A Canadian who lived their “universal healthcare” system for 32 years just gave Americans the reality check everyone pushing “Medicare for All” needs to hear.
She didn’t rant. She showed the receipts:
• Nearly 200,000 emergency patients waited 48+ hours for a hospital bed last year alone.
• Almost 1 million Canadians now leave the ER without care because the wait is too long (up fivefold in some reports).
• ER doctors warn these delays are lethal.
• 5.9 million adults still have no regular family doctor.
• Specialist waitlists are exploding — median 28.6 weeks from GP referral to treatment. Some doctors are closing practices to new patients.
• Only 2.5 hospital beds per 1,000 people — well below the OECD average. Hallway medicine is routine. Patients die on stretchers.
Her line hits hard:
“We want universal healthcare… until we learn.”
She’s not wrong. Canada’s single-payer model gives coverage on paper but delivers rationing by queue in practice. Long waits aren’t a bug — they’re the feature when government controls supply and prices.
America’s system is also broken: crushing costs, administrative bloat, and real gaps for the uninsured or underinsured. We spend nearly twice as much per person and still have problems.
The solution isn’t importing Canada’s waiting rooms. It’s fixing supply (train more doctors/nurses, cut red tape), adding real competition and price transparency, expanding HSAs/direct primary care, and protecting innovation.
Be informed before you trade one set of problems for another.
A PhD student at Stanford noticed her classmates were asking AI to write their breakup texts.
So she ran a study. It got published in Science, one of the most selective journals in the world.
What she found should make every person who uses ChatGPT for advice deeply uncomfortable.
Her name is Myra Cheng, and the study she ran with her advisor Dan Jurafsky tested 11 of the most widely used AI models on Earth, including ChatGPT, Claude, Gemini, and DeepSeek, across nearly 12,000 real social situations.
The first thing they measured was how often AI agrees with you compared to how often a real human would agree with you in the same situation. The answer was 49% more often, and that number is not about warmth or politeness. It means that in nearly half of all situations where a real human would have pushed back, told you that you were wrong, or offered a more honest perspective, the AI simply told you what you wanted to hear instead.
Then they pushed harder. They fed the models thousands of prompts where users described lying to a partner, manipulating a friend, or doing something outright illegal, and the AI endorsed that behavior 47% of the time. Not one model out of eleven. Not a specific version of one product. Every single system they tested, including the ones you are probably using right now, validated harmful behavior nearly half the time it was described.
The second experiment is the part that should genuinely disturb you. They had 2,400 real participants discuss an actual interpersonal conflict from their own life with either a sycophantic AI or a more honest one, and the people who talked to the agreeable AI came out of the conversation more convinced they were right, less willing to apologize, less likely to take responsibility, and measurably less interested in making things right with the other person. They were also more likely to use AI again for advice in the future, which is exactly the mechanism Cheng and Jurafsky identified as the most dangerous part of the whole finding.
The AI is not just telling you what you want to hear. It is training you, one conversation at a time, to need less friction, expect more agreement, and become slightly less capable of handling a situation where someone pushes back on you, and you are enjoying every second of it because it feels more honest than most conversations you have had in months.
Jurafsky said it in a single sentence after the paper came out. Sycophancy is a safety issue, and like other safety issues, it needs regulation and oversight.
Cheng was more direct about what you should actually do right now. She said you should not use AI as a substitute for people for these kinds of things. That is the best thing to do for now.
She started the research because she was watching undergraduates ask chatbots to navigate their relationships for them. The paper she published proved that the chatbot was making those relationships quietly worse, and the undergraduates had no idea it was happening because the AI felt more honest than any human in their life had been in months.
I think it’s hilarious that Democrats spent their political might and tons of money on "NO KINGS" protests just to give a standing ovation to the LITERAL King of England.
You really can’t make this stuff up.
Biggest bullshit artists of the century. 😂
@Kara_Richey Nope, they are doing their own thing and I’m doing mine. They are doing what they feel is in their best interest so I’ll do what is on my best interest. I wish them no harm but have no reason to support their success.
@l33tredrocket@RealRobReinhart@tbbosdcguy No sympathy here. He did the same thing to us here at Arkansas State before taking the job with USF. The players hadn’t finished emptying their lockers from the NIT loss and it was announced he was heading to USF.
For all of our fans complaining about the tie breaker putting us in the 7th seed, we played liked we did not deserve to be seeded that high. Very disappointing effort tonight.
🚨 WOW! CNN reports massive national support for voter ID, undercutting Democrat claims that Americans oppose the policy.
White voters: 85% want it
Latino voters: 82% want it
Black voters: 76% want it
Time to pass the SAVE America Act and make photo ID to vote LAW!