I upvoted you, and I'm actually glad you asked the question despite downvotes. I imagine those who did are of the opinion that essentially you're ascribing too much function to the neurotransmitters themselves, as opposed to the contexts in which the presence of the neurotransmitters are used as signals.

Take a look at this brain schematic here [0]. I vehemently disagree with some of the presented-as-fact ideological aspects of the article, but the depiction of neurotransmitters working differently in different brain regions is illustrative.

i.e., a dopamine molecule does not already constitute a meaningful coordinate system -- it doesn't have a meaning in and of itself, such as "the reward molecule", or euphoria/"feel-good"/"addiction trap"/excitement molecule) in the brain. Rather, the dopamine molecule has locally-interpreted semantics.

To make this more concrete with examples of different aspects of dopamine alone:

- "dopamine is known to encode the confidence level of motor predictions" - Scott Alexander, psychiatrist [1]

- saturating the synaptic cleft between neurons with released (or non-recycled) dopamine is a part some euphoric processes (e.g. drugs, orgasm, gambling) in the striatum negra

- 'excess' (not a simple thing to determine for individuals imo) dopamine is related with psychosis (not per se causally), and antipsychotics are often designed to blunt dopamine transmission

However,

- dopamine transmission is also fundamentally necessary for muscle movement, in the motor cortex

- additionally, the conscious sensation of dopamine is highly dependent upon the frequency of dopaminergic neuron spikes

- Parkinson's disease is (iirc, said to be,) the result of the degeneration of motor neurons; shakiness, problems sleeping;

What does that mean for AI? Well, if we want to go beyond network topology, and start to use new varieties of component substrates, the individual types of signals they represent must either a) be fairly meaningless outside of a specific context or b) not be suited for learning from evidence and generalization of data. Check out [2], [3], and [4] for more.

[0] http://www.nationalgeographic.com/magazine/2017/09/the-addic...

[1] http://slatestarcodex.com/2017/09/12/toward-a-predictive-the...

[2] https://www.edge.org/conversation/stephen_wolfram-ai-the-fut... (not that i am a huge fan of wolfram :P)

[3] https://www.edge.org/responses/what-scientific-concept-would..., ctrl-f "biological"

[4] https://en.wikipedia.org/wiki/Multi-state_modeling_of_biomol...