Archive for January, 2013

Singularity Institute and Google: what are their plans?

A few days ago I read a New York Times interview of Ray Kurzweil, who thinks he’s going to live forever and also claims he will cure cancer if and when he gets it (his excuse for not doing it in his spare time now: “Well, I mean, I do have to pick my priorities. Nobody can do everything.”). He also just got hired at Google.

As a joke I suggested that Google employees read the interview and then quit their job.

My reasoning went like this: if someone who is clearly narcissistic and delusional gets hired by your company, and given a position much higher than you (Kurzweil’s title is “Director of Engineering,” and although that doesn’t mean he is in charge of everyone in Engineering, it is nonetheless a high position), then you can give up all hope of ever being promoted based on your actual contributions. Companies have natural stages in their lives, and Google has evidently reached the stage of hiring “thought leaders” who nobody could actually work with but are somehow aligned with the agenda of the leadership.

Since then I’ve learned a bit more about Kurzweil, and about the Singularity Institute (based on the idea that computers will become self-aware and super-intelligent which will culminate in a very special moment for some parts of humanity), and the related ideologies of Futurism (fetishizing technology), Transhumanism (the idea we are going to be immortal), and “human rationality” as espoused by the blog lesswrong. Note I usually link to wikipedia articles but in the above cases, especially for the Singularity Institute, the associated wikipedia article is suspiciously sanitized of actual information.

A lot of my research is covered in this New York Times article from 2010 about the Singularity Institute’s opening. In particular it describes the close relationship between the Google royalty and the Singularity Institute. Suffice it to say there is a serious relationship between the founders of Google and this Institute.

But I’m not writing this to point out the number of ties between those institutions – this is well-documented in the above article and has only grown more obvious with the recent acquisition of Kurzweil.

And I’m also not writing to suggest that the Singularity Institute is a cult. I honestly think they make the case better than I could when the Executive Director, Luke Meuhlhauser, posts things entitled “So You Want to Save the World” wherein he states:

The best way for most people to help save the world is to donate to an organization working to solve these problems, an organization like the Singularity Institute or the Future of Humanity Institute.

Don’t underestimate the importance of donation. You can do more good as a philanthropic banker than as a charity worker or researcher.

It’s really that last sentence I want to focus on. It’s where the creepy elitism of this ideology comes out. Because make no mistake, this is a massive circle jerk for techie men (mostly men) to think of themselves as joining up with gods due to their superior intelligence and creativity.

Whatever, I’ve been around nerds all my life, and it’s nothing new to me that some of them want intelligence to count for more than just getting an edge in education and the job market. Somehow this ideology creates a hunger for much more than that: immortality, for one, and the feeling of being chosen.

You see, I believe in incentives. I want to prepare myself for what people will do next based on what I think their incentives are, and these Singularity Institute guys are on the one hand pretty hardcore with their beliefs, and on the other hand infiltrating Google, which is an incredibly powerful force in an essentially unregulated domain. So what are their plans?

Just to give you an idea, check out this line from Vernor Vinge’s now famous 1993 essay on the Singularity (emphasis mine):

Suppose we could tailor the Singularity. Suppose we could attain our most extravagant hopes. What then would we ask for: That humans themselves would become their own successors, that whatever injustice occurs would be tempered by our knowledge of our roots. For those who remained unaltered, the goal would be benign treatment (perhaps even giving the stay-behinds the appearance of being masters of godlike slaves). It could be a golden age that also involved progress (overleaping Stent’s barrier). Immortality (or at least a lifetime as long as we can make the universe survive [9] [3]) would be achievable.

A few comments:

  • Vinge didn’t think the singularity was inevitable when he wrote that.
  • Vinge recently spoke at the October 2012 Singularity Summit hosted by the Singularity Institute (along with Director of Research from Google, Peter Norvig). Here’s a video.
  • The “stay-behinds” are the people who don’t get to transcend with the machines if and when the Singularity occurs.

Personally, I have fun thinking about the Singularity. I think it’s already happened, in fact, and my best argument for why machines are already smarter than us is this: when someone much smarter than you is saying something, maybe not to you, you don’t always know that that person is smarter – sometimes it just feels like they’re being confusing. But that’s exactly how we humans all feel about this mess we’ve made with the financial system: we are confused by it, we don’t understand it, and moreover we have no hope of dumbing it down to our level. That’s a sign it is superintelligent. Maybe not self-aware, but on the other hand how can you test that? In this light, the “stay-behinds” are Canadians.

Also, I totally believe everyone has the right to their own opinions, and for that matter they have a right to join a cult if they feel like it. In fact people who want to live forever, you could argue, are more likely to take care of the environment and their own children, because those are major investments for them.

On the other hand, what is their plan for the rest of us? Is it to, like Vinge says, give us the appearance of being masters of godlike slaves? Are those slaves our smart phones? Are we being intentionally shepherded into an artificial existence of play-power? Because I’ve suspected that very thing ever since I read the Filter Bubble. What else, especially in the context of the ongoing competition for resources?

The Singularity may never happen, or it may already have happened- that’s irrelevant to me. My thought experiment is this:

What are the consequences of a bunch of people who believe in something called the Singularity and who are also in control of a powerful company?

Categories: modeling, musing

Money in politics

I’m excited about the upcoming weekend, because I’ll be at the Bicoastal Datafest: analyzing money in politics. The event is full at Columbia (but not yet at Stanford) but I believe you can still participate remotely, and of course you can keep an eye on things in any case.

One way to do that: I am setting up a wiki with my friend and colleague Lee Drutman from the Sunlight Foundation. Actually my husband set it up for us (thanks! and happy birthday!).

Let’s visualize the influence of money, people!

Categories: data science

Bill Gates is naive, data is not objective

In his recent essay in the Wall Street Journal, Bill Gates proposed to “fix the world’s biggest problems” through “good measurement and a commitment to follow the data.” Sounds great!

Unfortunately it’s not so simple.

Gates describes a positive feedback loop when good data is collected and acted on. It’s hard to argue against this: given perfect data-collection procedures with relevant data, specific models do tend to improve, according to their chosen metrics of success. In fact this is almost tautological.

As I’ll explain, however, rather than focusing on how individual models improve with more data, we need to worry more about which models and which data have been chosen in the first place, why that process is successful when it is, and – most importantly – who gets to decide what data is collected and what models are trained.

Take Gates’s example of Ethiopia’s commitment to health care for its people. Let’s face it, it’s not new information that we should ensure “each home has access to a bed net to protect the family from malaria, a pit toilet, first-aid training and other basic health and safety practices.” What’s new is the political decision to do something about it. In other words, where Gates credits the measurement and data-collection for this, I’d suggest we give credit to the political system that allowed both the data collection and the actual resources to make it happen.

Gates also brings up the campaign to eradicate polio and how measurement has helped so much there as well. Here he sidesteps an enormous amount of politics and debate about how that campaign has been fought and, more importantly, how many scarce resources have been put towards it. But he has framed this fight himself, and has collected the data and defined the success metric, so that’s what he’s focused on.

Then he talks about teacher scoring and how great it would be to do that well. Teachers might not agree, and I’d argue they are correct to be wary about scoring systems, especially if they’ve experienced the random number generator called the Value Added Model. Many of the teacher strikes and failed negotiations are being caused by this system where, again, the people who own the model have the power.

Then he talks about college rankings and suggests we replace the flawed US News & World Reports system with his own idea, namely “measures of which colleges were best preparing their graduates for the job market”. Note I’m not arguing for keeping that US News & World Reports model, which is embarrassingly flawed and is consistently gamed. But the question is, who gets to choose the replacement?

This is where we get the closest to seeing him admit what’s really going on: that the person who defines the model defines success, and by obscuring this power behind a data collection process and incrementally improved model results, it seems somehow sanitized and objective when it’s not.

Let’s see some more example of data collection and model design not being objective:

  1. We see that cars are safer for men than women because the crash-test dummies are men.
  2. We see that cars are safer for thin people because the crash-test dummies are thin.
  3. We see drugs are safer and more effective for white people because blacks are underrepresented in clinical trials (which is a whole other story about power and data collection in itself).
  4. We see that Polaroid film used to only pick up white skin because it was optimized for white people.
  5. We see that poor people are uninformed by definition of how we take opinion polls (read the fine print).

Bill Gates seems genuinely interested in tackling some big problems in the world, and I wish more people thought long and hard about how they could contribute like that. But the process he describes so lovingly is in fact highly fraught and dangerous.

Don’t be fooled by the mathematical imprimatur: behind every model and every data set is a political process that chose that data and built that model and defined success for that model.

This is what it feels like to be a snob

Got home from Nebraska last night, and I’ve learned an important lesson about how it feels to be a snob. Because, as it turns out, I’m unequivocally a snob in ways I didn’t even realize.

So, I couldn’t find good coffee in Lincoln. That is, in the hotel they had a coffee maker with a tiny pod, and I made myself two cups the first morning I got there, then I went downstairs and drank two more cups of the free coffee you get with the free breakfast and I swear it was hot water.

Then I looked around and wondered, where can I get something with caffeine in it?? After asking a few people this question, I suddenly realized: this is what it feels like to be a snob. Internally it feels weird that other people don’t have the same standards, but externally it looks like a smart-ass New Yorker complaining about the quality of free things.

Next: people would be walking around the hotel in what seemed like pajamas. Not the mathematicians, who came from everywhere, but the other guests in the hotel. They were young, maybe in college, and I swear they were wearing pajamas all the time. Sometimes they switched it up and wore clothes you might wear when watching a football game on the sofa.

Then I realized: people in New York spend way too much time getting all dolled up, and I used to know that, but nowadays I’m just used to it. So this is what is feels to be a snob.

Good to know, because:

  1. Next time someone who’s a huge snob talks to me I’ll have more empathy and explain the situation in clear sentences: you are looking like a snob because you have different standards, and the sooner you understand that the better for everyone.
  2. Next time I travel I plan to bring my own coffee and possibly even my own coffee maker, which I used to think is crazy  snobby but now I get it – it actually saves time versus searching on foot in the winter for a good cup of coffee in a town you are unfamiliar with. I’m embracing my snobbery, people.
  3. Although then again maybe I’ll just bring a big ol’ vat of Nodoz.



Categories: musing

Advice for young women math professors

I’ve been here at the Nebraska conference for undergrad women in math for a couple of days now. There are quite a few grad students and young professors as well and I’m finding myself giving a few pieces of advice over and over again to the new female professors. I thought I’d write them down here too.

Obviously you can take this advice or leave it.

  1. Ban guilt from your child-rearing experience. The tenure system being what it is, it’s just impossible for you to work enough, including research, and to spend 4 hours a day with an awake baby. Instead think of it this way: it takes a village to raise a child, and this is the time when it’s more village than mom, which is ok. Make sure they are in loving environments, have super nice babysitters, get the best daycare you can, and stop worrying about being a crappy mom. Turns out you’ll have plenty of time to do awesome things with your kids and in the meantime they need you to be a role model, which means pursuing your dreams.
  2. I’m not suggesting working too much either – having a really set schedule which allows time for work during daycare and then time for family before and after is great, and your students and colleagues will just need to accept that you are available during working hours and not otherwise. Don’t apologize for this, just do your job, and don’t assume people are judging you for it either. 
  3. I met a ton of women who seem to have taken on all of the household duties and are overwhelmed by them, especially when they also have small children. First of all, lower your standards. Houses can be messy, it doesn’t actually kill anyone if you ignore an upturned lego box because you want to go think about math. Second, budget a housecleaner – one woman described how she and her husband decided to sell their car but kept their housekeeper, and I fully endorse this trade-off. Third, sit down with your partner and write a list of chores and split them up. It’s not sexy but it works. Finally, be sure your kids help as soon as they can. Turns out kids can make their own school lunches starting when they’re 8 if the ingredients are readily available.
  4. Personally I never do more volunteering at the kids’ schools than my husband as a matter of principle. And it also turns out my husband never does any. This makes me a bitch but also saves me a ton of time. Consider it.
  5. Make time for something other than kids and work. Carve it out with a knife if necessary. It will be worth it and will keep you sane and remembering why you made this plan.
  6. Also don’t forget to have dates with your partner.
  7. Finally, if you ultimately decide it’s not working, remember you have lots of options with a math Ph.D. – don’t underestimate yourself and your options.

I hope that’s helpful!

Categories: women in math

Aunt Pythia’s advice

I’m here in Nebraska at a conference for undergraduate women, already late to the morning session, so we’re going with a speed round of advice this morning. Apologies for the shallowness.

If you don’t know what you’re in for, go here for past advice columns and here for an explanation of the name Pythia, and most importantly, please submit your question at the bottom of this column.

First, let’s review last week’s advice you helped out with:


Dear Aunt Pythia,

I was one of those kids who when asked “What do you want to be when you grow up?” said “Errrghm …” or maybe just ignored the question. Today I am still that confused toddler. I have changed fields a few times (going through a major makeover right now), never knew what I want to dive into, found too many things too interesting. I worry that half a life from now, I will have done lots and nothing. I crave having a passion, one goal – something to keep trying to get better at. What advice do you have for the likes of me?

Forever Yawning or Wandering Globetrotter

Dear FYoWG,

Look at Savanarola’s excellent advice and also keep in mind Mathematrucker’s maxim, “life is to enjoy”

Aunt Pythia


Aunt Pythia.

Can something as vast and as complex as the universe ever be reduced to the scope of human mental capacities, or are there natural limits to what we can know?



There are definitely natural limits to what we know, but even more to what we wonder about.



Aunt Pythia,

If you could make any robot, what would it do?


Robocop: It would be an Alf-like character sitting in the corner and making wise-cracks.



Aunt Pythia,

Favorite planet?


Elon: earth.


Aunt Pythia,

I teach statistics and find myself often getting frustrated and angry at my students. They don’t want to do any work, but they all expect A’s anyway. They seem to think that blessing me with their presence (although certainly not their attention) is enough. I lay it all out for them at the start of the semester, yet still have a line of whiners out the door 3 months later when their grades reflect their ACTUAL level of effort and understanding. How should I handle this frustration? Am I just not cut out for teaching?

Universities would be great without all the students

Dear Universities,

Two suggestions. First, be very precise on the first day about your grading policy and expectations for the class, and tell them it’s fixed. This avoids future people whining about turning stuff in late (of course you might have a policy about turning stuff in late but in that case hold firm to it).

Second, keep in mind that as young people and as Facebook users, these kids are used to having different personas in different places in their lives, and use that fact to manipulate influence them in your class. Which is to say, talk about how awesome they are and how hard they work, and how you know they know they can’t learn this stuff without working hard, and you know they’re up to the task.

A good strong dose of early positive encouragement prevents a lot of later negative reinforcement in my experience.

Of course, there will always be students who just don’t do the work for one reason or another (if it’s because of a serious problem, and if they have a doctor’s note, please be kind). In that case refer to the very clearly spelt out rules and don’t give it a further thought.

It’s also possible you aren’t cut out for teaching. If you have a visceral reaction against being encouraging to students then that’s a sign. If so, please do everyone a favor and get out.

Aunt Pythia


For you guys, have fun with it!

Dear Aunt Pythia,

I need a pie crust recipe and a personal lubricant recommendation. Please try to incorporate lard into both answers.

Apple Pie Seductress


And please submit questions, thanks!

Categories: Aunt Pythia

Sentiment should not be the new horizon in journalism

This is a guest post by Anchard Scott, and is cross-posted at aluation.

Nate Silver’s high-profile success in predicting the 2012 election has triggered a wave of articles on the victory of data analysts over pundits. Cathy has already taken on the troubling aspects of Silver’s celebrity, so I’d like to focus instead on the larger movement toward big data as a replacement for traditional punditry. It’s an intriguing idea, especially given the sad state of political punditry. But rather than making things better, it’s entirely possible that the methods these articles propose could make things even worse.

There’s no question that we need better media, especially when it comes to politics. If we take the media’s role to be making sure that voters are informed, then they’re clearly doing a poor job of it. And one of the biggest problems is that political coverage has largely abandoned any pretense of getting to the truth in favor of “he said/she said” and endless discussion of the horse race, with the pundits being the worst offenders. Instead of “Will this be good for citizens?” we get “Will this be good for the Democrats/Republicans in the next poll?”

This is where the big data proposals enter the picture, and where I think they go wrong. Rather than addressing the accuracy or usefulness of the information being provided to us as voters, or working to shift the dialogue away from projections of how a given policy will play in Iowa, the proposals for big data revolve around replacing pundits’ subjective claims about shifting perceptions with more objective analysis of shifting perceptions.

For example, this piece from the Awl convincingly describes the potential for the rapid analysis of thousands or even millions of articles as a basis for more effective media criticism, and as a replacement for punditry by “anecdata.” A more recent post from the Nieman Journalism Lab at least acknowledges some methodological weaknesses even as it makes a very strong case for large-scale sentiment analysis as a way of “getting beyond pundits claiming to speak for others.” By aggregating and analyzing the flow of opinion across social media, the piece argues, journalism can deliver a more finely tuned representation of public opinion.

It’s true that perceptions in a democracy matter a lot. But it’s also true that getting a more accurate read on perceptions is not going to move us toward more informative coverage, let alone toward better politics. Worse still, these proposals ignore the fact that public perception is heavily affected by media coverage, which implies that pulling public perception more explicitly into the coverage itself will just introduce reflexivity rather than clarification.

In other words, we could end up with a conversation about the conversation about the conversation about politics. Is that really what we need?

As I see it, there are two precedents here, neither of which is encouraging. Financial markets have been treated as a source of perfect information for a very long time. The most famous justification for this was Hayek’s claim that the price system inherent in markets acts as “a system of telecommunications” that condenses the most relevant information from millions of agents into a single indicator. Even if we accept this as being true when Hayek wrote his essay in 1945 (which we shouldn’t), it’s certainly not true now. That’s in part because financial markets have attracted more and more speculators who base their decisions on their expectations of what others will do rather than introducing new information. So rather than informational efficiency, we get informational cascades, herding and periodic crashes.

The other example is consumer markets, which have the most experience with sentiment analysis for obvious reasons. In fact, this analysis is only the latest service offered by an enormous industry of advertising, PR and the like that exists solely to engineer and harness these waves of sentiment and perception. Their success proves that perception doesn’t exist in some objective void, but is closely shaped by the process of thinking about and consuming the very products it’s attached to. Or to be wonky about it, preferences can be more endogenous than exogenous in a consumer society.

Which is ultimately my point. If we want to treat the information provided by the media – the primary source of information for our democracy – as a more and more finely tuned consumer good whose value is determined by how popular it is, then this sort of analysis is emphatically the way to go. But we should not be surprised by the consequences if we do.

Categories: data science, guest post