Super Crunchers

by Ian Ayres

  In part, the struggle in education is a struggle over power. The education establishment and the teacher on the line want to keep their authority to decide what happens in the classroom. Engelmann and the mandate of “scientifically based” research are a direct threat to that power. Teachers in the classroom realize that their freedom and discretion to innovate is threatened. Under Direct Instruction, it is Zig who runs the show, who sets up the algorithm, who tests which script works best.

  It’s not just the teacher’s power and discretion that is at stake. Status and power often go hand in hand. The rise of Super Crunching threatens the status and respectability of many traditional jobs.

  Take the lowly loan officer. Once, being a loan officer for a bank was a moderately high status position. Loan officers were well paid and had real power to decide who did and did not qualify for loans. They were disproportionately white and male.

  Today, loan decisions are instead made at a central office based on the results of a statistical algorithm. Banks started learning that giving loan officers discretion was bad business. It’s not just that officers used this discretion to help their friends, or to unconsciously (or consciously) discriminate against minorities. It turns out that looking a customer in the eye and establishing a relationship doesn’t help predict whether or not the customer will really repay the loan.

  Bank loan officers, stripped of their discretion, have become nothing more than glorified secretaries. They literally just type in applicant data and click send. It’s little wonder that their status and salaries have plummeted (and officers are much less likely to be white men). In education, the struggle between the intuitivists and the Super Crunchers is ongoing, but in consumer lending the battle ended long ago.

  Following some other guy’s script or algorithm may not make for the most interesting job, but time and time again it leads to a more effective business model. We are living in an age where dispersed discretion is on the wane. This is not the end of discretion; it’s the shift of discretion from line employees to the much more centralized staff of Super Crunching higher-ups. Line employees increasingly feel like “potted plant” functionaries who are literally told to follow a script. Marx was wrong about a lot of things, but through a Super Crunching lens, he looks downright prescient when he said that the development of capitalism would increasingly alienate workers from their work-product.

  These algorithm-driven scripts have even played a role in the outsourcing movement. Once discretion is stripped from line employees, they don’t need to be as skilled. A pretested script is a cheaper way to lead customers through a service problem or to upsell related products—and it’s even cheaper if the script is read by someone sitting in a Third-World call center. Some individual salespeople using their intuition and experience may in fact be legitimately outstanding, but if you’re running a large-scale operation selling relatively homogenous products, you’re going to do a heck of a lot better if you can just get your staff to stick with a tried-and-true script.

  The shift of discretion and status from traditional experts to database oracles is also happening in medicine. Physicians report that patients now often treat them merely as alternative sources of information. Patients demand, “Show me the study.” They want to see the study that says chemo is better than radiation for stage-three lung cancer. Savvy patients are treating their doctors less like 1970s television icon Marcus Welby, and more like a human substitute for a web portal. The physician is merely the conduit of information.

  The rise of evidence-based medicine is changing our very conception of what doctors are. “It is a signal that in medicine,” Canadian internist Kevin Patterson laments, “ours is a less heroic age.”

  “So the warriors are being replaced by the accountants,” Patterson said. “Accountants know the whole world thinks their lives are gray—demeaned by all that addition. Doctors aren’t used to thinking of themselves that way. But in the real world, where numbers matter, accountants know how powerful they are.”

  Physician status is in decline. People are looking past the M.D.s, who merely disseminate information, and toward the Ph.D.s, who create the database to discover information. While a graduate student in sciences has to actually create information in his or her thesis to get a Ph.D., med students only have to memorize other people’s information (including how to do certain procedures). In a world where information is sovereign, there may come a time when we ask, “Are you a real doctor, or just a physician?”

  Or maybe not. Respect doesn’t necessarily come with power. Society is used to revering sage intuitivists. It can bow down to the theoretical genius of an Einstein or a Salk, but it is harder to revere the number-crunching “accountants” who tell us the probability that our cancer will respond to chemotherapy is 37.8 percent. In the movie Along Came Polly, Ben Stiller plays your typical actuarial gearhead. He’s the kind of guy who’s afraid to eat bar peanuts because “on average only one out of every six people wash their hands when they go to the bathroom.” His character leads a small, circumscribed life that is devoid of passion. He may wield power, but he doesn’t claim our respect. Power and discretion are definitely shifting from the periphery to the Super Crunching center. But that doesn’t mean Super Crunchers are going to find they have an easier time dating.

  Would You Buy a Used Car from a Super Cruncher?

  Even in areas where number crunching improves the quality of advice, it can sometimes perversely undermine the public’s confidence. The heroic conception of expertise was that of an expert giving settled answers. People are more likely to think of statistics as infinitely malleable and subject to manipulation. (Think of the “Lies, damn lies and statistics!” warning.)

  This is a more precise, but less certain world. The classical conception of probability is a world of absolutes. To the classicist, the probability of my currently having prostate cancer is either 0 or 100 percent. But we are all frequentists now. Experts used to say “yes” or “no.” Now we have to contend with estimates and probabilities.

  Super Crunching thus affects us not just as employees but also as consumers and clients as well. We are the patients who demand to see the study. We are the students who are forced to learn The…Fast…Way.™ We are the customers who are upsold by a statistically validated (outsourced) script.

  Many of the Super Crunching stories are examples of unmitigated consumer progress. Offermatica helps improve your surfing experience by figuring out what websites work the best. Thanks to Super Crunching we now know that targeted job search assistance is a lot more effective than financial incentives in getting unemployed workers back on the job. Physicians may dislike the reduction in their status and power, but at the end of the day medicine should be about saving lives. And for many serious medical risks, it is the database analysis of scientists that points toward progress.

  Super Crunching approaches are winning the day and driving out intuition and experience-based expertise because Super Crunching improves firms’ bottom-line profitability—usually by enhancing the consumer’s experience. A seller that can predict what you want to buy can make life easier. Whether it’s Amazon’s “Customers who bought this, also bought this” feature or Capital One’s validated upselling, or Google’s heavily crunched Gmail ads, the bottom line is an improvement in quality. Statistical software is even in place to tell you what not to buy. Peapod, the online grocery store, will interrupt my online session to ask, “Do you really want to buy twelve lemons?” because they know that’s unusual and they’d prefer to catch mistakes early and keep me a happy customer.

  Epagogix Agonistes

  Notwithstanding these benefits, there persists a lingering concern that the Super Crunching of product attributes will lead to a grinding uniformity. The scripted performances of Direct Instruction teachers and CapOne sales reps are not just wearing on the employees; they can wear on the audience as well. Epagogix’s meddling with movie scripts is even more troubling.

  The story of Epagogix’
s interference with the movie business can be seen as the death of art. A major Hollywood figure recently told the head of Epagogix, “You know, you absolutely revolt me.” Copaken told me, “He kept calling me Jim Jones and saying that I wanted him to drink the Kool-Aid.” We have begun to live in a world where a statistical formula tells authors what to put in their scripts. Sorry, Mr. Ivory, the hero needs a buddy if you want us to make your movie.

  This truly is a scary picture of the future—where the artist is handcuffed by the gearhead. Yet this concern ignores the other shackles that are already in place. The commercialization train left the station long, long ago. Studios have been tampering with artistic vision for decades in an effort to increase movie sales.

  The biggest problem isn’t that studios have been interfering; rather, it’s that they’ve been doing it badly. I’m more scared of studio execs wielding their greenlight power based on nothing more than intuition and experience than I am of a formula. Epagogix doesn’t represent a shift of power from the artist to the gearhead as much as it does a shift of power from the overconfident studio apparatchiks to people who can make dramatically more reliable interventions. When Copaken recently suggested to a powerful producer that neural predictions might be more objective because they don’t have to worry about bruising the egos of stars, the producer responded, “I can be just as objective as any computer.” Copaken suggested that the producer “may be subconsciously affected by his responsibility and opportunities within the industry in a way that Epagogix is not.”

  There will always be legitimate and ultimately irresolvable tensions between artistic and commercial goals. However, there should be no disagreement that it’s a tragedy to mistakenly interfere. If a studio is going to change a writer’s vision in the name of profitability, it should be confident that it’s right. Epagogix is moving us toward evidence-based interference.

  It’s also a move toward meritocracy. The Hollywood star writer system gives inordinate weight to writers who’ve had a hit movie in the past. It’s very hard for a newcomer to even get read. Epagogix democratizes the competition. If you have a script that’s off the predictive charts, you’re going to have a lot better chance of seeing it on the screen whether you’re a “proven” writer or not. Even some successful writers have embraced the Epagogix method. Dick Copaken told me about a well-known writer who sought out Epagogix’s help because he’s trying to make the shift to directing. “He figures the best way to get a job directing,” Copaken said, “is to write a mega-successful script.”

  But oh, the humanity. Imagine the crushing uniformity, the critics remonstrate, that would be produced by this brave new world of film by formula. Again, this concern ignores the present pressures toward commercial conformity. Epagogix’s formula didn’t create the idea of a formulaic movie. It is entirely possible that an Epagogix world of cinema would exhibit more diversity than the present marketplace.

  Epagogix does not use a simple cookie-cutter formula. Its neural network takes into account literally hundreds of variables, and their impact on the revenue predictions are massively interdependent. Moreover, the neural network is constantly retraining itself. Of course, so are the experiential experts at the studios. But this is precisely the horse race of figuring out the correct weights that humans are bound to lose. The studio expert is much more likely to fall back on simpler rules of thumb that lead to even less variety.

  Epagogix’s financial success can actually facilitate more experimentation. If it’s really true that the neural network can help raise a studio’s batting average from .300 to .600, studios might have more flexibility to pursue riskier or unusual projects. All the extra cash from improved predictability might give studios more wiggle room to experiment. And while Epagogix is a great leap forward over the experientialist mode of prediction, its predictions are still bound by history. The Super Cruncher studios of tomorrow will also manufacture their own new data by experimenting.

  The Super Crunching of art seems perverse, but it also represents an empowerment of the consumer. Epagogix’s neural network is helping studios predict what qualities of movies consumers will actually like. It thus represents a shift of power from the artist/seller to the audience/consumer. Epagogix, from this perspective, is part and parcel of the larger tendency of Super Crunching to enhance consumer quality. Quality, like beauty, is in the eye of the beholder, and Super Crunching helps to match consumers with products and services that they’ll find beautiful.

  Beware of Super Crunchers Bearing Gifts

  Everybody loves a freebie—you know, those little gifts that sellers send their best clients. Still, we should be worried if we see a seller treating us better than its other customers. In a world of Super Crunching, sellers’ promotions are far from random. When Amazon sends you a nice desk ornament out of the blue, your first reaction should now be “Yikes, I’ve been paying too much for my books.”

  When firms Super Crunch on quality, they tend to help consumers. However, when firms Super Crunch on price, hold on to your wallet. The dark side of customer relations management is firms trying to figure out just how much money they can squeeze out of you and still keep your business. In the old days, the firm’s lack of pricing sophistication protected us from a lot of these shenanigans.

  Nowadays more and more firms are going to be predicting their customers’ “pain points.” They are becoming more adept at figuring out how much pricing pain individual consumers are willing to endure and still come back for more. More and more grocery stores are calculating their customers’ pain points. It would be a scandal if we learned that your local Piggly Wiggly was charging customers different prices for the same jar of peanut butter. However, there is nothing to stop them from setting individualized coupon amounts that they think are the minimum discount to get you to buy. At the checkout aisle, after they have just scanned in all that information about you (including swiping your loyalty card), they can print out tailored coupons with prices just for you. This new predictive art is a weird twist on the Clinton line “I feel your pain.” They feel your pain all right; but they experience it as pleasure because the high net price to you is pure profit to them.

  In a world of Super Crunching, it’s going to be a lot harder to rely on other consumers to keep your price in line. The fact that price-conscious buyers patronize a store is no longer an indication that it will be a good place for you, too. The nimble number cruncher will be able to size you up in a few nanoseconds and say, “For you, the price is…” This is a new kind of caveat emptor, where consumers are going to have to search more to make sure that the offered price is fair. Consumers are going to have to engage in a kind of number crunching of their own, creating and comparing datasets of (quality-adjusted) competitive prices. This is a daunting prospect for people like me who are commercially lethargic by nature. Yet the same digitalization revolution that has catalyzed seller crunching has also been a boon to buy-side analysis. Firms like Farecast.com, E-loan, Priceline, and Realrate.com allow customers to comparison shop more easily. In effect, they do the heavy lifting for you and help level the playing field with the price-crunching sellers. For consumers worried about the impact of Super Crunching on price, it is both the best of times and the worst of times.

  Discrimination, by Other Means

  The prospect of increased price discrimination is scary enough. Even more disturbing is the notion that Super Crunching can also be used to facilitate racial discrimination. Earlier I spoke about the uncontroversial successes of data-driven lending decisions. It really is true that statistical formulas beat the pants off any discretionary system of loan officers. In part, this is because statistical formulas don’t have feelings. Regression equations, unlike flesh-and-blood loan officers, cannot harbor racial animus. So the seismic shift toward centralized statistical lending and insurance decisions has largely disabled hatred as a motive for minority loan or insurance denials.

  However, the shift to statistical decision making has not been a civil ri
ghts panacea. The algorithmic lending and insuring policies open the possibility for race to influence centralized policies. It is highly unlikely that the algorithm would be expressly contingent on race. It’s simply too likely that a race-contingent formula would become publicly known. Yet the algorithms that are formally race-neutral have at times been challenged for facilitating a type of virtual redlining. Geographic redlining was the historic practice of refusing to lend in minority neighborhoods. Virtual redlining is the analogous practice of refusing to lend to any database group that has too many minorities. The worry here is that lenders can mine a database to find characteristics that strongly correlate with race and use those characteristics as a pretext for loan denials. Members of minority groups have challenged lending denials that rely on factors like the small size of a loan or a borrower’s poor credit history as pretextual characteristics that highly correlate with race.

  Our civil rights statutes prohibit race-contingent lending policies. Even if a lender found that Hispanics were more likely to default than Anglos with the same credit score, the lender could not legally condition its lending decisions on race. The lender may be tempted, however, to use Super Crunching to end-run the civil rights prohibition. As long as it uses a race-neutral means, it will be very hard to establish that race was an underlying, illicit motivation for the policy.

  Such virtual redlining may also take place in the insurance context. An African-American woman, Chikeitha Owens, who was denied homeowner’s insurance coverage due to her poor credit, sued Nationwide Insurance. She claimed that the company’s use of her credit score history effectively created a racialized category which denied coverage to applicants who were otherwise qualified.

  In fact, when it comes to affirmative action, the Supreme Court invites this kind of end run. Justice Sandra Day O’Connor as the swing vote for the Court in a series of crucial affirmative action opinions said that decision makers had to try to find “race-neutral means to increase minority participation” before implementing an affirmative action policy that was expressly contingent on race. Some schools have responded to the invitation by searching for race-neutral criteria for admission that disproportionately favor minority applicants. Some California schools, for example, now favor applicants whose mothers have not graduated from college. This admissions criterion is explicitly motivated by a goal of increasing minority enrollment. Yet Justice O’Connor’s standard is an open invitation to more elaborate formulas for predicting race. In a world where express race preference is prohibited, Super Crunching opens the possibility for conditioning behavior on predicted race.