AI Futures Policy Lab:


In January 2018, CIFAR and the Brookfield Institute for Innovation + Entrepreneurship (BII+E) formed a partnership to design and host five AI Futures Policy Labs aimed to generate greater awareness of the longterm implications of AI and build capacity to develop agile AI policy in Canada. The first lab took place on June 25, 2018 in Toronto, with participation from 18 emerging policy leaders.

On September 20, 2018, CIFAR and BII+E hosted the second AI Futures Policy Lab in Edmonton, Alberta. This event brought together 23 emerging policy leaders with the aim to:

  • Build capacity of future public service leaders to understand the policy implications of AI and respond appropriately;
  • Provide policymakers with a direct line of sight into the AI sector: the myths and hype, the evolving state of technological advances, and potential applications;
  • Contribute to early government responses to emerging AI technologies.

To achieve these aims, this lab was designed to raise awareness of the opportunities and challenges associated with current AI capabilities and applications, encourage critical thinking around potential future scenarios, and facilitate the development of policy recommendations. Feedback from the AI Futures Policy Lab Pilot in Toronto was integrated into the design of the Edmonton lab’s agenda and content. Rather than focusing on just one potential future scenario throughout the day, participants analyzed a pair of case studies associated with a specific policy domain (i.e. housing, justice, education, and health), one current state example and one potential future scenario. At the end of the day, groups produced and presented policy recommendations related to the two case studies they analyzed throughout the afternoon. The agenda developed for the day is provided in appendix A.

Case Study Policy Domains

Prior to the lab, four sets of case studies were developed. Each set was associated with a specific domain: housing, legal, education, or health. Participants were organized into groups of 4-5 and assigned a domain.


AI is impacting the housing sector in multiple ways, from smart-home devices like Nest to intelligent tools that help to curb energy use, and services that even act as the middle-man between landlords and tenants. Advancements in this domain afford residents with potential benefits, but also create challenges regarding privacy and safety in a domestic environment. Within this domain, participants examined Naborly (appendix B), a tenant screening application that generates risk scores to help landlords make smarter letting decisions. They were also presented with a scenario that imagined a future in which a smart-home contractor approached the local municipal government with the proposal of building affordable housing in exchange for the collection of resident data (appendix C).


The legal sector is being impacted by recent developments in AI and machine learning capabilities that have enabled applications to automate legal research, due diligence processes, contract review and management practices, and help to predict legal outcomes. Participants within this domain were given the chance to explore the policy impacts of ROSS intelligence (appendix D), an artificially intelligent legal research tool that applies natural language processing to increase lawyer’s ability to identify relevant information. This group was then presented with a future scenario in which legal decisions for minor infractions were made by an artificially intelligent agent (appendix E).


There is vast potential for AI to transform education in ways that make learning more accessible, provide personalized curriculum, and support educators in delivering content. Participants in this group analyzed Nestor (appendix F), an artificially intelligence class assistant that uses machine learning algorithms and advanced facial recognition to analyze the attention of students listening to online lectures. This group then examined a future scenario in which intelligent devices and toys are integrated within classrooms to help monitor children’s ability to learn, track their progress, and optimize their experiences (appendix G).


Advancements in AI capabilities hold enormous opportunities for delivering more efficient health care services in areas such as diagnosis, health monitoring, and treatments. However, this also raises challenges related to patient privacy and discrimination. Participants within this group explored InnerEye (appendix H), a research initiative led by Microsoft that applies computer vision and machine learning algorithms to automatically analyze three-dimensional medical CT (computer tomography) and MR (magnetic resonance) images to identify tumours. The group then explored a future scenario in which an individual’s health was constantly monitored by a set of ubiquitous devices and applications that tracked variables such as activity, sleep, speech patterns, expressions, movements, and pulse (appendix I) to proactively diagnose conditions and recommend treatment.


Read the full summary here

In partnership with the Brookfield Institute for Innovation + Entrepreneurship (BII+E), this project has been designed to help emerging policy leaders across Canada understand and respond to the opportunities and challenges that accompany the rapid development of artificial intelligence.