Artificial Intelligence in the Public Sector
Be Ready for a Future in which AI will be the Basis of Decision Making in the Public Sector!
February 18 - 19, 2020 · Ottawa, Ontario
Day One Agenda | Tuesday, 18 February, 2020
8:00 - 9:00 Registration and Continental Breakfast
9:00 - 9:10
Welcome and Opening Remarks from the Chair
John Lark, Co-Founder, Applied AI Canada Inc.
9:10 - 10:00
Laying the Groundwork
Francois Leblanc, Data Scientist, Treasury Board of Canada Secretariat
- Preparing for AI: What to Expect
- Data Science: Decision Support vs Automation
- Getting Your Data House in Order
- Building a Framework for Experimentation
- Focus on Your Business and the Rest Will Follow
10:00 - 10:15 Networking Break
10:15 - 11:15
Machine Learning applied to Cyber Security … This time it’s different?
Major James Lindsay, Chief Architect and Engineer of End Point Security, Department of National Defence
- Is Machine Learning, when applied to cyber security, just a buzzword that is nearing the end of a hype cycle. Or has a fundamental shift in technology occurred that requires the cyber community to rethink how it delivers cyber
- Quick Deep learning overview
- Where is Machine learning currently being used within cyber security
- Potential existing applications of machine learning to cyber security issues
- Geopolitical drivers of AI and Machine learning adoption
11:15 - 12:15
How Standards Bridge the Gap between AI Innovation and Implementation
Keith Jansa, Executive Director, CIO Strategy Council
- Learn about how standards play a critical role in facilitating innovation and addressing the ethical use of artificial intelligence
- Hear about the latest developments in the creation of Canadian standards for the digital space – from data governance to AI and cybersecurity
- Discover partnership and thought leadership that is bridging the divide between public and private sector innovation
- Explore novel use cases modernizing the toolkit for bringing AI products and services to market
- Learn about how Canada is poised to provide an international benchmark for the next generation of AI talent to drive future certification and credentialing programs at the national, regional and international level
12:15 - 1:15 Luncheon Break
1:15 - 2:15
Application of AI to Government Finance and Audit
John Craig, Director, Government & Integration Partnerships, MindBridge Ai
- Financial data is being created exponentially, and current financial management and audit processes are failing to detect errors, omissions and fraud, together referred to as financial anomalies
- Today, only specially trained analysts are able to review and detect financial anomalies, creating a resource bottleneck
- AI allows for the democratization of analytics, allowing all financial managers and auditors to leverage analytics without specialized training
- AI is 10x-30x more effective at detecting financial anomalies than current accounting methods
- AI provides a way for finance officers to detect financial anomalies (fraud and mistakes) before the audit process, and for auditors to more rapidly perform audits, and focus in on risky transactions
2:15 - 3:15
AI in the Public Sector – A source of uncertainty
John Lark, Co-Founder, Applied AI Inc.
The arrival of computers and the Internet changed all aspects of our lives, Artificial Intelligence is similarly swiftly changing our world from predicting products you may want to purchase to analysing medical test
results and predicting.
In response to this pervasive implementation of AI, the Treasury Board Secretariat has developed a Directive on automated decision making that comes into force on April 1, 2020 and which applies to any AI system developed
or procured after April 1, 2020. The objective of the TBS Directive is to ensure that automated decision systems are deployed in the federal government in a manner that reduces risk to Canadians and to federal institutions, and in a way
that leads to more efficient, accurate, consistent, and interpretable decisions.
- The following techniques are specifically identified as related to AI: rules-based systems, regression, predictive analytics, machine learning, deep learning, and neural nets
- The presentation will touch on how to determine whether AI is a good fit for the problem you have or the operation you are thinking of modifying
- There will be a question and answer session at the end to respond to specific areas of interest to conference participants
3:15 - 3:30 Networking Break
3:30 - 4:30
Building GC AI Clusters on Premises and in the Cloud
John Ogilvie, IT Architect, Bifrost Group
- AI clusters require specific "High Performance Computing" IT equipment
- GC users can deploy HPC/AI clusters on premises, in the cloud or at the shared GC HPC centre
- What are the pros and cons of each approach?
- What are the costs and schedules involved?
- What does a 'standard architecture' look like for HPC/AI?
4:30 Closing Remarks from the Chair