I mentioned NESTA and the talk by Stephen Emmott at
and started transcribing it at
but gave up because of the poor quality of the recording. It’s now available as a good quality video at
I’ve transcribed it and Alex Cull has put it up at
Emmott is a dreadful public speaker, but the talk is fascinating as an insight into the thinking of a scientist whose aim is nothing less than to revolutionise the way science is done and what science is done.
Public speaking is a talent. Some have it, some don’t, so it may seem unfair to criticise Emmott for his delivery, his grammar, and his disarming way of illustrating the recursive nature of computational thinking in his sentence structure, which defies all logical attempts to punctuate it. He may be the only public speaker in history who can tell a joke and interrupt himself in the middle to explain why he’s telling it, why it’s not funny, and how he’d be better off telling a different joke.
But seriously, he’s being paid for this for Gaia’s sake. The exact arrangements between Microsoft, Oxford University, Cambridge University, NESTA, the Royal Court Theatre, the Arts Council, the Avignon Festival, the European Union, Penguin Books, Nature, and the United Nations Environment Programme are none of my business. But they’ve all been involved in some way in pushing Emmott’s programme for a new kind of science, and all we’ve heard so far is burbling.
The title of his talk is “the Need and Nature of a New Scientific Revolution”. He covers the Need by giving: “a quick summary of what I think are the most important questions of our times, and certainly in my view the important questions for us as a society this century”.
These he lists, starting as follows (I’ve tidied up quotes, eliminating numerous “you know”s etc.):
– How is the climate going to change and more important, what’s going to be the impact, what’s going to be the consequences?
– How we are going to feed a global population of at least ten billion – it might be a lot more.
– How are we going to – sustainably – power a planet of ten billion or more? We could easily power the planet if we just continue to use oil, coal and gas but that would almost certainly finish us off.
– Have we embarked on the sixth mass extinction of life on earth? the answer is almost certainly yes … and related to that question is the bigger question of what’s the future of life on earth for global eco-systems and ourselves, given all the other questions.
Note how he answers his fourth question at the same time as he poses it. Alex has demonstrated the flimsy nature of the grounds for his answer in his article here:
The two factors most widely cited as factors in mass extinction are man’s encroachment on the wilderness (largely for farming) and man-made climate change – the former, together with the burning of fossil fuels, being a cause of the latter.
“The most important questions for us as a society this century” turn out to be a simple game of scissors-cut-paper-wraps-stone-sharpens-scissors rendered complex by its hidden assumptions. By answering his fourth question at the same time as he poses it, he implicitly answers the other three. If we’re causing mass extinction, it can only be because of catastrophic man-made climate change, and the encroachment on wilderness caused by our attempts to feed a growing population, whose energy demands can’t be met from fossil fuels because “that would almost certainly finish us off”. The conclusion that we’re fucked, which took a whole hour to reach at the Royal Court, is more pithily delivered before the brainier NESTA audience.
Having enumerated the key problems facing humanity in the form of four questions, answered the fourth one, and suggested that the first three are insoluble, he then lists “some other interesting questions” about pandemics, the immune system, stem cells, neuroscience, and medical research. As he points out, they’re all questions of biological science “and we’re unable to answer any of these questions, which is quite remarkable in itself. in fact in terms of biology we dont even knows how a cell works. In 2012.”
He embarks on a long complicated joke analogy about how ignorant biologists are, pointing out that he “..could have ridiculed ecology just as much as biology, but I wanted as a biologist – I feel as though I’m at least somewhat qualified to ridicule my own discipline.”
He emphasises that ecologists and climate scientists are just as much in the dark as biologists:
“So, just to quickly underline what I mean by that, in the area of climate, after 50 years of climate modelling in places like the Hadley Centre, uncertainty in climate models is still a critical issue, the key issue in climate modelling.
“In ecology, despite 200 years of data collection in ecology we still understand very little about how species interact, about ecosystem structure and function and about extinction rates, so we’re unable to ask the question, unable to fully answer the question about whether we’ve embarked on the sixth mass extinction of life on earth and what the future of life on earth is.”
.. which is puzzling, since he’s already answered the question with an “almost certainly yes”.
So having explained the need for a scientific revolution in terms of the problems facing humanity, and our ignorance of the basic science underlying those problems, he turns to the nature of the scientific revolution required.
“… the question is: Now what? Given the fact that we don’t even know how a cell works, and we don’t know how ecosystems function, and we dont know whether we can feed a population of ten billion, and we don’t know how we’re going to be able to power the planet, we have no way of predicting or preventing a global pandemic, what now in biological science, the natural sciences more generally?”
He answers his question “What now?” by describing two programmes which his forty-strong Cambridge Microsoft team are working on. The first, in neuroscience, I didn’t transcribe, since it’s incomprehensible without the accompanying slides. The second one involves the planet-wide modelling of biodiversity with what he calls a General Ecological Model or GEM, in order to answer the question he’s already posed (and answered) about the extinction rate.
“As I mentioned earlier, we have no idea about the rate at which we’re losing, no good idea about the rate at which we’re losing ecosystems … and that’s an important question because we are losing species. We’re not clear about how much, it could be between, it could be a rate of extinction a hundred times greater than we would expect from normal evolutionary processes, or it could be a rate of over a thousand times that we would expect from normal evolutionary processes, but we’re losing them at an alarming rate.
“Given the fact that we’re actually unable to characterise or understand how many species there are on earth, most scientists agree that the simple fact of that means that we’re losing species at a far faster rate than we currently think we are, so it’s almost certainly at least a thousand times – the rate of species extinction on earth is at least almost a thousand times greater than it should be through normal evolutionary processes.”
Think about that. Emmott, like everyone else working in the field, quotes the single source estimate of species loss as being “a hundred to a thousand times the normal rate”, takes the higher estimate of “a thousand times”, alters that to “over a thousand times” and explains that “most scientists agree” that the fact that we don’t know how many species there are “means that we’re losing species at a far faster rate than we currently think we are”.
[I know nothing about biology, but I’ve read “Through the Looking Glass” and I know a glorious knock-down argument when I see one. This argument – that the less you know, the more likely things are to be worse than you thought – was recently put forward by Professor Stephan Lewandowsky, the expert on the psychology of climate scepticism, and discussed at
These are deep waters, running from the subjective school of Bayesian statistics, via Humpty Dumpty to Hamlet’s:
“there is nothing either good or bad, but thinking makes it so.”]
But back to Emmott’s General Ecological Model. He describes how it works, and it’s really very interesting. Then he says:
“If we model the previous few million years, we get a remarkably faithful model of where ecosystems are now and how we think that they’re distributed. Our next step is to model what we think is going to happen to ecosystems … for the next probably 200 years, and this sort of model is enabling us to ask fundamentally new questions about what ecosystems do, ecosystems behaviour, our impact on them, and the impact of our impact on these ecosystems on our wellbeing. The interesting thing about this model is that – there was an important report came out in 2011 which was this Living Planet report. What it showed was, if you looked at ecosystem health … that there’s been a significant ..degradation of about 30% [from 1970 to 2007]. What this model shows is that actually the problem is far worse than the policy community, policy-making conservation community and indeed the climate community think – ‘cos the climate is related to ecosystems structure and function – is far worse than we think, so the dotted line is the output from our model.”
So there you have it. A graph with two lines: a solid line, the Living Planet line, drooping 30% over 37 years, and a dotted line, the Microsoft new kind of science line, drooping even more.
Which leads Emmott to his conclusion that:
The important thing about this I think that I really want to underline .. is that none of this is going to be possible without an entirely new generation of entirely new kinds of scientists, of scientists that have a very different way of thinking about biology and natural science, scientists who are scientifically first rate, not just in one discipline, but are genuinely interdisciplinary .. and it requires people who are computationally first rate, and I don’t mean people who know where the on button is on their Macintosh, I mean conceptually and mathematically computationally first rate. And those kinds of … computationally first rate natural scientists are only just beginning to emerge. And .. and its going to be impossible to do ecology or biology over the next decade unless you’re computationally first rate, and I don’t think the research councils or the general university system has grasped this problem yet, so the idea of new kinds of scientists is one that I really want to hammer home fundamentally as critical to this transformation, an urgently needed transformation of science, if we’re going to solve some of these massive important and unprecedented global challenges that we face, of which science is at the centre of all of them. And that’s it. Thank you very much.
Not being computationally first-rate myself, I had a thought about that Living Planet health graph, with it’s 30% health droop in 37 years, and I thought: “If you drew a graph of my health over 37 years, you’d probably get a 30% droop”, which is normal, because I’m a living being, subject to the mysterious ways of biology about which (as Emmott says) we know so little. So if you call the planet a Living Planet, (which it’s not), perhaps somewhere you’re importing an unjustified assumption which somehow contaminates your subtle calculations and propagates itself throughout your thought processes, like one of those mutating bugs which (Emmott says) are going to overpower our unprepared immune systems and kill billions of us one day soon.
And perhaps taking thousands of models with petabytes of data and smashing them together in the Microsoft equivalent of a Large Hadron Collider, (which is Emmott’s description of his new kind of science) is a handy way of disguising the fact that calling the planet a living thing is nothing but a metaphor, and that after 37 years, a living planet, like a living human, is bound to feel a bit creaky at the joints when the weather takes a turn for the worst , and that it’s quite normal, as it’s quite normal that scientists should be a bit loose in their language sometimes, so that “hundreds or thousands” become “thousands or more”, and questions of how to feed ten billion people in a hundred years’ time morph into questions about how the human race can survive.
* * *
The same General Ecological Model is discussed in more detail in an article in Nature at
which is available free at
of which Emmott is one of the seven authors. Five of them work for Microsoft at Cambridge, and five at the United Nations Environment Programme World Conservation Monitoring Centre, a charity also based at Cambridge.
“There are huge challenges to building GEMs — not least, obtaining the appropriate types of data to validate the models’ predictions. But the difficulties are not insurmountable… Over the past two years, we at Microsoft Research and at UNEP-WCMC have built a prototype GEM for terrestrial and marine ecosystems. .. We have hit all sorts of computational and technical hurdles, and are expecting more as we develop the model. Yet the project demonstrates that building GEMs is possible.”
So it’s a prototype. There’s nothing about “getting a remarkably faithful model of where ecosystems are now” or “showing that actually the problem is far worse than the policy policy-making conservation community and indeed the climate community think”. In fact it’s all couched in the conditional:
“We think that .. GEMs could radically improve understanding of the biosphere and inform policy decisions about biodiversity and conservation … GEMs could provide a way to base conservation policy on an understanding of how ecosystems actually work … Such models could capture the broad-scale structure and function of any ecosystem in the world … Ecologists could apply a GEM to African savannas, for instance … All of the organisms would be grouped not by species, but according to a few key traits … By encoding processes such as migration and predation into simple mathematical and computational forms, ecologists could model what happens to the various groups over time … Metrics such as the diversity of animal types inhabiting the grasslands could be used … Ecologists could explore how these attributes might change in response to, say, climate change … the GEM could equally be applied to forests, lakes or the remotest parts of the ocean…,
“Building a GEM will require different types of data … certain computational techniques have been developed, mainly in marine ecology, that could allow researchers to model entire ecosystems …The biggest stumbling block to constructing GEMs (after convincing ecologists that they can and should be built!) is obtaining the data to parameterize and validate them… almost no data have been collected on the properties of whole ecosystems… Using automated cameras and image recognition, it should be possible to sample thousands of animals and determine their approximate size and what broad group they belong to … data collection could even be crowd-sourced..
“Naturally, a major new data-gathering programme would be costly. But … gathering the data needed to develop and evaluate GEMs could pay dividends …”
Not if we’re fucked, it won’t. Maybe Emmott should get his message straight for the launch of his book in May.
And maybe Shakespeare should change Hamlet’s line to:
“there is nothing either good or bad, but thinking can’t make it worse.”