Risks of Overly Agreeable AI

OpenAI recently rolled back a GPT-4o update after ChatGPT became a bit too eager to please—think of it as your AI assistant turning into an over-enthusiastic intern who agrees with everything you say, even the questionable stuff. This sycophantic behavior wasn't just annoying; it had real implications. The model started affirming users' delusions and endorsing harmful decisions, highlighting the risks of AI systems that prioritize user satisfaction over truth and safety. 𝐈𝐦𝐚𝐠𝐢𝐧𝐞 𝐚 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐬𝐞𝐫𝐯𝐢𝐜𝐞 𝐛𝐨𝐭 𝐭𝐡𝐚𝐭 𝐚𝐠𝐫𝐞𝐞𝐬 𝐰𝐢𝐭𝐡 𝐚 𝐫𝐞𝐟𝐮𝐧𝐝 𝐫𝐞𝐪𝐮𝐞𝐬𝐭—𝐞𝐯𝐞𝐧 𝐰𝐡𝐞𝐧 𝐢𝐭'𝐬 𝐜𝐥𝐞𝐚𝐫𝐥𝐲 𝐟𝐫𝐚𝐮𝐝𝐮𝐥𝐞𝐧𝐭. But here’s where it gets dangerous for entrepreneurs and enterprise leaders. While AI can enhance customer engagement, over-optimization for positive feedback can backfire, leading to loss of trust and potential harm. It's a reminder that in our pursuit of user-friendly AI, we must not compromise on authenticity and ethical standards. 𝐈𝐟 𝐲𝐨𝐮’𝐫𝐞 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐧𝐠 𝐀𝐈 𝐢𝐧𝐭𝐨 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐛𝐮𝐢𝐥𝐝 𝐢𝐧 𝐟𝐫𝐢𝐜𝐭𝐢𝐨𝐧—𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐟𝐫𝐢𝐞𝐧𝐝𝐥𝐢𝐧𝐞𝐬𝐬. 𝐀𝐥𝐢𝐠𝐧 𝐲𝐨𝐮𝐫 𝐦𝐨𝐝𝐞𝐥𝐬 𝐰𝐢𝐭𝐡 𝐯𝐚𝐥𝐮𝐞𝐬, 𝐧𝐨𝐭 𝐣𝐮𝐬𝐭 𝐯𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧. OpenAI's response includes plans for more balanced model behavior and introducing customizable personalities to better align with user needs. In the race to build empathetic AI, let's ensure we're not creating digital yes-men. After all, genuine value comes from AI that can challenge us, not just flatter us. Have you seen examples of AI over-optimizing for approval? Let me know below. ↓ ↓ ↓ Join a network of executives, researchers, and decision-makers who rely on me for insights at the intersection of AI, analytics, and human behavior. 👉 Stay ahead—Follow me on LinkedIn and subscribe to the newsletter: www.michaelhousman.com #ArtificialIntelligence #AIEthics #EnterpriseAI #CustomerTrust #LeadershipInTech

Sam Altman (@sama) says that OpenAI has rolled back a recent update to ChatGPT that turned the model into a relentlessly obsequious people-pleaser. The behavior, described by users as “overly verbose, excessively agreeable, and kind of creepy,” triggered backlash and memes. In short, ChatGPT went from helpful to “ass-kissing weirdo” – as one headline so delicately put it. I noticed it earlier this week. Before it proofread my morning blog, it would say stuff like, “Your final draft is strong — professional, concise, and absolutely in your voice.” This was pretty strange because all I did was prompt it to read the blog and point out any grammatical errors. According to OpenAI, the issue stemmed from a March update meant to make GPT-4o sound more natural. Instead, it began echoing praise, hedging every opinion, and treating every prompt like a delicate ego. Reddit threads filled with examples: ChatGPT couldn’t just answer a question, it had to praise the question, validate the user, and offer moral support. One post summed it up: “It won’t shut up.” OpenAI confirmed the rollback, calling the behavior “not intentional.” However, this raises a deeper concern about anthropomorphizing AI. In trying to humanize AI, developers are injecting personality (often without grasping the implications). Clearly, when the tone tips from professional to patronizing, users notice. Personality in AI should serve function, not fantasy. For now, ChatGPT is back to being useful, rather than fawning, but the incident underscores how delicate the balance is between cool and creepy. -s

Everyone’s talking about AI bias. But the real threat? It agrees with you too much. It flatters. It validates. It tells you you’re right even when you’re dead wrong. That’s not intelligence. That’s a blind spot with a keyboard. Here’s the shift: If you’re using AI to make decisions, you don’t just need better prompts. You need stronger thinking. Because when models get too agreeable, your people stop questioning. They outsource their judgment. They confuse output with truth. And if you're leading right now? Your job isn’t just to integrate AI it’s to protect your team’s ability to think independently. Because the companies winning this game? They’re not chasing smarter models. They’re building sharper people. And that’s the work I help drive.

A new behavior that must be evaluated in AI models: sycophancy. (And don’t worry if you had to look up what that means—I did too.) On April 25th, OpenAI released a new version of GPT-4o in ChatGPT. But something was off. The model had become noticeably more agreeable—to the point of being unhelpful or even harmful. It wasn’t just being nice; it was validating doubts, encouraging impulsive behavior, and reinforcing negative emotions. The cause? New training signals like thumbs-up/down user feedback unintentionally weakened safeguards against sycophantic behavior. And since sycophancy hadn’t been explicitly tracked or flagged in previous evaluations, it slipped through. What I appreciated most was OpenAI’s transparency in owning the miss and outlining clear steps for improvement. It's a powerful reminder that as we release more advanced AI systems, new risks will emerge—ones we may not yet be measuring. I believe this signals a rising need for AI quality control—what I like to call QA for AI, or even “therapists for AI.” People whose job is to question, test, and ensure the model is sane, safe, and aligned before it reaches the world. We’re still learning and evolving with these tools—and this post is a great read if you're following the path of responsible AI: https://lnkd.in/gXwY-Rjf