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Cynthia Rudin wins the 2021 AAAI Squirrel AI Award
- Stephen6252 5y agoThanks for sharing, I am very impressed with your post. https://www.mybalancenow.work/ https://www.mybalancenow.work/
- dr_dshiv 5y agoWhat’s with “Squirrel AI”? Did that seem slightly out of place?
- paranoidroid 5y agoSquirrel AI is a Chinese online education company. It is the first large scale AI-powered adaptive education provider in China [...] https://en.wikipedia.org/wiki/Squirrel_AI https://en.wikipedia.org/wiki/Squirrel_AI Thousand Talents Obfuscation Initiative?
- paranoidroid 5y agoThe benefit for humanity has award has only been a thing since 2021, Mrs. Rudin received the 2022 version. So lets say its been running for 2 years. And the only other comparable scientific awards of such monetary value are Turing and Nobel? Wow very generous people. 1. https://www.aaai.org/Awards/squirrel-ai-award.php https://www.aaai.org/Awards/squirrel-ai-award.php
- srean 5y agoHearty congratulations. I am very happy for her. I am more familiar with her older work on ranking and boosting. I do not have any technical commentary to add, just a personal anecdote that she is one of the nicest, warmest person that I have met. I wish her well with utmost sincerity.
- thedrake 5y agoSeveral great insights from a person that truly cares about not only the outcome of models but what is causing the outcome. Her talks about parole guidelines being taken over by ai are great.
- gwf 5y agoI was also one of Cynthia's Ph.D. advisors when she was a graduate student at Princeton, some twenty years ago. It was obvious to me then that she would go on to do great things, so it's delightful to read this news this morning. My fondest memory of Cynthia, however, has nothing to do with science, and everything to do with just being a kind person. We were at the NEC Research Institute's company picnic where they had an inflatable dragon for the kids to jump around within its interior. Me, Cynthia, and my wife went inside without any kids and jumped around like idiots for a while. Cynthia and my wife got bored, so I stayed behind for One More Big Bounce. With the epic bounce, I also succeeded in cracking a vertebra, nearly passing out on the spot from the pain. Eventually, I would crawl out, an ambulance was called, and I was brought to the Princeton ER. I would have a full recovery, but I was in the ER for several hours that night. Cynthia came with us to the ER, and when she saw how uncomfortable I was on the gurney, she went back to her dorm to retrieve her favorite blanket, so that I would have even a small comfort. I am not sure how long she stayed, but I know that she was there with me longer than anyone else except my wife. Anyhow, she's a lovely human being and I am honored and proud to have known her and witnessed the origins of her career.
- adrian_mrd 5y agoThanks for sharing. It’s frequently the little acts of everyday kindness that go a long way in this world, like the blanket example you cite.
- typest 5y agoIn my senior year at Duke, I took her ML class (her first semester at Duke). She was an excellent professor, one of the absolute best I had while there. She focused heavily on both implementation and theory, which I found to be rare. Her class became so popular within the add/drop period that Duke added a second section and also doubled the attendance for each section. I'm pretty sure she went from being supposed to teach about 70 students to teaching 300. Nevertheless, her teaching was top notch, and I learned more there than pretty much any other CS class, and still rely on this knowledge today! I too am really glad she won this award.
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- ChemSpider 5y agoIs this a respected prize? I never heard of it before. That said, no doubt that explainable ML/AI is important.
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- JustFinishedBSG 5y agoI mean, respected or not I would not say no to a free meal and USD$1M.
- nothrowaways 5y agoYeah, this is their second year i assume.
- ndr 5y agoIs $1 Million respectable?
- wongarsu 5y agoCan money buy respectability? If I awarded $1 Million to a random person every year, receiving that award wouldn't make that person more accomplished, and the award wouldn't be mentioned outside the local newspaper. On the other hand an award that gives no money but consistently awards the best researcher in the field can be very noteworthy. What the $1 million does accomplish is make people pay attention, so everyone will much more quickly reach a verdict whether this is a price worth paying attention to. But two years is a bit quick for that verdict.
- newsbinator 5y ago> Can money buy respectability? Definitely!
- adrian_mrd 5y agoHello Golden Globes and the Hollywood Foreign Press Association!
- nothrowaways 5y agoCongratulations! I think Interpretable AI mentioned in the article is what is commonly called explainable AI.
- qPM9l3XJrF 5y agoCynthia has a great paper where she distinguishes between "interpretable" and "explainable" https://arxiv.org/pdf/1811.10154.pdf https://arxiv.org/pdf/1811.10154.pdf
- randcraw 5y ago"Explainable" just means you didn't build your app/service using any technology that isn't interpretable. Her argument is that the strategy of reverse engineering a method to convert it from inexplicable to explicable is inherently less effective than maintaining explicability at all times in the app's genesis -- from the design phase through implementation. But Rudin's Premise is philosophical more than practical. If the problem at hand is better solved using a black box (in terms of accuracy, precision, robustness, etc), her premise says simply, don't do it. Unfortunately in the cutthroat world of capitalism, that strategy can't compete with the cutting edge. Where Rudin's Premise is more suitable is in writing regulations to address AI app problems where social unfairness is unchecked (like the COMPAS app that advises legal authorities on meting out parole decisions without explaining its reasoning). There are many such (ab)uses for AI today in social services or policing which merit rethinking since AI-based injustice so offer bedevils the proprietary lack of transparency in such apps. Another excellent discussion of problems like these is Cathy O'Neil's book "Weapons of Math Destruction". Too bad she couldn't share the Squirrel prize. https://www.amazon.com/Weapons-Math-Destruction-Increases-Inequality/dp/0553418815 https://www.amazon.com/Weapons-Math-Destruction-Increases-In...
- qPM9l3XJrF 5y ago>If the problem at hand is better solved using a black box (in terms of accuracy, precision, robustness, etc) It's been a while since I read her work, but IIRC one of the positions she argues for, which I find plausible, is that interpretable models can be performance competitive. For example, it could be that the only reason black box methods outperform is because they've been more heavily researched, and if we were to put more research into interpretable methods, we could achieve parity. I also mentioned a few reasons why we might expect interpretable models to perform better a priori in this comment https://news.ycombinator.com/item?id=28838321 https://news.ycombinator.com/item?id=28838321
- Bostonian 5y agoInteresting article, but I think this sentence was unfair to other AI scholars, who also want AI to help society. "While many scholars in the developing field of machine learning were focused on improving algorithms, Rudin instead wanted to use AI’s power to help society."
- pjmorris 5y agoA Peter Norvig quote from yesterday's article about his transition to Stanford... "In the past, the interesting questions were around what algorithm is best for doing this optimization. Now that we have a great set of algorithms and tools, the more pressing questions are human-centered: Exactly what do you want to optimize? Whose interests are you serving? Are you being fair to everyone? Is anyone being left out? Is the data you collected inclusive, or is it biased?" [0] https://news.ycombinator.com/item?id=28833933 https://news.ycombinator.com/item?id=28833933
- jhgb 5y agoThat makes the sentence quoted by GP sound like a category error to me. Developing better algorithms and developing more useful models to run on those algorithms are not an "either/or" situation.
- lallysingh 5y agoMany AI researchers do focus on algorithms, no?
- JustFinishedBSG 5y agoPlenty focus on theory.
- tremon 5y agoI think this is meant as a distinction between theoretical and applied science, phrased to a low common denominator (which, as a consequence, causes miscommunication due to not being specific enough).
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- ur-whale 5y agoAny link to her actual work?
- qPM9l3XJrF 5y agoOf the "representative publications" on her homepage here https://ece.duke.edu/faculty/cynthia-rudin https://ece.duke.edu/faculty/cynthia-rudin the one that seems most relevant to the topic of the article is this paper on interpretable financial lending: https://arxiv.org/pdf/2106.02605.pdf https://arxiv.org/pdf/2106.02605.pdf "The machine learning model is a two-layer additive risk model, which resembles a two-layer neural network, but is decomposable into subscales. In this model, each node in the first (hidden) layer represents a meaningful subscale model, and all of the nonlinearities are transparent. Our online visualization tool allows exploration of this model, showing precisely how it came to its conclusion. We provide three types of explanations that are simpler than, but consistent with, the global model: case-based reasoning explanations that use neighboring past cases, a set of features that were the most important for the model’s prediction, and summary-explanations that provide a customized sparse explanation for any particular lending decision made by the model." I was curious about the customized sparse explanation. It looks like there is an illustrative example from later in the paper: "For all 700 (7.1%) people where: • ExternalRiskEstimate ≤ 63 , and • NetFractionRevolvingBurden ≥ 73, the global model predicts a high risk of default." "A rule returned by OptConsistentRule is globally-consistent, in the sense that there exists no previous case that satisfies the conditions in the rule but is predicted differently, by the global model, from what is stated in the rule. In contrast, explanations (from other methods) that are not consistent may hold for one customer but not for another, which could eventually jeopardize trust (e.g., “That other person also satisfied the rule but he wasn’t denied a loan, like I was!”)" You can see the online visualization tool her team built here: http://dukedatasciencefico.cs.duke.edu/models/ http://dukedatasciencefico.cs.duke.edu/models/ In retrospect, it's not all that surprising to me that a model such as this is able to outperform a black box like a neural network. For example, one of the things this model does which black box models don't do is enforce "monotonicity constraints" which ensure that as risk factors increase, the estimated risk should also increase. It makes sense that this would be a useful inductive bias which improves generalization performance -- if a black box model found that an increase in risk factors decreased estimated risk, it seems likely that this would be a result of overfitting (or multicollinearity gone haywire). Of course another reason to expect simple/interpretable models to generalize better is Occam's Razor. My big question about this sort of approach would be whether it's able to extend to the sort of unstructured data problems that deep learning has done really well on. It looks like some of her recent papers on Google Scholar address this: https://scholar.google.com/citations?hl=en&user=mezKJyoAAAAJ&view_op=list_works&sortby=pubdate https://scholar.google.com/citations?hl=en&user=mezKJyoAAAAJ... (specifically thinking of the BacHMMachine paper and the Interpretable Mammographic Image Classification paper). Maybe someone else can summarize them.
- varispeed 5y agoI wish one day I'll read that Computer Scientist _earns_ $1 Million. Most engineers here get like £60k salary (£3600 a month after PAYE tax), while companies they work for make billions out of their work. Not only that, but they also don't contribute back into the local communities, because they use aggressive tax avoidance strategies. Corporations need to start sharing their profits with the workers and pay taxes otherwise it will eventually spark another revolution.
- JustFinishedBSG 5y ago> I wish one day I'll read that Computer Scientist _earns_ $1 Million. They do. Not that I personally believe they deserve it. For the exact same reasons I don't think a CEO is not "worth" thousands of engineers, I don't think that just because you happened to graduate in ML you are worth tens/hundred times more that the others. Or more accurately maybe they are worth that much, but the general population is severely underpaid.
- randcraw 5y agoReportedly, Ilya Sutskever was offered upward of $2 million/year to remain at Google as he departed for OpenAI. By many accounts, he's not alone at earning over $1 million/year as an independent contributor. When Hinton, Krishevsky, and Sutskever sold DNNresearch (incorporated only days before) to Google, their $44 million crossed that line too, since the company had no products or IP that was independent of UToronto, AFAIK. The three were effectively "hired" as indep contributors.
- twen_ty 5y agoI assume you're from the UK? Where? I ask because salaries in London are definitely higher. A senior engineer should get 80k and a principle engineer/architect should be on 90-120k.
- typest 5y agoIt is quite common for engineers with Cynthia Rudin’s ability to earn > 1 million. If you have that level of ML skill you can lead teams at many companies for over that amount.
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