Day One: Tuesday, February 23, 2021
10:30 EST15 min
10:45 EST45 min
- 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 EST45 min
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 EST45 min
- 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 EST45 min
13:45 EST45 min
- 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 EST60 min
- 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 EST60 min
- 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
Day Two: Wednesday, February 24, 2021
10:30 EST15 min
10:45 EST60 min
11:45 EST60 min
- 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 EST45 min
13:30 EST60 min
- 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 EST60 min
- 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 EST60 min
- 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.