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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.

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?

UncleC

UncleC,

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

AP

——

Aunt Pythia,

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

Robocop

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

ALF

——

Aunt Pythia,

Favorite planet?

Elon

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

I love me some nerd girls

Last night I was waiting for a bus to go hang with my Athena Mastermind group, which consists of a bunch of very cool Barnard student entrepreneurs and their would-be role models (I say would-be because, although we role models are also very cool, I often think the students are role modeling for us).

As I was waiting at the bus stop, I overheard two women talking about the new Applied Data Science class that just started at Columbia, which is being taught by Ian Langmore, Daniel Krasner and Chang She. I knew about this class because Ian came to advertise it last semester in Rachel Schutt’s Intro to Data Science class which I blogged. One of the women at the bus stop had been in Rachel’s class and the other is in Ian’s.

Turns out I just love overhearing nerd girls talking data science at the bus stop. Don’t you??

And to top off the nerd girl experience, I’m on my way today to Nebraska to give a talk to a bunch of undergraduate women in math about what they can do with math outside of academia. I’m planning it to be an informative talk, but that’s really just cover to its real goal, which is to give a pep talk.

My experience talking to young women in math, at least when they are grad students, is that they respond viscerally to encouragement, even if it’s vague. I can actually see their egos inflate in the audience as I speak, and that’s a good thing, that’s why I’m there.

As a community, I’ve realized, nerd girls going through grad school are virtually starved for positive feedback, and so my job is pretty clear cut: I’m going to tell them how awesome they are and answer their questions about what it’s like in the “real world” and then go back to telling them how awesome they are.

By the end they sit a bit straighter and smile a bit more after I’m done, after I’ve told them, or reminded them at least, how much power they have as nerd girls – how many options they have, and how they don’t have to be risk-averse, and how they never need to apologize.

Tomorrow my audience is undergraduates, which is a bit trickier, since as an undergrad you still get consistent feedback in the form of grades. So I will tailor my information as well as my encouragement a bit, and try not to make grad school sound too scary, because I do think that getting a Ph.D. is still a huge deal. Comment below if you have suggestions for my talk, please!

The senseless war between business and IT/data

Last night I attended a NYC Data Business Meetup at Bloomberg, organized by Matt Turck of Bloomberg Ventures.

There were four startups talking about their analytics-for-big-data products. Most of the audience was on the entrepreneurial side of big data, and not themselves data scientists. Of the people on stage, there were four entrepreneur/marketing people and one data scientist.

I noticed, during the Q&A part at the end, that there was a weird vibe in relation to IT/data teams versus business teams. Not everyone present was involved, to be clear, but rather a consistent thread of the conversation.

There was a conflict, we were told, between business and data, and the goal of these analytics platforms seemed to be, to a large extent, a way of bypassing the need for letting data people own the data. The idea was to expedite the “handoff” between the data/IT people and the business people, so that the business people could do rapid, iterative data investigations (without interference, presumably, from pesky data people).

The discussion even went so far as to describe the IT/data team as “territorial” with the data, and there was a short discussion as to how to create processes so that control of the data is clearly spelled out and is in the hands of the business, rather than the data people.

All this left we wondering if I am crazy to believe that, as a data scientist, I am also a business person.

Are we in a war that I didn’t know about? Is it a war between the business side and the data side of the business? And are these analytics platforms the space on which the war is waged? Are they either going to make data people obsolete, by making it unnecessary to hire data scientists, or are they going to make business analytics people obsolete, by allowing data scientists to quickly iterate models?

Are there really such lines drawn, and are they necessary?

Personally, I didn’t leave research in academia so that I could be an mere implementer of a “business person”‘s idea. I left so that I could be part of the decision-making process in an agile business, so that I can be part of the process that figures out what questions to ask, and moreover how to answer them, using my quantitative background.

I don’t think this war is a good idea – instead, we should strive toward creating a scenario in which data scientists and domain experts work together towards forming the question and investigating a solution.

To silo a data person is to undervalue them – indeed my best guess as to why some business people see data people as belligerent is that they’ve been undervaluing their data people, and that tends to make people belligerent.

And to give a business analyst a button on a screen which says “clustering algorithm” is to give them tools they can perhaps use but very probably can’t interpret. It’s in nobody’s interest to do this, and it’s certainly not in the interest of the ambient business.

From now on, if someone asks me if they should accept an offer as a data scientist, I’ll suggest they find out if the place is engaged in an “IT/data versus business” war, and if they are, to run away quickly. It’s a mindset that spells trouble.

Categories: data science, rant

The Compliment Gang

Today I want to share a story with permission from my 10-year-old son.

There’s a bully in his school, a girl who is known to get other kids, boys and girls, together for the express purpose of choosing random victims and insulting them (his phrase is “dis”).

He claims to counteract this behavior by getting together his own posse of “nerd boys” and forming what he calls a compliment gang, where they essentially follow around the above dis gang and say things like, “Hey! I like your shoes!”.

He also enjoys challenging the ringleader to a dance-off, where he demonstrates absurd moves a la Chris Farley:

Categories: Uncategorized

Google search is already open source

I’ve been talking a lot recently, with various people and on this blog, about data and model privacy. It seems like individuals, who should have the right to protect their data, don’t seem to, but huge private companies, with enormous powers over the public, do.

Another example: models working on behalf of the public, like Fed stress tests and other regulatory models, seem essentially publicly known, which is useful indeed to the financial insiders, the very people who are experts on gaming systems.

Google search has a deeply felt power over the public, and arguably needs to be understood for the consistent threat it poses to people’s online environment. It’s a scary thought experiment to imagine what could be done with it, and after all why should we blindly trust a corporation to have our best intentions in mind? Maybe it’s time to call for the Google search model to be open source.

But what would that look like? At first blush we might imagine forcing them to actually opening up their source code. But at this point that code must be absolutely enormous, unreadable, and written specifically for their uniquely massive machine set-up. In other words, totally overwhelming and useless (as my friend Suresh might say, the singularity has already happened and this is what it looks like (update: Suresh credits Cosma)).

Considering how many people would actually be able to make sense of the underlying code base, then you quickly realize that opening it up would be meaningless for the task of protecting the public. Instead, we’d want to make the code accessible in some way.

But I claim that’s exactly what Google does, by allowing everyone to search using the model from anywhere. In other words, it’s on us, the public, to run experiments to undertand what the underlying model actually does. We have the tools, let’s get going.

If we think there’s inherent racism in google searches, then we should run experiments like Nathan Newman recently did, examining the different ads that pop up when someone writes an email about buying a car, for example, with different names and in different zip codes. We should organize to change our zip codes, our personas (which would mean deliberately creating personas and gmail logins, etc.), and our search terms, and see how the Google search results change as our inputs change.

After all, I don’t know what’s in the code base but I’m pretty sure there’s no sub-routine that’s called “add_racism_to_search”; instead, it’s a complicated Rube-Goldberg machine that should be judged by its outputs, in a statistical way, rather than expected to prescriptively describe how it treats things on a case-by-case basis.

Another thing: I don’t think there are bad intentions on the part of the modelers, but that doesn’t mean there aren’t bad consequences – the model is too complicated for anyone to anticipate exactly how it acts unless they perform experiments to test them. In the meantime, until people undertand that, we need to distinguish between the intentions and the results. So, for example, in the update to Nathan Newman’s experiments with Google mail, Google responded with this:

This post relies on flawed methodology to draw a wildly inaccurate conclusion. If Mr. Newman had contacted us before publishing it, we would have told him the facts: we do not select ads based on sensitive information, including ethnic inferences from names.

And then Newman added this:

Now, I’m happy to hear Google doesn’t “select ads” on this basis, but Google’s words seem chosen to allow a lot of wiggle room (as such Google statements usually seem to). Do they mean that Google algorithms do not use the ethnicity of names in ad selection or are they making the broader claim that they bar advertisers from serving up different ads to people with different names?

My point is that it doesn’t matter what Google says it does or doesn’t do, if statistically speaking the ads change depending on ethnicity. It’s a moot argument what they claim to do if what actually happens, the actual output of their Rube-Goldberg machine, is racist.

And I’m not saying Google’s models are definitively racist, by the way, since Newman’s efforts were small, the efforts of one man, and there were not thousands and thousands of tests but only a few. But his approach to understanding the model was certainly correct, and it’s a cause that technologists and activists should take up and expand on.

Mathematically speaking, it’s already as open-source as we need it to be to understand it, although in a dual way than people are used to thinking about. Actually, it defines the gold standard of open-source: instead of getting a bunch of gobbly-gook that we can’t process and that depends on enormously large data that changes over time, we get real-time access to the newest version that even a child can use.

I only wish that other public-facing models had such access. Let’s create a large-scale project like SETI to understand the Google search model.

The Yarn Whisperer

Everyone should get a yarn whisperer. Here’s mine:

Yes, she has her knitting project in that white bag, just in case there's a 2-minute lull

Yes, she has her knitting project in that white bag, just in case there’s a 2-minute lull

What does a yarn whisperer provide, you ask? Among other things:

  1. continuous advice on how to use the yarn you have,
  2. unadulterated enabling of buying more yarn that you don’t need, and
  3. companionship to annual “yarn events” (where #2 above takes place with wild abandon)

Yesterday me and my yarn whisperer went to Knitting Vogue Live (or VKL for those in the know), held at the Times Square Marriott. It was extra fancy, by knitting standards, which if you don’t know what that is, think Star Trek conventions for the knitterlati.

We had our very own knitting fashion show:

We are all looking at that hat.

We are all looking at that scrumptious hat.

Just take another look at this packed crowd:

A nicer group of frumpy crafty women from Connecticut you'll never see

A nicer group of frumpy crafty women from Connecticut you’ll never see

I was amazed to meet Alasdair Post-Quinn:

The number of scarf configurations is larger than the number of atoms in the universe.

The number of scarf configurations is larger than the number of atoms in the universe.

Alisdair is the author of the book “Extreme double knitting”:

You gotta say "EXTREME" like a Monster Truck Rally is coming to town.

You gotta say “EXTREME” like a Monster Truck Rally is coming to town.

And he does incredible double-knitting work. I told him he’s a mathematician, even if he wasn’t trained. Here are some examples:

That's *three strands* on the Escher-like scarf on the left!

That’s *three strands* on the Escher-like scarf on the left!

And here’s the back of the trees one:

I've always wanted to knit realistic trees.

I’ve always wanted to knit realistic trees.

I got a huge kick out of staring at people’s backs yesterday:

Don't worry, I asked before I took this picture.

Don’t worry, I asked before I took this picture.

I'm not a fan of glitter but if you go for it, you gotta GO FOR IT

I’m not a fan of glitter but if you go for it, you gotta GO FOR IT

I also enjoyed meeting this man with ENORMOUS KNITTING NEEDLES:

Sorry for the blur, couldn't stop giggling. Note his vest, also made from enormous yarn

Sorry for the blur, couldn’t stop giggling. Note his vest, also made from enormous yarn.

And the yarn sculptures were super:

Is it art or is it clothing?

Is it art or is it clothing?

 

Take this off before eating soup.

Take this off before eating soup.

Thank you, oh yarn whisperer!

Categories: musing

Aunt Pythia’s advice

It’s happily time for another installment of Aunt Pythia’s advice; 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, I need more questions!

I forgot to give the readers something to do last time, so let’s start out fresh.

——

Dear Auntie P,

Is it possible to convince others about how excited you are in a subject in which you have little trainng, and make them give you a chance to work in this field? I’m a recent post-doc in pure mathematics trying to be a population scientist.

Hard Dreamer

Dear HD,

Credentialing is a tough thing in general, but in my experience a math Ph.D. is pretty useful in most situations. In industry it will get you an interview, especially if you also have some relevant skills like computer programming. Once you are in the interview, of course, you have to turn on the charm and communication and generally behave like a human being that people can relate to.

The exception might be other academic fields. There’s a feedback loop in academics, whereby people have a very precise idea of what makes a good researcher in their field, and they just kind of ignore people without those credentials. Since you really can’t do good research whilst being ignored (or at least it’s really hard), it’s a self-fulfilling blindspot, and the ignored people really do end up not doing very well, which reinforces the notion that one should ignore them.

One reason I think this happens less in industry is that there, people are used to the fact that they have to work in teams of people with various skills, so they know that someone who’s a proven quantitative problem solver will be useful. On the other hand, the problems they solve are typically less involved and theory-based, so it’s easier to train a smart person to be helpful. So really that’s two reasons.

My advice to you, or anyone else who wants to switch from math to a different academic research discipline, is to find someone deep in that field and ask them what the credentialing in their field looks like, and how to rebrand yourself as something closer to their ideal. Maybe you can collaborate with them on a paper, to show you are capable of bridging the communication divide.

Good luck!

Aunt Pythia

——

Aunt Pythia,

Can I remain in academia despite the crazy status-conscious, petty and grandiose nature of it?

Out on the Island

Dear OOTI,

You never get rid of your problems, you only get a new set of problems. Look into your options and their accompanying problems and decide what to do in that light. Keep in mind, academia is at least not unethical (usually).

Aunt Pythia

——

Aunt Pythia,

My friend has a new friend who is pretentious and snobby and hard to be around. Now these qualities are wearing off on my friend, one of the sweetest naturally people I know. Is there a way to make her see this?

Concerned Friend

Dear Concerned Friend,

Easy peazy lemon squeezy. Next time you are alone with your friend, complain about her friend the snob for being a snob – make sure not to mix it in with other complaints or she will just think you’re mean or jealous. So, say something like, “I generally really enjoy Martha’s company but it really embarrassed me how she treated the waiter the other day, what an elitist snob!”

It’s the oldest back-stabbing trick in the book, and it will make her aware of the snobbery, which she probably doesn’t see, and it will also make her aware that you don’t like that kind of behavior, so she will be conscious of her snobby ways near you. Problem solved!

If you are conflict-avoidant, or just think the above suggestion is rude (same diff), then you could first try making a general complaint about snobby people, and give an example very similar to something your friend’s friend did recently in her and your presence (“Don’t you hate it when people yell at flight attendants?”). But if that’s not sufficient, move on to the above.

Tell me what happens!

Aunt Pythia

——

Yo,

When I’m in polite company I sometimes feel the need to scratch my balls. How can I do so without attracting notice?

Somewhere in the world

Yoyo,

Isn’t that what pockets are for? Jeez.

AP

——

Dearest Aunt Pythia,

What’s the most important? Length, width, magic of the performer? Doesn’t matter above/below a certain threshhold?

Just wanna read you write about sex

Dear JWRYWAS,

Glad you asked. There’s been a quantitative study  on the matter which I’ve been dying to share. The key visual:

penis_preference

 

Hope that helps!

Aunt Pythia

p.s. I’ll keep an eye out for a quantitative study comparing “penis” with “magic” to finish answering your question.

——

Dear Aunt Pythia,

What are the effect of alcohol on your state of mind?

Boy from Delphi

Dear Boy,

Alcohol merely allows me to say what I really want to say, as if I don’t already.

Aunt Pythia

——

Here’s a question for you. It’s rather vague but I think you guys will have something important (or funny, or pithy) to suggest:

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

——

Please submit questions, thanks!

Categories: Aunt Pythia

Alt-Banking calls on Senate to defend Main Street against Wall Street (#OWS)

This is crossposted from the blog of the Alternative Banking Working group of #OWS.

Dear Senators,

It is now up to you to restore the integrity of the Department of the Treasury.

As the Department’s web site states, Treasury’s job is to:

“Maintain a strong economy and create economic and job opportunities by promoting the conditions that enable growth and stability…protecting the integrity of the financial system, and manage the U.S. Government’s finances and resources effectively.”

President Obama’s nominee, Jacob Lew, does not measure up to the task.

Since the days of the Clinton Administration, the office of the Treasury Secretary has morphed into the custodian of Wall Street interests, allowing fraudulent banking practices to lead us into a recession, paying little or no heed to the concerns of Main Street about economic growth or jobs. Moreover, unlike the George W. Bush presidency where Enron executives were jailed — little has been done since the latest crisis to prosecute the people responsible for the widespread criminality and total disregard of ethics and values in finance.

The new Treasury Secretary should be an individual who looks out for the 99%, not a Timothy Geithner clone who would rather save financial players than enforce the law. We need someone who will focus on the productive economy and jobs. We need someone who will push back against Wall Street, not someone who will do their bidding.

Jacob Lew’s tenure at the original too-big-to-fail bank, Citigroup, has disqualified him. He received a $900,000 bonus from Citi in 2008, essentially paid out of the taxpayer bailout, just before he returned to government. At best this has the “appearance of impropriety”.

As HSBC’s “too big to jail’ settlement shows, the too-big-to-fail problem persists. We need a Treasury Secretary who will work to address this. Despite being near the heart of the storm, or perhaps because he was at Citigroup, Jack Lew shows no recognition that the current structure of the banking system is the heart of the problem. We must block his appointment.

Criminality and greed are embedded in the culture of the financial system and only major reform will get rid of it.  Please join us in our efforts to reject Jacob Lew and ask President Obama to nominate someone who can truly live up to the mandate of the U.S. Treasury.

Sincerely,

Members of the OWS Alternative Banking Group

Marni Halasa
Josh Snodgrass
Hannah Appel
Linda Brown
Nicholas Levis
Cathy O’Neil
Anchard Scott
Yves Smith
Akshat Tewary

Categories: #OWS

R is mostly like python but sometimes like SQL

I’m learning a bit of R in my current stint at ThoughtWorks. Coming from python, I was happy to see most of the plotting functions are very similar, as well as many of the vector-level data handling functions. Besides the fact that lists start at 1 instead of 0, things were looking pretty familiar.

But then I came across something that totally changed my mind. In R they have these data frames, which are like massive excel spreadsheets: very structured matrices with named columns and rows, on which you can perform parallelized operations.

One thing I noticed right away about these rigid data structures is that they make handling missing data very easy. So if you have a huge data frame where a few rows are missing a few data points, then one command, na.omit, gets rid of your problem. Sometimes you don’t even need that, you can just perform your operation on your NA’s, and you just get back more NA’s where appropriate.

This ease-of-use for crappy data is good and bad: good because it’s convenient, bad because you never feel the pain of missing data. When I use python, I rely on dictionaries of dictionaries (of dictionaries) to store my data, and I have to make specific plans for missing data, which means it’s a pain but also that I have to face up to bad data directly.

But that’s not why I think R is somewhat like SQL. It’s really because of how bad “for” loops are in R.

So I was trying to add a new column to my rather large (~65,000 row) dataframe. Adding a column is very easy indeed, if the value in the new column is a simple function of the values in the current columns, because of the way you can parallelize operations. So if the new value is the square of the first column value plus the second column value, it can do it on the whole columns all at once and it’s super fast.

In my case, though, the new value required a look-up in the table itself, which may or may not work, and then required a decision depending on whether it worked. For the life of me I couldn’t figure out how to do it using iterated “apply” or “lapply” functions in the existing dataframe. Of course it’s easy to do using a “for” loop, but that is excruciatingly slow.

Finally I realized I needed to think like a SQL programmer, and build a new dataframe which consisted of the look-up row, if it existed, along with a unique identifier in common with the row I start with. Then I merged the two dataframes, which is like a SQL join, using that unique identifier as the pivot. This would never happen in python with a dataset of this size, because dictionaries are very unstructured and fast.

Easy peasy lemon squeazy, once you understand it, but it made me realize that the approach to learning a new language by translating each word really doesn’t work. You need to think like a Parisian to really speak French.

Categories: open source tools

Quantifying the pull of poverty traps

In yesterday’s New York Times Science section, there was an article called “Life in the Red” (hat tip Becky Jaffe) about people’s behavior when they are in debt, summed up by this:

The usual explanations for reckless borrowing focus on people’s character, or social norms that promote free spending and instant gratification. But recent research has shown that scarcity by itself is enough to cause this kind of financial self-sabotage.

“When we put people in situations of scarcity in experiments, they get into poverty traps,” said Eldar Shafir, a professor of psychology and public affairs at Princeton. “They borrow at high interest rates that hurt them, in ways they knew to avoid when there was less scarcity.”

The psychological burden of debt not only saps intellectual resources, it also reinforces the reckless behavior, and quickly, Dr. Shafir and other experts said. Millions of Americans have been keeping the lights on through hard times with borrowed money, running a kind of shell game to keep bill collectors away.

So what we’ve got here is a feedback loop of poverty, which certainly jives with my observations of friends and acquaintances I’ve seen who are in debt.

I’m guessing the experiments described in the article are not as bad as real life, however.

I say that because I’ve been talking on this blog as well as in my recent math talks about a separate feedback loop involving models, namely the feedback loop whereby people who are judged poor by the model are offered increasingly bad terms on their loans. I call it the death spiral of modeling.

If you think about how these two effects work together – the array of offers gets worse as your vulnerability to bad deals increases – then you start to understand what half of our country is actually living through on a day-to-day basis.

As an aside, I have an enormous amount of empathy for people experiencing this poverty trap. I don’t think it’s a moral issue to be in debt: nobody wants to be poor, and nobody plans it that way.

This opinion article (hat tip Laura Strausfeld), also in yesterday’s New York Times, makes the important point that listening to a bunch of rich, judgmental people like David Bach, Dave Ramsey, and Suze Orman telling us it’s our fault we haven’t finished saving for retirement isn’t actually useful, and suggest we individually choose a money issue to take charge and sort out.

So my empathetic nerd take on poverty traps is this: how can we quantitatively measure this phenomenon, or more precisely these phenomena, since we’ve identified at least two feedback loops?

One reason it’s hard is that it’d be hard to perform natural tests where some people are submitted to the toxic environment but other people aren’t – it’s the “people who aren’t” category that’s the hard part, of course.

For the vulnerability to bad terms, the article describes the level of harassment that people receive from bill collectors as a factor in how they react, which doesn’t surprise anyone who’s ever dealt with a bill collector. Are there certain people who don’t get harassed for whatever reason, and do they fall prey to bad deals at a different rate? Are there local laws in some places prohibiting certain harassment? Can we go to another country where the bill collectors are reined in and see how people in debt behave there?

Also, in terms of availability of loans, it might be relatively easy to start out with people who live in states with payday loans versus people who don’t, and see how much faster the poverty spiral overtakes people with worse options. Of course, as crappy loans get more and more available online, this proximity study will become moot.

It’s also going to be tricky to tease out the two effects from each other. One is a question of supply and the other is a question of demand, and as we know those two are related.

I’m not answering these questions today, it’s a long-term project that I need your help on, so please comment below with ideas. Maybe if we have a few good ideas and if we find some data we can plan a data hackathon.

ThoughtWorks

January 15, 2013 Comments off

Yesterday morning when I got to my office, where I’ve been doing a temporary consulting gig, I was surprised to learn that I’d been working in the same room with Aaron Swartz for the past 3 weeks.

The company is called ThoughtWorks, and I’d learned about it through my last company, where some of the best developers had come from the “ThoughtWorks family,” and one of them was still going back to the office every week to work on a volunteer coding project which uses technology to help find missing children. And that’s not all.

The first time I formally met the ThoughtWorkers was on a retreat in lower Manhattan, when I came as an Occupier to pitch a web app to help people find a credit union. I got immediate response, and they quickly formed a team of developers and product people to help our Occupy group build the app (for unrelated reasons this project has stalled, namely we couldn’t find a long-term home for the app inside the credit union community).

So it wasn’t that surprising to learn that they’d hired Aaron 9 months ago, knowing full well what legal problems he was having, understanding and valuing his activist activities, and hiring him on with a new project aimed to promote justice.

It just made me wish I’d introduced myself to everyone last week rather than yesterday, when we were talking in sadness and anger at losing him. As I said yesterday, it speaks well of ThoughtWorks that they’d made a home for Aaron, and I am proud to be working there now, even if it’s only for a short time.

They expressed a desire to carry on in Aaron’s name, which of course different people will go about in different ways. But if you ask me, that means promoting justice and fair access to resources through scrappy technology, broadly understood. Because as I’ve learned, he was a generalist of the best kind when it came to working towards a fairer society.

Categories: Uncategorized

Should the U.S. News & World Reports college ranking model be open source?

I had a great time giving my “Weapons of Math Destruction” talk in San Diego, and the audience was fantastic and thoughtful.

One question that someone asked was whether the US News & World Reports college ranking model should be forced to be open sourced – wouldn’t that just cause colleges to game the model?

First of all, colleges are already widely gaming the model and have been for some time. And that gaming is a distraction and has been heading colleges in directions away from good instruction, which is a shame.

And if you suggest that they change the model all the time to prevent this, then you’ve got an internal model of this model that needs adjustment. They might be tinkering at the edges but overall it’s quite clear what’s going into the model: namely, graduation rates, SAT scores, number of Ph.D’s on staff, and so on. The exact percentages change over time but not by much.

The impact that this model has had on education and how universities apportion resources has been profound. Academic papers have been written on the law school version of this story.

Moreover, the tactics that US News & World Reports uses to enforce their dominance of the market are bullying, as you can learn from the President of Reed College, which refuses to be involved.

Back to the question. Just as I realize that opening up all data is not reasonable or desirable, because first of all there are serious privacy issues but second of all certain groups have natural advantages to openly shared resources, it is also true that opening up all models is similarly problematic.

However, certain data should surely be open: for example, the laws of our country, that we are all responsible to know, should be freely available to us (something that Aaron Swartz understood and worked towards). How can we be held responsible for laws we can’t read?

Similarly, public-facing models, such as credit scoring models and teacher value-added models, should absolutely be open and accessible to the public. If I’m being judged and measured and held accountable by some model in my daily life as a citizen, that has real impact on how my future will unfold, then I should know how that process works.

And if you complain about the potential gaming of those public-facing models, I’d answer: if they are gameable then they shouldn’t be used, considering the impact they have on so many people’s lives. Because a gameable model is a weak model, with proxies that fail.

Another way to say this is we should want someone to “game” the credit score model if it means they pay their bills on time every month (I wrote about this here).

Back to the US News & World Report model. Is it public facing? I’m no lawyer but I think a case can be made that it is, and that the public’s trust in this model makes it a very important model indeed. Evidence can be gathered by measuring  the extent to which colleges game the model, which they only do because the public cares so much about the rankings.

Even so, what difference would that make, to open it up?

In an ideal world, where the public is somewhat savvy about what models can and cannot do, opening up the US News & World Reports college ranking model would result in people losing faith in it. They’d realize that it’s no more valuable than an opinion from a highly vocal uncle of theirs who is obsessed with certain metrics and blind to individual eccentricities and curriculums that may be a perfect match for a non-conformist student. It’s only one opinion among many, and not to be religiously believed.

But this isn’t an ideal world, and we have a lot of work to do to get people to understand models as opinions in this sense, and to get people to stop trusting them just because they’re mathematically presented.

Leaning into the pain

I didn’t know Aaron Swartz personally, but I’ve been reading about his life and death (hat tip Suresh Naidu) in the past day and he was clearly a remarkable thinker. His writing about procrastination in the context of computer programming (hat tip Matt Stoller) is particularly resonant. From the essay:

Yes it’s painful, but the trick is to make that mental shift. To realize that the pain isn’t something awful to be postponed and avoided, but a signal that you’re getting stronger — something to savor and enjoy. It’s what makes you better.

Pretty soon, when you start noticing something that causes you psychic pain, you’ll get excited about it, not afraid. Ooh, another chance to get stronger. You’ll seek out things you’re scared of and intentionally confront them, because it’s an easy way to get the great rewards of self-improvement. Dalio suggests thinking of each one as a puzzle, inside of which is embedded a beautiful gem. If you fight through the pain to solve the puzzle, you unlock it and get to keep the gem.

The trick is: when you start feeling that psychological pain coming on, don’t draw back from it and cower — lean into it. Lean into the pain.

You should really read the whole thing. Aaron explains something about good coding practices that elevates coding to a philosophical activity (which it deserves but rarely achieves) and, like any good philosophy, makes us reconsider how we spend our time and what we choose to do with it.

I know exactly what pain I’m leaning into this morning.

Categories: musing

Aunt Pythia’s advice

It’s time for another possibly final installment of Aunt Pythia’s advice; 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, I need questions! In fact I’m pretty much going to answer all my remaining questions today, just to show you how much I need questions. So this will be the last installment of Aunt Pythia unless I get new questions.

From last time, I asked about the etiquette of ignoring Elsevier referee requests from the perspective of an editor:

Aunt Pythia,

If an editor of an Elsevier journal asks you to referee a paper, wouldn’t it be the norm to decline the request instead of leaving it unanswered, or does Gowers’s revolution includes that anyone who has not joined for one reason or another should be shunned and considered a pariah?

Trapped Editor

The answers were pretty clear: etiquette demands we say why we’re not doing it. If you haven’t got an actual refusal, you’re dealing with a lazy-ass, not a political activist.

——

Dear Aunt Pythia,

Every time I say I admire how Lionel Messi plays for Barcelona and Argentina, my husband says it is a crush. According to my husband, women cannot admire men without them mixing up some lust or crush or impure love. What do you say?

novembertwentyeleven

Dear 11/11,

I agree with your husband, but at the same time I don’t see any problem whatsoever with having a crush on Lionel Messi, he’s hot:

lionel

 

In general I project onto others what I have experienced internally, so I would always assume a crush when it comes to a strapping young male athlete, yes. I may be wrong, but even if you insist I am, I will suspect I’m right. But what does it matter really?

I hope that helps,

Aunt Pythia

——

Dear Aunt Pythia,

Dear Aunt Pythia, How much do you tip on to go orders?

Outrageous in Oakland

Dear Outrageous,

What?! I don’t tip on to-go orders at all. If I’m standing there an picking up my own food from a restaurant I kind of don’t think they need extra money for all the service they’re providing me.

If you mean on delivery, then I tip at a rounded-up 10% rate to the nearest dollar, with a $5 minimum. One time I tipped less than this and a belligerent deliverer refused to leave. It was a learning experience.

AP

——

Dear Aunt Pythia,

Dear Aunt Pythia, as an alpha female are you able to fall in love?

Happy Brownian

Dear Happy,

What a bizarre question. But I’m going to answer it anyway.

Yes, I definitely fall in love, but since you asked I’m going to throw in that I don’t expect love to be magical, to find a soul mate, or to have my partner complete me in some weird way. I find that kind of romantic notion utterly weird and unattractive and it’s never made sense to me why people would even desire that loss of self. I’m tempted to think this is related to my being alpha, but I’m not sure.

For me true love means finding someone you still want to hang out with and are still surprised by 17 years after you met them, even though they never learned to play bridge.

AP

——

Dear Aunt Pythia,

Do you know you give a new meaning to the acronym MILF?

DrunkGuy

Dear DrunkGuy,

Now that you’ve sobered up, can you be more specific as to the “new meaning” part? For now I’ll assume you mean “Momma I’d like to Fund (for her open model initiative)”.

Aunt Pythia

Again, please ask questions, I’m out.

Note: it is okay to recycle old Dan Savage questions: I have no ethics here.

Categories: Uncategorized
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