January 28, 2009
Kenneth Arrow, Stanford University
Abstract
Many allocation decisions require costs today (or, at least, beginning today ) with benefits extending into the distant future, affecting lives not yet in existence. The leading example today is policy to meet anthropogenic climate change, but that problem is by no means unique. How do we think about the balancing of values? To some extent, the questions have to do with empirical regularities, but to a major extent, they depend on value judgments about our obligations to future generations. The decisions are further complicated by uncertainties about the future.
March 25, 2009
Sandy Pentland, Massachusetts Institute of Technology
Abstract
How can you know when someone is bluffing? Paying attention? Genuinely interested? The answer is that subtle patterns in how we interact with other people reveal our attitudes toward them. These predictive patterns seem to be biologically based "honest signals," evolved from ancient primate signaling mechanisms, and we find that they are major factors in human decision making in situations ranging from job interviews to first dates. By analyzing these signals using data from mobile phones, electronic ID badges, or digital media, we can create a "gods eye" view of how the people in organizations interact, and even `see' the rhythms of interaction for everyone in a city.
May 27, 2009
Ion Stoica, University of California, Berkeley
Abstract
Building large scale distributed application is hard; debugging and profiling them is even harder. Today, almost every web request involves an application running distributedly on many machines in one or more data centers. These applications need to run 24x7, handle inputs that vary by multiple orders of magnitude, and seamlessly accommodate hardware and software upgrades. To successfully build and run such applications it is critical to model and understand their behaviors. In this talk, I will discuss some of our initial efforts to build tools that provide a comprehensive understanding of the behavior of distributed applications, and allow careful offline analysis by faithfully reproducing race conditions and non-deterministic failures that occurred during the original execution.
July 29, 2009
Jeannette Wing, National Science Foundation
Abstract
My vision for the 21st Century: Computational thinking will be a fundamental skill used by everyone in the world. To reading, writing, and arithmetic, let's add computational thinking to every child's analytical ability. Computational thinking has already influenced other disciplines, from the sciences to the arts. The new NSF Cyber-enabled Discovery and Innovation initiative in a nutshell is computational thinking for science and engineering. Realizing this vision gives the field of computing both exciting research opportunities and novel educational challenges. The field of computing is driven by technology innovation, societal demands, and scientific questions. We are often too easily swept up with the rapid progress in technology and the surprising uses by society of our technology, that we forget about the science that underlies our field. In thinking about computing, I have started a list of "Deep Questions in Computing,” with the hope of encouraging the community to think about the scientific drivers of our field.
October 29, 2009
Ronald Graham, University of California, San Diego
Abstract
There is no question that the recent advent of the modern computer has had a dramatic impact on what mathematicians do and on how they do it. However, there is increasing evidence that many apparently simple problems may in fact be forever beyond any conceivable computer attack. In this talk, I will describe a variety of mathematical problems in which computers have had, may have or will probably never have a significant role in their solutions.
December 2, 2009
Leroy Hood, Institute of Systems Biology
Abstract
The challenge for biology in the 21st century is the need to deal with its incredible complexity. One powerful way to think of biology is to view it as an informational science. This view leads to the conclusion that biological information is captured, mined, integrated by biological networks and finally passed off to molecular machines for execution. Hence the challenge in understanding biological complexity is that of deciphering the operation of dynamic biological networks across the three time scales of life—evolution, development and physiological responses. Systems approaches to biology are focused on delineating and deciphering dynamic biological networks and their interactions with simple and complex molecular machines. I will define our contemporary view of systems biology and then focus on our efforts at a systems approach to disease—looking at prion disease in mice. We have just published a study that has taken more than 5 years—that lays out the principles of a systems approach to disease including dealing with the striking signal to noise problems of high throughput biological measurements and biology itself (e.g. polymorphisms). I will also discuss the emerging technologies (measurement and visualization) that will transform biology and medicine over the next 10 years—including next generation DNA sequencing, microfluidic protein chips and single-cell analyses. I will as well discuss some of the computational and mathematical challenges that are fundamental to the revolution in biology and medicine. It appears that systems medicine, together with emerging technologies and the development of powerful new computational and mathematical tools will transform medicine over the next 5-20 years from its currently reactive state to a mode that is predictive, personalized, preventive and participatory (P4) medicine. I will discuss the impact P4 medicine has on society and several ISB-strategic partnerships that have been established to attack the technical and societal barriers to the realization of P4 medicine.
Big Thinkers Archives
2008 Calendar of Events
2007 Calendar of Events
2006 Calendar of Events
Video and Event Recap