In 1900, the German mathematician, David Hilbert, presented a list of the most important outstanding problems in mathematics at a conference in Paris.
Of these 23 problems, some have been convincingly solved. The 3rd problem, for example, asks the following:
Given any two polyhedra of equal volume, is it always possible to cut the first into finitely many polyhedral pieces which can be reassembled to yield the second?
The answer: no!
Others remain unsolved and the subject of ongoing research, such as the Riemann hypothesis.
But together, Hilbert’s problems have been hugely influential, becoming an important focal point for mathematical investigations for over one hundred years.
Because of this, leaders in many other disciplines have listed grand challenges in their own fields. The idea is to stimulate research in the same way that Hilbert did.
Today, Dirk Helbing at the Swiss Federal Institute of Technology in Zurich attempts this feat for the social sciences and economics.
Helbing is the driving force behind an ambitious project called FuturICT, which we’ve looked at here. His plan is to gather data about the planet in unheard of detail, use it to simulate the behaviour of entire economies and then to predict and prevent crises from emerging.
He is currently waiting to discover whether he will receive the €1 in billion funding he needs from the European Commission. So in the meantime, he’s listed the most important challenges that his project (and others) will need to tackle in the future.
In total, he lists over 60 challenges. Here are some of them:
How to promote security and peace (e.g. avoid organized crime, terrorism, social unrest)?
How to measure characteristics of society, the social fabric, social norms, social capital, social impact, social change, interactions, systemic risks, institutional constraints, context, and culture globally and in real-time?
What are the limits of predictability and controllability in complex, networked systems? Is the economic system designed in a controllable way (from a cybernetic point of view)? If not, what would have to be changed to make the system better manageable?
How do environment and environmental change interact with human behavior and social change?
How to create resilient networks and systems? How to avoid that local perturbations can have destructive systemic impacts on a global scale?
How does innovation arise? What drives or impedes innovation? How to model creativity?
Of course, the first and most important challenge is to make the list shorter. Without some kind of mechanism for filtering out the most important challenges (or the most easily answered), the list is too long. Nobody can focus on 60 challenges.
Helbing suggests that his FuturICT project will become a kind of clearing house in which stakeholders can put forward grand challenges and interested bodies–research agencies, individuals or commercial companies, for example–can fund work on problems they are likely to benefit from.
That’s an interesting idea. It’s worked in other areas with relatively small problems with specific payback requiring little investment.
But grand challenges that require significant investment and high risk approaches to solve are a difficult kettle of fish. It’s not at all clear how the risks involved will be managed.
So it’ll be interesting to see whether Helbing’s grand challenges have the same impact on economics and social sciences as Hilbert’s had on mathematics. Opinions in the comment section please!
Ref: arxiv.org/abs/1208.3883: Accelerating Scientiﬁc Discovery By Formulating Grand Scientiﬁc Challenges
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