The world’s not short on disagreements. Politics, with its ever-clashing perspectives, showcases this in technicolor. Whether that’s a visual treat or a nightmare depends on your vantage point. Historically, our go-to approach for conflict resolution looked a lot like one-sided advertising—or, more bluntly, propaganda. This strategy centered on loudly broadcasting our ‘truths’ while conveniently ignoring counterpoints.

https://pagead2.googlesyndication.com/pagead/js/adsbygoogle.js?client=ca-pub-4525975167034551

However, automated conflict resolution presents a game-changer. It challenges us to move beyond entrenched positions and instead, to recognize our shared underlying interests. Isn’t it intriguing that underneath the loud clashes of disagreement, there often exists a harmonious consensus?

This fresh approach highlights the crucial difference between a stance and the motivation behind it. It’s about grasping the underlying ‘why’ beneath every ‘what’. This isn’t merely about letting in a gust of fresh thought; it’s about building bridges to mutual understanding. Disputes aren’t doomed to be draining battles—they can transform into collaborations where everyone finds common ground.

Emphasizing objective standards ensures decisions aren’t tainted by biases but are based on clear, transparent benchmarks. While the idea of automated conflict resolution may sound plucked from a sci-fi novel, foundational work like the Harvard Negotiation Project has been pointing in this direction for a while. Now, we set our sights on a digital evolution, marrying intuitive algorithms with the power of collective intelligence—think of it as the Wikipedia of conflict resolution.

In this chapter, we’re going on a deep dive. We’ll uncover how automated conflict resolution isn’t merely a tool for mediation but a catalyst for reimagining the very nature of disagreements. Instead of limiting ‘either/or’, we’ll explore the expansive ‘and/both’. So, hold tight—it promises to be quite the journey.

What do we mean by Automated Cost Benefit analysis? It is just a website that:

1) lets us brainstorm potential costs and benefits. It then uses combinations of people and algorithms to categorize them, group similar ways of saying the same thing (to avoid redundancy), and then send them through processes to estimate their individual likelihood.

Automated conflict resolution is a powerful tool that promotes democratic values, conflict resolution, and effective policy selection.

A) Why? The need for Automate Conflict Resolution

The Need for Innovation in Conflict Resolution

Moving Beyond Traditional Approaches

A World Awash with Disagreements: Whether it’s the vibrant clash of Republicans and Democrats or daily skirmishes on social media, conflicts are omnipresent. Historically, our go-to method of conflict resolution has eerily mirrored propaganda — we loudly proclaim our ‘truths’, while conveniently tuning out the counterarguments. But there’s a silent chorus of agreement beneath the clamor of these disagreements, and its high time we tuned into it.

The Case for a New Paradigm: Automated conflict resolution presents an opportunity to break free from the stalemate. Rather than merely trading blows, we start to dance in tune, uncovering shared melodies. It’s all about understanding the ‘why’ beneath the ‘what’. No more exhausting tug of wars; instead, we strive for a shared rhythm.

Harmonizing the Cacophonies of Conflict: The Harvard Negotiation Project has given us solid groundwork. Now, imagine leveraging modern technology, intuitive algorithms, and the power of collective intelligence, akin to Wikipedia at its best. Picture a vast digital orchestra, harmonizing global disagreements.

B) Automating Arbitration, A Tried-and-True Conflict Resolution Algorithm

Understanding Arbitration Algorithms

Applying Automation in Conflict Resolution

The Essence of Arbitration: Historically, when two parties found themselves locking horns, they often turned to arbitration. A neutral third party would step in, weigh the evidence and arguments, and then make a judgment. This traditional method was favored for its speed, confidentiality, and informality compared to litigation.

The Humanity Problem: Even the best arbitrators are only human. With humanity comes unpredictability, potential biases, susceptibility to influence, and, sadly, mistakes. There’s also the simple matter of bandwidth; one person can only handle so many disputes at a time.

Modern Solutions for Age-Old Problems: Automation offers a tantalizing solution to these human-centric issues. By introducing algorithms and technology into the arbitration process, we stand to eliminate or reduce many of these pitfalls. The software can be designed to sift through evidence, cross-reference databases, ensure consistency with past judgments, and render decisions efficiently.

The Upsides: The benefits of this approach are manifold:

Bias Reduction: Machines, when correctly programmed, operate without personal biases. They don’t get swayed by emotions, dramatic narratives, or the stature of the disputing parties.

Speed and Scalability: Automation can handle multiple cases simultaneously, making it possible to address a larger volume of disputes more swiftly.

Consistency: With the right database and algorithm, each decision is in line with previous similar judgments, ensuring predictability.

Challenges Ahead: But as with any innovative solution, there are wrinkles to iron out:

Designing Unbiased Algorithms: Ensuring that our algorithms aren’t inheriting human biases is a significant challenge.

Trust in Machines: Convincing people to trust machine-made decisions will be an uphill battle, especially in cases with high stakes.

Continuous Updates: Technology, societal norms, and laws evolve. Our automated arbitration systems will need regular updates to stay relevant and effective.

Case in Point: [Here, you could introduce a hypothetical or real-world example of how automated arbitration might work. For instance, describe a dispute between two parties, detail how the algorithm assesses it, and what kind of judgment it renders.]

The Road Ahead: Automated arbitration isn’t a magic bullet, but it promises to reshape the landscape of dispute resolution. With careful implementation, rigorous oversight, and an open-minded approach, it could represent the future of fair, fast, and efficient conflict resolution. As technology advances, the harmony between human intuition and machine precision may just become the gold standard in arbitration.

Feel free to adjust, refine, or expand upon this draft as you see fit. I’ve aimed for a balance of informative content and engaging storytelling, while adhering to your request for simplicity and clarity.

C) The 1st Arbitration Algorithm: “Separate people from the Problems”

Why we need to separate problems from personal drama and self-expression.

Separating people from the problems or their pet solutions, sidesteps Biases and the will to “win.”

B) The Power of Well-Designed Online Forums

Function as Neutral Platforms

Structure Pros and Cons Discussions

Evaluate Arguments on Merits, Not Personal Affiliations

C) Utilizing Algorithms for Objective Analysis

Dissecting Arguments into Components

Employing Natural Language Processing, Machine Learning, and Logic

Linking Conclusions to Supporting Evidence

D) Ensuring Transparency and Openness

Displaying the Process and Reasoning

Encouraging Public Scrutiny

Avoiding Hidden Agendas and Biases

E) The Call to Action

Inviting Participation in Fact-Based Decision Making

Finding Common Ground in Political Discussions

F) The Complexities of Virtues

Understanding the Nuances of Compassion, Kindness, and Mercy

Acknowledging Unintended Consequences

Recognizing the Risks of Misplaced Trust

One critical process involved in conflict resolutions is “Separate People from the Problem,” which involves focusing on the issue at hand rather than being sidetracked by people and drama.

Why get bogged down in drama and gossip when we can zero in on the real issues? Political talks can turn into a sticky mess faster than you can say “filibuster.” People tend to pick sides based on party loyalty, much like cheering for your home team, regardless of how badly they’re playing. However, just as we can’t improve our team’s performance by overlooking their weaknesses, we can’t make informed decisions without facing the facts.

That’s where well-designed online forums swoop in like superheroes. They separate the issues from the personalities and affiliations of those involved, So, we can discuss the pros and cons in a structured way. By evaluating arguments based on their merits, not who’s presenting them, we can sidestep biases and focus on the real issues at hand. It’s like wearing a pair of 3D glasses that make all the distractions fade away, leaving only the core issues crystal clear.

Our approach dissects arguments into individual components and uses various algorithms, including natural language processing, machine learning, and logic, to scrutinize each element’s strength. Breaking down arguments allows us to link the conclusion’s power to the supporting evidence, ensuring that decisions are based on the best available information.

To ensure transparency, we provide an open process and show our math. Everyone can see how we arrived at our conclusions and evaluate the evidence’s strength for themselves. It’s like watching the replay of a game to see how a referee made a controversial call. We want everyone to see the evidence and draw their own conclusions, without hidden agendas or biases getting in the way.

So, join us in our mission to evaluate arguments effectively and make well-informed decisions based on facts, not theatrics. With our approach, we can concentrate on the issues that matter and find common ground—even in the most heated political food fights. We believe that our approach can help people make better decisions, based on facts and evidence, rather than on emotion or personal bias.

The virtues of compassion, kindness, and mercy are undoubtedly valuable. However, they cannot be applied universally as one-size-fits-all remedies. There are situations where the application of these virtues can lead to unintended harm. For instance, an excessive focus on compassion towards adults can neglect the needs of children, and misplaced kindness towards criminals might lead to additional victims. Trust, another cherished virtue, when misplaced, can result in tragic outcomes.

How we can automate it

ii. The How: Methods and Strategies

We can combine natural language processing (NLP), sentiment analysis, and topic modeling algorithms to separate people from the problem in an automated conflict resolution system. Here’s a step-by-step process:

Preprocessing: Clean and preprocess the text data from online discussions, removing irrelevant information like emojis, URLs, and special characters. We have already discussed addressing redundancy by developing “equivalency Scores” and identifying “better ways of saying the same thing.”

Topic Modeling: Apply topic modeling techniques, such as Latent Dirichlet Allocation (LDA), to group related comments and identify the main themes or topics in the discussion. This allows the system to separate comments focused on the issues from those centered around personal drama.

Sentiment Analysis: Use sentiment analysis to identify emotionally charged content. This can help detect and filter out personal attacks, aggressive language, and comments targeting individuals rather than focusing on the issue.

Named Entity Recognition (NER): Employ NER algorithms to identify and extract personal names, organizations, and other entities. This can help detect comments that focus on individuals or groups rather than the issue itself. These comments can then be deprioritized or flagged for review.

Argument Acceptance Consistency Tracking: When people indicate that they support arguments when they help their side, keeping track and showing users how the other side uses the same idea to support conclusions the user has rejected. This is commonly referred to as ensuring “what is good for the goose is good for the gander” and can be used to help users use logic consistently.

Anonymize Participants: Assign unique, anonymous identifiers to each participant to ensure that the focus remains on the content of their arguments, not their personal identity or affiliations.

Prioritize Issue-Focused Content: Rank comments and arguments based on their relevance to the identified topics and their logical coherence, prioritizing issue-focused content over personal drama.

Moderate and Filter: Implement a moderation system that flags or filters out content that doesn’t adhere to the guidelines of focusing on issues rather than people. This can be done by setting thresholds for sentiment scores, topic relevance, and entity mentions.

Continuous Improvement: Continuously update and refine the algorithms based on user feedback and performance metrics, ensuring that the system remains effective in separating people from the problem.

By implementing these techniques, an automated conflict resolution system can promote democratic values and effective policy selection by focusing on issues rather than personal drama.

iii. The Code: Implementing Algorithms

Check out the GitHub for the latest code!

https://github.com/myklob/ideastockexchange/wiki/Automated-Conflict-Resolution#code-to-separate-people-from-the-problem

Online conflict resolution and arbitration techniques can be employed to foster democratic values, effective conflict resolution, and the selection of optimal policies. “Getting to Yes,” a book by Roger Fisher and William Ury of the Harvard Negotiation Project, presents a method of “principled negotiation,” often called “Conflict Resolution.” The book provides a proven, step-by-step strategy for reaching mutually acceptable agreements in every conflict. Automating these steps through a well-designed web forum can enable the internet to support democracy rather than hinder it.

Moreover, we can combine online conflict resolution with Collective Intelligence techniques (not AI) and Google’s PageRank algorithm to evaluate solutions, encourage reason, and build a better society.

By implementing the following conflict resolution methods, media platforms can facilitate more informed democratic interactions:

Separate the people from the problem.

Insist on using objective criteria.

Focus on interests, not positions.

Invent options for mutual gain.

These methods can foster more intelligent and respectful conversations online, leading to a better-informed citizenry, improved policies, and a stronger democracy.

Social media platforms like Twitter, Facebook, and YouTube have organized issues chronologically and by their ability to control and manipulate our emotions. This organization has resulted in societal problems such as misinformation, echo chambers, and cyberbullying. More crucially, our reason-based approach to life gives way to emotion and manipulation.

Embracing more intentional strategies for open and transparent conflict resolution and dialogue on social media can help address these issues and promote healthier democratic interactions.

Automated conflict resolution is a promising tool for promoting democratic values and resolving online disputes. By using objective criteria, focusing on interests rather than positions, inventing options for mutual gain, evaluating solutions collectively (not artificially), and promoting reason through Google’s PageRank algorithm, we can create a more intelligent and respectful online environment and evidence-based political parties.

B) Focusing on Interests, not Positions

Focus on Interests, not Positions” is the second step to conflict resolution, as described by Fisher and Ury in their influential book, Getting to Yes.

How to create forums that automatically focus on interests not positions.

We will brainstorm the likely interests of individuals who support and oppose each belief. Additionally, we will identify shared and opposing interests between these groups. To further evaluate their significance, we will categorize them within Maslow’s hierarchy of needs and assign validity scores based on the performance of pro/con arguments. This will help determine the relative importance of each interest compared to others.

Why

In political discussions, people often prioritize “winning” or obtaining their pre-stated position. Once they focus on a specific solution or their stated position, they fail to entertain alternatives that might be better for both sides.

Professional arbitrators, mediators, and experts in conflict resolution emphasize the importance of identifying each side’s valid stated and unstated interests rather than letting disputing sides repeat why their pre-defined solution or position is the best.

Focusing on interests allows us to be dispassionate evaluators of costs and benefits rather than blindly adhering to a position out of a desire to “win” or due to confirmation bias, saving face, or other psychological factors.

Even news outlets often fall into the trap of emphasizing winning and losing, distracting from the possibility of elegant win-win solutions.

Therefore, designing a web forum that can identify each side’s most likely interests or motivations will be highly beneficial. By promoting a more open-minded and constructive approach to discussions, such a forum will facilitate the discovery of mutually agreeable solutions and improve the quality of political discourse.

How?

Our process for focusing on interests, not positions, involves the following steps:

Evaluate the arguments supporting a particular belief and identify the values or interests (pre-conditions) that must be accepted for those arguments to be valid. This involves utilizing our argument importance score and analyzing pro/con sub-arguments to uncover the root motivating interests.

Identify individuals who strongly represent one side of the belief. Request that these individuals share their values, interests, and reasons for defending that side.

Reward participants who submit the potential values and interests of each side.

Reward users who post reasons for agreeing or disagreeing that each side can be characterized as being motivated by specific interests and motives. Develop scores to quantify how much each side agrees with characterizing holding particular values or being motivated by certain interests.

Use algorithms, such as our modified version of the Google PageRank algorithm, argument-to-conclusion linkage scores, and truth, relevance, and relevance scores, to evaluate the relative performance of the pro/con arguments.

Allow pro/con arguments that each interest or value should be categorized or prioritized within different hierarchies (e.g., Maslow’s hierarchy of needs). The performance of these arguments is used to categorize the interest.

Allow pro/con arguments that each interest or value is more or less important than other values, interests, or needs. The performance of these arguments is used to indicate the degree to which the motives of each side are essential.

Following these steps generates Interest Attribution Confidence Intervals (IACI), which indicate the strength of the evidence that we have accurately identified the interests of each side. Interest Validity Scores (IVS) are then produced in the last two steps, which indicate the categorization and prioritization of interests.

By following this process, we can create a more constructive and productive environment for political discussions, identifying areas of agreement and disagreement and working towards solutions that meet both sides’ needs. This process can also help detect potential biases and ensure that our discussions are based on logic and evidence, ultimately leading to a more informed and engaged citizenry. Focusing on interests, not positions, is crucial for achieving this goal.

Tailoring Solutions to Individual Values and Priorities

To tailor the recommended solution to individual users, we can let them adjust different knobs that align with their values. For instance, different users may prioritize justice, forgiveness, charity, and responsibility to varying degrees. They may also have different levels of willingness to avoid harm, provide care, ensure fairness, punish cheating, ensure liberty, fight personal oppression, require loyalty, punish betrayal, respect authority, promote subversion, value sanctity, or prevent degradation. Additionally, they may have different risk tolerances for various groups. It’s essential to allow users to adjust these inputs. We will seek comprehensive lists of reasons to agree and disagree with every belief.

Less philosophical (more boring) decisions can also alter complex algorithm outcomes. For example, we could consider the ratio of evidence supporting or weakening a belief, or we could count the total number of reasons to agree minus the number of reasons to disagree. Users should be able to play with these factors to determine which scoring method produces which recommended actions.

It is important to consider not only the total number of reasons to agree or disagree but also the hierarchy of reasons, such as further removed reasons to agree or disagree, akin to a tree structure, with reasons to disagree with a reason to disagree being a reason to support the initial belief. Additionally, one should evaluate the past success of societies that have adopted different philosophies and how it relates to the current situation. It is crucial to assign the most points to the strongest arguments and carefully evaluate the validity of each argument before making a decision.

With the list of reasons to agree and disagree, one can determine what causes the score to change.

We cannot base our future on the emotional needs of those who refuse to acknowledge valid reasons to oppose their decisions. Therefore, we should embrace reason and logic, which are critical for Democracy to thrive.

While not everyone wants to live rationally and many prefer to make emotional decisions, it is crucial to have a well-organized list of reasons to agree or disagree with each decision. We must be willing to leave confirmation bias, anecdotes, and intuition in the past and move forward to make data-rich decisions that are not affected by outdated notions.

It is not about taking away people’s right to be irrational, but we shouldn’t build our future based on the emotional needs of people who ignore valid reasons to oppose their decisions.

Perfection, i.e., reaching everyone, or defeating other parties with elections, should not be the enemy of improvement, i.e., reaching anyone. We don’t must convert a specific number of people for the effort to be worthwhile.

Internal motivation to uphold the principles of justice is more critical than external motivation to win. Justice is depicted as a woman holding a scale, weighing pros and cons. We should try to be worthy of justice. We should uphold both sides of the argument, even if it means going against our beliefs. Winning is a hollow victory when we only show one side of the argument. Self-integrity should prevent us from enjoying a victory if we never permit the other side to take the field or even play devil’s advocate on our website.

Making better decisions involves considering the cons to our natural inclinations, which will ultimately result in a better life. We all need a friend who is willing to call BS on us, and we need the same politically. We, for our own selfish purposes, should want costs and benefits on the same page. If we are going to share information online, it should be in an environment that corrects misinformation.

People who go to the environment to outline their arguments cannot avoid making their arguments, even if people do not listen. An inborn desire to work our beliefs out with others, share our arguments, test our ideas, and update our assumptions, drives us to be part of this process, independent of how many people follow us.

When thinking about people who need direction, such as kids, it is essential to provide an organized cost-benefit analysis forevery decision. It can be frustrating to find one’s way on every single issue without any guidance. Kids shouldn’t must read through contradictory advice and weigh all the arguments for themselves. We need to provide honest arguments for both sides on the same site, So, kids don’t must start with a clean slate and can instead start off standing on the shoulders of giants.

In politics, winning is often what matters, much like in war. However, as there are no winners in stupid wars, there is no winning in partisan winning. If you defeat a man against his will, he is of the same opinion still. The only enduring way to “win” is to listen to those who, in good faith, believe we are in the wrong. We have met the enemy, and he is our overconfident self.

Customizing Solutions Based on User Values and Priorities

We can customize the recommended solution by considering well-organized lists of reasons for and against a solution and considering each user’s values. For instance, users may prioritize justice, forgiveness, charity, and responsibility differently. They may have varying levels of willingness to avoid harm, provide care, ensure fairness, punish cheating, ensure liberty, fight personal oppression, require loyalty, punish betrayal, respect authority, promote subversion, value sanctity, or prevent degradation. They may also have different risk tolerances for various groups. Users should be able to adjust these inputs and view the recommended solutions that align with each preference.

Code

View the Latest Code on Github:

https://github.com/myklob/ideastockexchange/wiki/Automated-Conflict-Resolution#code

Types of Needs:

Physiological needs

According to Maslow’s hierarchy of needs, meeting our physiological needs is the foundation upon which all other levels of human motivation rest. These needs are the biological requirements necessary for human survival and are driven by internal motivation. Without satisfying our physiological needs first, we cannot pursue higher levels of intrinsic satisfaction.

Some examples of physiological needs include air, heat, clothing, hygiene, light, water, food, excretion, shelter, and sleep. These needs must be met to keep the human body in a state of homeostasis. For instance, air is a physiological need that is more critical than higher-level needs, like a sense of social belonging.

When a person is struggling to meet their physiological needs, they are unlikely to focus on safety, belonging, esteem, and self-actualization needs. These higher-level needs can only be pursued once basic physiological needs have been satisfied. In other words, meeting our physiological needs is the first step toward fulfilling all other aspects of our lives.

By satisfying our physiological needs, we can prevent disruptions to the body’s regulation and avoid cravings like hunger and thirst. This allows us to function at our best and strive towards achieving our goals and aspirations. Meeting our physiological needs is crucial for our overall well-being and is the foundation of our human hierarchy of needs.

Safety needs

Equality

The numbering system below describes a system that scores groups of people within a range of 1 to 10 by how much they value equality.

These people undervalue equality. People who value equality at a “1”, do not value equality very much. These people are willing to accept inhuman or unnatural cruelty to others or specific groups. They do not value all life equally. People from their group (family, race, nationality) are acceptable. However, they give little or no concern to those from other groups or actively seek to harm those from other groups.

These people overvalue equality. Someone who overvalues an otherwise positive value like equality would be willing to sacrifice other good values to satisfy equality. These people are not only willing to steal from Peter to give to Paul. Still, they are willing to trample over concepts such as “freedom of choice,” the “law of the harvest,” justice, or the practical application of mercy to ensure that Peter does not have anything more than Paul. An example of someone overly concerned with equality hates the strong, consequential, or beautiful. These people are not just concerned about equality of opportunity but also equality of outcome. They are willing to sacrifice freedom and require massive power to guarantee the outcome they see fit. They don’t care if anyone is happy, just that no one is happier than others. They are So, concerned with equality that they cannot accept that truly evil might be sad or noble people to experience any happiness. They feel bad for Hitler. These people would say that no tradition, norm, or action is wrong or worse than other actions. It is wrong to say that someone is bad and another person is good. We are all equal; therefore, everyone can be whatever they want if they are not better than someone else.

Equality to the Extreme can lead to evil Communism & The French Revolution

All principles and political philosophies are stupid when taken to the extreme.

We need Algorithms that mediate (or balance) opposing interests and principles

Love and social belonging needs

After the physiological and safety needs are met, the third level of human needs is interpersonal and involves a sense of belongingness. According to Maslow, humans possess an inherent need for acceptance and a sense of belonging among social groups, regardless of their size. Being part of a group is crucial, whether in work, sports, friendships, or family. The sense of belongingness comes from “being comfortable with and connected to others that results from receiving acceptance, respect, and love.” Large social groups may include clubs, religious groups, professional organizations, sports teams, gangs, and online communities.

In contrast, small social connections may include family members, intimate partners, mentors, colleagues, and confidants. Humans need to love and be loved, both sexually and non-sexually, by others, according to Maslow. Without this love or belonging element, many people become susceptible to loneliness, social anxiety, and clinical depression. This need is extreme in childhood and can override the need for safety, as evidenced by children who cling to abusive parents. Deficiencies in hospitalism, neglect, shunning, ostracism, etc., can adversely affect an individual’s ability to form and maintain emotionally significant relationships. Mental health can significantly impact an individual’s needs and development. When an individual’s needs are not met, it can cause depression during adolescence. Children in higher-income families are less likely to experience depression because all their basic needs are met. Studies had shown that when a family experiences prolonged financial stress, depression rates are higher because their basic needs are not being met and because this stress strains the parent-child relationship. The parents are stressed about providing for their children, and they are also likely to spend less time at home because they are working more to make more money and provide for their family.

Social belonging needs include:

Family

Friendship

Intimacy

Trust

Acceptance

Receiving and giving love and affection

This need for belonging may supersede physiological and security requirements, depending on the strength of peer pressure. Conversely, for some individuals, the need for self-esteem is more critical than belonging, while for others, the need for creative fulfillment may be more important than even the most basic needs.

Esteem needs

Esteem refers to the respect and admiration a person has for themselves and from others. It is an essential psychological need, and most people require stable esteem based on their actual capacity or achievement. According to Maslow, there are two types of esteem needs: the “lower” version involves a need for respect from others, which may include status, recognition, fame, prestige, and attention. The “higher” version involves a need for self-respect, which includes strength, competence, mastery, self-confidence, independence, and freedom. These two versions of esteem needs are interrelated rather than separate.

Esteem is developed through day-to-day experiences that provide opportunities for personal growth and self-discovery. It is especially critical for children to have positive and successful experiences that help them develop a sense of self and discover their competence and capability as learners. Adults, such as parents and educators, must create a supportive environment that provides children with opportunities to develop their skills and a positive sense of self. Maslow also noted that the need for respect or reputation is essential for children and precedes real self-esteem or dignity, reflecting the importance of both internal and external sources of esteem.

C Invent Options for Mutual Gain (i.e., Brainstorming Solutions)

Getting to Yes recommends the brainstorming session, where we “Generate a variety of possibilities before deciding what to do.” With the vast potential of the internet, we could brainstorm solutions and analyze difficulties, but there is no well-organized website for it yet. Conflict resolution teaches that groups should be large enough for various opinions but small enough foreveryone to participate. To prevent a single person from monopolizing the conversation, we should organize web forums by topic, like Wikipedia. Each problem should have a list of “best” solutions, ranked by the ratio of potential benefits to costs.

Online forums can guide participants through conflict resolution steps, and we can follow these principles:

Disputing sides meet at the proverbial “negotiation table” with one website for “pro” beliefs and another for “anti” beliefs.

The system incentivizes users to evaluate the top “pro” reasons before voting “anti.”

To enhance argument evaluation, we can create systems ranking argument validity, build conclusion strength on supporting/opposing arguments’ relative strength, and perform online cost-benefit analyses. We can allow crowdsourcing of reasons to prioritize assumptions.

There are many ways to: “Invent options for mutual gain” in well-designed online forums.

We can make the internet a force for good by promoting open dialogue, mutual understanding, and democratic values. An online platform that incorporates conflict resolution and arbitration techniques can achieve this goal. Facebook, Google, and Microsoft could promote more intelligent democratic online interactions by adopting conflict resolution techniques, such as separating the people from the problem, focusing on interests, inventing options for mutual gain, and insisting on using objective criteria.

To separate the people from the problem in online forums, we can focus on the issue or problem at hand instead of the people involved. This strategy helps to minimize personal biases and emotional responses and can lead to more productive discussions. To focus on interests, not positions, we can generate opposing or shared interests between conflicting parties and identify their genuine interests and motivations. By inventing options for mutual gain, we can sort solutions based on their likelihood of meeting the valid claims of each party, using techniques such as placing interests within Maslow’s hierarchy of needs. Finally, to insist on using objective criteria, we can evaluate scientific studies that both agree and disagree on the issue and rank them based on their relevance, scientific rigor, number of participants, and conclusiveness.

It’s important not toe that this isn’t an attempt to put technocrats or nerds in charge. Instead, the goal is to promote a democratic evidence-based political party that shows its math and allows anyone, like on Wikipedia, to comment on the assumptions, likelihood of costs, benefits, or risks. Let’s move beyond the chaos and divisiveness of social media and build a platform that brings us together, not tears us apart.

D Insist on using objective criteria

E Automatic Conflict Resolution For the People

i) Conflict resolution probability

ii) Short and Long-Term Costs and Benefits

For crucial issues, it’s necessary to examine short-term and long-term costs and benefits separately. By evaluating the costs and benefits of each issue, we would already be ahead of existing political parties.

Reasons to agree:

Current political parties tend to consider costs only when they oppose an idea.

Conversely, current political parties tend to focus on benefits when they support an idea.

It is important not toe that effective altruism or evidence-based policy does not presume to judge between causes or individuals with different goals. As humans, we all share common needs like food, water, shelter, pollution-free environments, access to resources, transportation, and more.

While evidence-based policy may not instantly solve every problem, it aims to identify the most effective ways to achieve universally desired outcomes, such as reduced corruption, better representation, lower crime rates, improved criminal justice, enhanced test scores, fewer carbon emissions, decreased pollution, more efficient use of taxes, reduced death and suffering, increased biodiversity, preserved natural habitats, mitigated global warming, and promoted recycling.

In some cases, balancing competing interests from different groups is necessary. However, pointing out that a solution is not perfect is not a valid criticism.

Explanation: Each argument will have scores for the importance of the proposed benefit and the likelihood of it being achieved by accepting the statement or belief. These are organized by Maslow’s hierarchy of needs and sorted by importance and likelihood score.

Physiological or homeostasis benefits related to food, water, and shelter:

Potential safety benefits such as personal, financial, health, and well-being:

Likely social belonging benefits, including friendships, intimacy, and family:

Self-esteem and self-actualization benefits, such as freedoms related to mate acquisition, parenting, using abilities and talents, and pursuing goals and happiness:

Other types of benefits (submit a new category)

iii) Required Compromise Level

F) Code Variables:

Variables for determining the size of each cost or benefit:

CI: Current Impact Size – The current predicted impact size of the cost or benefit, measured in the specified units of measurement.
IT: Impact Type – Indicates whether the impact is a cost or a benefit.
PIM: Proposed Impact Multiplier – Allows users to propose different values to multiply the current predicted size of the cost or benefit.
UoM: Units of Measure – The specified units of measurement used to quantify the impact size of the cost or benefit.
CA: Cost or Benefit Amount – The actual value or amount of the cost or benefit once actual values become available.
Variables for assessing the likelihood of each cost or benefit:
CIL: Current Impact Likelihood – The current likelihood or probability of at least a specific amount of cost or benefit. We will use a normal distribution to represent the likelihood of the impact size and alter the shape of the bell curve based on the performance of the pro/con arguments.
IM: Impact Multiplier – The proposed value to multiply the current predicted size of the cost or benefit.
CL: Confidence Level – The confidence level associated with the proposed impact multiplier.
Variables used for both:
UOM: Units of Measurement – The specified units of measurement used to quantify the impact size of the cost or benefit.
L: Likelihood – The likelihood or probability of at least a specific amount of cost or benefit. We will use a normal distribution to represent the likelihood of the impact size and alter the shape of the bell curve based on the performance of the pro/con arguments.
A: Amount – The actual value or amount of the cost or benefit once actual values become available.

Note: There may be additional variables needed depending on the specific decision being analyzed. These variables should be identified and defined as needed.

Strength of Evidence for Ranking Arguments and Conflict Resolution

Identifying Costs and Benefits

List potential costs and benefits

Group them according to relevant impact categories (e.g., environmental, social, economic)

Tag each cost and benefit with their respective source (e.g., Congressional Budget Office, think tanks, university, specific online user, etc.)

Evaluating and Ranking Sources

Assess the reliability and credibility of sources

Rank sources based on their past performance and accuracy in predicting costs and benefits

Assign a Source Confidence Interval to each source based on their ranking

Tracking the performance of the belief that this factor (the Source Confidence Interval) is essential, to determine it’s multiplication factor.

Weighing the Likelihood of Each Cost and Benefit

Use Google’s PageRank algorithm to rank arguments for or against different likelihoods by their strength of arguments and evidence

Evaluate arguments based on the following criteria:

Truth: Is the argument logically sound or verifiable from independent (blind or double-blind) replications?

Importance: In a cost-benefit analysis, how great of an impact should an argument have relative to the other arguments if it were assumed true?

Relevance: To what degree can we say an argument should strengthen a conclusion if it were assumed to be true?

Evaluate the causal relationships and assumptions associated with each cost and benefit

Assess the accuracy of these relationships and assumptions under different scenarios over time, and reasons why they should be altered in specific ways or abandoned all together

Assign linkage scores and confidence intervals to the causal relationships and assumptions

Incorporate the evaluation of causal relationships and assumptions into the overall likelihood assessment for each cost and benefit

Combining Information to Determine Likelihood

Use the rankings and confidence intervals from both source evaluation, argument strength, and causal relationship assessments to determine the overall likelihood of each cost and benefit

Incorporate this likelihood assessment into the overall cost-benefit analysis

In conflict resolution and mediation, ranking arguments by the strength of evidence can help to identify the most convincing and credible arguments, leading to better decision-making and conflict resolution. One approach to achieve this is to use Google’s PageRank algorithm, which can be applied to rank arguments based on the likelihood of their cost and benefits.

Google’s PageRank algorithm was used to rank the “best” websites for each topic, and has helped the company to earn more than $822 billion as of 2020. The patent for PageRank expired in June 2019, which means that the algorithm can be used to rank arguments with similar math used to rank web pages.

PageRank works by counting the number of links to a website as “votes” for its quality, but not all votes are equal. Google ranks the quality of links from a website by the number of links to that site, both direct and indirect. By analyzing the connections between different websites, PageRank can identify the most influential and credible sources on a given topic.

Similarly, we can apply PageRank to rank arguments by their strength of evidence. Suppose we have several pro and con arguments for any belief or conclusion. Each argument should be evaluated based on the following criteria: