The Geek Doesn’t Always Get the Girl: A Novelist on Hacking Romance

In today’s Silicon Valley, the hacker wunderkinds are ascendant. Boy-kings are running billion-member social networks, founding massive new venture capital firms, building incubators that churn out hundreds of new startups every year, and even fighting poverty and disease by drilling for water in Ethiopia. Materially, at least, their revenge on whatever high-school cliques once excluded and demeaned them is complete.

But do they understand women?

In the community of coders, there’s a sincere belief that systematic thinking and action isn’t simply the key to making a guy rich and carrying him to the top of the corporate ladder—it can also help him win dates and maybe even a spouse. But I’ve been spending some time lately with a new novel that challenges those notions. It’s called The Unknowns (Little, Brown; $25). It’s the kind of book that, like Less Than Zero or Infinite Jest or A Heartbreaking Work of Staggering Genius, singles out a certain type of young American male—in this case, the programmer-entrepreneur—and holds up a sympathetic but not entirely flattering mirror.

The book’s narrator and protagonist is Eric Muller, who is in his early twenties and lives in San Francisco; the year is roughly 2002. Eric has recently earned $18.4 million by selling his behavioral-targeting startup, Demographic of One, to another company. But he isn’t doing much with his fortune. In fact, he’s settled into an aimless existence punctuated by awkward dinner parties with his old high-school friends, the occasional Ecstasy-fueled sexual encounter, and lots of time with his Xbox and his comic books.

Eric finds solace in code, but none in other people, who mainly distress and puzzle him. His parents are needy, self-involved, and distant. While San Francisco represents a kind of meritocratic refuge from his past as a misunderstood teenager in suburban Denver, he’s still flustered by the city’s hilly emotional topography. More than anything else, Eric wants to find a girl who will appreciate his talents and perhaps bring him out of his shell.

So he decides to “hack the girlfriend problem” by doing everything he can to win the heart of Maya Marcom, a witty, cuttingly perceptive journalist for an alternative weekly newspaper. Thereby hangs the tale. And if the ending is a little predictable, the journey there is compelling, in what a book-jacket blurb writer might call a funny, affecting, tragicomic way.

Eric Muller’s creator is Gabriel Roth, a Brooklyn-based writer and software developer who covered San Francisco for the Bay Guardian during the years of the dot-com boom and bust. The Unknowns is his first novel. Because it focuses on a world I also inhabited (as San Francisco editor for Technology Review) and a personality type I’ve come to know well, I was eager to read it and to pick Roth’s brain about its themes. Our full interview follows below.

Gabriel Roth

Gabriel Roth

On one level, the book asks a timeless question: can human relationships, even in principle, be reduced to logic, algorithms, and craft? It’s a question Ovid explored two thousand years ago in his version of the Pygmalion-Galatea story, and novelists and filmmakers have revisited it many times since. I think of 2001: A Space Odyssey, where HAL is such a diligent student of human nature that he learns to lie and murder, and of Richard Powers’ 1995 novel Galatea 2.2, whose artificially intelligent protagonist, Helen, ultimately chooses suicide over sentience. Roth even has a contemporary competitor in the form of Scott Hutchins, whose 2012 novel A Working Theory of Love, about a project to create a conversational computer, is also set in the San Francisco startup world. (I haven’t finished reading it yet, so I can’t tell you where Hutchins comes down on the moral implications of AI.)

Roth’s book is about people, not machines. But what gets tested in the novel—this is, after all, a coming-of-age story—is Eric’s belief that negotiating a relationship, like building a complex computer program, boils down to understanding and managing all the variables. With his engineer’s mindset, plus his theoretical understanding of what people want, Eric thinks he can at least simulate a kind of closeness with another person—and that maybe this will lead to the real thing. (“With enough calculations per second you can generate the impression of spontaneous compatibility, the way a grid of tiny pixels becomes a photograph,” he postulates in one passage.)

More importantly, Eric believes that if he can figure out what’s going on in Maya’s head—if he can know all the unknowns—he can make himself into the perfect boyfriend. Unfortunately for him, the baggage that Roth has given to Maya’s character comes with some unbreakable locks. As Roth put it in our interview, “The problems in his relationship with Maya aren’t just problems of complexity, they’re problems of ambiguity or opacity.”

Given that each one of us is, to some extent, ambiguous and opaque to the people around us, Eric’s approach to intellectualizing “the girlfriend problem” seems disastrously incomplete. The genius of the novel is that it makes us care sufficiently about Eric—he’s perceptive and sweet, even if he’s stuck in emotional amber—that his failure with Maya, in the end, seems sad and poignant despite its inevitability.

My conversation with Roth covered not just the “hacking love” question, but mechanics of novel writing, the San Francisco startup scene of the early 2000s, the Turing Test, and his favorite science-fiction authors. An edited transcript follows; it contains mild plot spoilers.

Xperience: First of all, I want to say I know how awkward it can be for a writer to have to talk about his or her book, since a book is supposed to be self-explanatory, to some extent. So, thanks in advance for putting up with my questions.

Gabriel Roth: There are always a lot of thoughts or ideas that don’t find their way into a book, for whatever reason, and I’m sort of eager to talk about them. So, no problem.

X: What brought you to the point where you started to write your first novel? Are you the kind of person who’s always had a novel bubbling up in them somewhere?

GR: It wasn’t like that for me. I always enjoyed writing, and felt relatively competent at it, but I was never able to write fiction that was at all satisfying to me. I found myself working in San Francisco as a journalist, and I sort of realized it wasn’t something I was especially good at. There were important skills for a journalist that I just didn’t have. It seemed like writing a novel might work better for me than figuring out how to be a really good journalist. So I left the paper, did some work on my own, did an MFA at San Francisco State University, and tried to figure out how fiction works.

X: The narrator of the novel, Eric, is a programmer who’s living in San Francisco, just after the dot-com crash and 9/11 and around the time of the U.S. invasion of Iraq. What parts of your own story relate to the startup scene during those days?

GR: I got to San Francisco in 1996 and left 10 years later, so I was there for the whole first boom and bust. So some of it was from doing reporting in various contexts. I moved there right out of college, so a lot of it was that my friends were going to startup jobs.

At that time, the thing for a company to do was to spend as much money as you could, as fast as possible, and hire a ton of people. So I knew a lot of people who were getting jobs that they couldn’t properly explain, and where I didn’t understand what the companies did. There were a lot of parties. It was fascinating and in ways sort of mystifying to me.

By the time I started working on the book, I had become interested not so much in the startup business but in the programming side of things. I had begun reading essays and books by programmers—there was a boomlet of writing about programming in the first decade of this century. That got me interested in programming as a pursuit separate from startups. And that’s how I came to this aspect of Eric’s character—the idea that he was someone who would enjoy immersing himself in this intensely rational, cognitive activity. In the end, the fact that he makes a bunch of money by founding a startup is, for him, almost an accident or an afterthought.

X: There are a number of passages in the book where you seem to appropriate the language of startups in an ironic and dismissive way—for example, there’s one sentence that reads “I made myself into the person she needed, and while it wouldn’t scale it was at least a proof of concept.”

GR: I think that’s because I have ambivalent feelings about it. I learned a little bit about programming in the course of writing the book, and became an intermediate-level programmer, but there is something I very much admire about people who become really expert programmers. They seem to be driven by natural curiosity and a love of making things and a creative impulse, and I find all those things admirable. In particular, a lot of programmers—more then than now—are people who don’t care whether it’s cool to do or not, they are just fascinated by it. That is the aspect of the classic programming geek that I really admire. I aspire to that quality of focus. There is something monastic about it—these are people who are separating themselves from the world to try and figure something out.

About the people nowadays who come out of business school and decide they want to disrupt the parking meter space, or something like that, I say good luck to them. Maybe they will make something useful, but I don’t find myself as sympathetic to that impulse.

In a way, if I see one big difference between the startup-founder-programmers of Eric’s generation, around the turn of the millennium, and those of today, it’s that the technology has gotten so much better. Nowadays you can build a modern startup website with social features largely by assembling components that have already been developed by other people. You can use a framework like Ruby on Rails and host it on Amazon servers and a lot of the work has been abstracted away. Which is terrific, but the modern startup scene has less of a role for intense programming. So the advantage that somebody like Eric had in 1999 or 2000 would no longer be such a competitive advantage.

X: One thing about Eric’s biography seemed improbable or at least outdated to me. He’s very rich as a result of selling his software startup, and he’s still in his early twenties, but he seems totally stalled in life. Today there’s a very well marked out path for people in that situation—they become angel investors and start putting money into their friends’ companies, and eventually they start something new of their own. But Eric isn’t doing any of that. He’s not even trying to stay plugged into the startup scene.

GR: There are more of these guys today than there were 10 years ago. Back then, there weren’t things like Y Combinator. There weren’t books explaining what you need to do to start a disruptive company. It certainly could happen, but it wasn’t a known strategy. So there’s more of a default path, now that there is a more stabilized startup culture.

But more importantly, I think this is an area where Eric is not representative of anything beyond himself. He is a guy who fell into this by accident—he says at one point that he wasn’t even trying to get rich. I could imagine Bill Fleig [Eric’s teenage hacker buddy and eventual co-founder] as a successful innovator working on another startup. But for Eric there was this whole other set of problems that he was preoccupied with, even as he was writing the code that would eventually make him very wealthy.

As I thought about, “Okay, what would happen to him after he’s made all that money and no longer has to worry about a day job?,” it did seem like it would be difficult for him. I didn’t think he would have much interest in networking with people. There’s a scene where he goes to a conference and afterward, people are mobbing him and trying to get him to invest in their companies, and the only interesting thing to him is that maybe being surrounded by these people will elevate his status and help him become what he actually wants to be, which is an attractive person that a girl will love.

X: Eric comments early in the book that “some people found social life as obvious as I found computers.” How real do you think that dichotomy is? Are there some people who just instinctively understand how other people think, and people who don’t?

GR: I certainly don’t think it’s a dichotomy. It’s not that there are people who get it and people who don’t get it. It’s a spectrum. People like Bill Fleig are probably more hopeless than Eric is. Eric in many ways is extremely insightful and empathic and understands other people quite well. His problem, in a way, is that his intense self-consciousness makes it difficult for him to respond in an appropriate or natural way, after he has processed the data correctly.

I do think there are people who, for whatever reason, have a natural ability to be likeable, or to act in ways that are socially appropriate, and there are others for whom that comes harder. Adolescence is really the time when that gets sorted out—when people are revealed to have that natural sense or not. Everybody sort of figures it out along a slightly different path, and that can make those four or five years extremely intense and, for some people, extremely uncomfortable. That’s why there are sections in the book about Eric’s teenage years.

X: The core perception that seems to set Eric up for romantic disaster is this idea that it’s possible to “hack the girlfriend problem.” He’s obviously unsuccessful at that with Maya, but what do you think about the impulse itself? Eric seems to be trying to work with the tools he has. Is that so misguided?

GR: What I sympathize with in Eric is the intensity of his inspiration. He wants it so badly, he is willing to try anything. And he doesn’t have a lot to work with. His parents certainly haven’t given him much to work with, and nature hasn’t equipped him with much to work with in certain respects. But it has equipped him with this high cognitive intelligence, so he’s working very hard with what he’s got. I’m really sympathetic to that.

It would be much better if he weren’t stuck in his head so much, and if he had a more natural way to act around other people. He would be very fortunate if he had even a slight increase in those things. He doesn’t, and so he’s in trouble.

X: But what about this idea that it’s possible to reduce human relationships to algorithms—that a coder’s mindset might actually help you understand other people? You don’t have to look to fiction to find people who believe that’s actually true.

GR: Let’s say I’m skeptical. I think we should call it “thinking” rather than algorithms. I think that thinking is very useful, up to a point. Thinking about what other people feel and want, and what you yourself feel and want, can be really helpful. But if it’s divorced from feeling and emotional insight, then it’s hard for me to imagine building a really satisfying relationship out of it.

X: Toward the end of the book Eric observes, “We can only know each other the way we know distant stars: by observing years-old light, gathering outdated information, running calculations and making inferences.” That seems to be a defense of his original idea that there’s a kind of calculus for managing relationships. That passage left me feeling unsure whether Eric has really learned anything.

GR: Those lines about distant stars feel very important to me, and I read them slightly differently from the way you do. I think what he is acknowledging in that moment is that people are inherently unknowable—that there is a limit to what you can see of other people’s minds. And that engaging in a relationship with another person involves dealing with something that is ultimately opaque, and that you have to go ahead in your life and figure out how to proceed with that.

Eric is really good at solving problems of complexity, but the problems in his relationship with Maya aren’t just problems of complexity, they’re problems of ambiguity or opacity. That is what he has recognized in the end that he didn’t know at the beginning. But unfortunately, he has recognized it too late.

X: For Eric to be able to hack a relationship, he wants all the variables to be known. But as you’ve just described, it’s important for the arc of the coming-of-age story to have him learn that this just isn’t possible. Is that why you gave Maya’s character this issue where she’s struggling with what may be repressed memories of sexual abuse? That was a big cultural theme in the 1990s, and it still seems like a question that just can’t be unraveled.

GR: I think the answer is yes. Structurally, putting her in that situation is a way of giving Eric a problem to solve that will be the problem that tests him and ultimately breaks him. You want to put your character in a situation that is not just as difficult as possible, but difficult in a way that reveals something about who he is. Giving Maya this aspect that is so important and so entirely unknowable and unresolvable seemed like a good way to do that.

In addition, I think that was an interesting period in our history. It seems to have begun in the late 1980s with the McMartin preschool case, and to have died out by 1999 or so. After being a central cultural preoccupation for a while, it disappeared just like that. It was something I was interested in at the time, and when I went to study it more thoroughly for the book, I came to think that this was a situation that our culture had gotten itself into where it had raised questions that it was unable to answer. Here was something that was sort of exciting and in a way titillating and psychologically gripping, but suddenly it became too complicated for the culture to really figure out, so we just agreed to stop talking about it. That was interesting to me.

X: In the end, you seem to leave it deliberately unclear whether Maya was abused or not.

GR: I am not going to disagree with that.

X: I worried a little about Maya’s character. As I made my way through the first third of the book, before you really get into the repressed-memory stuff, I was afraid she might turn out to be a Manic Pixie Dream Girl—the kind of female character that doesn’t have an inner life or a story of her own, except to the extent that it advances the male protagonist’s story. It didn’t turn out that way, but by the end I felt like she might be another kind of character type—maybe the Manic Depressive Dream Girl. Did you struggle with how fully realized you wanted Maya’s character to be? Or was it important for the plot that she stay somewhat opaque?

GR: Well, let me say first that in a novel like this one, there are some characters who are intended to be round and some who are intended to be flat, to use a distinction that E.M. Forster made. There are some characters in the book who are supposed to be lively and funny and serve a function, but they are not intended to be fully rounded humans. My intention was for Maya to be as round a character as possible. And to the extent that she isn’t, that is just my failure as a writer—that is not to do with intention.

It’s difficult, obviously, when everything is so firmly locked into one character’s point of view, to make the other characters round when you want them to be. You have to do it through their actions and dialogue, mostly. I had the benefit of getting to do some storytelling from Maya’s point of view when she talks about her childhood, which at least gives the reader a sense of her voice and what things looked like from her perspective.

At the same time, as you brought up, there are central things about her that the reader can’t know for sure—that are just not resolved. And that’s the way it has to be for the book to work. Maybe that compromised my ability to make her a fully rounded character, but anything beyond that is just the result of my shortcomings as a writer.

X: Going back to a technology question. At one point Eric says: “With enough calculations per second you can generate the impression of spontaneous compatibility, the way a grid of tiny pixels becomes a photograph.” That made me wonder what Eric, or you, would say about the Turing Test. Do you think it will ever be possible for a sufficiently advanced computer to fool a human into thinking that it’s human?

GR: I don’t know. There are people who have spent long enough thinking about that that it would be dumb for me to venture an opinion. What is interesting about the question is that it is exactly a version of what a novelist is trying to do, and of what we were just talking about. Is Maya a rounded character, or is she a caricature? Well, either way, both are just arrangements of letters and punctuation marks on the page. That is literally all they are. It’s a very limited set of symbols—only around 100—that you can manipulate, and out of that I have to make real, alive human beings, at least for the duration of the book, and insofar as you are willing to suspend your awareness that they are not real. Any programmer working on passing the Turing Test is engaged in an activity that novelists have been doing for hundreds of years.

X: I’ve also been reading Scott Hutchins’ book A Working Theory of Love, which is another first novel set in San Francisco, and is also, in a way, about the extent to which relationships can be reduced to algorithms. Do you think it’s somehow symptomatic of our times that writers such as yourself are driven to explore these questions about technology and human consciousness and emotions?

GR: I’m aware of the book, but I didn’t read it, just out of superstition. But here’s what I think, and I sort of suspect this would be true for Hutchins as well. I think novelists in general, and me in particular, are interested in what it’s like to be alive. That is a fundamental and only very loosely timely question. What it’s like to be alive may change over time, but it changes pretty slowly.

In the end, talking about computers and programming and having a character who is a computer programmer is not so much out of a theoretical interest in technology or programming. It’s more about trying to find a different way of talking about the experience of being alive and the way human beings relate to each other. This material happens to be there, and it hasn’t been worked over as much as some other stuff, so that is what I am going to use.

But that’s probably the wrong thing to say to make your audience read the book!

X: Well, I’m a little surprised to hear you soft-pedal the technology part. Maybe it’s just the position I’m in as a technology journalist, but it seems like technology actually is changing what it means to be alive, and far faster than in the past.

GR: And I think there is a ton of interesting stuff to say about that. But much of the interesting stuff points to the future. Already, I can see how life is different from a few years ago, before social media. How will the experience be different for my kid, who is now very little? I have no fucking idea, but it’s going to be crazy. And there are novelists using fiction to think about that question—William Gibson is probably the greatest of them—but that is not quite the kind of book I was writing. I don’t know that I have the insights to go into those kinds of future-oriented questions.

The Author

Wade Roush is a contributing editor at Xconomy.

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  • Bill Ghormley

    Wade — this seems the quintessential battle between Memetics and Biology.
    “The Unkowns” as you depict it sets up the Man/Meme vs. Man/Gene problem in bright light — having to give in to the unknowns of a relationship to reproduce, as opposed to building an engineered world through solving for unknowns — building one’s memetic legacy. This interview was poignant, and powerful, on a number of levels — thanks.

  • Jerry Jeff

    Really good stuff, Wade.