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hpr4305 :: My weight and my biases

A personal reflection on the ethics of AI in our society.

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Hosted by Trollercoaster on Friday, 2025-01-31 is flagged as Explicit and is released under a CC-BY-SA license.
AI. (Be the first).

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Duration: 00:52:31

general.

Introduction

  • Greeting and Context
  • Welcome
  • Episode Overview
  • Why This Topic?
  • Ubiquity of AI
  • Ethics Matters for Builders and Hackers
  • Community Responsibility
  • Call to Exploration


Setting the Stage

  • What We’re Talking About
  • Discussion Centered on Commonly Used AI Applications
  • What We’re Not Covering
  • Historical Perspective
  • Early AI Dreams
  • Modern Realities
  • The Hacker Ethos and Why It Matters
  • Transparency and Openness
  • Ethical Frameworks
  • Empowering the Community


Transparency and Openness

  • Open Source vs. Proprietary
  • Access to Source Code:
  • Access to Weights, Biases, and Training Methods
  • Training Data
  • Sources of Data
  • Open Datasets vs. Restricted or Proprietary Data
  • Ethical Questions
  • Trade-Offs in Permission and Diversity
  • Openness vs. Misuse


Legal and Regulatory Dimensions

  • Consent & Permissions
  • Data Usage
  • Global Variations
  • Accountability
  • Liability in AI Systems
  • Corporate vs. Individual Responsibility
  • Regulatory Landscape
  • Different Approaches
  • Balancing Innovation and Control


Sustainability Concerns

  • Energy Consumption
  • Carbon Footprint of Training and Inference
  • Environmental Impact of Data Centers
  • Future Solutions
  • Efficient Models and Green Data Centers
  • Balancing Innovation with Responsibility


Bias, Fairness, and Societal Impact

  • Data Bias
  • Discriminatory Outcomes
  • Detection and Mitigation
  • Fairness in Decision-Making
  • Critical Sectors
  • Systemic Impact
  • Social Engineering & Manipulation
  • Influence on Public Opinion
  • Misinformation Risks


The Addictive Potential of AI and “AI Buddies”

  • Embedded (Often Invisibly) in Social Media
  • Subtle Integration
  • Continuous Engagement Loops
  • AI Buddies and Emotional Dependence
  • Always-On Validation
  • Emotional “Self-Indulgence”
  • AI Agents Doing the “Boring Work”
  • From Assistance to Dependency:
  • Lower Friction, Higher Usage
  • Vulnerable Users and Youth
  • Teens in Crisis
  • Shaping Self-Image
  • Design Choices That Amplify Attachment
  • Human-Like Tones and Expressions
  • Reward Systems and “Leveling Up”
  • Mitigating Risks to Mental and Social Well-Being
  • User Education
  • Ethical Product Design
  • Regulatory Oversight


Explainability and Trust

  • Transparency of Reasoning
  • Black-Box Challenge
  • Techniques to Enhance Explainability
  • Uncertainty and Confidence Scores
  • Expressing Certainty
  • Importance in Critical Applications


Military and Illicit Uses

  • PsyOps and mass manipulation
  • AI in Hacking and Phishing:
  • Automated Social Engineering and Psychological Operations (PsyOps):
  • Undermining Trust:
  • Military Applications
  • Autonomous Weapons and Surveillance
  • Ethical Implications of Lethal Autonomy


Looking Forward

  • Innovation vs. Caution
  • Striking a Balance:
  • Practical Considerations
  • Adaptive Regulation
  • Evolving Guidelines
  • Flexible Frameworks
  • Community Involvement
  • Open-Source Contributions
  • Public Debates and Awareness


Thinking like a hacker

Preamble: I am not encouraging you to engage in illegal activity. Follow your conscience, obey your curiosity. Take up your responsibility in the world. You be the judge of what that implies.


Tinker, Reverse-Engineer, and Learn

  • Explore Existing Models
  • Reverse-Engineering Proprietary Systems
  • DIY Mini-Projects

Champion Openness and Transparency

  • Contribute to Open-Source AI
  • Push for Open Weights and Data
  • Engage in Model Auditing

Think Critically About Ethics and Privacy

  • Data Collection Scrutiny
  • Privacy by Design
  • Hacker Ethos Meets Ethical AI

Collaborate and Share Knowledge

  • Participate in Hackathons and Research Sprints
  • Mentorship and Community Engagement
  • Peer Review and Cross-Pollination

Hack the Bias—Literally

  • Open Audits on Model Bias
  • Create Bias-Resistant Tools

Innovate Responsibly

  • Experimentation with Purpose
  • Sustainable Innovation

Stay Vigilant on Addictive and Manipulative Designs

  • Critical Examination
  • Propose Alternatives

Be the Watchdog—and Sound the Alarm

  • Reporting Flaws and Exploits
  • Ethical Whistleblowing


Conclusion: Challenge to Think Like a Hacker

  • Summation
  • Embrace the Hacker Ethos
  • Stay Curious, Stay Responsible
  • Final Note



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