Interpretable and Explainable AI and Machine Learning

TheBoard on Mathematical Sciences and Analytics (BMSA)of the National Academies of Sciences, Engineering, and Medicine leads activities in the mathematical sciences at the National Academies in topic areas including from applied mathematics, scientific computing, and risk analysis.TheCommittee on Applied and Theoretical Statistics (CATS)of the National Academies of Sciences, Engineering, and medicine organizes studies and events focusing on the statistical sciences, big data and data science, statistical education, the use of statistics, and issues affecting the field. CATS occupies a pivotal position in the statistical community, providing expertise in methodology and policy formation.

NASEM Math and Statistics

Join us to explore the latest developments in artificial intelligence and machine learning across cognitive science, healthcare, and policy.

Advances in artificial intelligence could improve how we make decisions for a broad array of applications, such as healthcare or urban planning. However, practitioners need to understand and trust how complex machine learning systems make choices before these new tools can be more widely adopted.Please join the National Academies for a symposium on Interpretable and Explainable AI and Machine Learning on Tuesday, June 21 from 1-4pm ET. During the symposium, expert speakers will discuss the possibilities and challenges of interpretable machine learning across a variety of applications, including cognitive science, healthcare, and policy. The symposium will conclude with a moderated panel on the future landscape of interpretable and ethical machine learning.Featured Talks:<ul><li>Dr. Been Kim (Google Brain) will explore how to translate artificial intelligence for humans. </li><li>Dr. Gari Clifford (Emory University) will discuss the use of interpretable machine learning in healthcare and its impact on bias and ethics. </li><li>Dr. Christian Lebiere (Carnegie Mellon University) will present on cognitive models at the interface of humans and machines. </li><li>Patrick Hall (bnh.ai and The George Washington University) will share proposed guidelines for the responsible use of explainable machine learning. </li></ul>Download the full agenda for the event on the <a href="https://www.nationalacademies.org/event/06-21-2022/interpretable-and-explainable-ai-and-machine-learning" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">event page</a>.The event will be livestreamed and open to a limited number of in-person participants in Washington, DC (see below for details).This symposium is organized by the National Academies&#x27; Committee on Applied and Theoretical Statistics. Learn more about the committee and sign up for updates on <a href="https://www.nationalacademies.org/our-work/committee-on-applied-and-theoretical-statistics" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">our website</a>.<h3>WEBCAST PARTICIPANT INSTRUCTIONS</h3>Watch the webcast and submit questions for our speakers on the <a href="https://www.nationalacademies.org/event/06-21-2022/interpretable-and-explainable-ai-and-machine-learning" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">event page</a>.The direct link to the livestream is: <a href="https://livestream.com/accounts/7036396/events/10440911" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer"></a><a href="https://livestream.com/accounts/7036396/events/10388725" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">https://livestream.com/accounts/7036396/events/10388725</a>If you register on this page, you&#x27;ll also receive login information via email before the event.<h3>IN-PERSON PARTICIPANT INSTRUCTIONS</h3>This meeting will be held at the National Academies Keck Building at 500 5th St NW, Washington, DC 20001 in Room 100.All in-person participants must pre-register on this page in advance of the event, by no later than June 20, 2022 at 12pm ET. If we reach capacity for in-person attendance, you will have the opportunity to sign up for the waitlist and/or register to participate remotely.Please note that all visitors to National Academies facilities must be up to date with their vaccinations against COVID-19 per <a href="https://www.cdc.gov/coronavirus/2019-ncov/vaccines/stay-up-to-date.html" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">CDC guidance</a>. Visitors may choose to wear a mask but are not required to do so.Upon entry to the building, visitors must show a photo ID and an official COVID-19 Vaccination Record Card (or a digital photo of the card) to the security staff. We recommend arriving ~15 minutes early to allow time for this check. Please note that visitor vaccination information will not be recorded or stored by the National Academies; the information will simply be verified to allow access to the facility. Anyone who fails to present a vaccination card (or its copy) will not be allowed access to our facility; no exemptions or exceptions will be accommodated.For the most up-to-date information on visiting our facilities, please check our <a href="https://www.nationalacademies.org/about/operating-status" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">current operating status</a>.<h3></h3>

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Interpretable and Explainable AI and Machine Learning

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