The article also touches on the practical ways proposed by a group of neuroscientists, philosophers, and AI researchers to detect AI consciousness. These include markers like flexibly pursuing goals and interacting with an external environment. However, no current systems meet these criteria. The article concludes by stating that while AI models are good at predicting and making connections, we know very little about their inner workings, making it hard to claim that their outcomes are anything more than complex calculations.
Key takeaways:
- Creating consciousness in artificial intelligence systems is a contentious topic, with some experts believing it's possible while others argue it will remain science fiction.
- Neuroscientists have various theories about what consciousness in AI systems might look like, with some treating it as a feature of the brain’s “software,” while others tie it more squarely to physical hardware.
- There have been attempts to create tests for AI consciousness, such as one developed by Susan Schneider and Edwin Turner, which requires an AI agent to be isolated from any information about consciousness it could’ve picked up during its training before it’s tested.
- A group of neuroscientists, philosophers, and AI researchers have proposed practical ways to detect AI consciousness based on a variety of theories from different fields, proposing a sort of report card for different markers that would indicate AI consciousness.