[andrewdb]

I have found the below to be a good starting point for formulating text into classical formulated arguments.

Intake the following block of text and then formulate it as a steelmanned deductive argument. Use the format of premises and conclusion. After the argument, list possible fallacies in the argument. DO NOT fact check - simply analyze the logic. do not search.

format in the following manner:

Premise N: Premise N Text

ETC

Conclusion:

Conclusion text

Output in English

[the block of text to analze]

[sandspar]

Useful, thanks. Note that the "after the argument, list fallacies" part can be swapped out for other lists.

For example:

1. Evaluate Argument Strength: Assess the strength of each premise and the overall argument. [ChatGPT is an ass kisser so always says "strong"]

2. Provide Counterarguments: Suggest possible counterarguments to the premises and conclusion.

3. Highlight Assumptions: Identify any underlying assumptions that need examination.

4. Suggest Improvements: Recommend ways to strengthen the argument's logical structure.

5. Test with Scenarios: Apply the argument to various scenarios to see how it holds up.

6. Analyze Relevance: Check the relevance and connection between each premise and the conclusion.

[andrewdb]

Those are good suggestions. I will use some of them!

It is also interesting to go back and forth with the model, asking it to mitigate fallacies listed, and then re-check for fallacies, then mitigate again, etc, etc.

I have found that a workflow using pytube into OpenAPI Whisper into the above prompt is a decent way of breaking down a YouTube video into formulated arguments.