Issues in Software Design The Media Equation The Man Who Lied to His Laptop

1. Issues in Software DesignThe Media EquationThe Man Who Lied to His Laptop

2. Programming Isn’t Everything • In the Computer Science Major we focus on Programming • But there are psychological and sociological factors to consider • Source: The Media Equation, Nass & Reeves; The Man Who Lied to His Laptop, Nass • Complement to emphasis on program correctness, efficiency • Develop the social/emotional aspect of computer software as opposed to the features/requirements aspect

3. The Media Equation • Media = Real Life At least, to people’s brains. That is, an individual’s interactions with computers, television, and media in general are fundamentally social and natural, just like interactions in real life.

4. Media and Real Life

5. Media Equation Hypothesis • People will subconsciously and automatically treat media as if it was real life • Reason: evolution • Over 200,000 years of evolution, humans evolved in a real environment with real things. • Brains evolved with real and real people, not virtual things and computer agents • Very difficult for brains to get out of the automatic response (e.g. telling yourself “It’s only a movie” during a scary movie)

7. Testing The Hypothesis : Steal from Social Science Research 1. Go to social sciences section of the library and find work how people respond to each other or the natural environment. 2. Cross out the words “person” or “environment” in the study, and substitute “media” or “computer”. For example, “people like other people who have personalities like their own” with “people like other computers that have personalities like their own.” 3. Run the same exact experiment, with the computer or media substituted for one of the participants. 4. Draw implications. Results from some of these experiments….

8. Manners

9. Politeness and Computers • We can make the computer be polite, but will people be polite back to the computer? • Social Science: • Bob presents lesson to Alice. • Bob rates his teaching performance as great (raises the stakes!) • Alice now rates Bob’s performance. • If Alice reports directly to Bob, politeness will tend to dominate and Alice will give a higher rating than if she gives her evaluation to some neutral party.

10. Politeness and Computers • Repeat the experiment on a computer • Computer presents lesson to subject • Computer rates his teaching performance as great • Subject now rates the computer’s performance. • One group of subjects: rated performance on the SAME computer • Second group of subjects: rated performance on a DIFFERENT computer • Subjects that rated on the same computer gave higher ratings than the subjects on the other computer • People didn’t say they were being polite

11. People and Flattery • Social Science: • People are suckers for praise, even if it is insincere flattery • Everyone likes interacting with and thinks well of people who praise sincerely as those that flatter.

12. People and Criticism • People dislike criticism and leaves them feeling bad. • Criticism that is unwarranted leaves us feeling bad AND leaves ill-feelings of the baseless person that made the remarks

13. Computers and Flattery/Criticism • Can we substitute the flatterer or the criticizer with a computer and get the same results?

14. Computer and Flattery • Computer played a 20 question “Guess the Animal” game where the computer tried to guess an animal the human was thinking of • When the game was over, participants were asked to type better questions into the computer. • Participants in group 1 were praised on their excellent question. • Participants in group 2 were given criticism. • Half of all participants were told the computer’s comment was derived from years of statistical analysis. • Half of all participants were told the computer randomly selected the analysis. • All participants evaluated how well they thought they did on the game, how much they liked the computer, and how well they thought the computer played the game.

15. Computers and Flattery • Flattered participants ranked the computer high on likeability and on ability to play the game. • Criticized participants ranked the computer low on likeability and ability to play the game. • Warranted criticized participants ranked their score lower. • Unwarranted criticized participants ranked their score higher. • Implications for designing software: If you want users to like your software, make your application praise more, avoid unwarranted criticism

16. Criticism in the Car Simulator • Body reactions to criticism • Increased heart rate • Rise in adrenaline • Rise in blood pressure • How to deliver criticism? • Couple criticism with suggestions for improvement • Go deep and specific rather than broad; listener actually remembers better after criticism

17. Praise in the Car Simulator? • Would participants drive better if they are praised on their driving behavior? • Drivers more relaxed, but didn’t do any better • Praise affects behavior less than criticism • Can help ensure continued positive behavior but unlikely to spur someone to new heights

18. Interpersonal Distance • Social Science • Close proximity to people is arousing, especially if you don’t know the person very well • If media appears “close” via zoom, image doubling, etc. does this have the same effect?

19. Interpersonal Distance • Hypothesis • When viewers see a picture of a person that appears close rather than far, their evaluations of the person will be more intense. • Viewers will pay more attention to pictures of people who appear close. • Pictures of people who appear close will be remembered better than pictures of people far away.

20. Computer-Person Distance • Experiment • Subjects viewed several faces in several combinations of screen size, shot size, and viewing distance. • Subjects rated the people in the pictures using adjectives describing liking and personality. • Attention was measured by attentiveness to a secondary task, pressing a button upon hearing a tone. • Results: Close pictures evaluated with more intense words, and were remembered with higher recall. Attention dropped during the close pictures and was high during the far pictures. • Implications for software applications involving video

21. Specialists • Social Science • People tend to respect professional specialists over generalists. • Believe a GP over a neurosurgeon? • The question with media is, can media have specialties as well? • Hypothesis: Content labeled a “specialist” in that type of content will be perceived as superior to identical content labeled “generalist”.

22. Specialists • Experiment • Subjects were shown identical news stories on television. • Group 1 saw the stories on a TV labeled “News and Entertainment Television” • Group 2 saw the stories on a TV labeled “News Television” • Subjects rated the articles in terms of quality, likeability. • Results: • Subjects with the “News Television” ranked the stories significantly more important, informative, interesting, and serious. Similar results have been shown with MTV, Food Network, etc. • Applications: Assign the specialist label to your program if it applies, to improve its evaluation.

23. Teams • Social Science • Team members tend to like each other. • Feelings of mutual admiration, cooperation, even if assigned randomly. • Hypothesis: • People teamed with a computer will feel more similar to the computer than people not teamed. • People teamed with a computer will think better of the computer. • People teamed with a computer will cooperate more with the computer.

24. Team Experiment • Experiment • Group 1 was named the “Blue Team”. They were given blue badges and the computer they used had a blue border. • Group 2 had no team affiliation and used computers with no team name. • The computer performed a desert survival ranking task • The humans also performed the desert survival ranking, then worked with the computer to form a new ranking. • Results: • Humans on the team formed lists closer to the computers ranking than the non-team humans. • Humans on the team collaborated more frequently. • Humans on the team thought the computer was more friendly and insightful than the non-team humans. • Applications: Simple commonalities (colors, similar language) can increase the media/human bond and cooperation

25. Gender • Social Science on gender stereotypes in the USA • Praise from males is taken more seriously than praise from females • Women are thought to know more about love and relationships than men • Men are thought to know more about technical subjects than women • Hypothesis: Do these stereotypes apply to a computer if assigned gender?  • Male computers should be taken more seriously than female computers • Female computers will be seen as more knowledgeable about love/relationships than male • Male computers will be seen as more knowledgeable about technical subjects than female

26. Gender Experiment • Experiment • Subjects were tutored by the computer on three topics: • Love/relationships, mass media, and computers. • Identical information presented to a group with a male voice, another group with a female voice • Participants ranked the computers performance. • Participants took a test on the material. • A different computer, either male or female, then praised the participant on their test. • Participants rated their own test results. • Results: • Participants ranked the female computer most knowledgeable on love/relationships. • Participants ranked the male computer most knowledgeable on computers. • Participants ranked themselves higher if praised by the male computer than by the female computer. • Gender stereotypes apply to computers, so design appropriately

27. The Tale of Clippit, aka Clippy 1997-2007

28. Clippy Reaction

29. Fixing Clippy • Technological approach: Better understanding of the user is trying to do, artificial intelligence, remember past interactions • Social Science approach: How to unpopular people make friends?

30. Clippy 2.0 • Create a scapegoat • Clippy would give a suggestion and ask if was helpful. If no, Clippy would say something like "That gets me really angry! Let's tell Microsoft how bad their help system is.“ • While typing the complaint “C'mon! You can be tougher than that. Let 'em have it!” • Testers loved the new Clippy, but Microsoft didn’t – retired as a default in 2001 and completely in 2007

31. Summary • Factors from social science play a role in software design • People appear to unconsciously treat media as it were real life based on numerous experiments • Can design software appropriate based on sociological response • Many other factors to consider in addition to social factors • Today there is considerable thought given to the user interface and user-centered design