The Social and Ethical Responsibilities of Computing (SERC) is bringing together social scientists and humanists with engineers, computer scientists, and computing-related faculty for a daylong symposium at MIT to address the challenges and opportunities that have emerged with the broad applicability of computing in many aspects of our society. Join us for a series of panels and sessions featuring a distinguished lineup of speakers. We will also bring the vision and activities of SERC to the forefront by showcasing the work that is already taking place, and highlighting the faculty, postdocs, and students that are advancing SERC-related education and research across disciplines at MIT. Tuesday, April 18, 2023 7:00 am-5:30 pm (registration opens at 7:00 am; program begins at 8:00 am; reception from 4:30-5:30 pm) MIT Building E14, 6th floor (Media Lab) 75 Amherst Street Cambridge, MA 02139 View map Learn more about getting to MIT, building access, and where to park. Algorithms are now impacting every aspect of our lives, whether in the context of social media, online commerce, automated tasks, and now a wider range of interactions with the advent of large language models. There is little doubt that more is to come.

ECOLOGICAL INFORMATICS FOR SUSTAINABLE DEVELOPMENT GOALS Environmental Policy Analytics Scalable environmental start-up initiatives Communicating Science and Informing decision Futurecasting research and education in Ecological Informatics We envisage the three themes to be both independent as well as interdependent. Note: 1- The topics listed under each theme are only indicative. The organizers will be glad to accommodate relevant topics that are not indicated at present. In addition to expanding the scope by adding new themes, we look forward to building upon and take forward theme(s) initiated in Jena. Responsibilities of session chair: As a proposer of an accepted ICEI 2020 1 session, you will become the session chair.

A fast performing, dictionary-based tagger [1] constitutes EXTRACT's core. The tagger relies on a set of dictionaries that map biological names to corresponding terms in biological ontologies, or to pertinent records in public biological databases.