I never thought I’d see the day when AI-generated fakes would actually drive people offline.

But here we are. Deepfakes, cloned voices, and perfectly “human” bots are everywhere.
And something unexpected is happening: people are starting to miss what’s real.
time.com/7326718/sora...
#AI#Deepfakes

AI detection sounds futuristic… but no, social platforms can’t magically spot every fake.
The “state of the art” is fragile, and people trying to mislead others know it.
We need a shared global system to track and verify AI content. 🤝

#AI #Deepfakes #AIDetection

This week I read "The Ones Who Walk Away from Omelas" book.
A perfect city built on one child’s suffering.

It reminded me of AI progress.
We celebrate every breakthrough, but someone always pays the price.

Often, it’s unseen workers labeling data for almost nothing.🧵

Can AI truly understand when a teen is in distress, or is it just scanning for a list of “worrying” words? 🤔
OpenAI’s new Parental Controls for ChatGPT try to alert parents to signs of “emotional distress” in teen conversations. The idea sounds reassuring: more safety, more oversight, less risk. 🚨🧵

Is AI helping us connect, or just making us feel more alone?

People chat with AI for support.
It’s always available.
No judgment. No awkwardness.

But is easy comfort the same as real belonging?

We risk losing the messy, human parts of connection.
The kind that comes from listening to each other->

What if AI benchmarks stopped rewarding perfect answers and started rewarding honest ones? 🤔

We train language models to give answers fast and with confidence. But in real life, knowing when to pause or even admit “I’m not sure” is a skill we respect in people.

I see it often: AI systems fill in 🧵

Is AI making us forget what real belonging feels like? 🤖

AI “friends” are everywhere now.
Chatbots that always listen. 🗣️
No judgment.
No awkward silences.

It’s easy.
It’s safe.
But is it real?

I see teens telling bots more than people.
Adults trust AI with things they keep from friends. 🧵

A new study just tested how easily an LLM like GPT-4o-mini can be nudged to cross its own persuasion “guardrails.” Researchers used carefully crafted prompts to see if the model would help persuade people, even when it wasn’t supposed to. With just a bit of effort, those guardrails slipped. 🧵

Fashion just hit a weird new milestone.

H&M and Vogue both use AI models, but there’s a big difference. 🤖

H&M makes “digital twins” of real people.
These models keep some control and get paid. 💸
There’s always a real person behind each image.

Vogue went all in on fully generated AI for Guess.🧵

Every time I get an interview I get asked,
“How do you spot an AI video?”

Well, the short answer is: it's tricky.
The old giveaways, weird hands, vanishing objects, those tricks really don’t work anymore.

Honestly, I study this stuff every day and even I have trouble spotting a well-made 🧵

Everyone in AI is obsessed with giving LLMs memory: new features, products, research.

But the rush for memory is outpacing ethics and transparency.

A system that remembers you feels helpful. It adapts, recalls your style, even past chats. But where’s the line between helpful and unsettling? 🧵

There’s a new playbook for online influence and it’s powered by LLMs.

What once took experts building personas by hand is now fast, cheap, and automated.

@AnthropicAI recently exposed an “influence-as-a-service” network running 100+ fake personas across X and Facebook. These weren’t chasing 🧵

I recently read a Technology Review article on AI-powered scams thriving on social media. It made me think: people often ask why platforms don’t just “hire better engineers” or “throw money” at the problem.

But after years working in human-centered AI, I can tell you it’s not🧵

bodies, not just stereotypes.

As I told Factchequeado: if AI can’t see us all, it’s not good enough.

🔗 factchequeado.com/teexplicamos/20250507/ia-imagenes-diversidad-latinos

Do you remember Sydney Sweeney’s American Eagle “great jeans” campaign?

It reminded me of a much bigger issue: how beauty gets flattened into one narrow standard.

And AI is doing the same thing.

Have you ever prompted a generative model to create an image of a “beautiful” woman or man?

Everybody’s talking about large language models these days: ChatGPT, Gemini, Claude, LLaMA.

But almost nobody talks about the voices they leave out.

I grew up speaking Spanish, but I know there are hundreds of languages out there with even less data online. When we build AI models on 🧵

Science depends on trust, especially in peer review.
But what happens when AI agents start reviewing, and even writing, scientific papers?
Lately, I've heard more and more conversations about suspected AI-generated reviews, even at top journals.