The logic system should not only be valid but also realistic.
✅ VALID: well-structured arguments, but not necessarily ensuring the correctness of the conclusion.
✅ REALISTIC: well-structured arguments that can provide a realistic conclusion.
✅ SOUND: well-structured arguments that can sufficiently adopt reality.
Why is classical 'premise-conclusion' (deductive) logic less realistic❓
〰 Classical logic elements include propositions, conjunctions, disjunctions, implications, negations, and quantification.
〰 Also rules like modus ponens, modus tollens, law of identity, law of non-contradiction, and others. These are good but do not encompass all the elements of life that are contextual.
✅ How can these contextual elements be adopted❓ By adopting probability.
A classic example of reasoning with probability is using 'Naive Bayes."
Optimizing Realism
So, how can classical logic be optimized to be more realistic while still maintaining its fundamental characteristics❓ Simply put,
Avoid involving short premises. For one premise, it can be as long as one paragraph, so that all relevant contexts are adequately involved.
Do not equate it to reasoning cause and effect, which, even with limited data, can still be maintained realistically.
Example of minimal context premises:
🧿 A = B (Not Moving - Rock)
🧿 C = A (Cat - Not Moving)
👉 C = B (Cat is Rock) ❌
🧿 A = B (Breathing - Human)
🧿 C = A (Cat - Breathing)
👉 C = B (Cat is Human) ❌
Compare with cause-and-effect reasoning...
📌 Create the collection
〰 Not Moving = {Rock, Cat}
〰 Breathing = {Human, Cat, ...}
📌 Create the flowchart
💈 Not Moving > {rock, cat}
💈 Breathing > {human, cat}
It is evident that the cat is not a rock but another different member in a set.
Short Premises vs. Long Premises
Even when you're not that astute, by using adequate premises, it may still be inadequate if the explanation is not sufficiently long.
This is an example comparing too short premises with their longer versions. You can see that after lengthening the premises, what previously could have been a premise-conclusion arrangement becomes difficult.
Example:
🧿 A = B (Not Moving - Rock)
🧿 C = A (Cat - Not Moving)
👉 C = B (Cat is Rock) ❌
🧿 Not Moving Without Sleeping is Like a Rock
🧿 The Cat is Not Moving Because it's Asleep
👉 The Cat is Not a Rock❓
This indicates that by accepting sufficiently long premises, it will be easy to identify its anomalies, and we can create a new, more realistic premise-conclusion.
I added '(reality)' in parentheses to make it more realistic.
🧿 Not Moving Without Sleeping is (Like) a Rock
🧿 The Cat is Not Moving Without Sleeping (let's say = dead)
👉 The Cat is (dead) (like) a Rock ✅
FILTER
So to reason validly using classical logic, which is simpler than other logics, use longer premises.
Even if you accept short premises, lengthen them to reveal the context. From here, it will be apparent whether the two premises previously accepted as an argument can still be accepted or rejected (due to its anomalies).
With such precision (vigilance), reasoning using classical logic becomes more realistic. Not only because (whether conscious or not) we are forced to examine cause-and-effect relationships in a premise more carefully, but also capable of formatting arguments with little risk of misunderstanding and able to detect anomalies.
How long should a premise be❓As long as you clearly see its contextual direction to compare with the context in the second premise, thus making the comparison of conclusions relevant.
OBJECTIVITY OF PREMISES
Ensure that lengthening premises involves direct field testing to see consistent cause-and-effect relationships, or if direct testing is not possible, lengthen the premises using data from objectively proven experiences.
If you can do this, you will be surprised to see that your previous reasoning using classical logic reveals its previously unnoticed errors, replaced with more sensible (realistic-objective, also stemming from realistic premises) corrected conclusions.
