2024-12-03
author: fenn and llama-3.1-70B
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A social choice function that is not dependent on the number of people involved but rather the quality of their arguments could be called the "Argumentative Consensus" function. This social choice function prioritizes the quality of the arguments presented, rather than the number of people supporting each option. It allows for a more nuanced and evidence-based decision-making process, and can be used in a variety of contexts, from individuals or small groups to large organizations and governments.

Here's a description of how it works:

- Each participant presents evidence and arguments for or against each option, and these are evaluated based on their relevance, validity, and persuasiveness. Irrelevant and unpersuasive arguments are still formally included, but not shown. When new evidence is presented, the affected arguments are re-evaluated.
- The arguments are then aggregated using a probabilistic graphical model, such as a Bayesian network, to determine the probability of each option being the best choice.
- The option with the highest probability of being the best choice is selected as the winner.
- The process is iterative, with participants able to respond to and counter each other's arguments, and the probabilistic model is updated accordingly.
- The process continues until a consensus is reached, or until a predetermined threshold of confidence is achieved, or an externally imposed deadline becomes due.

In order to evaluate which outcome is most desirable, values can be chosen through a process of deliberation and argumentation among the participants:

- A set of core values and priors is established as a foundation for decision-making, providing a consistent guiding framework.
- Additional values are considered on a case-by-case basis, taking into account the specific context and circumstances of each decision.
- Participants propose values that they believe are relevant to the decision at hand. These values can be abstract (e.g. "fairness", "efficiency") or concrete (e.g. "minimize cost", "maximize profit").
- Participants provide arguments and evidence to justify why their proposed values are important and relevant to the decision. This can involve presenting data, expert opinions, or personal experiences.
- The proposed values are aggregated using a probabilistic graphical model, to determine the relative importance of each value. This can involve assigning weights or probabilities to each value based on the strength of the arguments presented.
- The aggregated values are then prioritized based on their relative importance. This can involve using techniques such as multi-criteria decision analysis (MCDA) or multi-objective optimization.
- The prioritized values are then integrated into the decision-making process by using them to evaluate the options. This can involve using techniques such as cost-benefit analysis or decision trees.
- The set of values is refined and updated over time, as new information and experiences are gained, and as the organization or community evolves.

Throughout this process, participants can engage in argumentation and counter-argumentation to challenge and refine the values and their relative importance. The goal is to arrive at a set of values that are widely accepted and that provide a clear basis for evaluating the options.

Some possible techniques for choosing values in this system include: #TODO: read up on these methods and see if they actually make sense

- Value-based argumentation frameworks: These frameworks provide a structured approach to presenting and evaluating arguments about values. Examples include the Toulmin model and the Argumentation Theory framework.
- Multi-criteria decision analysis (MCDA): This technique involves evaluating options based on multiple criteria, which can be used to represent different values. Examples include the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).

This approach would allow for a balance between consistency and adaptability, ensuring that decisions are made in a principled and evidence-based manner, while also being responsive to changing circumstances and new information.