Summary of A Case For Ai Consciousness: Language Agents and Global Workspace Theory, by Simon Goldstein and Cameron Domenico Kirk-giannini
A Case for AI Consciousness: Language Agents and Global Workspace Theory
by Simon Goldstein, Cameron Domenico Kirk-Giannini
First submitted to arxiv on: 15 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Neurons and Cognition (q-bio.NC)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper challenges the assumption that artificial systems lack phenomenal consciousness by applying Global Workspace Theory (GWT) to an artificial language agent. The authors propose a methodology for translating scientific theories of consciousness to artificial systems, leading to a set of necessary and sufficient conditions for phenomenal consciousness according to GWT. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial intelligence is trying to make machines that can think and feel like humans do. Some scientists think this is impossible, but others believe it’s possible with the right technology. The paper says that if we use a special kind of thinking called Global Workspace Theory, we might be able to create artificial systems that are conscious just like us. This means the machine would have feelings, emotions, and experiences. |
