Men in Computer Science

There have been some discussions lately on gender ratios and equality in Computer Science. In this post I don’t want to rehash the scientific studies, but just talk about my own experience as a man in the field of theoretical computer science, ever since I started graduate school nearly 20 years ago. I don’t presume to talk for all males, but I don’t think my story is completely non-representative. This is also a good opportunity to recommend that people read the research life stories series that Omer Reingold initiated on this blog, as well as the Turing centennial series on Luca Trevisan’s blog.

 

Like many other new grad students, when I just started at the Weizmann Institute of Science, I was extremely anxious. While I loved (the little I knew about) theory, I was not sure if I’m smart enough to do original research in this area. The professors seemed like beings from another world, but one thing that helped was that at least I did share some background with them. Almost all of them were males (and in fact, this being Israel, almost all were, like me, Ashkenazi secular jews). So, it was not completely unthinkable to imagine that I would some day be like them.

 

Another thing that helped me a lot in my early time in Weizmann was my study group.
I quickly found three friends, all male, and we spent many hours together studying for exams, talking about research, but also playing video games.

 

As I progressed in the field, I’ve had a great many research interactions and collaborations. I’ve met people at all hours and various locations, including coffee shops, restaurants, and private homes. I’ve never had to worry about the potential for sexual harassment, nor that I would be judged by my looks or what I wear. I am the type of person that speaks their opinion loudly, perhaps sometimes a little too loudly. In my experience, women that act the same are judged by a different standard and often “rub people the wrong way” and get tagged as having problematic personalities. Also, I was never afraid to ask potentially stupid questions. I did not need to fear that asking such a question would confirm people’s bias about me that I don’t belong in this field. Asking potentially stupid questions is one of the most useful ways to learn and evolve as a scientist.

 

Last but not least, I would most definitely not be where I am if my wife did not quit her job in Israel to move with me across the Atlantic for my postdoc. Also, while I think of myself as an involved father, I have to admit that Ravit still does more of the childcare duties. (As I’m reading this out loud, my daughter is commenting that I am not such an involved father…) Again, I am not saying that all male scientists are like me, nor that there are no female scientists that greatly rely on the support of their partners, but I don’t think my situation is atypical.

 

On more general terms, one misconception I see about science in such discussions is that it is about “things” or “facts” and not people, and hence perhaps should be free of biases.
But in fact science is an extremely social enterprise. Since graduating, I have never written a solo paper. Much of my work is spent talking to people in front of a whiteboard or notepad, and I’ve learned a great deal from discussions with fellow scientists. This also explains why certain subfields of science can have outlying gender or ethnicities ratios. People just feel more comfortable working with others similar to them, and role models greatly influence the fields students choose to pursue. For example, there is nothing innately Hungarian about combinatorics. Similarly, there is nothing innately feminine about cryptography, but rather a few extremely strong female scientists have had a huge effect. The influence of people such as Shafi Goldwasser, Tal Rabin, and others has not been limited just to their (amazing) research results but also as role models and mentors to many female cryptographers (and many male cryptographers as well, myself included).

 

I don’t like the expression “leveling the playing field” because Science is not a game. This is not about competing but about collaborating with each other to uncover the mysteries of the universe. But us males (especially those that, like me, come from amply represented ethnicities), should be aware and grateful for the advantages we’ve had in our careers. We should not try to remove these advantages: access to role models, freedom from bias, ease of networking, are all good things. We should however strive for a world where everyone enjoys the same benefits. In such a world we’ll have more scientists that are more productive and happier, and that will only be better for science.

A Social Blogger

Since the close of MSR-SVC, I seem to have lost my taste for blogging. I think I finally know why: For me blogging is a social activity. I loved discussing the posts with my down-the-hall colleagues and friends. So, to regain this wonderful feeling, we (Stanford Theory) are opening a new theory group blog – Theory Dish. I hope this experience would be as great as starting “Windows on Theory” has been (for us and the readers).

As for “Windows on Theory,” we seem to have left the wonderful Boaz to hold the fort on his own, which he has done valiantly so far. Surely, recruiting Boaz has been one of my greatest contributions to the world of theory blogging and I simply love his posts. Nevertheless, I am not leaving Windows on Theory and we have great plans for it, including guest posts and more. Stay tuned!

Stanford, Here I Come

Most of the stories in the research-life story project (including mine) are already processed and often told with some well-packaged perspective the teller wants to share. Today I am sharing a moment as it unfolds: Come next fall, I’ll be joining the Stanford CS Department. I’m very excited.

Since the closing of MSR-SV, I’ve been lending a hand in efforts to create a new distributed-system group at Samsung Research America. But in a few months I’ll be returning to academia. Returning may be too strong of a word. The place where I was “academically born” and where I served as a CS Professor was The Weizmann Institute of Science. Weizmann feels to me (and I hope it will always feel) like home. But Weizmann and Stanford are very different. So the question that burns in me towards next year (and towards the decades I hope to spend at Stanford) is what can I do at Stanford that I couldn’t at my past wonderful work places?

Of course, the main thing I plan to do is (hopefully good) research. With the excellent Stanford students and faculty (theory and otherwise), I am sure it will be a lot of fun. But my feeling is that this should not be it. Buzzing in my mind are many ideas (which I expect would require many years and some/most would never happen): New intro courses to CS (targeting different populations- Humanities, Math, Sciences, Information Science), new popular science books, new programs for K-12 education, a stronger connection with local theorists in industry, and perhaps most importantly to me is contributing to making academia a more humane place for students, junior faculty and in fact for all of us. The research-life story project was motivated by similar desires, and I hope to join efforts around the world that take this approach much further. I have the feeling that Stanford would be a particularly suitable place to promote these agendas (and others).

So what would you be passionate about in my shoes?

Doing a 180 and still spinning

I taught my first class last quarter and it was an enjoyable and eye-opening experience at many levels. First some background. The class was undergraduate algorithms or as popularly known in UCLA – CS180. There were 129 students (kind of like jumping into the deep end to test the waters). Like most other CS curricula, it is a core required course and as I later heard from the students, the class can have a significant impact on where you intern or even get employed eventually (all software companies want to know how you did in this course).

This post is meant to record some of my observations.

How I felt: The first two weeks felt a bit stressful and burdensome. But once I got used to it, I started enjoying the lectures and it was indeed quite pleasing to hear (and in some cases see) that a good fraction of the students liked the material and see them participating in class.

Hindsight: The most significant point was the level of the assignments. Here I erred mainly due to a mismatch in expectations. The first assignment, the median was 100% so I increased the level. The next one was at 77% which still felt high and not challenging enough for the students. At this point I consciously had 50% of each assignment be moderately easy problems (directly based on class work) and the remaining 50% range from not-so-easy to problems requiring at least one new idea. While perhaps the concept was right, the proportions were off from what the students expected. A 80-20 or so split would have been much better in hindsight. I got it almost right for the final with the median being 75%.

There were no real surprises in the syllabus covered with most topics being in common with other similar classes (you can compare here: Harvard, MIT 1, MIT2, MIT 3, CMU 1, CMU 2, Stanford 1, Stanford 2, Coursera-Stanford). However, it did feel a little ambitious in the end and the content needs some pruning. For instance, I spent one lecture each on three somewhat non-standard topics – analyzing sampling methods, contention resolution and cuckoo hashing. For the next time perhaps covering one of them or even none would be better.

A few people asked to include a programming component in the course. This makes perfect sense and I indeed considered it seriously at the beginning and thought about doing something like what Jelani Nelson used at Harvard. But it was plainly infeasible to have programming components in the assignments with the available resources (Jelani tells me he had 10 TAs for a class of about 180). Perhaps for the next time around I can suggest problems for students to play with even if they won’t be graded.

One other request was for practice midterm/final questions. I am still undecided about this one.

Proofs: I spent a lot of time in class proving that various (in some cases extremely simple) algorithms work. This is not an exception for this course, but seems to be true for most similar courses (check the syllabi: Harvard, MIT 1, MIT2, MIT 3, CMU 1, CMU 2, Stanford 1, Stanford 2, Coursera-Stanford).

So, as a few students asked, why so much emphasis on proofs in an algorithms class? There are two separate issues here. First, perhaps my not-so-clear presentation (this is the first run after all). Let us separate that from the second, probably more pressing one – if the goal of an algorithms course is to develop algorithmic thinking and/or prepare the students mainly for a career in software engineering, why should we (by we I mean all algorithms courses across the universities) emphasize proofs?

First, which proofs did I spend a lot of time doing? Well, there was 1) BFS/DFS, 2) FFT, 3) Minimum spanning trees, 4) Sampling, 5) Quicksort, 6) Hashing.

BFS/DFS we can explain as they serve as examples to illustrate induction, invariants etc. For FFT, the algorithm and the proof are one and the same – you can’t quite come up with the algorithm without the proof. But how about the others?

Take MST, Quicksort, hashing. With the right questions, you can motivate students to come up with the algorithms themselves as they are indeed quite natural and simple. But shouldn’t that be the end of developing algorithmic thinking? Same goes for Quicksort, hashing. Randomized divide & conquer makes intuitive sense and so does making random choices when in doubt. Why go deeply into probability, linearity-of-expectation to analyze these? Here are two worthwhile reasons (among many) I can think of.

First, speed is not everything – we need to be sure that the algorithm works. At the end of the day, even when you just want to build something hands on, in many cases you need to be absolutely sure that what you have actually works. For example, it is easy to come up with examples where greedy fails. In class I did do an example (knapsack) where greedy strategy fails. However, looking back I should have emphasized it more and drawn a parallel with other examples where greedy fails.

Second, the goal of the course is not just to help with programming faster code but also to serve as a launching pad for a path to computer science (with emphasis on the ‘science’). Even in the former case, thinking about algorithms in a principled way and being able to analyze them will eventually help in designing new algorithms; especially so when you have to tweak existing algorithms for new applications. Looking back, including more examples to demonstrate this concept would have been quite helpful.
Future: I look forward to teaching the class again keeping the above points in mind. It should only get better for me and hopefully for the students too.

Goin’ up, down, all around, it’s like a see saw*

This is my last research life-story (at least for now), possibly concluding this project (though you are all very welcomed to share more as long as this blog lives). My main hope was to give legitimacy to all of us to acknowledge and discuss our uncomfortable feelings and the “non-scientific” challenges of our careers. My experience with myself and others is that many of these neuroses are quite universal. And they are not necessarily correlated with success, which sometimes only adds internal pressure. Paraphrasing what Russell Impagliazzo told me the first time we met (years ago): we really are competing with ourselves, and this is a hopeless competition (I’m sure he said it better). As for myself, I feel that I learned how to enjoy our profession much more over the years (mainly through becoming a little less childish with time). Still, at times, I do feel inapt. Such a period is the topic of my last story.

During my last postdoc year, we had our first child. This was a wonderful event that I had been craving for years. But it was also very demanding. My son was colicky and we were inexperienced and mostly alone in the U.S. In addition we had three house moves, one of which was back to Israel (a move that was surprisingly non-smooth). I was very content with putting my young family at the center and I realized that this is a period that will not repeat itself and should be cherished (turns out that with kids, many periods are like that). I also understood that I cannot expect to do too much research at this period. There was nothing concrete I was worried about: I had just landed my dream position at Weizmann, I wasn’t worried about getting tenure, and I already had many results that I was very proud of (including one with Irit Dinur on PCPs that was quite recent). I could allow myself to take it easy, but my ego was not ready for that. With time, internal pressure accumulated. “Is this it? Did my creativity dry up? Is it downhill from now on?”

At the end of that year at Weizmann (with my son being just a bit over a year), I headed with my family to a summer trip to Berkeley (to work with Luca Trevisan and Irit Dinur) and to Cambridge (to Work with Salil Vadhan). I decided to invest all of the effort in problems related to RL vs. L and felt that this is a test for me. If I’ll fail, then I will scale down my expectation of myself. With this shaky (and so very silly) state of mind, I came to a complexity-theory workshop that started the trip. Though my talk about the work with Irit was very well received, I felt quite depressed. It felt like everyone have been doing these wonderful research and only I was idle. I especially remember one of these talks, with a speaker (who I knew to be very nice) that had an over-confident demeanor. Such individuals always put me off, but at this strangely vulnerable state of mind, it was a challenge to keep the tears inside.

The summer continued quite differently. Spending time with wonderful friends (who happen to be brilliant researchers), having a lot of time for vacationing with my family (thanks to Luca’s great life balance), and ending up with a result that exceeded all of my hopes (undirected connectivity in log-space). I remember very vividly the exact moment when two ideas that I had for many years suddenly clicked in an exciting new way. I remember pacing back and forth in our hotel room, going over the proof that then only existed in my mind. Could it be true? Surely not! But where could the bug be hiding? I remember going out to find a store that would have a notepad and pen for me to start writing the proof down and the slowly growing confidence that came from writing it down and every session of verification (Luca, Irit, Salil, …). And most of all, I remember all of the colleagues being happy with me and for me.

I am not sure if there is a lesson to be learned here. Perhaps, don’t believe everything you are feeling. Or at least – if you are neurotic, you are not the only one here.

* title inspired by Aretha .

Collaboration, competition, and competition within collaboration

Another instalment on my research-life stories.

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The Talmud says: “competition/envy among scholars increases wisdom” (kinat sofrim tarbe chochma). Good or bad, competition is here to stay. Nevertheless, one of the strengths of our community is in its collaborative nature. This is good for science, but in my eyes also makes our life so much better. A recent example is a research project with Guy Rothblum. For a few weeks, we met quite regularly and every meeting went more or less as follows: First, we would go over the solution from the previous meeting and find a bug. Then we would work together on a new and improved solution. This sounds frustrating (and would probably have been frustrating if I worked alone), but instead it was a great joy. We got to solve this problem again and again, and in the process enjoy each other’s creativity and company. Unfortunately, our current solution seems quite robust, so our fun ritual ended.

My best example for turning competition into collaboration is in my long-term collaboration with Salil Vadhan. It started when Ran Raz and I had a modest result on Randomness Extractors (following the breakthrough work of Luca Trevisan). We then learned that Salil had the same result, and already managed to write it down. Salil invited us to join (and I’m sure he was a bit sad to lose his first single-authored paper), on the other hand, Ran and I decided to decline and give up on the result altogether (and I was sad to lose a paper at this early stage of my career). In retrospect, losing that result would have been quite inconsequential, and similarly for Salil. But what did turn out to be extremely significant was what happened next. The three of us started collaborating together, leading to a stronger paper and then an additional collaboration, and before long Salil and I established not only a long-term research collaboration but also a great friendship. The unfortunate accident turned out to be most fortunate after all! Not all collaborations end up so fruitful, but I almost never regretted a collaboration (DBLP gives me 74 coauthors so this is a large sample). I hope that the set of collaborators that regret working with me is equally small.

So let’s all choose collaboration over competition and happily ride into the sunset. Right? Well, not so fast. Collaboration and competition are not mutually exclusive. Turns out, we cannot shut down our egos even when we enter a collaboration. While I strongly believe that the contributions to a collaboration cannot be attributed to any one of the contributors, we all like to feel that we contributed our fair share and that we demonstrated our worth (to others and more importantly to ourselves). An over-competitive collaboration can be destructive, but in moderation it could indeed be that competition among scholars does increase wisdom.

Woos and boos: my research talks

Coming back to the research-life stories project I intend to write a few (three that currently come to mind) more stories of my own, hoping that they will inspire more stories by others.

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My first research project progressed very quickly. A few months after I started working with Moni, I found myself writing my first paper (having only read very few papers before), and then preparing my first research talk (having attended very few research talks before). My first talk was at Weizmann, where I managed to utterly confuse some of the most brilliant scientists of our generation. During the talk I apologized and Adi Shamir said something to the effect of “it’s not you it’s us.” After the talk, Oded Goldreich made sure I will not be misled by Adi’s gallantry 🙂 Indeed, it wasn’t them – it was all me. I learnt some valuable lessons about research talks (for example that the intuitions that lead your research may be irrelevant and even confusing when presenting it). It was also the first of many opportunities for Moni to (try to) teach me to never apologize. Unfortunately, even that Moni is completely correct, the temptation is often just too strong for me to resist.

Soon after, I was getting ready for a trip to my first conference and a few seminar talks I managed to schedule. I was quite terrified. Afraid to mess up the talks, afraid to expose my ignorance and even anxious about the practical aspects of travel (it was only the third time I left Israel, and the first time I did it by myself).

On the night before my early morning flight, I get an email addressed to Moni, to me and to a large collection of dignitaries (for example, David Harel, whose only fault was being a past department chair). The email from Professor X went something like “I saw the abstract of your coming talk at MIT. You claim to give the first construction of Z. This is arguably a big fat lie as Professor Y and I already did it in our paper. The only honorable solution on your part is hara-kiri“. I was horrified. I didn’t know their paper and his claim could easily have been correct (it couldn’t have but I wasn’t fully aware at the time of Moni’s encyclopedic knowledge). It was too late to call Moni and I was afraid he will not see the email before my flight. My deck of slides was printed and my first talk was the morning after I land. Disgrace was imminent!

Fortunately, very soon after, Moni replied. I think that Professor X never answered Moni’s email and years later when he interviewed me for a faculty position he have shown no sign of remembering this incident. Professor Y accepted Moni’s explanation (in a private email if I remember correctly) but still managed to squeeze in a couple of rather aggressive questions during my conference talk. By then I was fortunately prepared and calm (and answered: “are you the first to do Z?” with an innocent “yes”).

My second talk during the trip was in MIT. Between the regulars and the visitors, my audience included half of my reference list. I was in awe. The talk was extremely vibrant, with many questions from the audience and if my memory serves, especially from Leonid Levin. I was ecstatic, and I did not mind at all that Adi and Oded (who were just starting a sabbatical in MIT) were taking on many of the questions directed at me. And why should I mind? Here are so many of my idols vividly debating my work! Who am I to disturb them? I only realized it might have been unusual when Michael Luby (giving a talk the day after) answered the first question he got with something like “unlike yesterday’s speaker, I’d like to talk more than five minutes … .“ Still, over dinner, Oded promoted the idea that it may be better if a talk is given by someone other than the authors. So I felt somewhat vindicated.

Throughout the years I gave many more talks, some praised, some scowled, and some both (sometimes even by the same person). Giving a bad talk can be painful (and when you are young it sometimes feels like the end of your career). I vividly remember how the criticism over my first practice job-talk paralyzing me for almost all of the time I had before the first interview (till Moni gave me a few simple comments that dramatically improved the talk). I am still beating myself for not customizing my ICM (International Congress of Mathematics) talk to the non-cs audience. On the other hand, giving a good talk can be quite empowering. One of the sweetest comments that I remember came from Avi Wigderson who told me after a survey talk on RL vs. L that I left the audience no choice but to work on the problem. Like many other things in life, the more you invest in preparing a talk the more you get out of it. While I enjoy giving talks a lot, it is very hard to recreate the rush that comes from overcoming fear in those early talks of my career. I doubt that I sufficiently appreciated this rush at the time (a Joni Mitchell song comes to mind).

Craving for Stories

My FOCS PC work slows down the flow of stories (but feel free to send me your stories without all the redundant arm twisting, you know I’ll get to you at some point anyway 😉 ).

In the meanwhile, here are two pointers that are relevant. First, People of ACM has some great stories. In particular, read about the connection between storytelling and computer science (by Christos Papadimitriou).

Another pointer is an essay (which went viral among my academic Facebook friends) by Martin A. Schwartz on The importance of stupidity in scientific research. It touches on some points that came up in past stories on our project.

Research Life-Stories: Erin Wolf Chambers

Next story on our project from Erin Wolf Chambers:

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I spent most of my first couple of years of graduate school unsuccessfully trying to figure out what “research” meant.  I read papers and had plenty of meetings, but somehow had no luck really making new progress on any of the problems I looked at.  I tried meeting with different professors in different areas, but always seemed to run into logistical issues.  (Indeed, several of the faculty wound up leaving, proving that I wasn’t selecting potential advisors very well at the time!)  I dutifully kept a research notebook full of random thoughts and problems, as well as records of every talk I went to.

None of it seemed to help.  By the end of my second year, I was frustrated and confused about what was going wrong.  Around this time, I had a meeting with my advisor where I confessed my frustration, and told him that I was afraid I wasn’t cut out for grad school after all and was planning to quit if I couldn’t turn things around in my third year.  (He had just been on sabbatical for a year, so this was probably out of nowhere from his perspective.)   His answer was strangely reassuring and also terrifying: “Oh, you’ve reached THAT stage in your PhD.  Alright – let’s get to work.  You can do this.”

I’ll be honest – my internal thought process at that point was that this was some sort of hazing ritual, where I had to hit rock bottom before I could start to swim.  Yet at the same time, the fact that he had faith in me is still motivating to this day.  And it turns out, at least for me, that he was pretty much correct.  In those fruitless years of banging my head against walls, I had actually absorbed a ton of techniques and background.  More importantly, I had figured out what I liked (and didn’t like), so we were able to really dive into a few mutually interesting problems and made good progress.

A year or two later, I was wondering if this really constituted success.  How would I know if I was cut out to keep going and try for a faculty position?  (Keep in mind that at this point, a bunch of my friends had already dropped out and gotten ridiculously lucrative industry positions.  They seemed really happy, so that fate didn’t seem like the end of the world.)  About this time, we had a distinguished speaker in our department colloquium who was a theoretician – one of those amazing and brilliant ones that are terrifying because you could never, ever imagine how they did it.  The department organized a meeting for the graduate students after his talk, which a few of our faculty also came to in order to moderate.

In the meeting, one of the most junior students shared a concern that resonated.  He said, “So far, essentially all my progress has come suddenly and randomly – months apart, usually because of a good idea in the shower!  This isn’t sustainable, and clearly won’t get me through a career.  How do I figure out a way to make steady progress?”  The speaker laughed, and replied that in his career, it wasn’t about finding a way to make steady progress; rather, it was just about coming to believe that those random ideas would keep coming.  All the students were rather shocked, but all the faculty in the room were nodding agreement.  This was a revelation – were we all really just flying by the seat of our pants through our careers?

I’m still not sure I have it figured out, or when I’ll reach that elusive success.  People all have their own suggestions for how to go about this odd process of theoretical research, but finding what works for you is a lifelong process.  I am not anyone else, and the things that motivate me don’t seem to match a lot of what I heard in graduate school.  However, each suggestion and hint has been useful, if only to weed out things that don’t work for me.  And one or two things have resonated and changed the way I worked; for those suggestions, I will always be grateful to my mentors and collaborators.

In fact, I think this perpetual hunt is the most important lesson I took away from my early years in research.  Keep hunting, because progress is elusive and can be unexpected.  Find what motivates you, because that is what will keep you thinking about the problem in the shower.  Find mentors who believe in you and inspire you, because no one can really get there alone.  Perhaps just as importantly (at least for me), find collaborators you like to work with, because it helps to have someone to talk about ideas with in order to keep you motivated.  And have faith, because we’re all jumping in without any guarantees, and hoping for that next good idea to come to us in the shower.

On intellectual passion and its unfortunate confusion with sexual passion (and how it may relate to issues of gender)

The following is a post by Oded Goldreich which I found very interesting. It is based on a brave and important Hebrew post/essay, and I’m grateful to Oded for bringing it to my attention, translating parts of it and allowing me to post it here as well. I think that this is exactly the kind of discussion our community should have about research life, (and I thus liberally tagged it as part of our research-life stories project).

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The following text is based on a post, in Hebrew, that I saw in an Internet forum on gender relations in Israeli academia. The general context of the original text, which deserves to be called an essay, is that of the underrepresentation of females in academia, especially in certain disciplines. The specific text (hereafter the essay) referred to a mostly unnoticed aspect of this underrepresentation.

The author, an anonymous female graduate student in Humanities, starts her essay with four short anecdotes that illustrate the analysis presented later. She then recalled the two standard arguments made in favor of affirmative action: (1) compensating the candidates themselves for the social problems that hindered their earlier development, and (2) serving the next generation by providing adequate role models. At this point, she offered a wise and courageous insight, which has escaped me before (although I thought of these issues a lot). She suggested “Another reason, a fairly complex one, which hinders the participation of females in academia.” Following is her analysis (slightly revised and freely translated by me):

For a person seeking wisdom (and indeed loving it), the discovery and study of ideas are strong emotional experiences: They reveal a strong passion, an intellectual passion. This passion is characteristic of great researchers, those deeply devoted to the pursuit of wisdom. A strong emotional tie is created among those who share the pursuit, among those who share the intellectual passion for similar questions. This passion is present in their interactions, in which progress is achieved by sharing and confronting ideas. But this intellectual passion presupposed an asexual sphere, where people can be passionate in their interactions, and be understood as intellectually rather than sexually passionate.An academic world consisting mainly of males is a world in which this intellectual passion is not as freely experienced by females (to say the least), because for them this asexual sphere does not exist (i.e., their passion is always understood as sexual). Thus, intellectual passion is always problematic for females, whereas it is hardly so for males. For females but not for males, a big question always exists (i.e., questioning the nature of their passion, asking whether it is intellectual or sexual). Consequently, the intellectual passion of females is restrained, which results in pushing them to more secure confines, which are more mediocre. The process works at several levels.

  1. The social level (“what will they say?”): Whenever I express passion or excitement in an intellectual interaction, external parties are likely to think that my passion/excitement is sexual. I am interested in the intellectual aspect, but when they see a male at the target of my intellectual passion, they use the social equation female+male+passion = sexual situation. Even when the passion/excitement is linked to an intellectual contents, it stands the danger of being interpreted as a disguise for the sexual. This social prejudice is applied to all females (regardless of whether they are straight, bisexual or lesbian), but it is never applied to males (regardless of whether they are straight, bisexual or gay).
  2. The first bilateral level (“what will he think?”): I do not want our relationship to become sexual, I want to keep it intellectual because this is what I’m interested in. But what will he think of my behavior? If I show excitement or passion, will he not misinterpret them as sexual? Therefore, if I want to keep it intellectual, I better restrain myself, be less passionate. I will lose in the intensity of our interaction, but I may keep away from the danger of losing it all due to misinterpretation. This danger of misinterpretation is relevant to all females (except maybe proclaimed lesbians), and is irrelevant to males (except maybe proclaimed gays).
  3. The second bilateral level (“what will he think that I may think?”): But he is also away of all of this. So he may also be threatened if I am too passionate, because he may feel that responding positively may be misinterpreted by me as a demonstration of sexual interest. So he thinks that he better not be intellectually passionate with me, and so I lose again (since this means a less intense interaction). He loses less since there are many alternative (males) around, with whom he can feel “safe”. For me there are few “safe” alternative (i.e., less females).
  4. The personal level (“what do I actually think?”): The above refers to cases where there is absolutely no sexual interest on my side, and I only fear of being perceived as having such an interest. But what if things are less clear? What if I am really sexually attracted to him? Or what if I am just confused about it, which is possible in light of the confusion between the intellectual and sexual passion? Either way this would be very confusing for me, and this confusion will have a cost (i.e., hinder my intellectual performance).

In principle (or “in theory”), all these problems may arise also for males, but in the reality of an academic world that consists mainly of males, these problems occur much more often and much more intensively for females. So an academic world with a less disproportional gender representation will be less problematic for females, but indeed more problematic for males. Needless to say, the latter “sacrifice” (as giving away any other privileges) is fair to ask for and to expect.

Of course, an ideal solution would be a radical revolution in society; getting rid of the prejudices of gender roles, stopping to label situations as sexual or not according to the gender of the participants.

My reproductions of parts of the essay comes to an end here. Originally I thought of stopping just here, because I found the argument clear and requiring no interpretations. Surely, any interested reader will have her/his own thoughts, and will draw his/her own conclusions. But a friend of mine thought that it will be nice if I end with some of my own thoughts.

I was aware of the emotional dimension of intellectual activities (and in particular, of the passions involved in it) ever since I can remember. It was also clear to me that a “resource sharing” is taking place here, sharing emotional resources between the intellectual and the personal/sexual. I was also aware of the classical Greek philosophical traditions and the psychological and social modern developmental theories that view the sexual and personal as a “corridor” towards the intellectual and the abstract. What I failed to see, until I read the foregoing essay, is that this “resource sharing” phenomenon may also cause problems in some social realities (i.e., ours).

I guess my blindness toward these problems is related to my experiences as a male in our social setting (at large), which offers different experiences to males and females. One advantage of the human society is that one can learn also from what other see, and even understand what others experience.

[Oded Goldreich, April 2013]