of examples. One of them is how voters make quick decisions on who they're going to vote for based on how competent the candidate looks. Another example was wine tasting--people rated more expensive wine as tasting better even if it tasted exactly the same as cheap wine. The author gives a bunch ore examples to help us understand mistake sources.
Hallinan then talks about how we see our memories through "rose-colored glasses". What that means is that we remember things that we do or say better than they actually were/are. We tend to make ourselves sound better than reality. Examples he gave were: the Watergate scandal and how Dean remembered events completely differently from how they actually occurred, gamblers and their wins, losses and near wins, and students remembering their grades.
In regards to multitasking Hallinan muses that we think we do it but in all actuality, we really don't. Usually multitasking slows us down and makes us forget what we were doing in the first place. It creates a need for downtime, the time it takes to refocus on the task at hand.
In the next chapter, Hallinan talks about framing. Framing is essentially how we view something. Hallinan gives a lot of examples in this chapter. He talks about the time that we take to make decisions can affect the outcome (immediate or future), multiple-unit ricing, wine buying based on the music and store tags. Customers will key in on the first part of tag and will have an "anchor" as to how many to buy.
Hallinan also talks about how we skim things. He gives a lot of examples of how we skim material and the trade-off along with it. Hallinan talks about how we miss a lot of important details and cites a rookie piano player that noticed an error that went unnoticed for several years. We only read the first few letters of a work and decide to assume the rest. Context is important when recognizing and remembering information.
The author then goes on to describe how we organize things within our memory. He talks about the hierarchical nature in which we like things organized. In addition, he gives a few examples about how people remember things. One of them was how people drew the Seine River much straighter than it actually was. He also goes on to talk about how people remember things. A lot of people will rationalize memories and change them, leaving out or making up details as they go. These added details cause them to remember events differently from how they happened.
People tend to believe that they're all above average. People are overconfident and it shows in things like golfing. The believes that this is caused by calibration, the difference between a person's actual and perceived abilities. He also goes on to talk about harder tasks and the overconfidence that comes along with it. People that are overloaded with knowledge believe they will be likely more right. Hallinan talks about how professionals have difficulty knowing when they are good or bad at something. Experts become experts by practicing. At a young age, they construct a library of specialized knowledge. He ends by talking about how people tend do do things the way they first learned it.
In chapter 13, the author talks about the thought processes behind important life decisions. People tend to focus on minor factors when doing so. He also discusses how people mispredict how they will feel about important life decisions in the future because of the focus on minor factors.
Hallinan concludes by giving advice to the readers as to how they can apply the the ideas discussed in the book. He recommends: think small, calibration should be taught, create a written record to take off the rose-colored glasses, expect failure, don't be set in your ways, slow down, be aware of anecdotes, get plenty of sleep, and be happy. He finishes by talking about how money does not eliminate mistakes.
Discussion
I really liked this book. I feel like I really got a lot out of it. Many of the concepts seemed pretty obvious when reading them but things that I had forgotten to take into consideration. He gave a bunch of good examples and really stresses on looking at the bigger picture when making big decisions. Making mistakes is something very natural to do and it is good to understand why they happen.
Book Reading #51: Living With Complexity Microblog
Reference Information
Title: Living With Complexity
Author: Donald A. Norman
Editors: The MIT Press (2010)
Summary
Chapter 1: Why is Complexity Necessary? (32 pages)
Norman begins by talking about the idea of things being complex and things being complicated. Things being complex refers to the state of the world, the tasks we do and the tools we use. Things being complicated refers to the psychological state of a person attempting to understand, use or interact with something in the world.
He then talks about how complicated systems occur as a result of poor design and different ways of coping with complexity. There are several examples however of when we like complexity as it seems to be appropriate. One of the ways that he measures complexity is by the time it takes to learn and master a task.
Chapter 2: Simplicity is in the Mind (30 pages)
Norman talks about the conceptual model, the underlying belief a person holds about how something works. The conceptual model helps to simplex complexity in systems. He goes on to talk about "featuritis", adding more and more features to a product thereby increasing its complexity. Norman prefers an intermediate level of complexity as simpler looking products do not always result in simpler to use.
Discussion
In regards to the first chapter, I really liked how he measured complexity. One of my favorite books is called "Outliers" by Malcolm Gladwell and in it, he talks about something called the"10,000 Hour Rule". The rule is basically that to become a master at anything, it takes about 10,000 hours. He gives examples of the early Beatles, Bill Gates, and Canadian hockey players.
I also really liked what he talked about in chapter 2 about "featuritis". I've seen that happen to a lot of projects that I work on. I keep adding features and all of a sudden it balloons up and there's crap everywhere.
Summary
Chapter 1: Why is Complexity Necessary? (32 pages)
Norman begins by talking about the idea of things being complex and things being complicated. Things being complex refers to the state of the world, the tasks we do and the tools we use. Things being complicated refers to the psychological state of a person attempting to understand, use or interact with something in the world.
He then talks about how complicated systems occur as a result of poor design and different ways of coping with complexity. There are several examples however of when we like complexity as it seems to be appropriate. One of the ways that he measures complexity is by the time it takes to learn and master a task.
Chapter 2: Simplicity is in the Mind (30 pages)
Norman talks about the conceptual model, the underlying belief a person holds about how something works. The conceptual model helps to simplex complexity in systems. He goes on to talk about "featuritis", adding more and more features to a product thereby increasing its complexity. Norman prefers an intermediate level of complexity as simpler looking products do not always result in simpler to use.
Discussion
In regards to the first chapter, I really liked how he measured complexity. One of my favorite books is called "Outliers" by Malcolm Gladwell and in it, he talks about something called the"10,000 Hour Rule". The rule is basically that to become a master at anything, it takes about 10,000 hours. He gives examples of the early Beatles, Bill Gates, and Canadian hockey players.
I also really liked what he talked about in chapter 2 about "featuritis". I've seen that happen to a lot of projects that I work on. I keep adding features and all of a sudden it balloons up and there's crap everywhere.
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