The Future of AI in Quebec: Bridging Gaps to Drive Innovation, Growth and Social Good

Artificial intelligence (AI) is transforming societies and economies around the world at a rapid pace. However, Quebec risks falling behind in leveraging the opportunities of AI due to several gaps in its ecosystem. In this blog post, I analyze the current limitations around AI development, adoption, and governance in Quebec across the public, private, and academic sectors. Based on this diagnosis, I then provide targeted, actionable recommendations on how Quebec can build understanding, expertise, collaboration, and oversight to unlock the full potential of AI as a force for economic and social good. Read on for insights into the seven key areas requiring intervention and proposed solutions to propel Quebec into a leadership position in the global AI landscape.

Recommendations to address the lack of understanding around AI and its impacts in Quebec:

Public awareness campaigns - The government should launch public awareness campaigns to educate citizens on what AI is, how it works, its benefits as well as potential risks. This will help foster greater public trust and acceptance of AI.

Educational initiatives - Introduce AI education in schools and universities to develop an AI-literate workforce. Offer training programs for government employees working with or regulating AI.

Stakeholder engagement - Facilitate open dialogues between policymakers, companies developing/deploying AI, civil society groups, academics, and other stakeholders to share perspectives and concerns around AI. Working with organizations like the Montreal AI Ethics Institute that specialize in this work can help accelerate the achievement of this goal.

Transparent communication - Require companies to clearly communicate when and how they are using AI, share impact assessments, and allow external audits of AI systems. The government can publish its own assessments of AI projects.

New governance models - Explore novel collaborative governance models for AI, like participatory design and citizen juries/assemblies where the public provides input and oversight over AI policies.

Recommendations for addressing the lack of AI expertise among leaders in Quebec:

Leadership training programs - The government can sponsor executive education programs at universities focused on AI strategy, governance, ethics etc. This will help leaders make informed decisions about AI adoption.

Recruiting incentives - Provide tax credits or other incentives to companies hiring or training AI specialists into leadership/board roles. This helps build internal AI expertise.

Immigrant talent programs - Fast track work visas or permanent residency for experienced AI researchers, engineers, entrepreneurs willing to immigrate. Conduct outreach at global AI conferences.

Advisory councils - Leaders can be supported by multi-stakeholder advisory councils with technical experts providing AI advice and risk assessments before deployment.

Internal upskilling - Companies should invest in comprehensive internal training programs to develop managers' AI fluency. Governments can subsidize costs.

Hands-on learning - Programs that allow leaders to get direct experience with AI systems through lab visits, pilot projects etc. to complement classroom learning.

Public-private partnerships - The government can collaborate with tech companies and universities to co-develop leadership AI talent through courses, mentoring.

Recommendations to provide greater support for AI startups and SMEs in Quebec:

Government funding - Create targeted grants, loans, tax credits to help startups and SMEs afford the costs of developing, validating and deploying AI systems.

Access to resources - Facilitate access to compute resources, data, testing facilities through public-private partnerships between tech players and government.

Regulatory sandboxes - Allow controlled testing of AI innovations in real-world environments without excessive red tape. This de-risks adoption of new technologies.

Business mentoring - Establish programs that connect seasoned executives and entrepreneurs as mentors to early stage AI companies.

Incubators & accelerators - Fund more incubators and accelerators focused on nurturing Quebec’s emerging AI startups through training, networking, business advice.

Shared technology platforms - Develop collaborative shared technology platforms, data repositories, and open-source libraries, which startups/SMEs can build upon.

Export assistance - Provide legal, marketing and technical support to help startups expand internationally and tap new markets.

Investor incentives - Offer tax credits to angel investors and VCs backing early stage Quebec AI startups. This stimulates availability of capital.

Recommendations for increasing collaboration between industry, academia and government for AI development in Quebec:

Joint research projects - Provide funding and incentives for collaborative AI research projects involving companies, universities and government labs. This promotes knowledge sharing.

Personnel exchanges - Implement secondment and sabbatical programs for talent exchanges between academia and industry. This builds relationships and understanding.

Shared workspaces - Create hubs/innovation centers for academics, entrepreneurs, policymakers to work side-by-side on common challenges. Enable informal interactions.

Communication channels - Facilitate regular communication through townhalls, workshops, hackathons involving all stakeholders to align priorities and foster synergies.

Multistakeholder councils - Assemble advisory councils with representatives from all sectors to provide strategic advice, set standards and address AI ethics concerns.

Pipelines for commercialization - Develop streamlined processes for transferring academic IP to industry through licensing, spin-outs and joint ventures. Incentivize tech transfer offices.

Government as early adopters - Government agencies could proactively pilot promising AI solutions from local startups/research projects to provide validation and feedback.

Global partnerships - Fund visits and collaborations between Quebec AI ecosystem players and international hubs to exchange best practices.

Recommendations for how the Quebec government can better support socially beneficial AI projects:

Dedicated funding - Create grants, incentives and preferential procurement specifically for AI innovations focused on environmental, healthcare, accessibility, economic equality and other social impact goals.

Streamlined processes - Simplify paperwork and compliance for social impact AI startups to reduce regulatory burdens. Provide subsidized access to technical resources.

Public-private partnerships - Collaborate with social enterprises, non-profits and ethical AI companies on pilot projects for developing AI solutions addressing social challenges.

Awareness campaigns - Showcase and promote socially beneficial AI innovations to the public to highlight positive examples of AI application.

Social procurement policies - Implement policies that prioritize purchasing from tech vendors who demonstrate social responsibility and apply AI ethically.

Inclusive design - Mandate participatory design processes so underrepresented groups help shape socially oriented AI projects. Improve representation in data collection too.

Multi-stakeholder oversight - Oversight committees for social impact AI projects could include domain experts, community representatives, ethicists to provide holistic guidance.

Outcome-based evaluation - Focus on social ROI rather than financials when evaluating success of publicly funded social impact AI deployments.

Recommendations for establishing a clear and effective AI governance structure in Quebec:

Centralized agency - Consider forming a dedicated provincial AI oversight agency to streamline governance, set standards, assess risks, and monitor compliance.

Multistakeholder councils - Assemble advisory councils with diverse representation from industry, civil society, and academia to inform AI policies and regulations.

Transparent principles - Develop and publish guiding principles focused on ethics, transparency, accountability, and inclusivity to shape both public and private sector AI deployment. Take the Montreal Declaration for Responsible AI as a great starting point.

Phased roadmap - Roll out policies and regulations in phases, starting with foundational items like transparency criteria for risk assessment before moving to more complex areas.

A balanced approach - Find the right regulatory balance between being flexible enough to allow innovation while providing adequate oversight and public safeguards.

Compliance assistance - Provide frameworks, checklists, toolkits, and incentives like tax breaks to help companies comply with AI governance norms rather than just enforcing penalties.

Pilot regulatory sandboxes - Allow controlled testing of innovative AI governance models with select participants before scaling to minimize unintended consequences.

Public consultation - Proactively gather feedback from citizens, experts, and businesses to improve AI policies over time and address concerns or gaps.

Recommendations to help retain AI talent in Quebec:

Competitive compensation - Offer salaries, benefits, and equity options comparable to global tech hubs to incentivize talent to stay. Consider targeted tax breaks.

Invest in emerging companies - Fund more seed/early-stage Quebec AI startups to provide interesting career growth paths. Prevent brain drain.

Support networks - Sponsor professional associations and networking platforms for AI specialists to collaborate and feel connected to the local community.

Immigration assistance - For foreign AI experts, provide expedited visas, grants for relocation, and language training to ease the transition to living in Quebec.

Inclusive culture - Ensure women, minorities, and international talent feel welcomed and supported both at work and in the broader Quebec AI ecosystem.

Cross-sector mobility - Develop mechanisms for talent exchange/secondments between academia, startups, and large enterprises to provide variety.

Mentorship programs - Experienced AI professionals can guide and inspire the next generation of Quebec students and entrepreneurs to build careers locally.

Remote work - Provide incentives for Quebec companies to allow remote work, making location less important for retaining talent.

Ongoing training - Significant investment in continuous hands-on training and upskilling to keep Quebec at the cutting edge of AI innovations.

Recommendations to counter a lack of activation and action in the Quebec AI ecosystem, in particular towards commercial opportunities:

Financial incentives - Provide tax credits, grants, and subsidies to offset the costs of procuring AI solutions and training employees. This reduces barriers to adoption for businesses.

Awareness programs - Launch campaigns showcasing AI success stories and benefits to make businesses more receptive to adoption. Also, educate on risks to mitigate concerns.

Support networks - Facilitate peer learning by creating spaces/channels for companies to share AI adoption experiences and best practices.

Accessible AI infrastructure - Invest in shared data repositories, computing resources, tools, and sandboxes that provide affordable access to SMEs with limited in-house AI capacity.

Talent development - Expand educational initiatives like vocational training, apprenticeships, and incentives for re-skilling employees to work alongside AI.

Other options include simplified regulations around AI testing, the availability of skilled workers and experienced AI consultants, and incentives for research partnerships between industry and academia. The focus should be on making adoption as frictionless as possible.

Conclusion:

In conclusion, Quebec has a strong foundation in AI research and talent, but pragmatic steps must be taken to convert this potential into tangible benefits. Boosting awareness, capability building, funding, partnerships, and regulation are all crucial levers to activate Quebec's AI ecosystem. If coordinated efforts can align stakeholders from industry, government, and academia, Quebec can foster an AI-first culture focused on translating ideas into products and services. This will drive job creation, improved public services, economic gains, and social progress - allowing the province to serve as an international model for value-driven AI innovation. The recommendations proposed here aim to provide a roadmap towards this goal. By learning from global best practices while retaining connections to Quebec's history and values, the policies and initiatives outlined in this post can set the stage for an AI-enabled future that all Quebecers can actively participate in shaping.