Andrew Beam, PhD is an assistant professor in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health, with secondary appointments in the Department of Biomedical Informatics at Harvard Medical School and the Department of Newborn Medicine at Brigham and Women's Hospital. His research develops and applies machine-learning methods to extract meaningful insights from clinical and biological datasets, and he is the recipient of a Pioneer Award from the Robert Wood Johnson Foundation for his work on medical artificial intelligence. Previously he was a Senior Fellow at Flagship Pioneering and the founding head of machine learning at Generate Biosciences, Inc., a Flagship-backed venture that seeks to use machine learning to improve our ability to engineer proteins.
Welcome to our April 2021 monthly digest where you can catch up with any AIhub stories you may have missed, get the low-down on recent conferences and events, and much more. In this edition we cover a diverse range of topics including AI ethics, education, music, GPT-Neo, and Westworld. Marija Slavkovik wrote this very interesting retrospective on the AAAI symposium on implementing AI ethics. The aim of the symposium was to "facilitate a deeper discussion on how intelligence, agency, and ethics may intermingle in organizations and in software implementations." Another ethics conference on the horizon is the AAAI/ACM conference on artificial intelligence, ethics, and society, scheduled for 19-21 May.
Singing along to the ABC's is one of the first lessons we get as kids (whether or not you stick to the original or new-fangled version). Digital creative studio Hello Monday, in collaboration with the American Society for Deaf Children, wants to address this through its new online game, Fingerspelling.xyz. Using machine learning, the game hopes to provide families with the building blocks of a signed language. "We created this fingerspelling tool with Hello Monday to help parents support their child's mastery of sign language, and so parents can share the joy of communicating and connecting with their deaf child," said Cheri Dowling, director of outreach and programs for the American Society for Deaf Children. The game is a free, browser-based app accessible to anyone with a computer and webcam.
Sticks and stones may break my bones, but words will never hurt me. This was a mantra I picked up on the playground at elementary school--something I repeated over and over again anytime I came face to face with racism. It was a coping mechanism meant to guard my heart from the cacophony of discriminatory comments that shaped me as a young Korean American girl growing up in predominantly white spaces. But now that I'm well into adulthood, I think about the girls of color who are also being taught to pretend that words don't hurt--and the people this way of thinking actually protects. It's hard to escape the unrelenting consequences of racism: In the past year alone, we lost Breonna Taylor, George Floyd, Ahmaud Arbery, and the six women of Asian descent murdered in Atlanta (Xiaojie "Emily" Tan, Daoyou Feng, Suncha Kim, Yong Ae Yue, Soon Chung Park, Hyun Jung Grant) at the hands of this insidious disease--and those are just the names that were in the headlines. If we don't acknowledge ...
Should you follow the information on artificial intelligence, you will discover two diverging threads. The press and theatre often portray AI using human capacities, mass unemployment, and also a potential robot apocalypse. Scientific conventions, on the other hand, talk progress toward artificial general intelligence when acknowledging that present AI is feeble and not capable of lots of the fundamental elements of the human mind. But no matter where they stand compared to human intellect, now's AI algorithms have become a defining element for several businesses, such as healthcare, finance, production, transport, and a lot more. And quite soon"no area of human endeavor will Stay independent of artificial intelligence," as Harvard Business School professors Marco Iansiti and Karim Lakhani describe in their publication Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World.
This paper provides a roadmap that explores the question of how to imbue learning agents with the ability to understand and generate contextually relevant natural language in service of achieving a goal. We hypothesize that two key components in creating such agents are interactivity and environment grounding, shown to be vital parts of language learning in humans, and posit that interactive narratives should be the environments of choice for such training these agents. These games are simulations in which an agent interacts with the world through natural language -- "perceiving", "acting upon", and "talking to" the world using textual descriptions, commands, and dialogue -- and as such exist at the intersection of natural language processing, storytelling, and sequential decision making. We discuss the unique challenges a text games' puzzle-like structure combined with natural language state-and-action spaces provides: knowledge representation, commonsense reasoning, and exploration. Beyond the challenges described so far, progress in the realm of interactive narratives can be applied in adjacent problem domains. These applications provide interesting challenges of their own as well as extensions to those discussed so far. We describe three of them in detail: (1) evaluating AI system's commonsense understanding by automatically creating interactive narratives; (2) adapting abstract text-based policies to include other modalities such as vision; and (3) enabling multi-agent and human-AI collaboration in shared, situated worlds.
USING A computer used to mean bashing away at a keyboard. Then it meant tapping on a touchscreen. Increasingly, it means simply speaking. Over 100m devices powered by Alexa, Amazon's voice assistant, rest on the world's shelves. Apple's offering, Siri, processes 25bn requests a month. By 2025 the market for such technology could be worth more than $27bn.
Surgical training in medical school residency programs has followed the apprenticeship model. The learning and assessment process is inherently subjective and time-consuming. Thus, there is a need for objective methods to assess surgical skills. Here, we use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to systematically survey the literature on the use of Deep Neural Networks for automated and objective surgical skill assessment, with a focus on kinematic data as putative markers of surgical competency. There is considerable recent interest in deep neural networks (DNN) due to the availability of powerful algorithms, multiple datasets, some of which are publicly available, as well as efficient computational hardware to train and host them. We have reviewed 530 papers, of which we selected 25 for this systematic review. Based on this review, we concluded that DNNs are powerful tools for automated, objective surgical skill assessment using both kinematic and video data. The field would benefit from large, publicly available, annotated datasets that are representative of the surgical trainee and expert demographics and multimodal data beyond kinematics and videos.
Colby College is a private liberal arts school located in southern Maine. You can take classes in art history, chemistry, music, all the staples, and now the school is adding artificial intelligence to the list. Colby is among the first liberal arts colleges to create an artificial intelligence institute to teach students about AI and machine learning through the lenses of subjects like history, gender studies and biology. The college received a $30 million gift from a former student to set up its new institute. This, of course, comes as the world is grappling with ethics and AI and how to build a moral foundation into algorithms.