Concept Alignment

no code implementations • 9 Jan 2024 • Sunayana Rane, Polyphony J. Bruna, Ilia Sucholutsky, Christopher Kello, Thomas L. Griffiths

Discussion of AI alignment (alignment between humans and AI systems) has focused on value alignment, broadly referring to creating AI systems that share human values.

Concept Alignment Philosophy

Concept Alignment as a Prerequisite for Value Alignment

no code implementations • 30 Oct 2023 • Sunayana Rane, Mark Ho, Ilia Sucholutsky, Thomas L. Griffiths

Value alignment is essential for building AI systems that can safely and reliably interact with people.

Concept Alignment

Getting aligned on representational alignment

no code implementations • 18 Oct 2023 • Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Iris Groen, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths

Finally, we lay out open problems in representational alignment where progress can benefit all three of these fields.

Navigate Transfer Learning

Predicting Word Learning in Children from the Performance of Computer Vision Systems

no code implementations • 7 Jul 2022 • Sunayana Rane, Mira L. Nencheva, Zeyu Wang, Casey Lew-Williams, Olga Russakovsky, Thomas L. Griffiths

The performance of the computer vision systems is correlated with human judgments of the concreteness of words, which are in turn a predictor of children's word learning, suggesting that these models are capturing the relationship between words and visual phenomena.

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