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The risks of getting it wrong: We must not overregulate AI

Read the original at The Hub ↗
Cite

Kelly-Gagnon, M. (2026, November 9). The risks of getting it wrong: We must not overregulate AI. The Hub. https://thehub.ca/2026/11/09/the-risks-of-getting-it-wrong-we-must-not-overregulate-ai/

Dated from the outlet's own feed. Check the original for its byline.

The Hub · collected 2026-11-09 · by Michel Kelly-Gagnon commentary

Quick Summary

Roger McShane, deputy U.S. editor of The Economist, cautions against overregulating AI to prevent stifling innovation. Michel Kelly-Gagnon elaborates that overly strict regulations in Canada have delayed the approval of new drugs, making the country last among G7 nations and 19th out of 20 OECD countries for drug approval delays. He also cites a car brake startup failure partly due to regulatory hurdles, emphasizing the difficulty in striking an optimal balance between safety and innovation. Kelly-Gagnon argues that market forces like reputation and liability provide inherent incentives for companies to ensure product safety, suggesting that regulators should be cautious about overstepping.
Written by AI on 2026-11-09, from this article's own text only (the story summary below draws on all the coverage).

AI analysis

Story summary

Michel Kelly-Gagnon argues in The Hub that regulations can stifle innovation, citing pharmaceutical delays in Canada as an example. Roger McShane from The Economist sarcastically suggested that regulations halt progress in industries like drug development and car manufacturing. In Canada, new drugs face significant regulatory hurdles, making it the last among G7 countries and 19th out of 20 OECD nations for approval times, leading to delays that can harm patients. Kelly-Gagnon further notes that similar issues affect the automotive industry compared to the faster-paced AI sector.

Written for “Regulating AI Risks” on 2026-11-09, grounded in this article and the 0 other(s) covering the same event.
Why this leaning score
The model judged this article politically coded and scored it -0.65, but every quote it verified points right, so the score is not published.
Written under an earlier scoring contract, which gave a paragraph rather than checkable quotes. Re-analysing this article replaces it.
Leaning score withheld for article 137890: score contradicts its own evidence · logged 2026-11-09

Story

Regulating AI Risks
Technology · 1 article(s) covering the same event.

Compared with similar articles

Nothing to compare against. No article is close enough to this one for the pipeline to have linked or judged the pair.
How this article was measured signals, leaning charts, publisher record, byline, topics and claims

Signals How these are calculated →

Claims extracted
17
sentences that state something as happening or true
Uncertain
6%
1 of 17 hedged ("reportedly", "may", "according to")
Leaning
withheld
no quote in the article backed the model's score
Publisher signals
not measured
these signals count newsroom corrections; Commentary has none to count
Outlets on this story
1
Technology
Same framing elsewhere
1
articles that frame the event the way this one does
Analyzed 2026-11-09 · how these are computed

How this is being covered How these are calculated →

Article leaning vs. publisher reliability
Source leaning vs. consistency

Publisher

The Hub · 14 article(s) · 0 correction(s) detected
No corrections detected for this publisher. That may mean careful reporting, or simply that nothing has been checked.

Who wrote this

Michel Kelly-Gagnon
1 article(s) here · 1 carrying a prediction
Rather, I am saying that it is in fact quite difficult to calibrate regulations in an optimal manner and that regulators, when faced with the choice between perceived security and innovation, will almost always choose the former.
The only article under this byline in the corpus.

Topics

Canada Canadian OECD The Economist U.S.

Subjects

Canada GPE · 3× Canadian NORP · 2× Michel Kelly-Gagnon PERSON · 1× Montreal GPE · 1× OECD ORG · 1× Roger McShane PERSON · 1× The Economist ORG · 1× The Hub’s ORG · 1× Trump PERSON · 1× U.S. GPE · 1×

Narrative

And when it was decided that new drugs should be tested to see if they actually work, pharmaceutical companies halted all research.” While these lines were obviously written sarcastically, there is actually a strong case to be made that regulations can indeed often stifle innovation.
framing: assertive · carried by 1 article(s) · first seen 2026-11-09
Rather, I am saying that it is in fact quite difficult to calibrate regulations in an optimal manner and that regulators, when faced with the choice between perceived security and innovation, will almost always choose the former.
2026-11-09 · The Hub
The risks of getting it wrong: We must not overregulate AI · assertive framing

Claims (17 extracted, 1 hedged)

In a recent commentary on regulating AI, Roger McShane, deputy U.S. editor of The Economist, wrote: “We all know that innovation and regulation are inherently incompatible. asserted
innovation → regulate → Economist
Once they put speed limits on roads, manufacturers stopped producing new cars. asserted
manufacturers → put → cars
When air-traffic control was created, airlines stopped expanding. asserted
airlines → create → ?
And when it was decided that new drugs should be tested to see if they actually work, pharmaceutical companies halted all research.” While these lines were obviously written sarcastically, there is actually a strong case to be made that regulations can indeed often stifle innovation. asserted
regulations → decide → innovation
For instance, pharmaceutical regulations in Canada are a real quagmire, governed by various entangled regulatory bodies, both provincial and federal. asserted
regulations → govern → bodies
Partly because of this, new innovative medicines take substantially more time to reach Canadian patients than they should. asserted
they → take → patients
People suffer and even die as a result. asserted
People → suffer → result
Several years ago, I was an investor in a small startup company based in a suburb north of Montreal that was aiming to introduce a new (and tangibly longer-lasting) generation of brakes. asserted
that → base → brakes
It was ultimately killed, in part, because of the regulatory process. asserted
It → kill → process
My point here is not that there shouldn’t be any regulations on new generations of brakes, because it does indeed come in handy to be able to actually stop your vehicle when you need to. asserted
you → come → vehicle
Rather, I am saying that it is in fact quite difficult to calibrate regulations in an optimal manner and that regulators, when faced with the choice between perceived security and innovation, will almost always choose the former. asserted
regulators → say → former
Furthermore, we shouldn’t lose sight of the fact that the makers of new medicines, or of brakes, or of planes, or whatever else, have a distinct and inherent built-in incentive of their own to avoid killing their clients, regardless of any government dictates. asserted
makers → lose → dictates
The article discusses the balance between regulating AI and fostering innovation, arguing that overregulation can stifle progress. asserted
overregulation → discuss → progress
Michel Kelly-Gagnon highlights the risks of regulatory inertia and the challenges faced by regulators in understanding rapidly evolving technologies. asserted
Gagnon → highlight → technologies
He points out that while there are dangers in not regulating AI, excessive or poorly designed regulations can also have negative consequences. asserted
regulations → point → consequences
The piece advocates for a balanced approach to AI regulation, citing the self-regulating framework established by the Trump administration as a potential model. asserted
piece → advocate → model
Ultimately, the article suggests that Canada could benefit from avoiding hasty regulatory actions. uncertain
Canada → suggest → actions
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