Amplify scientific discovery with artificial intelligence

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Technological innovations are penetrating all areas of science, making predominantly human activities a principal bottleneck in scientific progress while also making scientific advancement more subject to error and harder to reproduce. This is an area where a new generation of artificial intelligence (AI) systems can radically transform the practice of scientific discovery. Such systems are showing an increasing ability to automate scientific data analysis and discovery processes, can search systematically and correctly through hypothesis spaces to ensure best results, can autonomously discover complex patterns in data, and can reliably apply small-scale scientific processes consistently and transparently so that they can be easily reproduced. We discuss these advances and the steps that could help promote their development and deployment.

Related Research Areas:

Future Web
Lead Professor: Jim Hendler
Description: Since its inception the World Wide Web has changed the ways people work, play, communicate, collaborate, and educate. There is, however, a growing realization among researchers across a number of disciplines that without new research aimed at understanding the current, evolving and potential Web, we may be missing or delaying opportunities for new and revolutionary capabilities. To model the Web, it is necessary to understand the architectural principles that have provided for its growth. Looking into the future, to be sure that it supports the basic social values of trustworthiness, personal control over information, and respect for social boundaries, a research agenda must be pursued that targets the Web and its use as a primary focus of attention. This research requires powerful scientific and mathematical techniques from many disciplines to explore the modeling of the Web from network- and information- centric views.