Something to read:

Hierarchical Bayesian Modeling of Human Decision-Making Using Wiener Diffusion http://gandalf.psych.umn.edu/users/schrater/schrater_lab/cou...

Decision Theory and Human Behavior http://www.umass.edu/preferen/Class%20Material/Bounds%20of%2...

Beyond Accuracy: How Models of Decision Making Compare to Human Decision Making http://fileadmin.cs.lth.se/cs/Personal/Carl_Christian_Rolf/c...

Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting http://papers.nips.cc/paper/5180-forgetful-bayes-and-myopic-...

>Our result shows that subjects’ choices, on a trial-to- trial basis, are best captured by a “forgetful” Bayesian iterative learning model [21] in combination with a partially myopic decision policy known as Knowledge Gradient [7].

I don't really want to discourage teenagers from public writing, but if you're really confused about why this is being negatively received...

The most glaring thing: your three argumentative points could be simultaneously true and the assertion "Probabilistic AI can't be AI" could still be false.

My personal suspicion is that it's an ensemble approach involving both probabilistic and symbolic methods. But I think that human intelligence is largely driven by probabilistic methods.

But, I also "am not an AI/ML anything", I just read a lot on the subject and think about it a lot.