The future of meteorology… will be shaped by major social drivers.

What is the future of meteorology?

Meteorologists know their discipline and its advance will help shape society and the future, much as Lorenz’s butterfly, going about its business, mindlessly impacts the weather and even climate downstream. But in the interim, the butterfly necessarily maintains laser-focus on its immediate environment – e.g., local wind speed, direction, and gusts – calling to mind the “inspirational (???)” poster from Despair, Inc, In the battle between you and the world, bet on the world.

So it is with our profession. Our future is being shaped by powerful global drivers; these are grinding away everywhere, their progress breathlessly covered by news and social media. Take, for example, the contents of the current print issue of The Economist. Three of the major articles cover: (1) the announcement, to great fanfare, that Amazon, Berkshire Hathaway, and JP Morgan Chase are entering the field of health care; (2) why the academic arms race – the willy-nilly pursuit of advanced degrees – might need to end; and (3) in what ways the rise of populism worldwide reflects real problems that should be addressed and contains seeds of benefit.

Okay, Bill. Dramatic stuff to be sure. Is it an accident that the three in turn address the private-, academic and public sectors – the three pillars of the so-called Weather Enterprise? BTW, none of the three would seem to bear directly on the future of meteorology.

Point taken. But let’s dig a bit deeper into each:

(1) Everybody talks about the weather… and… everybody does something about it. More than a century ago, Mark Twain famously observed that nobody does anything about the weather. As it happens, his statement wasn’t even that true at the time[1]. Even as he spoke, Cleveland Abbe and others at the Army Signal Service were working hard at weather predictions. Their efforts would first morph into the Weather Bureau and ultimately into today’s National Weather Service, and an entire ecosystem of other national weather services and private-sector- and academic partners. These cross-sectoral contributions to space-borne, airborne, and surface observations, numerical modeling and forecasts, dissemination, and impact-based decision support are now so pervasive and thoroughly comingled as to defy teasing them apart.

Improvements in forecasts and their utility are rapid. More advances are coming, and the pace is picking up. While we remain limited in our ability to modify the weather, confidently knowing what’s coming allows us to capture weather’s benefits and more fully enjoy its variability and variety.

The Economist article on healthcare treats two aspects that find analogs here: the rising importance of big data to the overall healthcare process, and the concomitant rise of what the print edition’s cover calls “Dr. You.”  There’s much to this – the article itself merits a complete and careful read – but the core idea is that our individual health data, combined with artificial intelligence, will progressively permit us to take control of our individual healthcare and optimize our chances for a happier, healthier future in unprecedented ways.  Each of us is destined to become our own primary physician. Doubters might google IBM’s Watson work on oncology; that’ll uncover a mix of supportive material as well as some cautionary notes, but it’s easy to see the trend. And IBM is by no means the only player. A number of competing AI developmental efforts such as DeepMind are evolving rapidly. Microsoft is entering healthcare analytics. Recall that the version of IBM’s Deep Blue that beat Garry Kasparov at chess in 1997 filled a small room. The version of Watson that won at Jeopardy in 2011 was the size of three pizza boxes. By 2022, comparable capabilities of a variety of origins will likely fit in a handheld. – and be available to each of us.

Expect, therefore, today’s Alexa to be replaced by stunning capabilities, whether she loses her voice or not, while giving the weather forecast. How cool was that! (Yes, I watched the game Sunday night; my condolences to my colleagues at AMS Boston headquarters.)

If Watson-era devices can absorb the 6000 papers in oncology that are published every day, then tracking corresponding weather information should pose no particular challenge. The cognitive intelligence of the future will anticipate weather that affects you and me, integrate that with our individual scheduled activities and preferences, and help us optimize accordingly. We’ll become masters of our weather-impact-based decision support. We’ll all be meteorologists as well as doctors. What’s more, the analogy doesn’t stop there. Increasingly, we’re also becoming our own lawyers. Our own journalists. Our own tax accountants (think TurboTax).

And our own educators.

That brings us to:

(2) In this world context of the future, learning per se will not be so important as learning-to-learn.

This has always been true. Yet academic institutions ranging from elite universities to K-12 public schools vary in their embrace of this idea. An example: I started graduate work at the University of Chicago in 1964, in physics. At that time, their qualifying exam tested on all of physics. Students were expected to be acquainted with it all – and there was a lot to know. After one year, I transferred to the Department of Geophysical Sciences. Given the state of the science, a lot less to know, at that time! Better yet (from the viewpoint of all my peers) their qualifying exam didn’t test on everything. Instead the faculty asked students to prove they could master subjects as needed. They negotiated with students individually to agree upon three[2], and confined the questioning to those.

In the fifty-plus years since I’ve been constantly learning on the job. However long it’s been since your last graduation, you’ve been almost 100% engaged in such OJT as well. But over that period how you and I learn has changed. Increasingly we learn in DYI partnership with search engines, whose own capabilities have been expanding rapidly. Take a moment to reflect on how you spend your workday. Chances are good you’ll realize that whatever your task, you’re getting more skilled at framing questions for your search engines, and at the same time, by paying attention to your questions, your search engines are getting better at tailoring their answers to your needs, in much the same way as feet adjust to new shoes and vice versa.

For their part, employers seek knowledge workers whose experience blends a level of expertise in some core subject matter with an ability to connect that expertise with others to solve real-world problems. According to The Economist article, employers seeking to build their labor force face skill shortages, not education shortages. Yet they are using proof of the latter as an expensive surrogate for proof of the former, essentially using universities as front-end recruiters – and preferring credentials from high-end universities in the bargain. In effect this forces students and early-career professionals to pay for pricey masters-degree educations when there might be far less costly ways for them to demonstrate mastery of core competencies.

Unsurprising that this might lead to resentment – among those students caught up in this reality – but even more so among the vast majority of young people, who find themselves on the outside looking in. That disgruntlement is one of the contributors to:

(3) Populist political trends, both in the United States and worldwide.

Globalization and innovation are together creating new opportunities and vast wealth, but these opportunities and this wealth are unevenly distributed. The Gini coefficient that tracks such things shows inequality to be increasing nation-by-nation around the world.  This is one of the biggest stories of the past few decades, and results in no little part by the disenfranchisement of large numbers of the world’s peoples who are shut out from the benefits of 21st-century social change and technology advance. This marginalization is a contributing cause to much if not most of the polarization and factionalism in our society today.  These disenfranchised are largely those whom the K-12 public education system has failed – those who haven’t learned-how-to-learn or been taught how to think critically over the course of their education. They may get a first job after their formal studies end, but may be unable to adapt when that first job has run its course. They won’t get that same opportunity or enjoy that same success at being their own professional, whether doctor, lawyer, meteorologist – or educator. What’s more, they’re aware of this separation. They can readily see the dysfunction in the system, and all too naturally conclude it’s more evidence that the workplace playing field isn’t level – and favors “the elites.”

Bottom line? If you and I wish to live in a society that embraces innovation and prospers as the world changes, we might choose to get more involved in improving our local public education.  Over time, as our entire population learns-to-learn, we won’t grow apart; we’ll draw closer together. We’ll become community. We’ll be better doctors, better lawyers – and better meteorologists.


[1] Twain supporters might argue that he was really talking about weather modification. Of course that wall has been breached as well.

[2] In my case, ionospheric physics, fluid mechanics, and hydromagnetics (the latter, for some reason, more popularly known by its far more cumbersome synonym, magnetohydrodynamics).

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2 Responses to The future of meteorology… will be shaped by major social drivers.

  1. there is NO climate……………… there is only rain, no rain, snow, no snow wind, hot, cold and identifiable patterns- “I think it is going to rain.” It looks like snow.”
    The more abstract (scientific jargon) our metaphors get – the easier it is to deny them. Mark Twain did not say “Don’t like the climate – it will change in a minute!”
    Dick K

  2. As someone who set up a public-private partnership to help the “old, the poor and the sick” get the benefits they were promised (BTW, we’ve put over $3M back into their pockets in the last three years) I take a somewhat jaundiced view of how fast and far the revolution in health care that AI and Big Data will create may go. The rate limiting step won’t really be development of the data or the AI but rather the “choice architecture” that makes it useful. Thaler and Sunstein’s “Nudge” is very much on point.

    As I’ve said before on the CARRI blog site, income inequality is not really the issue; being mired in poverty with no hope of escape is the real issue. As a reductio ad absurdum, we can simply expropriate all wealth and spread it around evenly – no income (or wealth) inequality, but no one really interested in Big Data or AI either (and probably can’t afford tools for anyone to really pursue them). Your “learning to learn” is the answer to the real issue of intergenerational poverty; that, and the recognition by all that whether we want to be or not – “I am the Master of my Fate, I am the Captain of my Soul.”

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