What is your Bayesian prior on non-human animal emotion?

Although humans have a strong ability to communicate with other humans, we lack the ability to communicate as well with non-human animals. As a result, we know far more about the internal emotional states of other humans than we know about the internal emotional states of non-human animals. Where do we begin to make inferences about the internal states of non-human animals? What is the appropriate Bayesian prior for making inferences about the unknown internal states of non-human animals?

A long time ago, Rene Descartes (1649) posited that non-human animals are akin to machines (have no soul or mind and couldn't feel pain). Since then, it has been considered "scientific" to assume non-human animals actually are machines unless there is overwhelming evidence to the contrary. I propose that this is highly unscientific, and that it is an example of argumentum ad ignorantiam, that the absence of evidence is the evidence of absence. That is, Descartes, and millions since then, have found it convenient to presume that an absence of evidence about non-human animal emotion constitutes evidence of absence of non-human animal emotion.

Another approach to understanding non-human animal emotions, universally taken by infants, is to assume that "all others are like me." Indeed, this is how humans learn about each other. In the absence of a lot of knowledge, we assume that other humans (especially those that look like us) think and feel as we do. This is our Bayesian prior for interactions with other humans. Like Descartes's proclamation that non-humans are machines, this could also constitute a prior for understanding non-human animal emotion.

Is emotion likely to be a synapomorphy shared with a wide range of taxa? In my simplistic way of thinking, I propose two lines of reasoning that suggest it is. First, emotion in humans appears to be regulated in a primitive part of the central nervous system, whose structure is shared with a wide variety of taxa. If it looks like beer, smells like beer, tastes like beer, it might be beer. Second, emotions are useful. Fear and pain are widely recognized for their fitness benefit, for their adaptive value. I suggest that other emotions are likely to have similar fitness benefit. If a behavior generates joy or euphoria or happiness, organisms would be inclined to continue that behavior. Emotions could help provide mechanistic links between biochemistry and behavior.

Bayesian inference is useful in that it requires we think hard and think carefully about our prior beliefs. In that sense, it helps us become more scientific and maybe even more moral.