Ask More: The Power of Questions to Open Doors, Uncover Solutions, and Spark Change pdfdrive com

Is it the yoga that’s making the difference or is your body just healing
over time?

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You think yoga is working. Maybe yoga can move your body and joints and
muscles in ways that minimize the pain from your injury. That’s your
hypothesis.
You decide to try a little experiment and see if your hypothesis holds up.
You stop the yoga. Within a few days, you’re pretty sure the pain is getting
worse. Sometimes it’s hard to tell because it’s been such a constant part of your
life since the accident. Every day you chart your pain—rating it on a scale of one
to ten—when you wake up, at lunchtime, before dinner, and when you go to bed.
After a few weeks, you see a trend: Your pain is worse in the morning, after you
get up. It goes down around lunch, picks up again around dinner, and ticks up a
little more before bedtime. It follows this pattern over several weeks.
You wonder if the morning pain is due to stiffness from sleeping or because
you’re going to bed with more pain and sleeping poorly. You wonder whether
the increase in pain in the evening is because you’re just tired and feeling it
more, or whether you’re feeling the effects of a day’s worth of activity. You
decide to start the yoga again, this time doing it twice a day—in the morning
when you wake up and again just before bed.
After another couple of weeks, you see a change. Your pain still peaks in the
morning, but it’s down from where it was when you weren’t doing the yoga. It
still ticks up around dinner, but now it goes back down before bedtime. You
conclude yoga twice a day is helping. You can’t be 100 percent sure that it’s just
the yoga. But your chart and your experience indicate a connection between
more yoga and less pain.
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?

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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

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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.