{"id":21199,"date":"2026-10-13T10:18:12","date_gmt":"2026-10-13T10:18:12","guid":{"rendered":"https:\/\/news.theck1.no\/?p=21199"},"modified":"2026-10-13T10:18:12","modified_gmt":"2026-10-13T10:18:12","slug":"do-ais-already-process-information-in-a-way-that-gives-rise-to-consciousness","status":"publish","type":"post","link":"https:\/\/news.theck1.no\/?p=21199","title":{"rendered":"Do AIs already process information in a way that gives rise to consciousness?"},"content":{"rendered":"

AI-rewritten:<\/strong> This is a summary of an article from New Scientist, rewritten by AI (Qwen, running locally) to make it easier to read. The facts come from the original article – read it for the full story.<\/p>\n

New Scientist • David Robson • October 12, 2026<\/strong><\/div>\n\n

Philosophers and neuroscientists are gathering on a yacht in Ecuador to debate whether artificial intelligence possesses consciousness. The discussion centers on the "global workspace theory," which suggests that consciousness arises when information is broadcast across different brain modules for integration. While humans experience this through subjective awareness, researchers argue similar mechanisms might exist in animals like iguanas and crows, as well as in large language models such as Claude.<\/p>\n

<\/p>\n

Stanislas Dehaene, a cognitive neuroscientist at the Coll\u00e8ge de France, explains that consciousness acts as a bottleneck for information processing. His team has observed "ignition," a surge of neural activity across the brain when participants consciously perceive stimuli. This theory helps explain inattentional blindness, where people fail to notice obvious objects because their attention is occupied elsewhere. Dehaene notes that experiments with primates and crows show similar patterns, suggesting these animals may also have global workspaces.<\/p>\n

Anthropic recently published a paper claiming Claude has developed a comparable structure called the "J-space." Unlike traditional programming, large language models learn statistically from vast datasets, allowing new processing methods to emerge spontaneously. Researchers used a decoding tool to identify a focused zone in Claude’s neural networks that handles high-level reasoning, such as breaking down mental arithmetic into steps. When engineers altered information within this J-space, Claude’s responses became confused, mirroring how humans might react if key data were changed in their working memory.<\/p>\n

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Source:<\/strong> New Scientist • David Robson • October 12, 2026<\/p>\n

Read the original article at New Scientist →<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

AI-rewritten: This is a summary of an article from New Scientist, rewritten by AI (Qwen, running locally) to make it easier to read. The facts come from the original article – read it for the full story. New Scientist • David Robson • October 12, 2026 Philosophers and neuroscientists are gathering on a yacht in<\/p>\n

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