LLMs differ from human cognition because they are not embodied
Bibliographic Data
| ID | 4614866 |
|---|---|
| Authors | Anthony Chemero (0000-0001-5987-4106, University of Cincinnati, corresponding author) |
| Year | 2023 |
| Volume | 7 |
| Issue | 11 |
| Pages | 1828-1829 |
| Publication date | 2023-11-20 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Nature Human Behaviour (JOURNAL) |
| Journal identifiers | ISSN: 2397-3374 • E-ISSN: 2397-3374 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1038/s41562-023-01723-5 |
| PMID | 37985905 |
| OpenAlex | W4388824938 |
| Language | EN |
| Citations received | 14 |
| References cited | 7 |
Cognition · Cognitive psychology · Cognitive science · Embodied cognition · Epistemology · Social cognition · Sociology · Language and cultural evolution · Multimodal Machine Learning Applications · Neuroscience · Psychology · Topic Modeling
Knowledge-based representations of artificial intelligence and divine agents
AI as a partner in assessment
The Missing Half of Language Learning in Current Developmental Language Models
Psychomatics—A Multidisciplinary Framework for Understanding Artificial Minds
Transforming agency
Desire-fulfilment and consciousness
Sense-making reconsidered
Meaning Beyond Lexicality
Creativity, embodiment, and Covid-19
Problematizing language
AI takeover and human disempowerment
Large language models without grounding recover non-sensorimotor but not sensorimotor features of human concepts
Large models of what? Mistaking engineering achievements for human linguistic agency
Testing theory of mind in large language models and humans
| Unique citing works | 14 |
|---|---|
| Citations per year | 7 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 13 |