The Schwartz Reisman Institute’s (SRI) Solutions Stream is composed of parallel and complementing approaches to developing novel and practical solutions to the social, political, and economic challenges posed by advanced technologies.

What does the global landscape of AI standards look like, and can we identify key areas to leverage standards for AI assurance? What would a robust AI certification ecosystem look like, and how can we work towards building it? How might we overcome data access obstacles in healthcare in order to unlock major public benefit to patients and clinicians alike? 

SRI’s team of public policy researchers are investigating the crucial regulatory and legislative challenges of the artificial intelligence era—and proposing solutions for how governments, citizens, and organizations can navigate this uncertain new terrain with appropriate guidelines. SRI’s policy team considers, evaluates, and proposes innovative public policy frameworks that aim to foster technological innovation, harness AI for social good, and protect citizens, societies, and economies from harm.

SRI’s suite of Solutions workshops use design thinking and other innovative tools to move rapidly from problem analysis to idea generation to prototyping, in the process building bridges between academic researchers and stakeholders across industry, government, and civil society to tackle today’s most urgent problems in the social impacts of technology. 

Our Solutions workshops meet the tremendous demand within industry, government, and civil society for innovative, actionable, high value, and globally appealing solutions to the challenge of building safe, responsible, and inclusive AI and other advanced technologies. In our workshops, we collaborate with different partners to tackle pressing issues, test and try methods and tools and measures of success, and build a best-in-class model that takes our work beyond that of traditional research and into the world of deep societal impact.

Overall, our Policy & Solutions Stream aims to move beyond the current conversation that focuses on principles, ethics, and guidelines to develop real solutions. We believe that new models are needed, and these are likely to be models that reimagine the relationship between citizens, government, and the private sector. We aim to generate and evaluate smart, novel, and concrete ideas with attention to the practicalities of implementation, leveraging the expertise of our Institute’s research community and beyond.

• Since June 2021, SRI has partnered with Creative Destruction Lab (CDL) Toronto to provide mentorship and support to start-ups commercializing technologies that enable and expand the responsible use of AI. Through this partnership, ventures in CDL-Toronto’s AI stream gain access to SRI’s thought leadership in the areas of fairness, ethics, regulatory innovation, and Solutions initiatives around data privacy, algorithmic bias, model explainability and justifiability, and model robustness.

• In 2020 and 2021, SRI collaborated with the Rockefeller Foundation and the Center for Advanced Study in the Behavioral Sciences at Stanford University on an initiative entitled “Innovating AI Governance,” exploring novel approaches to evolve legal and regulatory systems to meet the challenges of AI regulation. The outcomes of our Spring 2021 workshop sessions yielded multiple prototypes, including Stanford’s AI Audit Challenge. Explore materials relating to our 2020 symposium with CASBS.

• In March 2021, SRI led a collaborative workshop with MaRS Discovery District and the Toronto Region Board of Trade to explore the risks, value, and feasibility of a proposed data collection tool to facilitate COVID-19 contact tracing and interrogate the use of commercial data for public good.

• In March 2020, SRI led a collaborative workshop with Diabetes Action Canada, which convened stakeholders from government, non-profit health informatics organizations, hospitals, law firms, research outfits, the private sector, and more to brainstorm improving access to and analysis of data stored in Ontario’s health system.