Speaker "Ramy Nassar" Details Back



Design Thinking for AI & Machine Learning: Methods and practices for human-centred AI solutions


Design Thinking offers a repeatable and scalable methodology for ensuring that products, services, and platforms create meaningful value for end users. This workshop introduces Design Thinking through the lens of AI and machine learning in order to teach frameworks, tools, and best practices for creating more impactful AI-driven solutions. The program begins with an overview of AI and machine learning targeted at professionals charged with leveraging these technologies. Participants can expect to walk away with a comprehensive understanding of how AI and machine learning work and a wide range of use cases including: recommendation engines, experience personalization, predictive analytics, conversational/voice interfaces, and process automation. From there, the workshop explores the fundamentals of Design Thinking - adapted to AI and machine learning. Participants will gain hands-on experience with unique methods and exercises that can be used to ensure that products & services meet the needs of end users and customers. Some of these methods include: • AI-specific ideation methods • User flow state design • Confusion matrices • Prototyping and validation The final component of the workshop will be an introduction to Responsible AI and present a structured approach to evaluate ethical consideration. Data bias, error state recovery, and the AI Ethics canvas are all presented.
Who is this presentation for?
Product designers, UX designers, digital strategists, data scientists, software engineers, product managers/leads.
Prerequisite knowledge:
None assumed
What you'll learn?
Upon completion of this program, participants should expect to: - Have confidence in speaking about AI and many of the subtopics within this space (machine learning, deep learning, narrow vs. general AI) - Be able to breakdown some common myths and misunderstandings about what AI as well as the types of problems that are most suited to be solved with AI - Gain an understanding about AI tools are applied to a wide range of use cases as well as how automation vs. augmentation scenarios differ in these applications - Understand AI design tools, such as a confusion matrix, and how to apply these methods in evaluating predictive AI or technology - Be comfortable in working through a structured approach to evaluating new technologies and what implications the technology can have to people, processes and an organization as a whole - Have an appreciation for the ethical considerations associated with the use of any data-driven technologies, such as AI & ML - Understand the impact of data bias on machine learning algorithms and other tools / technologies - Be comfortable applying a basic AI ethics framework to a scenario or use case


Ramy is a Canadian engineer, designer and maker. As the former Head of Innovation for Mattel and Managing Director for Architech, he has led teams in the creation of disruptive products, services & platforms across retail, CPG and financial services. He currently leads a boutique digital strategy consultancy called 1000 Days Out, focused on corporate innovation and proposition design. With a background in computer engineering and Design Thinking, Ramy has straddled technical, design, and business-oriented roles, for clients including Cadillac Fairview, Apple, Air Canada, Facebook, New Balance, Rogers and CIBC. Ramy is a regular speaker at international events including World Usability Congress, IxDA, Machine Learning Exchange, AI Business Summit and Mobile World Congress. Ramy teaches Design Thinking at McMaster University as well as a range of topics at Saint Mary’s University, Ryerson, and the University of Toronto.