Here are my answers to the third and fourth questions from the “Enhancing trust in AI through increased transparency” Canadian federal government consultation feedback form:
AI-Generated Content
Question 3: Who in the AI value chain (developers, deployers, or others) should be responsible for providing transparency around AI-generated content? Why?
Paul’s (Draft) Answer: All players in the value chain have an obligation to provide transparency around AI-generated content. Going back to my earlier reflections on education every player in the education value-chain is expected to give attribution and acknowledge sources. They are also responsible for the legality, accuracy and validity of the content they produce. This should be true for AI too.
Focusing only on transparency is to limiting Developers and deployers should be responsible not just for transparency but for accuracy. As noted in Google’s Ambitious AI Search Changes Are Risky. Here’s Why “AI has a confidence problem. The sourcing problem in AI search is not a fringe concern. It’s been documented repeatedly, across multiple platforms, by independent researchers with no particular stake in the outcome.
A study published in 2025 by Columbia University’s Tow Center for Digital Journalism tested eight generative search tools, including Google’s Gemini, ChatGPT Search, Perplexity, and others, across 200 queries. AI search engines failed to produce accurate citations in over 60 percent of tests. Gemini and Grok were the worst performers, providing more fabricated links than correct ones. The study’s authors noted that content licensing deals with publishers, the kind AI companies have spent billions on, provided no guarantee of accurate attribution in the responses that followed.
A separate study, using the DeepTRACE evaluation framework, tested systems including Bing Chat, You.com, and Perplexity across 303 queries, scoring answers on whether claims were actually supported by the cited sources. Bing Chat had unsupported statements in 23 percent of cases. Perplexity reached 31 percent. Perplexity’s deep research agent performed worst of all, with 97.5 percent of its claims unsupported by cited sources. The researchers concluded that “current public systems fall short of their promise to deliver trustworthy, sourced responses.”
And research published jointly by the European Broadcasting Union and the BBC in October 2025 found that leading AI assistants misrepresented news content in nearly half of all responses tested, with 81 percent of responses containing some form of problem.
When asked about hallucinations at the time of the AI Overviews launch, Google CEO Sundar Pichai called them “an unsolved problem” and, in a phrase that deserves to be considered carefully, “in some ways an inherent feature” of large language models.”
Given this extent of inaccuracy it seems imperative that actors in the value chain be held responsible not just for transparency but for accuracy. It is interesting to note that that increasingly responsibility for accuracy is falling on end users rather than those who produce the underlying systems themselves as outlined in Beyond the Mirage: Beware of Generative AI and Hallucinations, and Academics in Meltdown Now That They’re Responsible for AI Hallucinations in Their Research Papers.
Question 4: Do existing market practices, technical tools, and legal frameworks make it easy enough to know when content is AI-generated? If not, where do gaps remain and what actions (e.g., regulatory measures, guidance and codes of conduct, standards and technical solutions, research and development, literacy initiatives, procurement requirements) do you think the Government should take?
Paul’s (Draft) Answer: There is a significant push to define the lack of trust in AI as a literacy issue. I think this is a false narrative. I think people are pushing back against the spread of AI into their daily lives without it being something they want. Librarians are hosting viral ‘Avoiding AI’ workshops for people who are fed up with Big Tech. There is a very real sense that AI is being forced on us. See Don’t like AI being forced on you? These librarians have the perfect first step. There is even a growing push related to anti-AI clothing. See also This shirt is like an AI invisibility cloak.
Another factor is the very real pushback against the consolidation of power related to AI in the hands of a very few high tech players. This is an equity and social issue that market practices have created. At this point in time AI technologies are not engaging in fair practices associated with reciprocity - see The Tragedy of AI. Furthermore the promise of AI to eliminate jobs, consume vast amounts of power and water to the detriment of citizens has resulted in booing of AI promoters at commencement addresses and protests against data centres leading to Canadian petitions like this. Transparency related to impact of AI on the public is swept under the carpet and replaced with ideas like watermarks. In the US Bernie Saunders introduced an AI Moratorium Act to completely freeze the construction and upgrading of new AI data centers until government passes comprehensive safeguards against job displacement and ensures these facilities do not raise utility prices for consumers.
AI has been overly hyped and is nowhere close to fulfilling the promises being made. AI has yet to even make business sense. See Is AI Profitable Yet? What will Canada’s response be to the bubble bursting? I found Bernie Saunders proposal for an AI Sovereign Wealth Fund Act arguing for public ownership of AI compelling. I like his view that:
"“It would do two extremely critical things,” Sanders said of his legislation. “First, it would give the American people a direct role in determining the future of this technology. No longer would the future of AI be dictated by a handful of Big Tech oligarchs, while the rest of the world sits back and watches them do what they want.
“Secondly, it would guarantee that the trillions of dollars potentially generated by AI are used to improve the lives of all of us — not simply to make the richest people on Earth even richer.”
And there is a very real issue related to transparency not just of the AI tools but of the entire AI technology stack (compute hardware, cloud platform, source data, enhanced data, models, API’s, apps and applications). AI relies on a suite of underlying technologies which are consolidated into the hands of a very few tech players. The consolidation of the underlying stack associated with AI in the hands of a few high tech players is largely opaque to users.
The issue isn’t just “transparency” it is also sovereignty. The Sovereign AI Index captures some of what is happening and shows Canada’s position, but it would be super helpful if Canada was more transparent around this effort and investing in a sovereign, public benefit approach to AI not a big tech one. I also think Canada should consider the sovereignty benefits associated with an open source approach to AI. The European Open Source strategy is one we too should take.
I think taking a Public AI approach will generate the greatest transparency and benefits to Canada.
