My geek CEO was fired. If you’re wondering whether she deserved it, or Yahoo! is better off for it, or Roy Bostock is a doofus or dorfus, I don’t really know.* But I do have a personal story about Carol Bartz that’s indicative of the kind of CEO she was and the kind of person she is, perfect for Ada Lovelace day, a day to blog about women in science and technology who inspire you.
In May 2010, my wife Lauren was diagnosed with breast cancer. On Sunday, May 9, 2010—Mother’s Day no less—I received a phone call. “Hello?,” I said. “Hi, this is Carol Bartz,” she said. “Wow!,” I couldn’t help saying. I had never spoken to her before. She proceeded to say how sorry she was for me and Lauren, to reassure us, to ask me questions, and to answer mine.
More than a year, multiple surgeries, and six chemo sessions later, I’m happy to say that Lauren is past the worst part of the treatment and, to the best of anyone’s knowledge, cancer free. At the time, we were frightened, bewildered, and angry. To me, the most overwhelming feeling was disbelief. Was this really happening to us? It was surreal. Lauren’s strength and sheer will to keep our home life as normal as possible, and her ability to turn the ordeal into a positive is amazing and helped me cope. That my mom and Lauren’s mom went through the same thing also helped. The more we looked into it the more we realized breast cancer was everywhere—shockingly common even at Lauren’s age. (Especially in New Jersey, one of only five states in the top tier for both incidence of and mortality from breast cancer.) The calls to increase the age of first mammogram border on criminal. One silver lining for Lauren has been meeting the amazing support community of breast cancer sufferers, survivors, and their friends. They have inspired her to give back in many ways. My mom, a radiologist and ACR fellow, was herself inspired to specialize in mammography and pursue breast cancer research.
It turns out, Carol Bartz is a survivor herself and, in addition to being one of the fifty most powerful women in business, is just another member of the breast cancer support community who cares deeply. Carol had over twelve thousand employees. To take the time to call one of them on a holiday weekend to address personal problems and pain shows the kind of leader she is. (And shows the kind of bosses Preston and Prabhakar are, who thought enough to bring it to her attention.) It’s a “Yahoo! moment” and a Carol moment that I remember vividly and continues to stick out in my mind. I suspect most stereotypes of corporate and public leaders as conniving powermad ladder climbers are just that: stereotypes. But still, I’m convinced that not all—probably few—CEOs would do what Carol Bartz did. Goodbye, good luck, and, most of all: Thanks, Carol.
* I will say that I respect Carol’s willingness give her blunt assessment of the board, possibly risking $10 million to do so, and to come right out and say “I was fired” rather than hide behind “more time with family” cliches. I’m not surprised that the board gave their full confidence to her in public just two months before firing her—of course a board always has to say that they have confidence in their current CEO. I am surprised and dismayed that, at least judging by her reaction, it seems the board was also giving their confidence to her in private. That’s HR 101: No one who’s fired should be surprised.
Even if you detest gambling, this should send a chill down your spine: theFBIseized the domain names of several poker websites who operate offshore and arrested their owners.
The action exposes the lie that the US government does not control the Internet or does not exercise that control and perhaps hastens the day of a fragmented Internet. It’s an example of the government’s hypocritical position on Internet freedom: how can we express outrage at countries that block facebook or censor google when our own country seizes domain names and, in another recent example, tries to pass an Internet Blacklist Bill to block file-sharing websites? To the hundreds of thousands who spoke out against the latter, kudos, but I submit that the former poses just as dangerous a slippery slope.
These companies are obeying the laws of the countries in which they are based. Who are we to block them let alone seize their Internet property?
Take a look at the middle right of the second page: it says “Play exciting games and win big” and features… Predictopus! That’s the Indian spinoff of Predictalot, the combinatorial prediction game I helped invent.
Predictopus has nearly 70,000 users and counting, and this ad certainly won’t hurt.
Yahoo!!!
BTW, I grabbed these images from an amazing site called Press Display, which I discovered via the New York Public Library.
The EC’11 list of accepted papers is out and the program looks great (including six papers from Yahoo! authors). And it’s not too late to submit a paper to one of the associated workshops. Two of particular interest, both on June 5, 2011, are:
The workshop will bring together researchers and practitioners from a variety of relevant fields, including economics, computer science, and social psychology, in both academia and industry, to discuss the state of the art today, and the challenges and prospects for tomorrow in the field of social computing and user generated content.
Social computing systems are now ubiquitous on the web– Wikipedia is perhaps the most well-known peer production system, and there are many platforms for crowdsourcing tasks to online users, including Games with a Purpose, Amazon’s Mechanical Turk, the TopCoder competitions for software development, and many online Q&A forums such as Yahoo! Answers. Meanwhile, the user-created product reviews on Amazon generate value to other users looking to buy or choose amongst products, while Yelp’s value comes from user reviews about listed services…
In the past decade we’ve seen a rapid trend toward automation in advertising, not only in how ads are delivered and measured, but also in how ads are sold… The rapid emergence of new modes for selling and delivering ads is fertile ground for research from both economic and computational perspectives…
We solicit contributions of two types: (1) research contributions, and (2) position statements…
Submission deadline: April 15th, 2011 (midnight Hawaii Time)
March Madness is upon us and Predictalot, the crazy game that I and others at Yahoo! Labs invented, is live again and taking your (virtual) bets. Filling out brackets is so 2009. On Predictalot, you can compose your own wild prediction, like there will be exactly seven upsets in the opening round, or neither Duke, Kentucky, Kansas, nor Pittsburgh will make the Final Four. You’ll want your laptop out and ready as you watch the games — you can buy and sell your predictions anytime, like stocks, as the on-court action moves for or against you.
Predictalot v0.3 is easier to play. We whittled down the ‘Make Prediction’ process from four steps to just two. Even if you don’t want to wager, with one click come check out the projected odds of nearly any crazy eventuality you can dream up.
Please connect to facebook and/or twitter to share your prediction prowess with your friends and followers. You’ll earn bonus points and my eternal gratitude.
The odds start off at our own prior estimate based on seeds and (new this year) the current scores of ongoing games, but ultimately settle to values set by “the crowd” — that means you — as predictions are bought and sold.
For the math geeks, Predictalot is a combinatorial prediction market with over 9 quintillion outcomes. Prices are computed using an importance sampling approximation of a #P-hard problem.
What kind of information can we collect that a standard prediction market cannot? A standard market will say that Texas A&M is unlikely to win the tournament. Our market can say more. Yes, A&M is unlikely to reach the Final Four and even more unlikely to win apriori, but given that they somehow make it to the semifinals in Houston, less than a two hour drive from A&M’s campus, their relative odds may increase due to a home court advantage.
Here’s another advantage of the combinatorial setup. A standard bookmaker would never dare to offer the same millions of bets as Predictalot — they would face nearly unlimited possible losses because, by tradition, each bet is managed independently. By combining every bet into a single unified marketplace, we are able to limit the worst-case (virtual) loss of our market maker to a known fixed constant.
Applications for Yahoo!’s third annual Key Scientific Challenges Program are due March 11. Our goal is to support students working in areas we feel represent the future of the Internet. If you’re a Ph.D. student working in one of the areas below, please apply!
We are thrilled to announce Yahoo!’s third annual Key Scientific Challenges Program. This is your chance to get an inside look at — and help tackle — the big challenges that Yahoo! and the entire Internet industry are facing today. As part of the Key Scientific Challenges Program you’ll gain access to Yahoo!’s world-class scientists, some of the richest and largest data repositories in the world, and have the potential to make a huge impact on the future of the Internet while driving your research forward.
THE CHALLENGES AREAS INCLUDE:
- Search Experiences
- Machine Learning
- Data Management
- Information Extraction
- Economics
- Statistics
- Multimedia
- Computational Advertising
- Social Sciences
- Green Computing
- Security
- Privacy
KEY SCIENTIFIC CHALLENGES AWARD RECIPIENTS RECEIVE:
- $5,000 unrestricted research seed funding which can be used for conference fees and travel, lab materials, professional society membership dues, etc.
- Access to select Yahoo! datasets
- The unique opportunity to collaborate with our industry-leading scientists
- An invitation to this summer’s exclusive Key Scientific Challenges Graduate Student Summit where you’ll join the top minds in academia and industry to present your work, discuss research trends and jointly develop revolutionary approaches to fundamental problems
CRITERIA: To be eligible, you must be currently enrolled in a PhD program at any accredited institution.
We’re accepting applications from January 24th – March 11th, 2011 and winners will be announced by mid April 2011.
I’m thrilled to report that Predictalot had an Indian makeover, launching as Predictopus* for the ICC Cricket World Cup. The Yahoo! India team did an incredible job, leveraging the idea and some of the code base of Predictalot, yet making it their own. Predictopus is not a YAP — it lives right on the Yahoo! Cricket website, the official homepage for the ICC Cricket World Cup. They’re also giving away Rs 10 lakhs — or about $22,000 if my calculations are correct — in prizes. Everything is bigger in India, including the crowds and the wisdom thereof. It will be great to see the game played out on a scale that dwarfs our college basketball silliness in the US.
The Y! India team reused some of the backend code but redid the frontend almost entirely. To adapt the game to cricket, among other chores, we had to modify our simulation code to estimate the starting probabilities that any team would win against any other team, even in the middle of a game. (How likely is it for India to come back at home from down 100 runs with 10 overs left and 5 wickets lost? About 25%, we think.) These starting probabilities are then refined further by the game-playing crowds.
It’s great to see an experiment from Labs grow into a full-fledged product run by a real product team in Yahoo!, a prime example of technology transfer at its best. In the meantime, we (Labs) are still gunning for a relaunch of Predictalot itself for March Madness 2011, the second year in a row. Stay tuned.
2011/02/24 Update: An eye-catching India-wide ad campaign for predictopus is live, including homepage, finance, movies, OMG, answers, mail, everywhere! Oh, and one of the prizes is a Hyundai.
The last decade has witnessed the emergence of enormous scale artifacts resulting from the independent action of hundreds of millions of people; for example, web repositories, social networks, mobile communication patterns, and consumption in “limitless” stores… the first Research and Analysis of Tail phenomena Symposium (RATS)… will explore the different computational, statistical, and modeling problems related to tail phenomena… We are particularly encouraging summer interns in any of the Bay Area research centers to join us in the event.
We will start with a video welcome by Chris Anderson (Wired), followed by a series of invited talks by Michael Mitzenmacher (Harvard), Aaron Clauset (Univ. of Colorado), Neel Sundaresan (eBay), Sharad Goel (Yahoo! Research, NY) and Michael Schwarz (Yahoo! Research, CA).
We invite proposals for short (20 minute) talks from students and researchers working in the area.
Were you crowdsourcing before it was cool? We want to hear about your projects.
We are inviting submissions on all topics regarding crowdsourcing, including:
Past, present, and future of crowdsourcing
Quality assurance and metrics
Social and economic implications of crowdsourcing
Task design/Worker incentives
Innovative projects, experiments, and applications
Submission Guidelines
Deadline: Sept. 1
CrowdConf will bring together researchers, technologists, outsourcing entrepreneurs, legal scholars, and artists for the first time to discuss how crowdsourcing is transforming human computation and the future of work.
Confirmed Speakers:
Sharon Chirella: Vice President, Amazon Mechanical Turk
Tim Ferriss : Author, The 4-Hour Work Week
David Alan Grier: Author, When Computers Were Human
Barney Pell: Partner, Search Strategist, and Evangelist, Microsoft Maynard Webb: CEO, LiveOps
Jonathan Zittrain: Professor of Law and Computer Science, Harvard
We welcome contributions on theoretical models, empirical work, and everything in between, including but not limited to:
Automatic aggregation of opinions or knowledge
Prediction markets / information markets
Incentives in social computation (e.g., games with a purpose)
Studies of events and trends (e.g., in politics)
Analysis of and experiments on distributed collaboration and consensus-building, including crowdsourcing (e.g., Mechanical Turk) and peer-production systems (e.g., Wikipedia and Yahoo! Answers)
Group dynamics and decision-making
Modeling network interaction content (e.g., text analysis of blog posts, tweets, emails, chats, etc.)
Social networks
[Covers] computational social science… [and] social computing… with an emphasis on the role of
machine learning…
I just left the 2010 ACM Conference on Electronic Commerce, where six (!) out of 45 papers were about prediction markets.
Yahoo! Lab’s own Predictalot market is now live and waiting for you to place almost any prediction your heart desires about the World Cup in South Africa.
Here are some terribly useful things you can learn this time around. All numbers are subject to change, and that’s kind of the point:
There’s a 37% chance Brazil and Spain will both make it to the final game; there’s only a 15% chance that neither of them will make it
There’s is a 1 in 25 chance Portugal will win the cup; 1 in 50 for Argentina
42.92% chance that a country that has never won before will win
19.07% chance that Australia will advance further than England
65.71% chance that Denmark, Italy, Mexico and United States all will not advance to Semifinals
If you think these odds are wrong, place your virtual wager and earn some intangible bragging rights. You can sell your prediction any time for points, even in the middle of a match, just like the stock market.
There are millions of predictions available, yet I really believe ours is the simplest prediction market interface to date. (Do you disagree, Leslie?) We have an excellent conversion rate, or percent of people who visit the site who go on to place at least one prediction — for March Madness, that rate was about 1 in 5. One of our main goals was to hide the underlying complexity and make the app fast, easy, and fun to use. I personally am thrilled with the result, but please go judge for yourself and tell us what you think.
In the first version of Predictalot, people went well beyond picking the obvious like who will win. For example, they created almost 4,000 “three-dimensional” predictions that compared one team against two others, like “Butler will advance further than Kentucky and Purdue”.
If you’re not sure what to predict, you can now check out the streaming updates of what other people are predicting in your social circle and around the world:
Also new this time, you can join a group and challenge your friends. You can track how you stack up in each of your groups and across the globe. We now provide live match updates right within the app for your convenience.
If you have the Yahoo! Toolbar (if not, try the World Cup toolbar), you can play Predictalot directly from the toolbar without leaving the webpage you’re on, even if it’s Google.
Bringing Predictalot to life has been a truly interdisciplinary effort. On our team we have computer scientists and economists to work out the market math, and engineers to turn those equations into something real that is fast and easy to use. Predictalot is built on the Yahoo! Application Platform, an invaluable service (open to any developer) that makes it easy to make engaging and social apps for a huge audience with built-in distribution. And we owe a great deal to promotion from well-established Yahoo! properties like Fantasy Sports and Games.
We’re excited about this second iteration of Predictalot and hope you join us as the matches continue in South Africa. We invite everyone to join, though please do keep in mind that the game is in beta, or experimental, mode. (If you prefer a more polished experience, check out the official Yahoo! Fantasy Sports World Soccer game.) We hope it’s both fun to play and helps us learn something scientifically interesting.
Professor John A. Tures, LaGrange College (via Yahoo! Contributor Network) reacts to my analysis of the most likely Republican vice presidential pairings, arguing (well) against Chris Christie. Nice article. […]
I'm quoted/cited in this (not particularly good) gigaom article: "According to a predictive analysis experiment by a Yahoo data scientist, U.S. voters can expect to see either a Mitt Romney-Chris Christie or a Newt Gingrich-Marco Rubio ticket to face off against Obama-Biden in this year’s presidential election. The experiment, which author David Pe […]
What is a better investment objective? Grow as wealthy as possible as quickly as possible, or Maximize expected wealth for a given time period and level of risk The question is at the heart of a fight between computer scientists and economists chronicled beautifully in the book Fortune’s Formula by Pulitzer Prize nominee William Poundstone. [...]
What exactly is a combinatorial prediction market? 2010 Update: Several of us at Yahoo! Labs, along with academic researchers, have theorized and written about combinatorial prediction markets for several years, as you’ll see below. But now we’ve gone beyond talking about them and actually built one. So the best way to answer the question is [...]
There are many examples of multi-outcome prediction markets, for example election markets with more than two candidates, or sports championship markets with dozens of teams. What is the best way to implement a multi-outcome prediction market? The simplest way is to effectively ignore the fact that there are multiple outcomes, breaking up the market into [...]
One of the purest and most fascinating examples of the “wisdom of crowds” in action comes courtesy of a unique online contest called ProbabilitySports run by mathematician Brian Galebach. In the contest, each participant states how likely she thinks it is that a team will win a particular sporting event. For example, one contestant may [...]
A number of naysayers [Daily Kos, The Register, The Big Picture, Reason] are discrediting prediction markets, latching onto the fact that markets like TradeSports and NewsFutures failed to call this year’s Democratic takeover of the US Senate. Their critiques reflect a clear misunderstanding of the nature of probabilistic predictions, as many others [Emile, Lance] have [...]
Robin Hanson invented a wonderful market maker well suited for use in prediction market applications with a long name: the logarithmic market scoring rule market maker, which I’ll abbreviate as LMSR. (In fact, Hanson invented an entire class of market scoring rule market makers, but the logarithmic variant seems the most useful.) Hanson’s two papers [...]
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A professional goodbye and a personal thanks to Carol Bartz
My geek CEO was fired. If you’re wondering whether she deserved it, or Yahoo! is better off for it, or Roy Bostock is a doofus or dorfus, I don’t really know.* But I do have a personal story about Carol Bartz that’s indicative of the kind of CEO she was and the kind of person she is, perfect for Ada Lovelace day, a day to blog about women in science and technology who inspire you.
In May 2010, my wife Lauren was diagnosed with breast cancer. On Sunday, May 9, 2010—Mother’s Day no less—I received a phone call. “Hello?,” I said. “Hi, this is Carol Bartz,” she said. “Wow!,” I couldn’t help saying. I had never spoken to her before. She proceeded to say how sorry she was for me and Lauren, to reassure us, to ask me questions, and to answer mine.
More than a year, multiple surgeries, and six chemo sessions later, I’m happy to say that Lauren is past the worst part of the treatment and, to the best of anyone’s knowledge, cancer free. At the time, we were frightened, bewildered, and angry. To me, the most overwhelming feeling was disbelief. Was this really happening to us? It was surreal. Lauren’s strength and sheer will to keep our home life as normal as possible, and her ability to turn the ordeal into a positive is amazing and helped me cope. That my mom and Lauren’s mom went through the same thing also helped. The more we looked into it the more we realized breast cancer was everywhere—shockingly common even at Lauren’s age. (Especially in New Jersey, one of only five states in the top tier for both incidence of and mortality from breast cancer.) The calls to increase the age of first mammogram border on criminal. One silver lining for Lauren has been meeting the amazing support community of breast cancer sufferers, survivors, and their friends. They have inspired her to give back in many ways. My mom, a radiologist and ACR fellow, was herself inspired to specialize in mammography and pursue breast cancer research.
It turns out, Carol Bartz is a survivor herself and, in addition to being one of the fifty most powerful women in business, is just another member of the breast cancer support community who cares deeply. Carol had over twelve thousand employees. To take the time to call one of them on a holiday weekend to address personal problems and pain shows the kind of leader she is. (And shows the kind of bosses Preston and Prabhakar are, who thought enough to bring it to her attention.) It’s a “Yahoo! moment” and a Carol moment that I remember vividly and continues to stick out in my mind. I suspect most stereotypes of corporate and public leaders as conniving powermad ladder climbers are just that: stereotypes. But still, I’m convinced that not all—probably few—CEOs would do what Carol Bartz did. Goodbye, good luck, and, most of all: Thanks, Carol.
* I will say that I respect Carol’s willingness give her blunt assessment of the board, possibly risking $10 million to do so, and to come right out and say “I was fired” rather than hide behind “more time with family” cliches. I’m not surprised that the board gave their full confidence to her in public just two months before firing her—of course a board always has to say that they have confidence in their current CEO. I am surprised and dismayed that, at least judging by her reaction, it seems the board was also giving their confidence to her in private. That’s HR 101: No one who’s fired should be surprised.