Riding the wave: Rethinking science & technology policy

by Andrew Maynard on October 15, 2009

Part 8 of a series on rethinking science and technology for the 21st century

Much to my embarrassment, I’ve just realized that it was over four months ago that I wrote the previous blog in this series – a series that was supposed to evolve over just a few weeks!  Most inconveniently, other priorities ended up interfering with my well-laid plans and I found myself distracted from completing the series, just three posts before its conclusion.

The good news though is that this gives me an excuse to provide a lightning summary of the story so far, which goes something like this:

  • We stand at a nexus of unimaginable technological potential, and unprecedented global challenges.  How we develop and use science and technology over the coming decades will determine the quality (and possibly even the quantity) of life for coming generations.
  • Three factors in particular are influencing the challenges we face, and the tools we have at our disposal to meet them.  These are the rate at which knowledge and ideas are propagating and influencing people, the increasingly strong links between human actions and environmental re-actions, and the ability of scientists, technologists and engineers to bend the material world to their every whim; from atoms and molecules to global weather systems.  These are my three “C’s” – communication, coupling and control.
  • The coupling between human actions and environmental re-actions is cumulative, non-linear, and rapidly increasing in importance.  Which means that we are now facing global challenges that are more complex and further reaching than any previous generation has had to deal with.
  • Rapid changes in how we communicate with each other are rewriting the rules on how society operates, from the global scale to the local level.
  • High-impact advanced in science and technology are being driven increasingly by advances in control over materials at the scale of atoms and molecules.  Atom-level control over everything from DNA to advanced materials to smart drugs is poised to vastly extend our technological reach as a species.
  • Separately, these three factors confront us with new challenges and new opportunities.  Together, they demand a new way of thinking about science and technology if we’re going to ride the wave of the future, rather than being engulfed by it.

The obvious question at this point – and the subject of this blog – is “how effective are current approaches to developing and using science and technology, and what (if anything) needs to change if we are to adapt and thrive as a species?”  In other words, how as a society can we make decisions that will ensure we have the necessary scientific understanding and technological know-how to overcome emerging challenges and realize the opportunities facing us, without creating more problems than we solve?

And that means we need to talk about science and technology policy.

Effective science and technology policy depends on a robust a framework for decision-making that helps ensure an appropriate level of investment in science and technology, and a good return on that investment.  Every developed country/economy has well-established approaches to science and technology policy—whether formally expressed, or simply in the form of a prevalent set of assumptions or beliefs amongst policy makers.  And these approaches have worked okay in the main over the past fifty years or so.

But are they flexible enough to weather the looming challenges of the 21st century?

In the United States, approaches to science and technology policy still reflect largely the thinking of Vannevar Bush.  In 1945, Bush presented President Truman with a vision of science in Science, The Endless Frontier that started with basic research, and ended with social and economic growth.  While thinking has evolved since then, many policy makers are still strongly influenced by his ideas.

In crude terms, Bush’s concept was that pure research (directed predominantly by scientists) leads to applied research, which in turn leads to technological innovation.  This in turn stimulates economic growth, which leads to more jobs, more money, and a better quality of life for citizens.

This top-down, linear model has worked well over the years in the U.S. – scientists have been funded reasonably well by the Federal Government, and have been given considerable latitude in what they do.  And in the U.S. at least, this investment seems to have resulted in considerable technology innovation and wealth generation.

But I’m not sure the same approach has got what it takes to address the very different challenges of the 21st century.

Although current approaches to science and technology policy tend to be more sophisticated than Bush’s model, there is still a tendency to take a top-down linear approach.  Typically under this model, goals for science and technology investment are crafted, funding levels decided, and mechanisms and routes by which those funds will be allocated are identified within government.  It is then assumed that this up-front decision-making will lead to innovation, which will lead to jobs, wealth and, at the end of the day, a better quality of life for citizens.

Old S&T Policy

The degree to which policy makers adhere to or diverge from this (admittedly simplistic) overview depends on where you are in the world.  But this general approach still plays a large role in determining the direction of and funding for science and technology policy in many countries.

Yet this very hierarchical approach to decision-making may not have what it takes to ensure scientific and technological success over the coming years.

First up, it assumes that heavy investment in basic research will naturally lead to technology innovation.  This over-simplistic assumption has been questioned repeatedly over the past decades, perhaps most notably by Donald E. Stokes in his book Pasteur’s Quadrant: Basic Science and Technological Innovation – it’s an assumption that is likely to be further challenged as the interplay between science, technology and society becomes increasingly complex and dynamic.

Then it assumes that up-front investment in science and technology will naturally lead to an improved quality of life through wealth creation.  Yet the values on which the model is based are beginning to look a little simplistic—dated even—in today’s diverse and interconnected world.

And finally, it supports a top-down approach to science and technology policy that encourages policy lock-in.  This occurs when there are few mechanisms to rethink policy decisions that don’t work—a very precarious position to be in where the policy process potentially lags a long way behind technological progress.

In other words, the widely used linear model of science policy could well fall flat in a world where communication, coupling and control demand responsive and adaptive approaches to guiding and utilizing science and technology.

So what’s the alternative?

A complete rethink of science and technology policy frameworks is way beyond the scope of this blog.  But two issues stand out as being at the top of the rethink-list: the need for a less hierarchical policy framework, and the need for more effective feedback mechanisms.

Starting from the bottom, most people would agree that the end goal of investing in science and technology is improved quality of life.  But what this means and the route to achieving it will vary, depending on a number of factors.  The concept that technology innovation and wealth generation will automatically lead to an improved quality of life is one perspective—but it isn’t the only one.  As social and political boundaries are redrawn through new ways of communicating and technology-driven possibilities advance at an increasing rate, I suspect this perspective will begin to look a little naïve.  An alternative approach is to have multiple goals for the science and technology endeavor—recognizing that wealth, jobs, quality of life etc. are important and intertwined, but not necessarily linearly connected.  In other words, recognizing that quality of life may depend on more than making money!

Similarly, I suspect there will need to be a rethink of the relationship between setting top-level goals for science and technology policy and the means of achieving those goals.  Rather than a top-level steer on science and technology policy, it is going to become increasingly important to flatten the process of crafting policies that determine the direction research and development is pointed in, how much is invested in it, and how the money is spent.

But perhaps most importantly, there will need to be increased feedback between what comes out of science and technology policy, and what goes in.

In any complex and dynamic system, feedback is the key to ensuring stability and adaptability.  The Bush-type hierarchical model of science and technology policy has relatively little in the way of feedback.  But this will need to change if policies are to lead to scientific research and technological innovation that achieve what they set out to.  Rapid advances in communication, coupling and control are pushing us a long way out of equilibrium—without effective feedback loops, the consequences could be catastrophic.

A robust science and technology policy framework will depend on many and varied feedback mechanisms.  But amongst these, the ability to review inputs against outputs, and the participation of people and organizations affected by policy decisions, will be essential.

From this perspective, a revised science and technology policy framework that will help us rise to the challenges of the 21st century might look something like this:

New S&T Policy

This is still rather simplistic.  It also reflects to a degree changes in science and technology policy that are already occurring in some countries.  But it does provide some insight into how approaches to science and technology might be crafted that will help us not just cope with life in the 21st century, but to thrive—to ride the wave of the future rather than being engulfed by it.

I’ll look at some of these approaches to science and technology in the next blog in the series – Completing the circle: Coupling science & technology outputs to inputs.

Notes

Rethinking science and technology for the 21st century is a series of blogs drawing on a recent lecture given at the James Martin School in Oxford.  This is a bit of an experiment—the serialization of a lecture, and a prelude to a more formal academic paper.  But hopefully it will be both interesting and useful.  I’ll be posting a “rethinking science and technology” blog every week or so, interspersed with the usual eclectic mix of stuff you’ve come to expect from 2020science.

Previously: Confluence: Where communication, coupling and control collide

Next: Completing the circle: Coupling science & technology outputs to inputs [Coming soon]

1 Andréia Azevedo Soares October 15, 2009 at 6:32 pm

Hi Andrew,
I am probably doing something wrong, but I cannot find a print friendly version of your blog. Since I commute everyday, it is more comfortable to read selected entries in paper – then I can file them with my own handwritten comments or underlined quotes.
Today, for example, I printed the blog “Communication: Science and technology in a connected world” in ten pages when only 5 would be sufficient.
Can you help me?
Thanks :-)***

2 Andrew Maynard October 17, 2009 at 5:27 pm

Hi Andréia,

An interesting challenge – let me see what I can do.

Andrew

3 Andrew Maynard October 17, 2009 at 5:44 pm

Hi again Andréia,

I’ve just added a “print” button to the “Share and Enjoy” bar at the bottom of posts – could you let me know how this works for you? There’s also a PDF option here.

Cheers,

Andrew

4 Andréia Azevedo Soares October 17, 2009 at 7:47 pm

Hi Andrew,

Thank you for that. It was very kind of you.
I read your blog yesterday on the train and re-read it today (printable version!). Found your discussion overall interesting and clarifying but got stuck in the “alternative” model suggested.
I obviously agree that the top-down linear approach has (or ought to be given) an one way ticket to the sci-policy cemetery. But some elements of the new model leave me scratching my head. Let me explain:

1) You praise a less linear relation between quality of life and science & technology. Fair enough. However, even though the association between those two elements appears more diffuse in the second model, the emphasis on this association clearly remains in your discourse. And it makes me worried about science policies that might disregard the value of knowledge itself. The knowledge that cannot be immediately of any use, applicable, profitable. This knowledge needs to be also funded (and accountable!) even if it does not improve society’s quality of life in a tangible way.

2) I am not sure of the place where “innovation” appears in the model. Innovation seems to be today a condition ‘si ne qua non’ to refine mechanisms and to captivate funds. So innovation, in my humble opinion, is probably rather a goal than an element among others. I don’t know. Maybe innovation is an aspect so pervasive that it can appear in more than one stage of the model.

3) I would be much more happier if the arrows were represented both ways. It is just an utopia of mine. :-)

Thank you for producing so much food for thought in your blog. My brain has been benefiting from reading regularly 2020 Science. It also says thanks to you.

Cheers,
Andréia

5 Andrew Maynard October 18, 2009 at 10:12 am

Thanks Andréia, this is great – I wish more readers would push back on what I write, as often these blogs are me trying to work through ideas, rather than present them fait accomplis! In this case, I’m still developing my thoughts on new approaches to science and technology policy, so your comments are particulary welcome.

I suspect that the next blog in the series will go some way to addressing your points, but let me try and explore them a little more here.

First the association between science and technology policy, and quality of life. Here, I was guilty of not defining what I mean by quality of life – a rather serious omission! I must confess that, from a policy perspective, I do struggle with the idea of knowledge for knowledge’s sake. I see no inherent value in knowledge devoid of a human context. BUT, when coupled with what I guess you might call the human condition, knowledge (and understanding) take on value. That value might be very practical – preventing and treating disease, or providing food and shelter. It might be more metaphysical in nature – leading to a greater understanding and appreciation of what it means to be human, and our place in the grand scheme of things. Or then again, it might simply be associated with the joy of developing greater insight into the universe (whether the insight can be put to practical use or not). To my mind, all of these increase “quality of life.”

So I would very much place value on how science in particular enriches our lives in intangible ways, as well as in very practical ways.

Just as an add-on to this, fundamental research is often justified in policy circles as being important because it creates a foundation of knowledge and understanding which underpins applied research and technology, and eventually leads to innovation. I’m afraid I don’t completely buy into this. Clearly, fundamental research is important as it lays the groundwork for many practical discoveries. But technological innovation often proceeds without a broad base of fundamental research – and as most researchers recognize, the boundaries between applied and fundamental research are usually rather fuzzy. More importantly however, this very “materialistic” world-view downplays the role of discovery as enhancing our lives in less tangible ways – and in doing so, diminishes us. I would argue strongly that there is always a need to invest to some degree in research that has no clear practical value, because of it’s role in helping us understand and appreciate what it means to be human.

Secondly – innovation as a goal, rather than an outcome. I think it can be both. One goal of investing in science and technology is clearly to stimulate innovation. Yet as a result of this, innovation – and in particular, the products of innovation, are a very clear output from the process. One of the reasons that innovation is on the outputs side of things in the revised model is that this is so much a part of policy thinking in the developed (and developing) world. To corrupt a well known mantra, “innovate or perish” is a central tenet of most leading economies.

Yet I’m not convinced that innovation is necessarily a singularly important step towards “quality of life” – which is why I moved it out of the chain and into parallel position with other outcomes of science and technology policy. In reality, there is a complex web of connections and relationships between innovation, wealth, security, quality of life etc., and within this, I would argue that innovation plays a critical role. But if you believe that quality of life depends on more than material comfort and wealth, it must be dependent on more than innovation.

Another way of looking at this (and you can see that my thoughts are still in the formative stage here) is that both quality of life and innovation are important outcomes of science and technology policy, but they are not always linked. This actually raises a couple of interesting questions, that I don’t have immediate answers to: Can science and technology lead to an increase in quality of life that doesn’t depend on innovation? And is innovation that is not directly linked to an increase in quality of life a laudable goal for science and technology policy? From my discussions above I think my answer to both is yes (although what is meant by “quality of life” is critical) – but this needs more thought and discussion.

Finally, the arrows. Actually, I was hoping that the “down” arrows were implicit in the central flow between policy inputs and policy outcomes – that probably needs to be made clearer. So I think we are in agreement here :-). The model as presented is based on typical feedback models though, where you have an input, and output, and then feedback between input and output that in effect regulates the process. Blame it on my physics up-bringing!

6 Andréia Azevedo Soares October 18, 2009 at 1:37 pm

Andrew,

What can I say reading such quotations of yours on the understanding of “quality of life”?

“That value (…) might be more metaphysical in nature – leading to a greater understanding and appreciation of what it means to be human(…) it might simply be associated with the joy of developing greater insight into the universe (whether the insight can be put to practical use or not). To my mind, all of these increase “quality of life.”

“I would argue strongly that there is always a need to invest to some degree in research that has no clear practical value, because of it’s role in helping us understand and appreciate what it means to be human.”

Well, all I can say is that I believe we are aligned to some degree!

Regarding the questions you formulate in your reply:

1) Can science and technology lead to an increase in quality of life that doesn’t depend on innovation?
2) Is innovation that is not directly linked to an increase in quality of life a laudable goal for science and technology policy?

They are both almost million dollar questions. It is very difficult to me even think of a rough draft to answer them. Optimistic as I am, I often allow my thoughts to be biased in questions involving the future of society. That is why I desperately want to believe in a loud “yes” to the first question and, to the second one, I desperately want someone serious and responsible to say yes for me (keeping my eyes covered in the meantime)!
This sort of response of the lay public towards science policies partly explains why the Bush’s model resisted so long. Linear relations and top-down measures offer us a stale comfort that is difficult to overcome.

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