Other good idea promoting algorithms: laws

I believe that tallying the number of laws that agree or disagree with a belief can serve as a measure of how strongly society deems something to be wrong.

For example, every society considers murder to be wrong and typically addresses it through some form of criminal justice system.

To quantify this, we can assign scores to conclusions based on the number of laws supporting a belief (e.g., murder is wrong) and the quality of arguments linking a law to that belief. Factors to consider could include the relationship score between the belief and the law, the severity of punishment for violating the law, and the relative number of laws that agree or disagree with the belief or any of its supporting arguments. This can be achieved by creating an equation and implementing it in software.

A comprehensive algorithm could be designed to account for all these factors in the following manner:

Law Score = Sum of scores for (Laws that agree - Laws that disagree) * Linkage Strength between law and the belief (the score of the arguments that the law is truly established on the belief) * Punishment Sevarity

We can represent the relationship between laws and beliefs more concisely using algebra and the following definitions:

Definitions:

• LAn/LDn: Laws that are argued to agree (LAn) or disagree (LDn) with a conclusion.
• LAn+LDn: Total number of laws submitted in this forum as reasons to agree or disagree with a conclusion. To normalize this factor and ensure it carries the appropriate weight, we could tweak multiplication factors or allow users to adjust them.
• LSn: Linkage Score - The linkage would be treated as its own argument, with reasons to agree or disagree, and a score ranging from -1 to 1. A negative score indicates a law that contradicts the intended suggestion, 0 means the law has no relation, and 1 signifies that the law fully supports the intended conclusion.
• Psn: Punishment Severity - This factor considers the classification of the offense (felony or misdemeanor) and the typical punishment duration (e.g., years of imprisonment).

By applying these definitions, we can create a comprehensive algorithm that takes into account various factors to determine the strength of the relationship between laws and beliefs.

Examples: Should the burqa be required or banned?

For instance, the fact that nearly all countries outlaw "murder of innocent adults" indicates the level of validity that most societies attribute to this belief. In some cases, laws might disagree and agree on controversial topics. For example, there are countries that both ban and require women to wear burqas. To measure society's opinion on whether it is wrong to wear a burqa, one could compare the number of countries that ban them (e.g., France) and the number of countries that require them (e.g., Afghanistan, Saudi Arabia). Depending on which side is being supported, the percentage of countries banning the burqa could be added or subtracted from the total number of countries with relevant laws.

Examples: Is shooting an intruder a justifiable action that protects law-abiding citizens, or is it an immoral act that ends a life prematurely?

In this case, one could consider the percentage of states that deem it wrong to shoot an intruder as evidence supporting the belief that it is morally wrong to do so.