While newspaper circulation continues to decline, many magazines have held their own in the digital age. Magazines differ from newspapers in that they have a more defined “identity”, such that Chip Conley (who now helps run a similar effort at AirBNB) developed successful boutique hotels around the concept of a magazine.
“We determine which magazines will best define the hotel, and then we come up with the five adjectives that best describe that magazine,” explained Conley in a recent Forbes interview. ”We’ve found that the people who fall in love with a hotel are people who use those five adjectives to aspirationally describe themselves. The Hotel Rex, in San Francisco, is based on The New Yorker, and the adjectives are “clever, literate, artistic, worldly and sophisticated.” When you check out of the Rex you feel like we’ve refreshed your identity. We’ve created an ideal habitat for you.”
There is a lot of research detailing how, as societal wealth increases, consumers’ needs are moving out of the realm of utility and into the realm of lifestyle and aspiration. Newspapers can’t compete by being simply informational, in a world where information is cheap and ubiquitous. What aspirational values can a newspaper help a reader fulfill?
A lot of my research has been about showing that different people have very different aspirational goals (values), not just goals that people in California deem readily aspirational like feeding the poor or achieving world peace, but also goals like being loyal to their group, keeping faith with family traditions, providing for one’s family, achieving success, etc. These later aspirational goals (among others) may prove more fruitful in a more conservative environment. The Army has a good case study in the use of such values toward achieving organizational goals. I would definitely recommend that forward thinking newspapers attempt to fill a specific aspirational niche, as a result.
Once a niche is decided, a news organization can consciously leverage the fact that these goals have specific storytelling and emotional triggers. For example, in work that I’ve been doing with Zenzi‘s Social Values project, our research indicates that newspapers that wants to serve more traditional aspirations may want to have more stories with happy endings, while a newspaper that wants to serve more hedonistic aspirations might want to instead consider featuring stories about people from far away places. Emotions such as disgust, empathy, and anger vary widely and predictably amongst people with different aspirational goals and stories could be framed accordingly. Editors likely have an intuitive sense of these relationships, but making them more explicit can bring cohesion to marketing, editorial, and journalistic practices toward a singular newspaper voice that better speaks to the higher-order needs of consumers in the modern age.
- Ravi Iyer
Recently, the topic came up of whether values profiles (and Moral Foundation Scores more specifically) predict behavior. On the one hand, social and contextual factors often loom larger than individual factors in determining moral behavior. On the other hand, it seemed rather unlikely that something as central as a persons values would not predict their behavior. While the effects may be small and indirect in many cases, I would expect a person’s value profile to predict almost everything they do in life sildenafil generico. As a test case, I decided to examine whether moral foundation scores, which measure how much a person cares about harming others, fairness, obeying authority, being loyal, and being pure, in the context of moral judgments, predict whether a visitor to YourMorals.org visited using a Mac vs. a PC. Below is the graph.
The Values Profile of Mac vs. PC Users
While all visitors to YourMorals.org are generally liberal, it looks as if Windows users are more conservative than Mac users, within this group. Note that while this isn’t a representative sample, in some ways it is better for answering this question as the users in this sample have such similar characteristics that many variables are naturally controlled for. Windows users appear to value harm less and purity more.
The take home message for me is that while context certainly matters, so to does a person’s values, even for relatively unrelated decisions, such as which computer to use in daily life.
- Ravi Iyer
I recently attended the main conference for social psychologists, even as I’m slowly transitioning to think of myself less as an academic and more as a data scientist. Of course, the term data science is a pretty poor term as all science has to do with data, but I think it serves a purpose in that there are methods for answering questions with data that operate across the domain where the data was collected. There is no real reason why a person well trained in understanding and analyzing data can’t apply their techniques on medical data, sports data, psychological data, and online data. In fact, research on the wisdom of crowds would suggest that any discipline would benefit from analyzing data in different ways as colleagues are likely to make correlated errors concerning understanding anything. This is certainly true in social psychology, where a common error that has been made is the under-valuing of exploratory research.
To our credit, social psychologists are beginning to understand this. Many years after Paul Rozin formally published a great article concerning the need for more diverse ways of researching questions, psychologists are starting to accept the idea that exploratory research has value alongside the experimental methods that are so popular. Below is a picture from one of several such talks given.
It’s great that psychologists are willing to consider exploratory approaches. However, I don’t think we necessarily need to pretend like we are starting from scratch. It seems like many psychologists want to simply let people fiddle with data in the haphazard ways they have been doing, label it exploratory, and then get on with “real” (confirmatory) research. This is an area where data science, with it’s emphasis on how to automatically, efficiently extract well-supported insights from large datasets, has a big head start. What can data science offer psychologists?
- More efficient exploration. Running haphazard regressions til you find a good model is inefficient for a number of reasons. It takes a lot of human effort and then when you do find something, you have no real way to reproduce the algorithm that you used to find the result you did on a subsequent dataset. To put it in more practical terms, every psychologist who wants to run exploratory regressions should at least understand GLMnet (details of which I’ll put in a future post).
- Cross-validated exploration. Data scientists have given a lot of thought to questions of how to be more sure that a result is true, when one is testing so many hypotheses that one is bound to find something by chance. Cross-validation is not a cure-all, but then again, nor are relatively artificial lab studies. Certainly a cross-validated exploratory finding is more likely to be true than a non-cross-validated exploratory finding. Broadly, just as some experiments are greater evidence than less well-designed experiments, so too are some exploratory findings greater evidence than other explorations. Of course, this last sentence will completely confound those who insist that publications can only publish “true” findings that are supported by p<.05 statistics, which leads me to my last point.
- Bayesian models of findings. There was a ton of talk about the problem of false positives, but the entrenched interests of the journal system (IMHO) inhibit the paradigm shift that is needed, which is to think of findings and papers as evidence as opposed to truth. Good publications are not true…they are merely stronger evidence. And rejected publications are rarely worthless. Rather, they may be weaker evidence or may not affect prior beliefs to quite the same degree. Setting a high bar for publication is great for creating a tournament for job seekers. But it’s a terrible way to find truth in an age where data and research is ubiquitous. If you want to read a more detailed argument about this, I’d read Nate Silver’s Book.
There are some things that social psychologists are really good at. They understand experimental methods and can critique them really well. They understand measurement much better than most disciplines. But there are some things that other disciplines do much better with data, such as exploration. The banner of data science presents the opportunity to break down these barriers, so that the social psychologist can help the Google engineer design the perfect study to validate the results of their latest machine learning algorithm, while the political scientist helps the social psychologist with representative sampling and the Google engineer helps the political scientist explore the latest national survey in a far more efficient way and then mash up that data with more ecologically valid social media behavior. And so, the end result is that there really isn’t a huge need for disciplinarity in an age of big data (which was a theme of Jamie Pennebaker’s presidential address at SPSP). It actually gets in the way of us all being data scientists.
- Ravi Iyer
Recently, I received news that Reid Hoffman, founder of LinkedIn, has decided to indirectly support some of the work I do with Jonathan Haidt, because he is a fan of Jon’s work. The news got me thinking a bit about the confluence of moral psychology and what LinkedIn does. As Ranker’s Principal Data Scientist, I will often find myself at data conferences with members of LinkedIn’s data team, which is one of the most visible and productive, given the wealth of data they have to mine. It may seem that what they do and what moral psychologists do are separate worlds, but as I argued in my 2012 SXSW talk, there is likely to be a convergence. Big data is merely a tool that inevitably will be used to answer the questions we care about, and for those of us with first world problems where crime is going down, war is less of an issue, and obesity is a bigger problem than hunger, the questions we increasingly ask tend to be more existential. It is only natural that we use the tools of the age (data) to answer the questions of the age, like how we can live a meaningful life.
Unlike some who are more dogmatic in their belief, I don’t believe that data can tell you what a meaningful life is or how you should live. In short, moral psychology cannot tell you what ought to be…but it can tell you what is. For example, in a partnership with Zenzi Communications, we have been working on describing the narratives that people of different value types tend to resonate with. I can’t tell you whether action or comedy movies are better, but I can provide a probabilistic fit between a person’s value orientation and the kinds of stories that they are likely to enjoy.
Similarly, companies and prospective employees are looking for such fits as well. Zappos wants people whose values tend toward the unconventional. LinkedIn wants people who will put their members’ first. In moral psychology terms, Zappos is looking for individuals who are high on traits like openness to experience and stimulation, while LinkedIn might be looking for individuals who are more self-transcendent in terms of putting others (their members) first.
These values are measurable both with self-characterizations and endorsements, just like LinkedIn skills, but also through more subtle means such as music tastes or use of certain words. Further, following on work by Shalom Schwartz, values can be organized as oppositional (see above graph using Zenzi’s value typology which is based on Schwartz’s work), so that self-presentation effects (e.g. “I’m high on all values!”) can be mitigated. In this way, companies and employees may potentially be able to find employment matches that are not just a job, or even a career, but are closer to a calling, leading to happier and more productive employees.
We get a lot of resumes at Ranker. They honestly all start to blend together at some point. The employment market needs more nuance, more subtlety, and more data to help create better matches. I don’t know if LinkedIn or some other organization will lead the charge, but I’m confident that this type of values based matching will indeed be part of the future of human resources recruiting, and it already is part of many forward thinking organizations’ processes. Just as the internet and information technology has made matching in other domains (e.g. classified ads or home buying) more efficient, values based matching in the labor market is bound to be a problem tackled by data science teams at online companies in the near future.
- Ravi Iyer
Very few days go by without a new article describing the limits of published scientific research. The headline cases are about scientists who plagarize or completely fabricate data. Yet, in my experience, most scientists are actually quite ethical, meticulous, hard-working, and really concerned with finding the truth. Still, non-scientists would likely be surprised to know that a large number of scientific studies are actually false. An Amgen study found that 46 out of 53 studies with ¡®landmark¡¯ findings were unable to be replicated. A team at Bayer found a slightly more optimistic picture where 43 out of 65 studies revealed inconsistencies when tested independently. Scientific journals continue to accept articles based on the novelty and projected impact of the submission, yet simulations illustrate how the bias of journals toward publishing novel results likely leads to an environment where most published results are actually false. My home discipline of psychology is currently doing some soul searching as it¡¯s a relatively open secret that many results are difficult to reproduce such that a systematic reproducibility project is taking place.
Crowdsourcing is, and always has been the solution. Indeed, the phrase at the bottom of Google Scholar, ¡°standing on the shoulders of giants¡±, acknowledges that science has always been about crowdsourcing, as every scholar is collaborating with the scholars before them. Findings are not produced in a vacuum and build upon (or challenge) previous findings. Replication by others, which effectively crowdsources verification of results, is at the heart of the scientific method. It is perhaps a sign of the narcissism of our age that scientists feel compelled to believe that they discover things largely independently, such that they feel compelled to attack when their findings are challenged. Yet a willingness to be wrong about something is essential to learning, as we can¡¯t learn to walk without falling or learn about relationships without heartbreak. When science becomes more about ego, career, and grant money, it naturally becomes less accurate. Insisting that findings be crowdsourced solves this. No single study, paper, or research group can prove anything by themselves.
Crowdsourcing is not simply averaging the opinions of the masses, as those who would argue against that straw man would have you believe. Mathematically, crowdsourcing is about reducing the influence of sources of error and there is a great deal of academic research on this topic. A good crowdsourcing algorithm does not weight all inputs equally, but instead seeks to identify clustered sources of error, which explains why aggregating across people with diverse personalities, perspectives or job functions produces better results. Inputs need to have some signal vs. noise and need to have uncorrelated error. The unfortunate assumption in most research is that error is uncorrelated statistical noise that can be dealt with using statistical tests. Yet error also occurs due to the unconscious biases of researchers, the sheer number of researchers trying to find novel findings, the degrees of freedom that a researcher has in trying to prove their hypothesis, the non-randomness of sampling, and the volume of available statistical tests that a researcher can use. Given all these other sources of error, it is no wonder that many findings are false. A good crowdsourcing algorithm would be weighted such that true results would have to be shown by multiple researchers using multiple methods, multiple samples, multiple statistical tests, and multiple paradigms. This requires crowdsourcing as no single person can do all this, and even if they could, they would still represent a single source of error.
Technology enables crowdsourcing to be conducted far more efficiently, as has been proven by successful science crowdsourcing projects like GalaxyZoo, FoldIt, Seti@Home, and psychology¡¯s reproducibility project. Trends like citizen science, the quantified self, open access publishing, and interdisciplinarity improve the diversity of perspectives which mathematically improves the ability to find truth. Every meta-analysis result and Nate Silver¡¯s success in aggregating polls in the last election take advantage of the mathematical principles that underlie crowdsourcing, specifically the certainty that aggregating across sources of error produces more truth. In our daily lives, we all crowdsource knowledge that we are uncertain about, looking for confirmation from multiple independent sources when we are skeptical. This same skepticism serves scientists well and scientists should embrace being wrong, confident that the broader truth will be revealed when all data is aggregated intelligently and all perspectives are valued. Crowdsourcing is not some new technique that threatens to fundamentally change scientific research. Rather, it is an extension of the collective effort of knowledge aggregation that is the heart of science and scientists should embrace it as such.
- Ravi Iyer
Part of my job at Ranker is to talk to other companies about our data. While people often talk about how “big data” is revolutionizing everything, the reality of the data marketplace is that it still largely revolves around sales, marketing, and advertising. Huge infrastructures exist to make sure that the most optimal ad for the right product gets to the right person, leveraging as much data as possible. For example, I recently presented at a data conference at the Westin St. Francis in San Francisco, which meant that I spent some time on their website. For the past few weeks, long after the conference, I’ve been getting ads specifically for the Westin St. Francis on various websites. At some level, this is an impressive use of data, but at another level, it’s a failure, as I’m no longer in the market for a hotel room. The data to solve this problem is out there as someone could have tracked my visitation of the conference website, understood the date of the conference, and better understood my intent in visiting the Westin. However, this level of analysis doesn’t scale well for an ad that costs pennies, and so nobody does this level of behavioral targeting.
I bring up this story because I believe this illustrates a difference between how people who think of themselves as businesspeople and people who think of themselves as technologists often think. When talking about Ranker data, I often see this dichotomy. People who are more traditionally business minded want a clear business reason to use data, while people who think of themselves as technologists seem more open to trying to envision a world where data does all sorts of neat things that data should be used for. For example, I recently graphed opinions about beer, illustrating that Miller Lite drinkers were closer to Guinness drinkers than to Chimay drinkers. As a technologist, I’m certain that a world will soon exist where bartenders can use data about me and others like me (e.g. the beer graph), to recommend a beer. I don’t worry as much about the immediate path from the conception of such data to monetization. I know that the beer graph should exist and I’m happy to help contribute to it, confident of my vision of the future.
This division between people who think like businesspeople and people who think like technologists is important for anyone who does business development or business to business sales, especially for those of us in the technology world where the lines are often blurry. Mark Zuckerberg is a CEO, but clearly he thinks like a technologist. My guess is that a lot of the CTOs of big companies actually think more like businesspeople than technologists. If I were trying to sell Mark Zuckerberg on something, I would try to sell him on how whatever I was offering could make a huge difference to something he cared about. I would sell the dream. But if I were selling a more traditional businessperson, I would try to sell the benefits versus the costs. I would have a detailed plan and sell the details.
I actually have a bit of data from YourMorals.org to support this assertion. We have started collecting data on visitors’ professions and below I compare businesspeople to technologists on two of the Big Five personality dimensions that are said to underlie much of personality: Conscientiousness and Openness to Experience. As you can see, businesspeople are more conscientious (detail oriented, fastidious, responsible), while technologists score higher on openness which is indicative of enjoying exploring new ideas and thinking of new possibilities.
The reality is that every business needs a balance between those who are detail oriented and precise (Conscientious) and those who think about a vision for the future (Openness to Experience). Often, technologists who start a company will eventually hire professional businesspeople who provide this balance (e.g. Sheryl Sandberg or Eric Schmidt). Clearly, the best sales pitch will be both detailed and forward thinking. However, if you’re talking to someone and have limited time and attention, considering whether you are speaking to someone who is more of a businessperson or more of a technologist may give you better insight into how to frame your pitch.
- Ravi Iyer
ps. Crossposted on Zenzi Communications‘ blog here, which is using a data driven approach to improving communications strategies.
I was recently asked about the Moral Foundations scores of those who are more concerned about the environment and so I analyzed the 15,522 individuals who took the Moral Foundations Scale on YourMorals.org and also answered a question on the Schwartz Values Scale concerning how much of a guiding principle of their life it was to “Protect the Environment”. I limited this analysis to those who placed themselves on the liberal-conservative spectrum, so that I could also control both for ideology and extremity of ideology, to some degree. The results (beta weights controlling for other variables) of the regression analyses, predicting a desire to “Protect the Environment”, are below.
My initial intuition was that ideology would be the greatest predictor, given how political the issue has become, but it appears that the Care/Harm foundation actually predicts as much unique variance as ideological identification. From an intuitionist standpoint, this makes sense as the specific care you feel for Polar Bears may drive one’s values more than more abstract concerns about the ocean’s water level, similar to the way that charities appeal to emotions with specific cases of need as opposed to statistics. Still a great deal of variance is indeed predicted by which ideological team you are on.
Also interesting to me was the significant, but small, negative relationship between ingroup loyalty and attitudes toward the environment. The item I used from the Schwartz Values scale is part of a subscale designed to measure Universalism, which relates to Peter Singer’s idea that we should expand our moral circles. While it is certainly possible to care both about one’s smaller circle/family and one’s larger circle/animals/trees, there is some tension there, especially in a world with limited resources where environmental choices that benefit the world at large, may negatively impact one’s local community.
There are certainly limitations to these results taken from a particular sample, so take them with a grain of salt. And there remains a healthy debate about which moral concerns are more central, so there certainly are moral concerns that may predict environmental attitudes that are not measured here. Still, these results converge well with what we see in the world. Environmentalists tend to be liberals who are particularly concerned about the welfare of distant others, perhaps expanding their moral circle to include animals, oceans, and trees.
- Ravi Iyer
Human beings are storytelling animals. There is no other species that spends large amounts of time watching the lives of others – fictitious or real – through the stories we read or watch. Stories do not just relate to the entertainment we consume, but are also central to the news we read or the companies that we resonate with. One of my favorite personality psychology theories concerns how our entire lives can be thought of as a set of narratives that bring coherence to our goals, desires, values, dispositions, and experiences.
I’ve recently been working with Zenzi, a communications company based in San Diego, that is attempting to leverage research on values to, among other things, better inform how companies can better engage with consumers. A good marketing campaign is one which doesn’t feel like someone is trying to sell something to you, but rather where there are shared goals between the company and consumer that are highlighted. Whereas these goals can be mundane (e.g. trading money for food), they are increasingly becoming more value driven. As such, kamagra oral jelly ajanta pharma, a key communications strategy for the post-modern world is learning to tell a company story that resonates with one’s clients deeper motivations. How can research on values help you do that?
One of the central tenets of the research we do is that values are not monolithic. Different people value different things and these values predict the kinds of stories that one enjoys. I recently conducted some research on yourmorals.org, where I examined the kinds of stories that different value types prefer. The below graph shows the correlations between dimensions of the Schwartz Values scale and questions concerning story type preferences, specifically relating to whether a person likes stories that provide an escape (e.g. I like stories that provide an escape from my real life) or stories that people can identify with (e.g. I like stories about situations that I can relate to). Note that it is entirely possible to enjoy both kinds of stories and most people do. Still, there is an inherent tension between giving people an escape and giving people stories they can relate to, and the below graph suggests how one might resolve that tension differently, depending on the values of one’s target audience.
Correlations between Schwartz Values and Story Preferences
People who value Power, Achievement, Spirituality, Tradition, Conformity, and Security seem to prefer stories that are closer to them, which they can relate to. In contrast, individuals who value Universalism, Self-Direction, Stiumulation, and Hedonism report a greater preference for stories that provide more of an escape from their everyday existence.
Whether you are a journalist considering how to frame a story, a screenwriter considering a plot twist, a marketer considering how to position a brand, or a novelist considering one’s next book, it helps to know your target audience‘s values when considering the kind of story you want to tell.
- Ravi Iyer
I’ve been meaning to write this post for awhile, not just in response to the recent tragedy in Connecticut, but anytime I read an article about homelessness or people who are mentally disturbed. Many people wonder what we can do to address the mentally ill, whether it is to prevent them from engaging in violence or prevent them from lapsing into homelessness. Medical professionals have many tools to help those with chemical imbalances, but the reality that the medical model of mental illness fails to capture, is that many (though not all) mental illnesses are qualitatively different than many physical illnesses. Mental illnesses are often matters of degree rather than of the categorical presence or absence of a condition, despite the categorical nature of mental health diagnoses. You either have AIDS or Malaria or you don’t, whereas many of us have some degree of anxiety, depression, mania, addiction, hyperactivity and other conditions, rather than being clearly normal or ill. Because we often think of mental illness using this medical model, we often think two things that are often untrue:
1. We believe that we can’t do anything about mental illness and only experts can help.
2. We believe that the mentally ill are “others” and that the people we know are categorically different.
Sometimes people break. All types of people break, but you can help. On occasion, I have spent some time at Dorothy’s Place, a shelter in Salinas where they care for a lot of the local homeless and the director would often tell visiting students about how people break. Imagine being a teenager who is dropped off at the shelter because your parents don’t want you any more. Imagine spending day after day in Iraq, looking around corners for snipers and explosives, one of which happened to kill several of your friends, and then trying to enter normal society without retaining the vestiges of that experience. Some mentally ill individuals certainly have brain chemistry issues, but others are people who would otherwise live relatively normal lives, save for an experience or series of experiences that break them.
What are these stressful life experiences? Below is a common, though perhaps outdated (from 1967!) ranked list of common life stressors that psychologists sometimes use to diagnose how much life stress people are undergoing, based on which of these events have been experienced recently.
How can you prevent mental illness? Many of your friends have the potential for mental illness and when they undergo the inevitable stresses of life, they need the support of their friends and family, before things get serious enough for a medical diagnosis and a prescription. You can be that support to the people around you, especially when you notice events such as divorce, breakups, and death that are especially strong stressors.
Consider the times in your life when you felt like you might break. Perhaps they involved the loss of someone you cared about, whether through a death or through a breakup. As an ultra-social species, these are deeply painful events. Consider how you got through those events. Why didn’t you break? I know that in my own life, the support of my friends and family helped me in those times. It is that social support that perhaps explains why mental illness is more prevalent in individualistic societies and less so in collectivist nations.
How can you prevent mental illness? Be the change you want to see in the world and help those around you when they go through life’s inevitable ups and downs. When you notice one of the events in the above list in someone’s life, even someone you aren’t that close to, make the effort to go out of your way to show them that you care and they are not alone.
- Ravi Iyer
On Thanksgiving evening, I started reading Greg Smith’s book, Why I left Goldman Sachs late in the afternoon. I finished it around midnight. It’s a relatively easy read with a relatively straightforward message: That Wall Street, as exemplified by Goldman Sachs’ evolution, has increasingly become a place where we send many of our brightest students to outwit the people who manage our pensions and retirement accounts.
Greg Smith is famous for resigning from Goldman Sachs via an op-ed published in the New York Times, accusing Goldman of evolving from a firm that serves its customers to one that often profits by taking advantage of them. Nothing illegal is documented in the book, but it does show how employees are encouraged to sell ever more complex products to customers in the hope of generating more fees, without consideration of whether these products make their customers’ lives better. Who are these customers? They are the people who manage the money in our retirement accounts, pension funds, and the wealth of philanthropic organizations. Like many Americans, they look to investment bankers like Goldman Sachs for advice on how to help their money grow.
There is little dispute about this, but not everyone believes it is morally wrong. The CEO of Goldman Sachs asserts that they have no obligation to tell customers when they sell them something that they believe will lose money. The Wall St. Journal’s review of the book essentially says that he should have known that Goldman Sachs was not built on selflessness, but rather on “tawdry commerce” and the “sometimes morally ambiguous business of sales”. Bloomberg News seems more interested in tearing him down personally than examining the morality of what he says in the book, asking “Hasn’t it always been about making money and isn’t it okay to be a bank that makes money?”
At the heart of this, is the question that recent financial reforms were designed to change. Specifically, should investment professionals have a fiduciary responsibility to their clients? More simply, should they be required to put their clients’ interests over their own, when making recommendations? I can’t say objectively whether it is morally wrong to take advantage of clients lack of knowledge, but I can examine our data from YourMorals.org to see which individuals believe that it is ok to conduct a “negotiation where not everyone completely understands the process” involved (e.g. opaque fees hidden in the fine print of investment products). The below table shows correlations of Schwartz Values Scale scores and demographics with belief that negotiations with information assymetries are wrong, with positive correlations first.
Correlations of information assymetry "wrongness" with values/demographics
Clearly, people disagree about how wrong it is to conduct a negotiation without complete understanding by all parties. People who hold self-transcendent values such as benevolence and universalism are the most likely to believe that such conduct is wrong. People who hold traditional values are also likely to believe that this is wrong. In contrast, younger, educated, more conservative males who tend to value power, of the type that populate most investment banks, are less likely to feel that such information asymmetry is wrong. As such, it is perhaps not surprising that the reaction of many in the business world to Smith’s book is a collective “so what?”
Those of us who are mere consumers of financial services, via our 401ks, pensions, and college funds, would do well to understand what is behind this collective yawn. What some in the finance world are telling us is that the primary goal of these financial companies is to make themselves money, not serve clients, and given that the average money manager fails to beat the market, we would all probably be better off simply buying broad, transparent index funds, rather than taking their sales calls. We should urge our city officials, counties, and pension managers to stop trying to beat the market with the advice of ostensibly wise finance professionals, who don’t really have their clients interests at heart, lest they suffer the fate of the city of Oakland or Jefferson County, Alabama who both ended up on the wrong side of deals with Goldman Sachs. And if there ends up being less demand for their products, perhaps we can move some of the genius that creates arcane financial products into creating things that people actually need.
- Ravi Iyer