I attended a talk this morning by Holger Hoos, from UBC, and then had a fascinating conversation with him over lunch. He’s on an 8 week driving tour across Canada and the US, stopping off at universities along the way to meet with colleagues give talks. Great idea – more academics should do this (although I can’t figure out what I’d do with the kids…)

Anyway, what piqued my interest was the framing Holger used for the talk: we live in interesting times, and are faced with many grand challenges: climate change, peak oil, complex diseases, market turmoil, etc. Many of these challenges are due to complexity of various kinds, and to tame this complexity we need to be able to understand, model and control complex systems. And of course, taming complexity is what much of computer science is about.

The core of his talk was a fascinating look at new heuristic algorithms for solving NP hard problems, e.g. algorithms that that outperform the best TSP algorithms and SAT solvers, by using machine learning techniques to tweak the parameters on the heuristics to optimize them for different kinds of input. Which leads to a whole new approach of empirical algorithm design and algorithm engineering. One theme throughout the talk was shift in focus for algorithm design from thinking about worst case analysis, to thinking about handling typical cases, which is something I’ve long felt is a problem with theoretical computer science, and one of the reasons the field has been largely irrelevant when tackling most real engineering problems.

Anyway, for all that I enjoyed the talk, there seemed  to be a gap between the framing (tackling the grand challenges of our time) and the technical content (solutions to computationally intractable problems). Over lunch we talked about this. My observation is that, for climate change in particular, I don’t believe there are any aspects of the challenge that require solving computationally complex problems. It would be nice if there were – it would help me complete my map of how the various subfields of computer science can contribute to tackling climate change. There are obvious applications for information systems (aka databases), graphics and visualization, human computer interaction (usable climate models!!), software engineering, ubiquitous computing (e.g. sensor networks), systems (e.g. power aware computing), and so on.

We talked a little about whether climate models themselves count, but here the main challenges are in optimizing continuous mathematics routines for high performance, rather than solving complex discrete mathematics problems. For example, we speculated whether some of Holger’s work on applying machine learning techniques to parameter tuning could be applied to the parameter schemes for climate models, but even here, I’m not convinced, because there is no oracle. The problem is that climate scientists can’t write down good correctness criteria for climate models because the problem isn’t to develop a “formally correct” model, but rather a scientifically useful one. The model is good if it helps test a scientific hypothesis about how (some aspect of) earth systems work. A model that gets a good fit with observational data because the parameters have been ‘over-tuned’ will get a poor reception in the climate science community; the challenge is to get a model that matches observational data because we’ve correctly understood the underlying physical processes, not because we’ve blindly twiddled the knobs. However, I might be being overly pessimistic about this, and there might be scope for some of these techniques because model tuning still remains a challenging task in climate modeling.

But the more urgent and challenging problems in climate change remain squarely in the realm of how to wean the world off its addiction to fossil fuels as rapidly as possible. This is a problem of information (and overcoming disinformation), of behaviour (individual and social), of economics (although most of modern economic theory is useless in this respect), and of politics. Computer Science has a lot to offer in tackling the information problems, and also some useful abstraction and modeling techniques to understand the other problems. And of course, software is a critical enabling technology in the switch to alternative energy sources. But I still don’t see any computational complexity problems that need solving in all of this. Tell me I’m wrong!

Here’s the intro to a draft proposal I’m working on to set up a new research initiative in climate change informatics at U of T (see also: possible participants and ideas for a research agenda). Comments welcome.

Climate change is likely to be the defining issue of the 21st Century. The impacts of a climate change include a dramatic reduction of food production and water supplies, more extreme weather events, the spread of disease, sea level rise, ocean acidification, and mass extinctions. We are faced with the twin challenges of mitigation (avoiding the worst climate change effects by rapidly transitioning the world to a low-carbon economy) and adaptation (re-engineering the infrastructure of modern society so that we can survive and flourish on a hotter planet)
These challenges are global in nature, and pervade all aspects of society. To address them, researchers, engineers, policymakers, and educators from many different disciplines need to come to the table and ask what they can contribute. There are both short-term challenges (such as how to deploy, as rapidly as possible, existing technology to produce renewable energy; how to design government policies and international treaties to bring greenhouse gas emissions under control) and long-term challenges (such as how to complete the transition to a global carbon-neutral society by the latter half of this century).
For Ontario, climate change is both a challenge and an opportunity. The challenge comes in understanding the impacts and adapting to rapid changes in public health, agriculture, management of water and energy resources, transportation, urban planning, and so on. The opportunity is the creation of green jobs through the rapid development of new alternative energy sources and energy conservation measures. Indeed, it is the opportunity to become a world leader in low-carbon technologies.
While many of these challenges and opportunities are already well understood, the role of digital media as both a critical enabling technology and a growing service industry is less well understood. Digital media is critical to effective decision making on climate change issues at all levels. For governmental planning, simulations and visualizations are essential tools for designing and communicating policy choices. For corporations large and small, effective data gathering and business intelligence tools are needed to enable a transition to low-carbon energy solutions. For communities, social networking and web 2.0 technologies are the key tools in bringing people together and enabling coordinated action, and tracking the effectiveness of that action.
Research on climate change has generally clustered around a number of research questions, each studied in isolation. In the physical sciences, the focus is on the physical processes in the atmosphere and biosphere that lead to climate change. In geography and environmental sciences, there is a strong focus on impacts and adaptation. In economics there is a focus on the trade-offs around various policy instruments. In various fields of engineering there is a push for development and deployment of new low-carbon technologies.
Yet climate change is a systemic problem, and effective action requires an inter-disciplinary approach and a clear understanding of how these various spheres of activity interact. We need the appropriate digital infrastructure for these diverse disciplines to share data and results. We need to understand better how social and psychological processes (human behaviour, peer pressure, the media, etc) interact with political processes (policymaking, leadership, voting patterns, etc), and how both are affected by our level of understanding of the physical processes of climate change. And we need to understand how information about all these processes can be factored into effective decision-making.
To address this challenge, we propose the creation of a major new initiative on Climate Change Informatics at the University of Toronto. This will build on existing work across the university on digital media and climate change, and act as a focus for inter-disciplinary research. We will investigate the use of digital media to bridge the gaps between scientific disciplines, policymakers, the media, and public opinion.

Climate change is likely to be the defining issue of the 21st Century. The impacts of a climate change include a dramatic reduction of food production and water supplies, more extreme weather events, the spread of disease, sea level rise, ocean acidification, and mass extinctions. We are faced with the twin challenges of mitigation (avoiding the worst climate change effects by rapidly transitioning the world to a low-carbon economy) and adaptation (re-engineering the infrastructure of modern society so that we can survive and flourish on a hotter planet)

These challenges are global in nature, and pervade all aspects of society. To address them, researchers, engineers, policymakers, and educators from many different disciplines need to come to the table and ask what they can contribute. There are both short-term challenges (such as how to deploy, as rapidly as possible, existing technology to produce renewable energy; how to design government policies and international treaties to bring greenhouse gas emissions under control) and long-term challenges (such as how to complete the transition to a global carbon-neutral society by the latter half of this century).

For Ontario, climate change is both a challenge and an opportunity. The challenge comes in understanding the impacts and adapting to rapid changes in public health, agriculture, management of water and energy resources, transportation, urban planning, and so on. The opportunity is the creation of green jobs through the rapid development of new alternative energy sources and energy conservation measures. Indeed, it is the opportunity to become a world leader in low-carbon technologies.

While many of these challenges and opportunities are already well understood, the role of digital media as both a critical enabling technology and a growing service industry is less well understood. Digital media is critical to effective decision making on climate change issues at all levels. For governmental planning, simulations and visualizations are essential tools for designing and communicating policy choices. For corporations large and small, effective data gathering and business intelligence tools are needed to enable a transition to low-carbon energy solutions. For communities, social networking and web 2.0 technologies are the key tools in bringing people together and enabling coordinated action, and tracking the effectiveness of that action.

Research on climate change has generally clustered around a number of research questions, each studied in isolation. In the physical sciences, the focus is on the physical processes in the atmosphere and biosphere that lead to climate change. In geography and environmental sciences, there is a strong focus on impacts and adaptation. In economics there is a focus on the trade-offs around various policy instruments. In various fields of engineering there is a push for development and deployment of new low-carbon technologies.

Yet climate change is a systemic problem, and effective action requires an inter-disciplinary approach and a clear understanding of how these various spheres of activity interact. We need the appropriate digital infrastructure for these diverse disciplines to share data and results. We need to understand better how social and psychological processes (human behaviour, peer pressure, the media, etc) interact with political processes (policymaking, leadership, voting patterns, etc), and how both are affected by our level of understanding of the physical processes of climate change. And we need to understand how information about all these processes can be factored into effective decision-making.

To address this challenge, we propose the creation of a major new initiative on Climate Change Informatics at the University of Toronto. This will build on existing work across the university on digital media and climate change, and act as a focus for inter-disciplinary research. We will investigate the use of digital media to bridge the gaps between scientific disciplines, policymakers, the media, and public opinion.