CCC supported three scientific sessions at this year’s AAAS Annual Conference, and in case you weren’t able to attend in person, we are recapping each session. This week, we are summarizing the highlights of the session, “How Big Trends in Computing are Shaping Science.” In Part 5, we share the Q&A portion of the panel. The panel comprised Jayson Lynch (Massachusetts Institute of Technology), Gabriel Manso (Massachusetts Institute of Technology), and Mehmet Belviranli (Colorado School of Mines), and was moderated by Neil Thompson (Massachusetts Institute of Technology).   Neil Thompson: “Gabriel, you highlighted just how dramatic the escalation in the amount of computing being used by these models is, and […]

CCC supported three scientific sessions at this year’s AAAS Annual Conference, and in case you weren’t able to attend in person, we are recapping each session. This week, we are summarizing the highlights of the session, “How Big Trends in Computing are Shaping Science.” In Part 3, we hear from Dr. Jayson Lynch, a Research Scientist in the FutureTech lab at Massachusetts Institute of Technology, who explains the speed at which algorithms are improving.   Dr. Jayson Lynch began their presentation by addressing the cliffhanger that Manso ended on: how quickly are algorithms improving, and will these algorithms serve as partial solution to the growing need for compute? “The main […]

CCC supported three scientific sessions at this year’s AAAS Annual Conference, and in case you weren’t able to attend in person, we are recapping each session. This week, we are summarizing the highlights of the session, “How Big Trends in Computing are Shaping Science.” In Part 2, we hear from Gabriel Manso, a first year PhD student at Massachusetts Institute of Technology, who explains the computational limits of deep learning.   Gabriel Manso, a first-year PhD student at MIT and a member of the MIT FutureTech research group, discussed the computational limits of deep learning along with insights from his research. Deep learning is pervasive across most areas of science […]

CCC supported three scientific sessions at this year’s AAAS Annual Conference, and in case you weren’t able to attend in person, we are recapping each session. This week, we will summarize the highlights of the session, “How Big Trends in Computing are Shaping Science.” In Part 1, we will hear from Dr. Neil Thompson, from the Massachusetts Institute of Technology, who will explain the computing trends shaping the future of science, and why they will impact nearly all areas of scientific discovery.   CCC’s third AAAS panel of the 2024 annual meeting took place on Saturday, February 17th, on the last day of the conference. The panel, comprised Jayson Lynch […]

The following blog post is from Computing Community Consortium (CCC) Vice Chair Elizabeth Bradley (University of Colorado Boulder) and CCC Executive Council member Suresh Venkatasubramanian (University of Utah). Algorithmic bias can be insidious, making it all but impossible to pinpoint factors that contribute to discrimination. This is particularly concerning in the context of high-stakes decisions. The new Department of Housing and Urban Development (HUD) guidelines around the use of algorithms to aid in housing decisions are an example of this. This HUD proposal acknowledges the existence of algorithmic bias but would shift much of the burden of proof to demonstrate discriminatory behavior back onto the plaintiffs, using standards for algorithmic […]

The Computing Community Consortium (CCC) recently released the Algorithmic and Economic Perspectives on Fairness workshop report. It is the output of the CCC’s 1.5-day Economics and Fairness visioning workshop that took place in May 2019, in Cambridge, Massachusetts. The workshop was organized by David C. Parkes (Harvard University, CCC Council) and Rakesh Vohra (University of Pennsylvania), with the support of the CCC’s Fairness and Accountability Task Force. It brought together computer science researchers with backgrounds in algorithmic decision-making, machine learning, and data science with policy makers, legal experts, economists, and business leaders to discuss methods to ensure economic fairness in a data-driven world. The report highlights the current trends and uses of algorithmic […]