With the growing use of voice assistants when seeking information, researchers conducted a study on their reliability to provide answers to health-related questions. https://t.co/rFnUl4R4MY

.@StanfordMed's Sonoo Thadaney Israni says "human-prioritized healthcare AI" means a commitment to justice, equity, diversity, and inclusion in AI development. Join her and other experts at the AI+HEALTH conference on Dec 8-9: https://t.co/hpwbcNToVK @StanfordCME @StanfordAIMI

Congratulations to Daniel Schwartz, Dean of @StanfordEd, who recently received the prestigious Klaus J. Jacobs Research Prize (@Foundation_JF) for his scientific achievements, including a teachable agent that helps children learn by teaching. https://t.co/8C7LUPK8Mx

What if we leverage our current understanding of brain circuits to explore new ways of building better AI systems? A review paper on the architectures of neuronal circuits suggests opportunities for AI to learn from neuroscience. https://t.co/eudgUPkvhn

Using a simulation, researchers studied how embodiment influences the evolution of AI. “To our knowledge, this is the first simulation to show that what you learn within a lifetime can be sped up just by changing your morphology," says HAI's @SuryaGanguli. https://t.co/qsBfKaxnmR

Will the future of the internet be voice? Stanford researchers start exploring how we can have an open #WorldWideVoiceWeb. Watch this workshop organized by @StanfordOVAL, HAI Faculty Affiliate @MonicaSLam, and Associate Directors @landay and @chrmanning: https://t.co/HKFH1WtWQD

As of 2021, there are nearly 4 billion social media users worldwide, with each person averaging 145 minutes of social media use per day. With social media's impact on mental health, how can we mitigate the risks and promote wellbeing? https://t.co/P8MWwhKUWI

At this year's fall conference, scholar @rajiinio discussed her proposal for enabling and supporting third-party auditor access to improve accountability in AI decision-making systems. https://t.co/zB9q2eR5gG

Help shape the future of technology education at Stanford! @StanfordEthics and @StanfordHAI's Embedded EthiCS Fellowship is a collaborative program that embeds the teaching of ethics directly into Stanford’s computer science curriculum. Apply by Dec 8: https://t.co/n5y3x3Kmij

Experts have published a set of AI governance proposals, including a black box for autonomous systems. “This approach would help assess the risks in advance and create an audit trail to understand failures. The main goal is to create more accountability." https://t.co/3vyxuPMOtm

Interested in machine learning, statistics, and public policy? Apply now for Stanford RegLab's postdoctoral fellowship, which involves a high-impact collaboration with the IRS to build a more effective and equitable tax system. Applications close Nov 28: https://t.co/AblHsAy6MZ

“As voice assistants become more ubiquitous, we need to know that they are reliable sources of information – especially when it comes to important public health matters,” says Grace Hong, a social science researcher at @StanfordMed. https://t.co/m5KXHhI8N7

.@Stanford scholars are working to develop solutions to bridge the gap between virtual and augmented reality technologies using expertise in optics and artificial intelligence. https://t.co/fbiV2j7F0n

Early this year, Congress enacted a task force to study and plan the creation of a National Research Cloud. To help inform their work, a multidisciplinary team of Stanford researchers studied its feasibility & design as part of a 10-month policy practicum: https://t.co/DxQGEN7fQy

Congratulations to HAI Junior Faculty Fellow @JEichstaedt for receiving @IPPAnet's Early Career Researcher Award! An incredible recognition for his outstanding contributions to positive psychology. https://t.co/4Jl33iBOiU

Exoskeleton devices can speed up our walking or make running easier. But what makes them effective? Here HAI Faculty Affiliate @StevenHCollins presents findings from new research that demonstrates the importance of training: https://t.co/bd8676s2rh

Drawing on their previous work with quantitative image analysis for predicting lung cancer prognosis, HAI faculty member Olivier Gevaert and his team found that a similar approach plus data fusion can be used to better triage Covid-19 patients. https://t.co/M1Tf2MpEmP