Day One: Tuesday, February 23, 2021
10:30 EST
15 minWelcome and Opening Remarks from the Chair
10:45 EST
45 minDiscussing the Path to Operations - Leveraging AI in Critical Infrastructure Sectors
- Improving mission effectiveness is the end goal
- Understanding your sector scope and interdependencies
- Maintain vigilance of emerging concepts and technologies impacting your sector
- Trust – how to show it and earn it?
- Have a solid organizational foundation to build on
11:30 EST
45 minFrom Artificial to Real: AI Stories from the Public Sector and the Fight Against COVID-19
Even before the pandemic, governments around the world face more challenges than ever: Providing citizens with better benefits and services at lower cost, while combating fraud and improper payments; improving public safety and national security in the face of new threats; delivering better health care while controlling skyrocketing health care costs; and the list goes on.
At the same time, government entities produce, collect and store an unprecedented amount of increasingly diverse data that could be used to help solve these problems. However, traditional approaches to gleaning insights from data are no longer sufficient given the volume, velocity and variety that modern governments must manage. It is becoming increasingly critical for governments to find new ways to transform data into actionable information – new ways that include techniques like artificial intelligence (AI) and machine learning.
In this session, we will briefly review government domain areas with the largest potential for benefit from AI, and then spend most of our time talking about stories from around the world in which these techniques have made a difference in the public sector. We’ll also highlight the many ways AI has helped the public sector on the front lines of the fight against COVID-19.
12:15 EST
45 minEnterprise Business Intelligence and Data Analytics Platform for Enabling AI and Big Data
Mohammad Ghodratigohar, Data Scientist & AI Cloud Solution, Transport Canada
- Problems, opportunities and strategies for data and analytics capabilities
- Data and analytics program transformation
- Building a modern Enterprise Data and Analytics Ecosystem forEnabling AI and big data
- Use Case Analytics & prioritization
- POCs and Use cases of AI
13:00 EST
45 minBreak
13:45 EST
45 minAdvanced Analytics and AI in the Government: Lessons from the Trenches
Yvan Gauthier, Director of Data Science, Department of National Defence
- What is really new about analytics and AI
- Aspects to consider when establishing a new data science team
- How to select the right use cases and demonstrate value early on
- Challenges (technical, analytical, political, ethical and data-related) involved in conducting advanced analytics and AI in a government or military setting
- Lessons learned
14:30 EST
60 minLeading in AI through Human to Machine Interactions
- Human to machine interactions
- What does future leadership look like?
- AI that is trusted and interpretable
- Preparing yourself and your team for human to machine interactions
- AI systems built to scale
15:30 EST
60 minThe Global Cooperation Imperative in AI Standards Setting
- Fostering global cooperation in AI: What does it take?
- Examine the intersection between the public and private sector
- Shaping marketplace rules and policy-oriented standards that govern our data and AI applications
16:30 EST
Closing Remarks from the Chair
Day Two: Wednesday, February 24, 2021
10:30 EST
15 minWelcome and Opening Remarks from the Chair
10:45 EST
60 min11:45 EST
60 minA Central Banking Perspective on Applications of Artificial Intelligence
- We are Canada’s central bank. How we apply the latest advances in artificial intelligence at the Bank of Canada to enhance the decision-making process impacting millions of people.
- Overview of the structure of data science at the Bank, strategic direction and in-demand skills.
- What are some of our latest innovative projects that benefit from AI/ML
12:45 EST
45 minBreak
13:30 EST
60 minArtificial Intelligence Use at Statistics Canada
Sevgui Erman, Chief Data Scientist & Director, Data Science Division, Statistics Canada
- Statistics Canada uses Machine Learning (ML)/ Artificial Intelligence (AI) methods for integration of alternative data sources in official statistics.
- ML/AI methods and tools allow the agency to deliver faster and timelier products to Canadians, reducing response burden on households and businesses, producing more granular and accurate statistics, enhancing privacy and confidentiality, and much more.
- Within the last two years, Statistics Canada has developed experience in the AI/ML space, and built advanced modelling expertise in image processing, natural language processing, integration of cloud tools, privacy preserving techniques, traceability methods, web information retrieval, news analytics, data anomalies and error detection, predictive analytics, and automation.
- Hear about some of the agency’s innovative projects that are fueled by AI.
14:30 EST
60 minBias and Fairness in AI
Somaieh Nikpoor, Research Advisor, Labour Program, Government of Canada
- What is an algorithmic bias and how it is introduced in the machine learning pipeline.
- There are multiple sources for bias, it is essential to understand them when designing AI systems.
- What it means for an algorithm to be fair and how to measure fairness
15:30 EST
60 minAugmenting Human’s Judgment with AI and Combating Fraud
- During times of crisis such as with COVID-19, we have witnessed how critical programs to support citizens and their businesses have become to help them navigate periods of economic uncertainty
- During this presentation, we will discuss how artificial intelligence can undertake quick investigations to identify insights and help increase situational awareness, identify risk/fraud, and help assess the impact such crises have on government, its citizens, and the economy.
16:30 EST
Closing Remarks from the Chair