This is a UMass event but I think that it will interest many at Amherst College as well, and relate to several AILA themes: Timnit Gebru UMass event 4. It will be on Zoom, but registration is required (via the link above). A video recording of the event is available here….
Machine Learning In Biomedical Research (feat. Dr. Jason Moore)
December 6, 2021 A recording of this talk can be found here. This TASTE (Talk About Science and Technology Experience) Seminar will feature Dr. Jason Moore, founding Chair of the Department of Computational Biomedicine at Cedars-Sinai Medical Center. He will be joining us for this exciting virtual event examining the expanding opportunities for the use of…
Making Robots Good People
Robots and AIs are increasingly involved in every facet of human life: transportation, warfare, criminal justice, medicine and, of course, social media and communication. And while in some cases they are promised to be better: fairer, more data driven, less prone to emotion, they often mirror back to us our own moral blindspots and biases. Perhaps we need to design AI systems that are not only good at their jobs but are, in a sense, good people – good moral agents. How should we go about doing that?…
Adversarial Intelligence (Feat: Una-May O’Reilly)
What do taxation, cyber networks, software and humans have in common? They each are vulnerable to adversarial conflicts. Taxation faces non-compliance, networks face attacks, software faces malware, and humans – among many vulnerabilities, are susceptible to disinformation. In this talk Dr. O’Reilly will describe work on Artificial Adversarial Intelligence (AAI), employing machine learning and evolutionary algorithms, to support the modeling and discovery of new knowledge of these systems’ adversarial nature….
AI and the Future of Your Mind (feat. Dr. Susan Schneider)
Humans may not be Earth’s most intelligent species for much longer: the world chess, Go, and Jeopardy! champions are now all AIs. Given the rapid pace of progress in AI, many predict that AI could advance to human-level intelligence within the next several decades. From there, it could quickly outpace human intelligence. What do these developments mean for the future of the mind?…
A Symbiotic Future For Machine Learning and the Humanities (feat. Laure Thompson)
Computational methods can help the humanities by making massive cultural heritage collections more explorable and analyzable. Machine learning and statistical methods provide an opportunity to view collections from alien, defamiliarized perspectives that can call into question the boundaries between established categories. But the converse is also true: the humanities have much to offer machine learning. The use of computational methods within humanities scholarship often tests and expands the affordances of these methods. The complexities and idiosyncrasies of humanities collections can improve our understanding of what models learn and how we might direct what they learn….
Towards Building Equitable Language Technologies (feat. Su Lin Blodgett)
Language technologies are now ubiquitous. Yet the benefits of these technologies do not accrue evenly to all people, and they can be harmful; language technologies reproduce stereotypes, prevent speakers of “non-standard” language varieties from participating fully in public discourse, and reinscribe historical patterns of linguistic stigmatization and discrimination. In this talk, I will take a tour through the rapidly emerging body of research examining bias and harm in language technologies….
Using Artificial Intelligence Without Coding (feat. Nirman Dave)
April 14, 2021 Businesses today are being transformed by a “No-Code” approach that enables them to accomplish tasks that previously required deep programming skills, but without writing any code at all. This means that common tasks such as building websites, phone apps, automation scripts, etc. can today be accomplished without any prior programming experience. One…