In ancient Roman mythology, the month of January is named after the god Janus. He is the god not only of beginnings and endings, but also of the liminal spaces — the gates, transitions, and passages that are betwixt and between one thing ending and another beginning.
As a visual manifestation of this duality, Janus is said to have had two faces looking in opposite directions. So, “Janus” is a perfect namesake for the first month of the year, a time when many people feel a natural inclination to look both backward at the year that has just ended and forward to the year just begun.
At the beginning of this new year of 2023, and in the spirit of Janus’ two faces, I would like to invite us to reflect on two competing — but ultimately complementary — perspectives from two insightful recent books on thoughtful decision-making. The first book largely leans toward cognitive, rational, scientific, and data-driven approaches to making decisions. It’s titled Don’t Trust Your Gut: Using Data to Get What You Really Want, by Seth Stephens-Davidowitz, who has a Ph.D. in economics from Harvard, and is a former data scientist at Google.
The second book is comparatively more trusting of our human emotional intelligence and gut instincts. It’s titled Wild Problems: A Guide to the Decisions That Define Us by Russ Roberts, the president of Shalem College in Jerusalem, who interestingly enough, also has a Ph.D. in economics.
Let’s start with how data can powerfully inform our decision-making; then we’ll move on to consider some of the “wild problems” that life periodically presents us with, problems that are messier and more complex than any straightforward data analysis could handle. For our most important human decisions, we are often wise to listen not only to our minds, but also to our hearts, bodies, and spirits
That being said, it is true that—distinct from any previous time in history—we live in an age of Big Data (Stephens-Davidowitz 1). You may have heard the explanation for why Google searches, gmail, social media, and so many other Internet-based applications are free: “If you’re not paying for the product, then you are the product” (The Social Dilemma). For better and for worse, we are decades into feeding internet algorithms with mind-boggling amounts of information about — ourselves!
Stephens-Davidowitz proposes that, since we have helped to co-create this world of Big Data, we should also leverage all that data to improve our lives — instead of leaving it to all the gigantic tech companies to capitalize on. His chapters on the big data of marriage, parenting, sports, money, success and more show just how personally-informative and beneficial data can be when making decisions.
Do you remember the book Moneyball that was also made into a film? It’s the true story of how the Oakland A’s baseball team used an innovative, data-driven approach to build a winning team on a small budget. The data revealed previously unnoticed and counter-intuitive recruiting advantages which allowed the A’s to recruit massively undervalued players. So you can think of Stephens-Davidowitz’s book as “Moneyball for your life” (5). Or, as a former Google CEO once said, “In God we trust. All others have to bring data” (6).
So what wisdom do the great algorithm gods have to offer us in making our most difficult decisions? I’ll limit myself to sharing three examples. As we ponder the intentions we may want to set for ourselves this new year, let’s focus on what big data has to tell us about dating, parenting, and happiness.
One of the biggest sources of useful data about current dating practices comes from online dating sites. The first modern online dating site was launched almost thirty years ago in 1994 (26). And today approximately 40% of couples meet online, a number that keep rising each year (27). So, what do decades of big data tell us about what makes for a good mate — in contrast to the — shall we say — more superficial things that sometimes lead people to “swipe right” on a dating app? No judgement! It all depends on what you’re looking for.
It is, however, worth reflecting here on what much of the research data shows about the four qualities most predictive of how happy you will be with someone — if you are looking for a longterm relationship. Notice that it helps if you have these qualities yourself — or are willing to work on having them:
- “Satisfaction with life” – in general, you and your partner have a proclivity to be grateful for the good things already present in your lives, as opposed to being perpetually dissatisfied and hypercritical.
- “A secure attachment style” – “can trust people and are trustworthy, are comfortable expressing affection,” and are open to intimacy.
- “Conscientiousness” – reasonably “disciplined, efficient, organized, and reliable.”
- “A growth mindset” – committed to lifelong learning and improving “your talents and abilities through hard work and persistence,” as opposed to getting plateaued and bored (51-53).”
Your mileage may vary, but this is what the data shows about the top four traits that are most predictive of how happy you and your partner might be in a longterm relationship.
Next, let’s consider what big data reveals about parenting? Have you ever heard the saying that “regardless of how your children turn out, you should take neither too much credit nor too much blame?” Science supports that adage: decades of research reveal that the long-term impacts of parenting are “shockingly small.”
Parenting has surprisingly little impact on “life expectancy, overall health, education, religiosity, and adult income.” Parents have a moderate effect on “religious affiliation, drugs and alcohol use and sexual behavior, particularly during the teen years, and how kids feel about their parents” (68). That last one’s my favorite: parents have, at most, a moderate affect on how kids feel about their parents! So, perhaps the biggest takeaway for parents from big data is to give yourself permission to “lighten up” (70).
There is, however, one factor that has been shown to have the greatest chance of making a statistical difference in a child’s life. It relates to the real estate axiom that in buying property, the most important consideration is “location, location, location.” Big Data demonstrates that, “The three big predictors that a neighborhood will increase a child’s success” are:
- “Percent of residents who are college graduates,” modeling the value of learning
- “Percent of two-parent households,” reflecting family stability.
- “Percent of people who return their census form,” correlating with citizens who are engaged with the community (81).
All this parenting data is helpful information to know, but if you’re like me, you may also feel your social justice button being pushed. These statistics should be a resounding call to build a world in which high quality college education is free for all, childcare is subsidized and affordable (so all types of households can be more stable), and civic engagement is more accessible. All neighborhoods (not just an elite few) should help children thrive and offer equitable opportunities for success.
And finally, what does Big Data tell us about happiness? I don’t have space here to get into all the details about the fascinating “Mappiness” app that has been used to map “3 million happiness measures from more than 60,000 people,” but I will share their findings of the top ten activities that tend to increase our happiness the most. Here too, your mileage may vary, but for most humans, the activities that result in the greatest gain in immediate happiness are:
- Intimacy / Making love
- Theater/Dance/Concert — The arts are so high on this list as silver and bronze medalists, giving a shout out not only for STEM, but also for STEAM (“Science, Technology, Engineering, Arts and Math”). We do our society a grave disservice when we cut funding to the arts and humanities in school.
- Bird/Nature Watching — note how many times being outside appears on this list! Half of this top ten list highlights that being in nature can often increase our happiness.
Close runners-up were “Hobbies/Arts/Crafts” and “Meditating/Religious Activities” (221).
One way to use this information is to post a copy of this list wherever you will see it regularly—perhaps on your refrigerator or bathroom mirror—and if you’re feeling down, pick one or more item to experiment with to see how they might help increase your happiness.
There is way more detail in the book covering a whole host of additional areas, but the author said that if he had to distill everything into one short sentence about what big data tells us about happiness, it would be this: “The data-driven answer to life is…be with your love, on an 80-degree and sunny day, overlooking a beautiful body of water, making love” (265).
Overall, Stephens-Davidowitz’s book argues that our gut instincts can be unreliable. What the data shows is that, over the long run, “We are frequently too optimistic; we rely on inaccurate anecdotes, latch on to information that supports what we want to believe, and harbor too many logical fallacies” (18).
Certainly, whenever the data is quite clear, we are wise to take it into strong consideration. But some decisions are just too complex to rely upon big data alone. Both our authors have doctorates in economics — one from Harvard and the other from the University of Chicago, and assuredly, they both care deeply about the quality and usefulness of data resulting from strong research (3).
However, our second author, Russ Roberts, invites us to more deeply differentiate between what he calls “tame problems” that are quantifiable through big data and “wild problems” that are rather more “mysteries to be entered,” mysteries about making long-term decisions whose long-term results can’t be predicted in advance (185-187).
Roberts says that, “Wild problems resist measurement. What works for you might not work for me, and what worked for me yesterday might not work for me tomorrow…. They’re a whole different beast compared to the tame problems where the standard techniques of rationality move us steadily forward” (4).
Consider the case of Persi Diaconis, a widely respected professor of mathematics and statistics at Stanford University. His primary area of research is chance, risk, and probability. He has one of the best technical skill sets in the world for performing rational, analytical data analysis on quality decision-making.
But when he personally was faced with the option of moving from Stanford to Harvard, he found himself boring his friends by endlessly weighing those options. Finally, one of his friends said impatiently, “You’re one of our leading decision theorists. Maybe you should make a list of the costs and benefits and try to roughly calculate your expected utility.”
Without thinking Diaconis found himself blurting out, “Come on, this is serious!” (42). What a fascinating gut reaction to a problem that was not at all tame, but wild. He knew that deciding whether to move across the country from Stanford to Harvard involved variables beyond the scope of any math equation because such wild problems cannot be resolved with the head alone, but also must include less strictly-rational approaches.
If you are curious, Diaconis remains at Stanford today. I suspect part of what was underneath his strong objection to his colleague’s suggestion is that he knew that statistically and on paper, Harvard (“the H-bomb”) might appear to win out. But for whatever confluence of reasons, he decided that on some deep level of heart, mind, body, and spirit, staying at Stanford was the best decision for him.
Other turning-point decisions such as “Should I have a child?” or “Should I marry this person?” are likewise beyond the sole power of Big Data (1). There may be guidelines from big data that can give us general parameters, but big data can’t conclusively tell you whether or not you specifically should have children, whether you should marry any one particular person, take a particular job, respond to any other wild problem that life periodically throws our way. You can’t know the answer in advance; you can only live into the answer over time.
Arguably, though, knowing that big data can’t give us all the answers is part of what makes life interesting. Poetically, Roberts expresses it this way:
Beware the urge for certainty….
The sure thing.
The lure of the bird in the hand.
Maybe one or twice, put all your eggs in one basket.
Take a chance….
Ask her out. Or him. [Or them.]
Go out on a limb.
Leave the safety of the streetlight…
the comfort of the campfire….
Make friends, [make] amends.
Your inner fire….
Aim high….[then] aim higher. (190-191)
Or, more playfully — and related to the mystery of wild problems with which we can only live into the answer over time — do any of you remember the final comic strip of “Calvin and Hobbes”? It came out on December 31, on the edge of a new year, a date that the ancient god Janus would have approved. There were five panels, each of which invoked the wondrous “beginner’s mind” of a child that we all still have within us:
- In the first panel, the boy Calvin remarks, “Wow, it really snowed last night. Isn’t it wonderful?”
- His stuffed tiger Hobbes agrees: “Everything familiar has disappeared! The world looks brand-new!” Then, Calvin adds, “A new year… A fresh clean start!”
- Hobbes: “It’s like a big white sheet of paper to draw on! A day full of possibilities!”
- Calvin: “It’s a magical world, Hobbes, ol’ buddy…”
- “…let’s go exploring!”
There is so much that is hard and broken about our world, but also so much that remains right and true and beautiful and magical (188-189). It’s a world full of possibilities, and I look forward to exploring it together with so many of you in this new year of 2023!
The Rev. Dr. Carl Gregg is a certified spiritual director, a D.Min. graduate of San Francisco Theological Seminary, and the minister of the Unitarian Universalist Congregation of Frederick, Maryland. Follow him on Facebook (facebook.com/carlgregg) and Twitter (@carlgregg).
Learn more about Unitarian Universalism: http://www.uua.org/beliefs/principles