Everyone seems to be talking about and planning for the H1N1 virus these days. My university, for example, sent out a memo to encourage us to plan for extended absences due to the virus as we plan our classes for the fall semester. Now we can all participate in world-wide planning for the potential pandemic, thanks to a group of researchers from Erasmus University Medical Center in Rotterdam, The Netherlands. They have created a new Flash game called The Great Flu that allows the player to try to stop the spread of a virus. The consequences of the player’s actions can be surprising, as when I isolated victims of the virus in China and Japan which caused “chaos”. This game is an example of a serious game, that is, a game with a serious purpose such as education or advocacy. There are so many examples of serious games that the category constitutes a subfield of game studies with organizations and conferences dedicated to it. Don’t let the name of the category fool you, though. Serious games can be fun too. The Great Flu is pretty good and I learned quite a bit about public policy implementation for virus containment. Who would have thought swine flu could be fun? Give the game a try here. The game also contains quite a bit of humor. At some point, as the deaths from the flu rose in Central and North America, one of the global events that occurred was that “No Virus” t-shirts began to be sold. That sounds about right. 🙂
As I’ve mentioned before, I’m chairing a panel at NeMLA in April about using Web 2.0 technologies to play. Because of this panel, I’ve spent much of my summer playing and thinking about playing online. Yes, I recognize that I have a great job!
The game that has captured my online attention this summer is Scrabble on FaceBook. There are a few people (Liz, Scott, Ann) that I’m playing with regularly, multiple games at a time. There are also a couple of people (Sally, Carrie) with whom I seem to constantly have one game going. And then there are a few people (Gary, Cathrine, Kate) that I play with occasionally. I even sometimes play with strangers, although I find those games less engaging, probably because the social aspect of the game, which I’ve also written about before, is lacking.
One of the things I really like about Scrabble on FaceBook is that it will not let you play an invalid word. So the game is completely about pattern recognition. When I play the game in person, nothing stops me from playing an invalid word and so I am unlikely to take a chance on a word that I am unsure about. If my opponent challenges me in the real life game and I have played an invalid word, I lose a turn. In the online version of Scrabble, I can’t lose a turn for playing an invalid word. As a result, I’m likely to try letter combinations that I would never have tried in real life. I’ve learned lots of new words by just trying out letter combinations. What is “zax” for example? Or “tranqs”? And I’ve learned many, many two letter words whose meanings I’m sure I’ll never know. Anyone know what “za” is? Or “xu”? Or “ka”?
Lots of other FaceBook games have come to my attention and not captured it this summer. I’ve tried Farkle and Rummikub, both of which I love in the real world. Many of my friends have been playing Farmtown and so I’ve created my own farm but I haven’t visited it for days. And Mafia Wars. And Bejeweled. Well, to be honest, I won’t allow myself to really play Bejeweled because it is exactly the kind of game that I could become addicted to and I don’t really want to be addicted to a game right now.
But the kind of play I’ve been most interested in this summer has not been play that is associated with games. I’m really interested in play as a way of practicing and expressing parts of one’s identity that is difficult to practice or express in the real world.
My FaceBook friends seem to do a lot of quizzes. They want to find out which philosopher most closely represents them and how well they know their Princess Bride quote trivia. They want the rest of us to know five places they’ve lived and five jobs they’ve had and five cars they’ve owned. For some reason, I have resisted these quizzes although I’ve been thinking a lot about what people get out of taking them. And what I’ve come to realize is that these quizzes are a way to reveal one’s identity, either your real one or the one you wish you had. This came to me the other night as I was engaging in non-gaming online play of my own. I like to play with memes that come in the form of lists of questions that you answer in a note on your FaceBook profile. A meme is a cultural idea that is transmitted from one mind to another, in this case, via FaceBook. There are lots of memes running around FaceBook. Most of these memes allow users to reveal things about themselves (or not), helping to construct a kind of online identity that supplements (or perhaps alters) one’s identity in the real world.
A few weeks ago, for example, I revealed to my friends the fifteen books that I’ve read that have stuck with me. The idea is that you list these books without thinking too much about them, presumably so you can’t make yourself seem cooler than you actually are. My list contained books that I’d talked recently with Ann about (Disgrace and The Road) as well as books that I’d seen on other people’s lists (To Kill a Mockingbird and The Color Purple). The list also really did contain books that popped into my head because they were memorable and important to me in some way (A Separate Peace, Mrs. Stevens Hears the Mermaids Sing, Gone to Soldiers and The Mists of Avalon). But I rejected a number of books from my list just because I didn’t think I’d want to reveal them (Valley of the Dolls, The Other and The Group). And I rejected some just because they didn’t send the message that I wanted to send (Heart of Darkness and Carrie). As I reflected afterward on the books that I put on my list, I started to think about identity management again, that is, how I present myself to the world, the FaceBook world in this case.
What does this have to do with play? The other night, the two concepts merged for me. I was playing with another of these memes, called My Life According to … . The note contains a series of questions that you are supposed to answer using the song titles from one artist or band. I chose the Indigo Girls so my note was called My Life According to the Indigo Girls. Here’s what I wrote:
Several people have tagged me with this–I won’t tag anyone. Play if you want to. Using only song names from ONE ARTIST, cleverly answer these questions. Pass it on to 15 people you like and include me (presuming I’m someone you like). You can’t use the band I used. Try not to repeat a song title. Repost as “my life according to (band name)
Are you a male or female:
“The Girl With The Weight Of The World In Her Hands”
How do you feel:
“Closer To Fine”
Describe where you currently live:
“Get Out the Map”
If you could go anywhere, where would you go:
Your favorite form of transportation:
“Midnight Train to Georgia”
Your best friend?
“She’s Saving Me”
You and your best friends:
What’s the weather like:
Favorite time of day:
“I Don’t Wanna Know”
If your life was a TV show, what would it be called:
“Lay My Head Down”
What is life to you:
“Moment of Forgiveness”
What is the best advice you have to give:
“Don’t Give that Girl a Gun”
Thought for the Day:
How I would like to die:
My soul’s present condition:
“Cold Beer and Remote Control”
Unless you have been on an island somewhere lately, you probably know that Eunice Kennedy Shriver has been hospitalized for the past few days and died this morning at age 88. The achievement she is most well-known for, of course, is founding the Special Olympics. She often cited her sister Rosemary as the inspiration for founding the Special Olympics, a fact that has been mentioned many times in the past few days. I heard an interesting comment about Rosemary on NPR today. The reporter said that Rosemary herself lived a very long life but had to be institutionalized for much of it because of her mental retardation. I think this is actually a false statement.
By all accounts, Rosemary’s mental retardation was mild. In fact, there is some dispute as to whether she was mentally retarded at all. But as an adolescent and young adult, she had violent mood swings and became difficult to control. Her parents heard about a radical new procedure that could mellow out those mood swings and met the man who performed the procedure. The man they met was Walter Freeman, whom I have written about before. He popularized the lobotomy in the United States and performed thousands of them, including one on Howard Dully when Dully was twelve years old. Dully went on to write the amazing memoir My Lobotomy, revealing that he probably is able to function as well as he does precisely because the procedure was performed when he was so young and his brain was able to recover. Rosemary Kennedy was not as lucky. Freeman performed the procedure on her when she was 23 years old and it left her with the mental capacity of an infant, incontinent and unable to speak. She was institutionalized for the rest of her life. Rose Kennedy (Rosemary’s mother) is said to have considered Rosemary’s incapacitation via the lobotomy to be the first of the Kennedy tragedies. So it was Walter Freeman and his revolutionary procedure that caused Rosemary to be institutionalized for most of her life, not her mental retardation.
My area of research when I was in computer science was artificial intelligence. AI is a broad field with many subfields, each of which has many applications. Within AI, I was particularly interested in pattern recognition via machine learning techniques. When I left computer science, I turned my research attention to the topic of this blog and began to focus more and more on the impact of technology on society and media technology issues. So I was quite interested this morning when my favorite National Public Radio show, On the Media, broadcast a story that shows the connection between these two research interests.
Pattern recognition sounds like an esoteric subfield of AI. But in today’s computer-focused society, there are many useful applications of pattern recognition. For example, I worked on two problems in microbiology while I was a graduate student. My master’s work involved looking for patterns in strands of DNA of an organism called Onchocherca volvulus which causes river blindness. We were trying to determine whether we could determine the evolution history and path of the organism to help with understanding the epidemiology of the disease. For my PhD, I worked on the famous “protein folding problem“, trying to predict the 3-dimensional structure of a strand of protein by looking at just the sequence of amino acids that make up the protein. The theory is that if we can predict the 3-D structure, we can predict the function of the protein as well and the implications of that are far-reaching. As I said, there are many practical applications of pattern recognition by computers.
On today’s edition of On the Media, there was a story that reminded me of the fact that pattern recogniton by computers is everywhere in our society. The story was about a contest by NetFlix, the DVD rental site. NetFlix allows subscribers to rate movies via a star system, where one star means “hated it” and five stars means “loved it”. Based on the ratings that a particular subscriber has given a set of movies, NetFlix attempts to recommend other movies that the subscriber will enjoy. NetFlix’s business model depends on these recommendations since a larger percentage of their movie rentals come from subscribers listening to these recommendations. Without the recommendations, subscribers would likely run out of movies that they know they want to see and then would eventually give up their subscriptions. But predicting what movies a person will like is a very difficult problem.
NetFlix does a pretty good job with their movie recommendation system, Cinematch, but if they can make better predictions, they’re likely to hang on to more subscribers. So they created a contest, offering a million dollars to anyone who can develop an algorithm that does 10% better in its predictions than Cinematch. Apparently, a number of groups immediately were able to develop algorithms that were 5% more accurate than Cinematch. Even getting to 8% more accuracy didn’t take that long. But a number of intriguing issues made reaching the 10% mark difficult. One of the most interesting is known as the “Napoleon Dynamite problem.” Napoleon Dynamite is a quirky, independent movie that came out in 2004. It seems that it is quite difficult to accurately predict whether a particular subscriber will like or dislike this movie. In fact, two people whose likes and dislikes are quite similar can disagree drastically about Napoleon Dynamite. So getting to the 10% mark will probably require a solution to the “Napoleon Dynamite problem.”
The contest closed a couple of days ago, although no winner has yet been announced. NetFlix says that they received 44,014 entries from 5169 teams in 186 countries. One of the requirements of the contest is that the winners must disclose their techniques to the world. Although getting more accurate movie recommendations is not a life or death problem, the solution to it is likely to provide insight into how to accomplish other pattern recognition tasks. And that’s good news for all of us.