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X-WR-CALNAME:Harvard Law School - Events
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BEGIN:VEVENT
UID:20260128T2331Z-1769643084.8348-EO-738651-1@10.73.0.4
STATUS:CONFIRMED
DTSTAMP:20260515T214013Z
CREATED:20260128T175705Z
LAST-MODIFIED:20260324T145533Z
DTSTART;TZID=America/New_York:20260409T122000
DTEND;TZID=America/New_York:20260409T132000
SUMMARY: HLS Beyond and BKC present: Evidence-Based AI Policy
DESCRIPTION: In this third and final session of the TechReg in AI series wi
 th Professor Alan Raul\, we consider what constitutes an “AI incident” for 
 policy and governance purposes. Who is monitoring and reporting them? How d
 oes the concept account for foreseeable harms\, near misses\, and distincti
 ons between systems performing as intended versus those that are malfunctio
 ning\, maliciously compromised\, or acting in novel or unexpected manners? 
 As we dig into today’s incident-monitoring ecosystem\, we’ll discuss releva
 nt challenges such as underreporting\, selection bias\, confidentiality\, r
 eproducibility and how to translate scattered\, anecdotal events into meani
 ngful evidence for risk management and harm prevention.
X-ALT-DESC;FMTTYPE=text/html: <div class="x_ms-outlook-mobile-reference-mes
 sage x_skipProofing"><span data-olk-copy-source="MessageBody">In this third
  and final session of the <i>TechReg in AI</i> series with <a title="https:
 //hls.harvard.edu/faculty/alan-raul/" href="https://hls.harvard.edu/faculty
 /alan-raul/" target="_blank" rel="noopener noreferrer" data-outlook-id="b7e
 15066-5974-4ae0-b617-a9b4963992df" data-auth="NotApplicable" data-linkindex
 ="0">Professor Alan Rau</a>l (see <a title="https://hls.harvard.edu/?p=7386
 43" href="https://hls.harvard.edu/?p=738643" target="_blank" rel="noopener 
 noreferrer" data-outlook-id="958eacc8-a652-4b23-8058-a73740b89d91" data-aut
 h="NotApplicable" data-linkindex="1">February 19th</a> and <a title="https:
 //hls.harvard.edu/?p=738645" href="https://hls.harvard.edu/?p=738645" targe
 t="_blank" rel="noopener noreferrer" data-outlook-id="0516571f-4c6b-43be-97
 61-eaa253c30a78" data-auth="NotApplicable" data-linkindex="2">March 12th</a
 ></span> events)\, we consider what constitutes an <a title="https://intern
 ationalaisafetyreport.org/sites/default/files/2026-02/ai-safety-report-2026
 -extended-summary-for-policymakers.pdf" href="https://internationalaisafety
 report.org/sites/default/files/2026-02/ai-safety-report-2026-extended-summa
 ry-for-policymakers.pdf" target="_blank" rel="noopener noreferrer" data-out
 look-id="62bb80b1-1e44-4a4e-981a-9d4f0b9c5762" data-auth="NotApplicable" da
 ta-linkindex="3">“AI incident”</a> for policy and governance purposes. Who 
 is monitoring and reporting them? How does the “incident” concept account f
 or AI systems performing as intended versus those that are malfunctioning\,
  maliciously compromised\, or acting in novel or unexpected manners? And ho
 w are "big” societal\, or systemic\, risks characterized and tracked differ
 ently from individual-level risks? <a title="https://oecd.ai/en/community/s
 ara-rendtorff-smith" href="https://oecd.ai/en/community/sara-rendtorff-smit
 h" target="_blank" rel="noopener noreferrer" data-outlook-id="cd75776c-8733
 -49ad-a846-6393ea13acc1" data-auth="NotApplicable" data-linkindex="4">Sara 
 Rendtorff-Smith</a>\, from the Organization for Economic Cooperation and De
 velopment (OECD)\, will join our session to discuss how her team conceives 
 of and operates the OECD’s AI risk monitor. (Read more at <a title="https:/
 /urldefense.proofpoint.com/v2/url?u=https-3A__oecd.ai_en_incidents-3Fsearch
 -5Fterms-3D-255B-255D-26and-5Fcondition-3Dfalse-26from-5Fdate-3D2020-2D03-2
 D17-26to-5Fdate-3D2026-2D03-2D17-26properties-5Fconfig-3D-257B-2522principl
 es-2522-3A-255B-255D-2C-2522industries-2522-3A-255B-255D-2C-2522harm-5Ftype
 s-2522-3A-255B-2522Other-2522-255D-2C-2522harm-5Flevels-2522-3A-255B-2522AI
 -2520incident-2522-255D-2C-2522harmed-5Fentities-2522-3A-255B-255D-2C-2522b
 usiness-5Ffunctions-2522-3A-255B-255D-2C-2522ai-5Ftasks-2522-3A-255B-255D-2
 C-2522autonomy-5Flevels-2522-3A-255B-255D-2C-2522languages-2522-3A-255B-255
 D-257D-26order-5Fby-3Ddate-26num-5Fresults-3D100&d=DwMFaQ&c=WO-RGvefibhHBZq
 3fL85hQ&r=ObZWbseMOHtoUGvT8OCqRA0iyE6yRs7JZPBE2DejFTs&m=gBEBZFIHSFtSSxxoVDF
 EY1fkgzdWEYKlvuH-GarBunyEx0f1qwqajW6b_8yG-7DL&s=XGFjjdL6MhaXhSbgucyoSbMsj0f
 Au_QCeHGiZM79mck&e=" href="https://urldefense.proofpoint.com/v2/url?u=https
 -3A__oecd.ai_en_incidents-3Fsearch-5Fterms-3D-255B-255D-26and-5Fcondition-3
 Dfalse-26from-5Fdate-3D2020-2D03-2D17-26to-5Fdate-3D2026-2D03-2D17-26proper
 ties-5Fconfig-3D-257B-2522principles-2522-3A-255B-255D-2C-2522industries-25
 22-3A-255B-255D-2C-2522harm-5Ftypes-2522-3A-255B-2522Other-2522-255D-2C-252
 2harm-5Flevels-2522-3A-255B-2522AI-2520incident-2522-255D-2C-2522harmed-5Fe
 ntities-2522-3A-255B-255D-2C-2522business-5Ffunctions-2522-3A-255B-255D-2C-
 2522ai-5Ftasks-2522-3A-255B-255D-2C-2522autonomy-5Flevels-2522-3A-255B-255D
 -2C-2522languages-2522-3A-255B-255D-257D-26order-5Fby-3Ddate-26num-5Fresult
 s-3D100&d=DwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=ObZWbseMOHtoUGvT8OCqRA0iyE6yRs7
 JZPBE2DejFTs&m=gBEBZFIHSFtSSxxoVDFEY1fkgzdWEYKlvuH-GarBunyEx0f1qwqajW6b_8yG
 -7DL&s=XGFjjdL6MhaXhSbgucyoSbMsj0fAu_QCeHGiZM79mck&e=" target="_blank" rel=
 "noreferrer noopener" data-outlook-id="6ea53dd4-a4b2-4eef-a2bc-255aac2a245f
 " data-auth="NotApplicable" data-linkindex="5">https://oecd.ai/en/incidents
 </a>).</div><div class="x_ms-outlook-mobile-reference-message x_skipProofin
 g">Come join the discussion and help us explore today’s incident-monitoring
  ecosystem! We’ll discuss relevant challenges such as underreporting\, ambi
 guous or conflicting definitions\, and how to correlate scattered\, anecdot
 al events into meaningful evidence for policymakers\, risk management and h
 arm prevention.<i> </i> <a href="https://forms.gle/rx3eVfZcvDWRkW3c9">Regis
 tration Required</a>.<em> Lunch will be provided.</em></div>
CATEGORIES:Discussion
LOCATION:Langdell Hall\; 232/233 Langdell
GEO:0;0
ORGANIZER;CN="Emily Rider Neill":MAILTO:eneill@law.harvard.edu
URL;VALUE=URI:https://hls.harvard.edu/events/hls-beyond-and-bkc-present-evi
 dence-based-ai-policy/
ATTACH;FMTTYPE=image/jpeg:https://hls.harvard.edu/wp-content/uploads/2026/01/Raul_Image2.jpg
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TZOFFSETFROM:-0500
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DTSTART:20260308T070000
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