PhD Stuff

Hey! So, I'm prepping to enter a PhD somewhere. My objective is to gain entry into something like the dual-PhD program here in Pittsburgh at CMU

Over the next few months, I'll drop a few posts here detailing some of the work I'm doing in prepping for that.

I've had a few nice chats with OpenAI, several well-known philosophers, and technology policy-makers about this over the last couple months.

Verdict's still out. Only time will tell.

Anyway, here's the first post on the subject:

We take propositional abstraction to be the process of “wrapping” any statement in an n-order predicate logic where n > 0 or any declarative expression expressed in the indicative mood into a suitable data structure like JSON equipped with a truth-evaluation through a controlled semantics.

Propositional abstraction example implemented in JSON format:


var propAbstractExample = {
    'truth-value': true,
    'semantics': {
        'cat': 'hat',
        'silly': 'billy',
        'control': {
            'ignore': 'cat'
        }
    },
    'assertion': {
        'silly': 'billy'
    }
}


The semantics can be contained internally with respect to the proposition so abstracted or it can reside externally. Which of these are preferred depends on use-case. For example, if modularity and independence are required we can stick the semantics right into the data structure. This allows each proposition so abstracted to contain different semantics. We can then extract the truth-values in order to perform basic logical operations - and between two or more semantics.

While familiar in Computer Science, in the realm of logic, mathematical logic, computer-assisted philosophy (hehe), etc. no such idea yet exists (that I'm aware of).