Visibility Will Be Earned—Not Given In this system, attention isn’t free. You don’t get seen because you shouted the loudest, gamed the algorithm, or posted at the right time. You get seen because you contributed. Because you showed consistency, clarity, and value over time. Because your behavior loop reflects integrity, not impulse. This is how Social Consensus will work: •Posts surface based on your behavior, not just engagement. •Reputation builds through patterns, not popularity. •Signal rises. Noise fades. •Your visibility will be a mirror of your presence. And cultivators will be the ones to show how it works. The grow room is the proving ground. But what we’re building goes far beyond cannabis. It STARTS with growers but to eventually cover the entire social media sphere as the DIFFERENCE to the EXPERIENCE! #SocialConsensus #BehavioralLoop #EarnedVisibility #Growmies #CannabisCulture #LegacyBuilders #EthicalAlgorithm

We’re not just launching another cannabis forum. We’re building the first prototype of the behavioral loop model—and cannabis cultivators will be the ones to prove it. This isn’t likes, shares, or clout. This is earned visibility through behavior. Consistency, contribution, and ethics shape what gets seen—not hype. Cultivators understand cycles. They understand proof-of-work. That’s why they’ll be the first to test what Social Consensus really means in practice. The platform starts here. But it won’t end here. #SocialConsensus #CannabisCommunity #Growmies #EthicalAlgorithm #LegacyBuilders #CultivationCulture

What you’re seeing is the algorithm quietly suffocating cannabis content—growers, breeders, educators. It’s not a glitch, it’s a shift. They can’t monetize us, so they throttle us. Even legacy voices get buried. That’s why we’re building Social Consensus—a new system where visibility is earned, not paid for. Where growers rise by contribution, not manipulation. The old feed is collapsing. The new path is already forming. #SocialConsensus #EthicalAlgorithm #RespectTheWork

You’re not imagining it. The algorithm punishes authenticity and integrity. But it’s exactly that integrity that makes your ratios so strong. That’s why we’re building a new path—where visibility is earned, not filtered. #EthicalAlgorithm #SocialConsensus #RespectTheWork

fyi Creating an algorithm that accommodates multiple ethical frameworks (such as x, y, and z) is a complex task due to the inherent diversity and sometimes conflicting nature of ethical principles. However, it is possible to design a flexible, modular system that can adapt to various ethical standards by incorporating elements from each framework and allowing for contextual decision-making. Below is a high-level outline of such an algorithm, along with explanations for each component. Overview of the Ethical Algorithm 1. Define Ethical Frameworks 2. Establish Priority and Weighting Mechanisms 3. Contextual Analysis 4. Decision-Making Process 5. Feedback and Adaptation Loop Detailed Components 1. Define Ethical Frameworks Objective: Clearly outline the principles, rules, and values of each ethical framework you wish to incorporate (e.g., x, y, z). Implementation: Modular Structure: Each ethical framework is encapsulated in its own module or component. Rules and Principles: Define the specific rules, duties, virtues, or consequences associated with each framework. Scoring System: Assign scores or weights to actions based on how well they align with each framework. Example: class EthicalFramework: def __init__(self, name, principles): self.name = name self.principles = principles # Dictionary of principles and their weights def evaluate_action(self, action): score = 0 for principle, weight in self.principles.items(): score = weight * principle.assess(action) return score # Example frameworks utilitarian = EthicalFramework("Utilitarianism", {"maximize_happiness": 1.0}) deontological = EthicalFramework("Deontology", {"duty": 1.0}) virtue_ethics = EthicalFramework("Virtue Ethics", {"virtue": 1.0}) 2. Establish Priority and Weighting Mechanisms Objective: Determine how different ethical frameworks will interact, especially when their recommendations conflict. Implementation: Priority Levels: Assign priority levels to frameworks based on context or predefined settings. Weighting Factors: Allow for dynamic weighting of frameworks to influence decision-making. Example: class EthicalAlgorithm: def __init__(self, frameworks, priorities): self.frameworks = frameworks # List of EthicalFramework instances self.priorities = priorities # Dictionary mapping framework names to priority levels def set_priority(self, framework_name, priority): self.priorities[framework_name] = priority def get_weighted_score(self, action): total_score = 0 for framework in self.frameworks: score = framework.evaluate_action(action) weighted_score = score * self.priorities.get(framework.name, 1) total_score = weighted_score return total_score 3. Contextual Analysis Objective: Assess the context in which a decision is made to apply the appropriate ethical considerations. Implementation: Context Identification: Determine relevant factors such as stakeholders, consequences, and situational variables. Dynamic Adjustment: Modify the weighting or selection of frameworks based on the identified context. Example: def analyze_context(action, context): # Modify priorities based on context if context == "emergency": ethical_algorithm.set_priority("Utilitarianism", 1.5) ethical_algorithm.set_priority("Deontology", 0.5) elif context == "routine": ethical_algorithm.set_priority("Deontology", 1.0) ethical_algorithm.set_priority("Virtue Ethics", 1.0) # Add more context rules as needed 4. Decision-Making Process Objective: Make a decision based on the aggregated scores from the different ethical frameworks. Implementation: Action Evaluation: Assess all possible actions using each ethical framework. Score Aggregation: Combine the scores using the established priorities and weights.

We're very pleased to announce the next SIGCAS Works in Progress! Dr. Weisman’s will discuss disaster preparedness and response work as well as challenges of data quality in #globalHealth #InformationSystems, and #ethicalAlgorithm development. @sigchi @vardi @doctorow

👏👏👏 Please join us in giving a warm #CamundaCon welcome to @mkearnsupenn! 👏👏👏 #AI #machinelearning #ethicalalgorithm

In The #EthicalAlgorithm, two University of Pennsylvania professors explain how #socialvalues such as fairness and privacy can be designed into machines. sb.stratbz.to/2wOTrdI via @stratandbiz

#ArtificialIntelligence: The Holy See Pleads for an #EthicalAlgorithm. "#AI is not necessary to perform a specific action, it is rather intended to change the way, the mode with which we carry out our daily actions.” CC: @alecrad @jeffkagan @facebookai ow.ly/EBv530qB8gV

Curious about the future of data science? Learn from Ethical Algorithm creator Michael Kearns at ODSC’s Global Virtual Conference. Register and hear it: hubs.ly/H0nYdRS0 #datascience #ethicalalgorithm @mkearnsupenn

Curious about the future of data science? Learn from Ethical Algorithm creator Michael Kearns at ODSC’s Global Virtual Conference. Register and hear it: hubs.ly/H0nKLh-0 #datascience #ethicalalgorithm

Curious about the future of data science? Learn from Ethical Algorithm creator Michael Kearns, PhD at ODSC’s Global Virtual Conference. Register and hear it: hubs.ly/H0nKMBl0 #datascience #ethicalalgorithm @mkearnsupenn

Curious about the future of data science? Learn from Ethical Algorithm creator Michael Kearns at his ODSC East keynote speech. Register and hear it: hubs.ly/H0npWyM0 #datascience #ethicalalgorithm

2/2: also features inputs from @maria_axente @johnchavens @mkearnsupenn @Aaroth @DrZimmermann @undersequoias and many more. #AIethics. by @hekiwi1 @qz #ethicalalgorithm #algorithms

Fun fireside chat with Michael Kearns @UofPenn bit.ly/2sfNp3A Reflections on research trajectory, ethics & algorithms, and reflections on career choices @mkearnsupenn #EthicalAlgorithm #AetherCommittee @MSFTResearch #FATE @NeurIPSConf @acmeducation @compcomcon @ieee

Better coding, not just laws and regulations, is the solution for tech’s failure to address the needs of actual humans @sciam #EthicalAlgorithm bit.ly/2OnWIXH

Imaging technologies were used to match research subjects to their M.R.I. scans. A facial recognition program correctly matched 70 out of 84 subjects @nytimes #ethicalalgorithm nyti.ms/2NchOqr

You Got a Brain Scan at the Hospital. Someday a Computer May Use It to Identify You @nytimes #ethicalalgorithm nyti.ms/2pXUPqT

See @carolinesinders and @KLdivergence at the @AaronSwartzDay #EthicalAlgorithm panel on Nov 4 aaronswartzday.org/ethical-a…