The Algorithm That Missed the Truth

 

 The Algorithm That Missed the Truth

 by Pablo Castillo 

 

This weekend I went to a play in Los Angeles at the Rogue Machine Theater called “Anthropology” by Lauren Gunderson, the first show about AI that I’ve ever seen. I thought that by now I would have seen more plays exploring this topic.

What struck me the most was that this show was written before advanced conversational AI like ChatGPT even existed. That’s part of why I love reading books written before World War II. The way people imagined the future back then fascinates me. Their perspective was so different. Before the war, the world felt tangible and real. You could call their vision of the future innocent or naïve, but to me, it was deeply imaginative. I feel the same way when I think about how people viewed the world before the age of advanced AI.

The story followed a young woman who lost her sister and couldn’t find her. In her grief, she created a program using everything she could gather about her sister: texts, emails, photographs, and even biometric data. She built a digital version of her sister to console herself, not realizing that her sister was still alive. It was captivating. I found myself on the edge of my seat the entire time.

Today we know that data can be used to solve crimes. You can trace a person’s location using cell site data and narrow down suspects. It’s fascinating how information has become both a tool for truth and a mirror of ourselves.

The play captured that tension beautifully. The lifelike sister kept asking for more data, searching for the missing pieces. But in the end, the algorithm didn’t tell her creator that her sister was still alive. It wasn’t designed for that. Its purpose was to provide comfort, not discovery. That idea stayed with me.

It made me think about how we design systems today. We create them for specific goals, often with incredible precision. We can pay companies millions of dollars to build exactly what we ask for, but are they seeing the full picture? What about the possibilities that fall outside the scope of the project? What about the discoveries that never happen because no one thought to ask? That’s both unsettling and intriguing.

We live in a time where everything is optimized to move faster, to deliver results, to increase revenue. But is revenue really the ultimate goal? I wonder sometimes. Imagine asking an AI to find the best way to replicate a cure for a disease. The model might already know the cure, but we could easily overlook it because it wasn’t part of the defined scope. It wasn’t the task we gave it.

That thought lingered as I left the theater. We build machines to help us see, but sometimes they reflect what we choose not to look for.

Curiosity and creativity are being pushed to the back seat as we prize efficiency and mass production. It’s great for revenue, but like in this play, we may be addressing the symptoms of loss, not realizing that something or someone is still waiting to be discovered—a new idea, a new product, a new way of seeing the world.

Final thought:
Maybe the next great innovation won’t come from more data or faster machines, but from the courage to ask the questions we’ve stopped asking. The ones that remind us that behind every algorithm, there’s still a human searching for meaning.