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DTSTART:20231105T020000
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UID:calendar.2741.events_uoft_date.0@www.statistics.utoronto.ca
CREATED:20231030T141142Z
DESCRIPTION:\nWhen and Where: \nMonday, November 13, 2023 3:30 pm to 4:30
  pm \n Hybrid \n\nSpeakers \nLuk Arbuckle \n\nDescription: \nThe use of ar
 tificial intelligence (AI) has become increasingly prevalent in various in
 dustries, leading to concerns about its potential impact on privacy and e
 thics, particularly in healthcare. To ensure that AI is trustworthy and o
 perates in an responsible manner, statistics plays an important role in t
 he development of robust and reliable AI models.This presentation will exp
 lore the importance of statistics in building trustworthy AI, including a
 dvanced statistical techniques such as synthetic data generation and conce
 pts such as NLP, LLMs, data wrangling, and ontologies. We will discuss 
 how these techniques can be used to address concerns related to privacy, 
 causality, and accuracy in AI models.Additionally, we will examine the p
 otential of AI in healthcare and how statistics can be used to ensure accu
 rate and safe outcomes. We will also discuss ethical considerations relate
 d to AI, including bias and fairness, and how statistical techniques can
  be used to address these concerns.Please join the event.About Luk Arbuckl
 eAs Chief Methodologist, Luk connects strategy to the safe and responsibl
 e use and sharing of data and AI, providing strategic leadership to clien
 ts and to IQVIA on the methods to get the most from data assets and AI whi
 le aligning stakeholders for successful execution through trustworthy syst
 em design. As an author and contributor to multiple articles, books, and
  guidance, Luk is also heavily involved on the global stage developing in
 ternational standards for data protection and privacy. This puts him in th
 e position to work with senior executives, standards-setting organization
 s, and other industry leaders across the spectrum of data protection and 
 privacy laws and regulations.Luk draws from an extensive background in AI 
 science, data protection and privacy technology, and regulatory investig
 ations, policy development, and research. He is an author of the book Bu
 ilding an Anonymization Pipeline (O’Reilly 2020) and Anonymizing Health Da
 ta (O’Reilly 2013), as well as numerous papers, guidance documents, and
  patents. He is the member of several industry groups, including the Inte
 rnational Organization for Standardization (ISO), the Clinical Research D
 ata Sharing Alliance (CRDSA), and the Synthetic Data Expert Group of the 
 UK’s Financial Conduct Authority (FCA). Overall, Luk’s professional backg
 round reflects a deep understanding of data protection and privacy, analy
 tics, and the legal and ethical frameworks that govern their use. \n\nCon
 tact Information: \n CANSSI \n\nCategories \n Data Science ARESOther Semin
 ars \n\nAudiences \n FacultyGraduate Students
DTSTART;TZID=America/New_York:20231113T153000
DTEND;TZID=America/New_York:20231113T163000
LAST-MODIFIED:20231030T141420Z
SUMMARY:Trustworthy AI: The Role of Statistics in Ensuring Ethical and Accu
 rate AI
URL;TYPE=URI:https://www.statistics.utoronto.ca/events/trustworthy-ai-role-
 statistics-ensuring-ethical-and-accurate-ai
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