Statistical Sciences ARES: Luk Arbuckle

Join us at the Statistical Sciences Applied Research and Education Seminar (ARES) with

Luk Arbuckle

Chief Methodologist, Privacy Analytics (an IQVIA company)
Director of AI Science at IQVIA

Free Hybrid (In-person/Online) Event | Registration Required

Talk Title

Trustworthy AI: The Role of Statistics in Ensuring Ethical and Accurate AI

Abstract

The use of artificial intelligence (AI) has become increasingly prevalent in various industries, leading to concerns about its potential impact on privacy and ethics, particularly in healthcare. To ensure that AI is trustworthy and operates in an responsible manner, statistics plays an important role in the development of robust and reliable AI models.

This presentation will explore the importance of statistics in building trustworthy AI, including advanced statistical techniques such as synthetic data generation and concepts 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 potential of AI in healthcare and how statistics can be used to ensure accurate and safe outcomes. We will also discuss ethical considerations related to AI, including bias and fairness, and how statistical techniques can be used to address these concerns.

Speaker Profile

As Chief Methodologist, Luk connects strategy to the safe and responsible use and sharing of data and AI, providing strategic leadership to clients and to IQVIA on the methods to get the most from data assets and AI while aligning stakeholders for successful execution through trustworthy system design. As an author and contributor to multiple articles, books, and guidance, Luk is also heavily involved on the global stage developing international standards for data protection and privacy. This puts him in the position to work with senior executives, standards-setting organizations, 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 investigations, policy development, and research. He is an author of the book Building an Anonymization Pipeline (O’Reilly 2020) and Anonymizing Health Data (O’Reilly 2013), as well as numerous papers, guidance documents, and patents. He is the member of several industry groups, including the International Organization for Standardization (ISO), the Clinical Research Data Sharing Alliance (CRDSA), and the Synthetic Data Expert Group of the UK’s Financial Conduct Authority (FCA). Overall, Luk’s professional background reflects a deep understanding of data protection and privacy, analytics, and the legal and ethical frameworks that govern their use.


The event is finished.

Local Time

  • Timezone: America/New_York
  • Date: Nov 13 2023
  • Time: 3:30 pm - 4:30 pm
U of T - Rooms 9014 & 9016

Location

U of T - Rooms 9014 & 9016
700 University Avenue, Toronto, ON
CANSSI Ontario

Organizer

CANSSI Ontario
Email
esther.berzunza@utoronto.ca
Website
https://canssiontario.utoronto.ca

Moderator

Rafal Kulik
Rafal Kulik
Website
https://www.uottawa.ca/faculty-science/professors/rafal-kulik

Professor, Department of Mathematics and Statistics, University of Ottawa