Dotblocks Technologies

There is significant uncertainty surrounding AI adoption, fueled especially by global pressure and concerns regarding potential risks. The successful outcome would be Clarity. If attendees leave the room with confidence in identifying appropriate versus inappropriate AI use cases, I'll consider the session a success.

AI capacity-building;Safe, secure and trustworthy AI;Protection and promotion of human rights;Transparency, accountability, and human oversight;

I look forward to an intersection of safety and ethics. By implementing and adopting safe, secure and trustworthy AI alongside robust capacity-building, we need to bridge technical gaps while ensuring human rights remain central to innovation. A focus on transparency, accountability, and human oversight, would ensure that AI development is both responsible and inclusive.

There is a strong lobby creating a sense of urgency for AI adoption. Many companies are rushing into AI adoption without achieving a clear return on investment. Non profit sector is feeling the pressure to keep up while simultaneously trying to stay true to their core missions. We must raise awareness regarding the unnecessary pressure from the supply side and improve literacy on how automating certain processes can actually increase complexity. AI is not a universal solution.

In Canada, the rush to adopt AI has created a significant disconnect. Driven by supply-side hype and a fear of falling behind global competitors, many Canadian entities are layering complex tools over inefficient processes, resulting in organizational strain where most energy is spent on compliance leaving little room for the genuine innovation or community impact.

The AI dialogue will ensure that AI governance is not just a conversation among wealthy nations or tech giants, but a collective global effort. It shifts the focus from purely technical safety to socio-ethical safeguards, prioritizing human rights and linguistic diversity.

Building on the UNESCO Recommendation on the Ethics of AI and the OECD AI Principles, the Dialogue can translate these high-level values into actionable global policy.

Governments must move beyond being mere regulators to becoming facilitators of a strong AI strategy that protects their citizens. The private sector must shift from a move-fast and break-things mentality to one of stewardship. Non-profits and advocacy groups can foster truly inclusive debates and act as watchdogs to identify and report algorithmic bias or human rights violations. Individual citizens, researchers, and workers provide the "lived experience" that proves whether AI governance is actually working.

The everyday consumer is missing from the discussions. These are the users who feel forced to adopt AI frameworks hastily assembled by tech giants, not because they are the best solutions, but because the market has been engineered to make any other option appear unsafe, inefficient, or obsolete. To include them institutionalize "People's Consultations".

Reverse Pitching Sessions: Instead of tech giants presenting their latest tools, let the civil society and governments pitch the specific social problems they need AI to solve. This flips the supply-side narrative, forcing developers to respond to actual human needs rather than market hype.

1. Borrowing from the Government of Canada's Directive on Automated Decision-Making, an AIA is a mandatory "stress test" before deployment. The organizations use a structured questionnaire to score a system's risk based on its impact on human rights, health, and economic interests. 2. Effective governance would replace the idea of "automated" with "augmented." This can be done by implementing tiered Human Oversight Models. a) Humans to review every AI decisions b)Other humans to monitor the system in real-time c)More humans to oversee the entire social and ethical impact of the system. 3. To counter supply-side hype, independent third-party auditors should be verifying that an AI system actually does what the vendor claims.