Relevance of deep neural networks to mindreading (Theory of Mind)

Ascertain whether deep neural networks can provide informative insights into mindreading (Theory of Mind), specifically whether such models can meaningfully elucidate the computations that underlie the attribution of mental states in biological agents.

Background

While deep learning has informed understanding of visual processing, the authors question its applicability to mindreading, which differs markedly from vision and may require distinct objectives, training regimes, and comparative neuroscientific data.

They explicitly state uncertainty about whether deep neural networks can illuminate mindreading at all, underscoring a foundational open question before pursuing specific algorithmic implementations or benchmarks.