I haven't thought this out very carefully. I'm imagining a transformer trained both to predict text, and to predict the next frame of video.

Train it on all available videos that show realistic human body language.

Then ask the transformer to rate on a numeric scale how positively or negatively a human would feel in any particular situation.

This does not seem sufficient for a safe result, but implies that LeCun is less nutty than your model of him suggests.

Why assume LeCun would use only supervised learning to create the IC module?

If I were trying to make this model work, I'd use mainly self-supervised learning that's aimed at getting the module to predict what a typical human would feel. (I'd also pray for a highly multipolar scenario if I were making this module immutable when deployed.)