FITC Toronto 2020

2020-04-19 00:00:00 2020-04-22 00:00:00 America/Toronto FITC Toronto 2020 FITC Toronto is a three-day professional celebration of the best the world has to offer in design, web development, media and innovation in creative technologies. Toronto FITC EST Toronto


AI and machine learning are dramatically changing how users interact with digital systems – but how are designers and product leaders adapting their practices in order to create solutions that best work with these technologies and create meaningful user experiences?

This presentation will introduce participants to core principles and methods to consider when working with these emerging technologies. Adapting methods from the field of human-centered design, this hands-on session will empower the audience with practical tools that they can use to transform how they integrate AI and machine learning into digital products, services and platforms. Participants will get the opportunity to put AI ideation and validation tools into practice with several interactive exercises.


Introduce participants to a new way of approaching the use of AI and machine learning that bring a more human-centered lens to solving complex problems.

Target Audience

UX Designers, Product Managers/Directors, Product Designers, Data Scientists & Data Engineers

Assumed Audience Knowledge

No specific technical knowledge is assumed

Five Things Audience Members Will Learn

  1. Just as the first generation of mobile designers created scaled versions of desktop sites, only to learn that the needs of mobile users are fundamentally different – we’re at an inflection point with respect to AI and machine learning
  2. AI and machine learning will over the next 1-2 years become core tools that all digital products, services and platforms will be expected to leverage
  3. An introduction to a few AI-specific design tools, including the confusion matrix, to better understand user impacts in the case of error states
  4. Gain an appreciation of the ethical impacts of using AI through the lens of data bias
  5. Be able to understand design patterns and use cases for AI products, services, and platforms