As AI language skills grow, so do scientists’ concerns

The tech industry’s latest artificial intelligence constructs can be pretty convincing if you ask them what it feels like to be a sentient computer

The tech industry’s latest artificial intelligence constructs can be pretty convincing if you ask them what it feels like to be a sentient computer, or maybe just a dinosaur or squirrel. But they’re not so good — and sometimes dangerously bad — at handling other seemingly straightforward tasks.

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Take, for instance, GPT-3, a Microsoft-controlled system that can generate paragraphs of human-like text based on what it’s learned from a vast database of digital books and online writings. It’s considered one of the most advanced of a new generation of AI algorithms that can converse, generate readable text on demand, and even produce novel images and video.

Among other things, GPT-3 can write up most any text you ask for — a cover letter for a zookeeping job, say, or a Shakespearean-style sonnet set on Mars. But when Pomona College professor Gary Smith asked it a simple but nonsensical question about walking upstairs, GPT-3 muffed it.

“Yes, it is safe to walk upstairs on your hands if you wash them first,” the AI replied.

These powerful and power-chugging AI systems, technically known as “large language models” because they’ve been trained on a huge body of text and other media, are already getting baked into customer service chatbots, Google searches and “auto-complete” email features that finish your sentences for you. But most of the tech companies that built them have been secretive about their inner workings, making it hard for outsiders to understand the flaws that can make them a source of misinformation, racism, and other harms.

“They’re very good at writing text with the proficiency of human beings,” said Teven Le Scao, a research engineer at the AI startup Hugging Face. “Something they’re not very good at is being factual. It looks very coherent. It’s almost true. But it’s often wrong.”