Congratulations. You did your own simple scientific experiment. And you feel better.
Nina Fedoroff, a plant biologist and former president of the American Association for the Advancement of Science, explained scientific inquiry to me by putting it in terms of “mental constructs,” the various ways that disciplines have of interpreting reality. In literature, imagination does the work of making sense of the world. In law, judges use precedents to interpret the law. Science, she says, links ideas to repeated observation and repeatable results of experimentation. The scientist, Fedoroff explains, says okay I have this idea, then asks:
How do I test my idea?
How can my idea be wrong?
In the practical world, there are few incentives to incorporate the mindset that accompanies this type of questioning into our lives and our work. It could be awkward to stand up in front of your boss and say, “Okay, I’ve got this idea for a new product. But maybe I’m wrong.” It would be odd to hear someone at the city council meeting declare, “I know how to make trash pickup more efficient. But we need to test it because I want to see if I’m wrong.” Imagine hearing a political candidate say, “I have a plan to raise taxes that will reduce the deficit and save Social Security. But there is some real uncertainty here.”
In most cases, we are rewarded for decisiveness and quick answers. The person at the meeting who speaks up with authority and offers to “fix the problem” is often the one who is praised and promoted. When we propose an idea, we don’t say to the boss or the shareholders, “I think I’m on to something here, but I’m doing my best to prove it wrong.” We’re expected to defend our point, not openly invite others to attack it.
The discipline of scientific questioning, however, moves us toward a more methodical form of inquiry, inviting more data and better measurement into the questions we ask and the answers we get. In Silicon Valley, where most everything is measured, one of the most important tools for improving online products is a simple form of experiment called A/B testing. Tech companies try out new features by offering a small percentage of users an updated app while most others use the old one. If the new version performs better—determined by metrics such as how many clicks it gets or how many purchases are made—it’s crowned the winner and becomes the version that everyone sees. If not, the better-performing original stays in place. This data-driven approach favors empirical results to pick winning ideas instead of the slickest sales pitch or the most confident employee.
As data becomes more accessible, we can expect more science and more metrics in the decision and questioning process. You have a new product you’d like to put into production. You think you should expand your business overseas to take advantage of a rising global middle class. You’re thinking of buying a salmon hatchery in Alaska. Applying some scientific inquiry would force you to slow down in order to observe, hypothesize, experiment, and quantify before leaping to conclusions. Maybe that bed and breakfast in Vermont is the better investment after all.
Slow Answers to Slow Questions
For Tony Fauci, HIV/AIDS research was heartbreakingly frustrating because time was on no one’s side. People died while he and other scientists painstakingly went about their work conducting experiments and proving themselves wrong. While researchers were testing and observing, AIDS activists were criticizing and protesting, bearing grim signs reading SILENCE = DEATH. Too little funding, they complained, and too little urgency. Fear and grief and frustration hit hard.
Finally, President George H. W. Bush, who spoke about a “kinder, gentler” America, boosted funding. Fauci put research in high gear. Still, it took three years of intense research before Robert Gallo of NIH and Luc Montagnier from the Pasteur Institute announced that they had identified the virus that causes AIDS—a retrovirus that could incubate in the body for years before erupting into full-blown AIDS.
Once the virus was isolated, researchers went to work to defeat it. Molecular virologists started sequencing it. They examined the genetic code. Then researchers discovered the antibody test, which allowed for prompt diagnosis. They started experimenting with off-the-shelf compounds to see which might inhibit the virus. But it was by no means a straight line. There were false hopes, setbacks, and flat-out failures.
A promising drug, AZT, emerged from this work, and the medical community felt a sudden, uncharacteristic burst of hope that the disease might be reined in. But clinical trials and experience established that AZT lost effectiveness over time because the virus developed resistance to it. Researchers discovered the virus could replicate and mutate, getting around AZT. A setback, which led to a question.
How do we stop the mutation and replication?
Researchers tested more drugs and found that a cocktail of medications, if taken together, could backstop one another and prevent the virus from mutating. The new regime, approved in 1996, increased a patient’s expected remaining life from eight months to as much as fifty years. HIV/AIDS still kills, especially in poorer parts of the world. But decades of methodical research—slow questions—paid off. The disease is no longer an automatic death sentence.
Science bases itself on the measurable world. But we can incorporate its method into the way we ask and answer other types of questions to become more precise, more focused, and more accurate. We can slow down, pose our questions more deliberately, and bring more data and facts to the discussion. We can challenge our hypothesis and invite others to do the same in a conscious search for problems with our findings and assumptions.
Scientific questioning can be applied in business, in daily life, and in our communities. Imagine how much more interesting a staff meeting, corporate board retreat, or a policy debate might be if people brought up an idea they had tried to prove wrong before they concluded it was right.
You’re thinking about putting money into your company because the competition is out-hustling you. What do your customers want? Where is the demand? What are they buying? As you answer these questions you develop a strategy—a hypothesis—that you can test.
You’re not sleeping well. You wake up at two in the morning or can’t get to sleep at all. Is it the caffeine, the food, or stress? Before you go to the doctor to do one of those involved sleep studies, what can you figure out on your own? How can you experiment to narrow down the cause of your own insomnia? Perhaps creating a spreadsheet or gathering your data on your own digital fitness tracker, which will tell you when you sleep and how you sleep, will help. Chart your caffeine and exercise, your diet, and your stress level to look for patterns. Come up with a hypothesis and test it.
From outer space to the subatomic particle, scientific questioning probes the real world, trying to figure out real mysteries. It relies on observation and measurement, and it demands patience. It is a humbling form of questioning because it is endless, dwarfed by the universe it seeks to decode.
After studying this line of inquiry, I find myself questioning differently. I think more deeply about what I can see for myself—the observable. I ask more about data, separating what I know from what I think I know. I want to hear more about uncertainty and how we explain and accommodate it. I ask:
What do we see and what do we actually know?
How do we know what we know and how might we explain it?
Could we be wrong, and what’s the next question to ask?
CHAPTER 10
THE EDISON TEST
Interview Questions
THE QUESTIONS MOST OF US know best but fear most are the questions that take place in the job interview. Whether you’re on the receiving end—trying to get the job—or on the giving end—trying to fill the job—the questions that get asked and answered here have real and immediate consequence. As a candidate, if you botch the answer to an important question, you don’t get hired. If you’re the boss and you fail to ask the right questions, you can miss a critical piece of information and hire the wrong person.