When AI Makes You Worse at Being Human
Relationship experts are sounding the alarm: people using ChatGPT to craft dating profiles and text messages are becoming "relationally stupid." They're losing the ability to show up authentically in conversations that matter.
This isn't just a dating problem. It's a preview of what happens when businesses deploy AI wrong in customer service.
The Fox News report highlights a troubling trend. Singles are outsourcing their personality to AI, letting chatbots write their bios, compose their messages, and essentially pretend to be them. The result? Connections that feel hollow because they are hollow. When you finally meet in person, the gap between AI-you and real-you becomes painfully obvious.
Sound familiar? It should. This is exactly what's happening in customer service right now.
The Copy-Paste Problem in Customer Support
Too many companies treat AI in customer service like a fancy template library. They use it to generate canned responses that sound polished but feel empty. The AI becomes a shield between the business and the customer, not a bridge.
Here's what that looks like in practice:
- A customer reports a complex billing issue and gets a generic "we're looking into it" response that could apply to any problem
- Someone asks about a specific feature and receives a beautifully written paragraph that doesn't actually answer their question
- A frustrated user needs immediate help and gets an AI-generated essay about "company values" and "commitment to excellence"
The words are perfect. The sentiment is absent. Just like those AI-written dating profiles.
Why This Happens (And Why It Matters)
The dating app problem and the customer service problem share the same root cause: treating AI as a replacement for human understanding rather than an amplifier of it.
When someone uses ChatGPT to write their entire dating profile, they're not asking "how can AI help me express myself better?" They're asking "how can AI do this for me so I don't have to think about it?" The difference is everything.
The same thing happens when businesses bolt AI onto their support systems without rethinking the underlying approach. They automate the surface-level stuff—the words, the formatting, the speed—but miss the deeper layer. They forget that customer service is ultimately about understanding what someone actually needs and helping them get it.
This is where AI-first thinking diverges from AI-lazy thinking. An AI-first approach starts with the question: what does this customer actually need, and how can AI help us deliver it better? It doesn't stop at "can AI write a response faster?"
What Authentic AI Customer Service Looks Like
The solution isn't to avoid AI. That ship has sailed, and honestly, you wouldn't want to even if you could. AI can handle customer conversations at a scale and speed that humans simply can't match.
The solution is to deploy AI that actually understands context, not just keywords.
Consider these scenarios:
Scenario 1 (Generic AI): Customer says their order is late. AI generates a polite apology, checks tracking, and shares the status. Five-minute resolution.
Scenario 2 (Contextual AI): Customer says their order is late. AI recognizes this is their third order this month, notes they're a loyal customer, sees the item was a birthday gift (mentioned in previous chat), understands the urgency, proactively offers expedited replacement with a personal touch. Two-minute resolution that strengthens loyalty.
The first approach treats every conversation as a transaction. The second treats it as a relationship moment. That's the difference between AI that makes you relationally stupid and AI that makes you relationally smarter.
The Training Data Problem
Here's where this gets technical but important: most AI customer service systems are trained on the wrong data. They learn from historical support tickets, which means they learn to replicate the mediocre, templated responses that humans have been sending for years.
It's like teaching ChatGPT to write dating profiles by feeding it thousands of profiles that all say "I love travel, wine, and The Office." The AI gets really good at being generic because generic is what it learned.
Building an AI workforce that delivers authentic service requires different training. The AI needs to learn:
- What questions customers are actually asking (not just the literal words)
- What outcomes actually solve their problems (not just what closes tickets)
- What context matters in different situations (purchase history, previous conversations, urgency signals)
- When to escalate to humans (because some conversations need that human touch)
This requires diving deep into the details of how customers actually communicate and what they actually need. Surface-level analysis produces surface-level responses.
The Real Risk of AI-Generated Everything
The dating app story reveals something darker: when we rely too heavily on AI to handle our human interactions, we atrophy the skills we need for those interactions. People forget how to be genuine because they've outsourced genuineness.
For businesses, the parallel risk is this: if you use AI as a black box that just spits out responses, your organization loses touch with what customers actually experience. Your support team stops learning from customer pain points because they're not engaging with them directly. Your product team loses the qualitative feedback that drives real improvement.
The goal isn't to remove humans from the equation. It's to free them from the repetitive work so they can focus on the complex, nuanced conversations that require empathy and creativity. Let AI handle the "where's my order?" messages so humans can handle the "I'm frustrated and considering switching to your competitor" conversations.
Moving Forward
The experts warning about "relational stupidity" in dating aren't arguing against AI. They're arguing for using it wisely. Use it to organize your thoughts, sure. Use it to check your grammar. But don't use it to replace the core task of being yourself.
The same principle applies to customer service. Use AI to scale your support, to speed up responses, to handle routine questions. But don't use it to avoid the hard work of actually understanding your customers.
The businesses that win with AI customer service will be the ones that treat it as a tool for deeper connection, not a shortcut around it. They'll build AI workforces that make every customer feel heard, not just processed.
Because at the end of the day, whether you're trying to get a second date or retain a valuable customer, authenticity isn't optional. It's everything.