• 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

• 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 security defence
• 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

• 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

• 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

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 analyzing 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

• 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?