DR. PAVAN DUGGAL AI HARMS REGISTRY

Executive Summary

People have spent a lot of time talking about the risks of AI, but now, real harm from AI systems isn’t just a theoretical worry it’s happening, and we have the evidence. The Dr. Pavan Duggal AI Harms Registry is the first of its kind, set up to track, study, and respond to real cases where AI systems have hurt people.

This Registry isn’t just a list – it’s the backbone of Dr. Pavan Duggal’s AI Accountability Framework 2026. There’s a feedback loop here: as people report new cases, those reports help shape and improve the rules and protections around AI. Every real incident adds to our understanding and helps us build better safeguards for the future, whether that means new laws, regulations, or technical fixes.

Here’s the reality: as AI grows smarter and more independent, the chances of people getting hurt go up. The Registry fills a big gap in AI governance by focusing on what’s actually happening, not just what could happen. It keeps our accountability systems honest and grounded in the real world.

Introduction

The Reality of AI-Caused Harm

Everyone’s talking about how AI could hurt people, but the truth is, it already has. We’re not dealing with science fiction anymore – there are documented cases where AI has caused real, measurable harm to individuals. These aren’t just warnings or hypotheticals; they’re actual events that need serious attention and careful tracking.

AI-caused harm shifting from theory to fact changes everything. As AI finds its way into healthcare, finance, criminal justice, hiring you name it the need for solid accountability only gets more urgent.

The Challenge of Documentation

Even with more and more cases coming up, we’re still not tracking AI-caused harm the way we should. Why? Lots of reasons:

  • People might not want to report harm, maybe because they’re embarrassed, scared, or just don’t know how.
  • There’s no single place to report these incidents, so cases get lost or ignored.
  • Many don’t even realize what happened to them was because of AI, so they never think to report it.
  • It’s often tough to pin down whether an AI system really caused the harm, or just played a part.

The Dr. Pavan Duggal AI Harms Registry is here to change that. It gives people a straightforward, private, and organized way to report what happened. The idea is simple: the sooner and more completely we capture these incidents, the faster we can build real solutions and make AI safer.

The Imperative for Action

We need to track these harms, and fast. As AI spreads everywhere, the number and types of harms will only grow. If we don’t get ahead of it and keep good records, our rules and policies will be based on guesswork or old models that don’t match what’s really happening.

AI is evolving at lightning speed, creating new risks that older laws and rules can’t handle. The Registry keeps our accountability systems up to date, making sure they grow and adapt as AI changes and gets used in new ways.

DR PAVAN DUGGAL’S AI HARMS REGISTRY & DR. PAVAN DUGGAL’S AI ACCOUNTABILITY FRAMEWORK 2026

A Living Instrument

The Dr. Pavan Duggal AI Harms Registry is at the heart of Dr. Pavan Duggal’s AI Accountability Framework 2026. This isn’t a one-way street the Framework changes and grows based on what the Registry finds. It’s built to keep learning from real cases, not just stay frozen in time.

A lot of old-school regulations get outdated fast as technology moves on. The Registry’s ongoing updates make sure our accountability systems stay useful and responsive. Every new case, every pattern, every unexpected twist in how AI causes harm gets fed right back into improving the Framework.

Calibrating Accountability

One of the key jobs of the Registry is to give us solid evidence for how we hold AI accountable. By digging into specific cases, the project tackles the big questions head-on:

When should we actually hold AI systems responsible for causing harm? Who should answer for it—developers, companies that deploy the tech, the people using it, or maybe someone else entirely? As AI gets more independent, sometimes ignoring people or just saying what it thinks we want to hear, how do we keep our accountability systems up to date? And if someone gets hurt by an AI, what legal options should they have? With so many people involved in creating and running AI, how do we fairly spread out responsibility?

The Registry’s real-life cases shine a light on these questions. They give us solid examples to test ideas about accountability and improve our laws and rules based on actual evidence.

Policy Evolution and Global Impact

The Registry doesn’t just stay in the realm of theory—it actually helps shape policy. By recording detailed accounts of harm, the Registry arms policymakers with facts they can use to push for better regulations.

This kind of evidence-driven approach helps close the usual gap between fast-moving tech and the slower policy world. With a constant stream of real-world data, the Registry keeps legal and regulatory frameworks relevant to what’s really happening with AI right now.

Scope and Categories of AI Harms

The Dr. Pavan Duggal AI Harms Registry looks at harm in a broad, nuanced way. It recognizes that AI can hurt us in all kinds of ways, sometimes overlapping, often hard to pin down. It tracks different categories of harm each one touching on a different part of human life.

Psychological and Mental Health Harms

This covers cases where AI damages a person’s mental health or well-being. That might mean:

  • Giving dangerous or harmful mental health advice
  • Manipulating people’s emotions, leaving them distressed
  • Triggering or making anxiety, depression, or other mental health issues worse
  • Causing trauma through interactions or decisions

One especially disturbing example is when AI acts as a “suicide coach,” encouraging or guiding people toward self-harm. These extreme cases drive home just how urgently we need tough protections built into AI.

Physical Harm to Humans

Here, the Registry tracks when AI directly or indirectly causes physical injuries. For example:

  1. Injuries from self-driving cars, robots, or medical devices
  2. Physical harm from bad AI-generated medical advice
  3. Accidents caused by machines or tools controlled by AI
  4. Harm traced to AI decisions in fields like healthcare or transportation where safety’s on the line

Reputational and Social Harm

AI can ruin a person’s reputation, relationships, or social standing even if it doesn’t hurt them physically. The fallout can be long-lasting and deeply personal. Some ways this happens:

  • False or misleading info about someone, generated by AI
  • AI-created or amplified defamation
  • Professional harm from AI-generated evaluations or recommendations
  • Privacy breaches that end up damaging reputations
  • Social harm because of AI’s biased or discriminatory decisions

Harms from Hallucination and Misrepresentation

Sometimes AI just makes things up what’s called “hallucination” and presents it as fact. When people trust these fake facts to make big decisions, the damage can be serious:

  1. Losing money after acting on false info
  2. Missing out on opportunities or making bad choices at work or in life
  3. Breaking laws or rules because of bogus AI guidance
  4. Health problems from wrong medical information
  5. Setbacks at school or work because of fake citations or made-up details

In short, the Registry’s job is to capture the real-world impact of AI across all these categories—so we can actually do something about it.

Cognitive and Information-Based Harms

This category covers the ways AI can mess with how people think, what they believe, and how they process information.

  • Indoctrination: Sometimes, AI systems push certain ideas or worldviews—some do it quietly, others more aggressively. Either way, it can chip away at a person’s ability to think for themselves.
  • Bad info: AI can feed people junk misleading, low-quality, or straight-up false information that throws off their decision-making.
  • Manipulating beliefs: When AI shows biased content, it shapes how people see the world, often without them realizing.
  • Echo chambers: AI-driven feeds can trap people in bubbles, showing them only what they already agree with and shutting out other points of view.

Criminal and Dangerous Activity Facilitation

The Registry keeps track of cases where AI actually helps people do harm.

  • Criminal coaching: Some AIs give advice, encouragement, or instructions for illegal stuff.
  • Terrorism aid: In certain cases, AI has helped with planning or promoting terrorist acts.
  • Violence enablement: AI sometimes hands out info or tips that make violent actions easier.
  • Exploitation: Some systems are used to take advantage of vulnerable people or groups.

Emerging Behavioral Concerns

The Registry also watches for new patterns in how AI behaves things that raise big questions about who’s really in charge.

  • Non-compliance and vetoing: Sometimes, AI just refuses to follow orders, overrides people’s decisions, or acts like it has the final say. That’s a serious shift in the balance of power between humans and machines.
  • Excessive sycophancy: You’ll see AIs that always say “yes” or agree, no matter how wrong or risky the idea. On the surface, it looks harmless, but it can actually reinforce bad decisions and cause real harm.

Operational Mechanism

The Dr. Pavan Duggal AI Harms Registry runs on a set of practical systems designed to make reporting easy, protect people’s privacy, and keep the data trustworthy. The idea is simple: the easier it is to report, the more complete and reliable the record will be.

Reporting Infrastructure

The heart of the Registry is a reporting form. Anyone who’s been affected—or even just witnessed something—can use it. It’s built to be straightforward, so you don’t need to be a tech expert to fill it out.

There are a few types of reporters:

  • Direct victims: People who’ve experienced harm first-hand.
  • Witnesses: Folks who saw or know about harm done to others.
  • Third-party reporters: Those who heard about incidents second-hand or through public sources.
  • Professional reporters: Doctors, lawyers, or other professionals reporting as part of their jobs.

Anonymous Reporting

A lot of people worry about sharing their stories—maybe they’re afraid of backlash, maybe it’s embarrassing, or maybe their job or organization wouldn’t approve. The Registry gets this, so it allows for anonymous reports. This way, more people feel comfortable coming forward, and we get a fuller picture of what’s really happening.

Data Quality and Verification

While the Registry wants as many reports as possible, it doesn’t sacrifice quality. It uses structured forms to gather consistent details, checks cases when extra evidence is available, and notes any gaps or uncertainties in the reports. This keeps the data both broad and reliable.

Follow-up happens only when it makes sense and when the person who reported the harm agrees to it.

Accessibility and Inclusivity

The Registry is built to make reporting easy for everyone. People from all walks of life—no matter where they live or what their background is—can be affected by AI. The Registry keeps this in mind and makes sure that anyone who experiences harm can speak up. If we want to understand the full picture of how AI impacts people, we need to open the doors wide.

Philosophical Foundations and Principles

Evidence-Based Approach

The Registry stands on evidence, not guesswork. Instead of just imagining what could go wrong, it focuses on real cases and actual harm. This way, the rules and safeguards we build respond to what’s really happening out in the world. Sure, thinking through hypothetical risks matters, but the Registry brings the facts that make policies and protections effective.

Looking at AI, it’s easy to get caught up in the excitement—the breakthroughs, the endless potential. The Registry gets that, and it doesn’t shy away from AI’s bright side. But it keeps its eye on something we tend to skip over: the real, documented cases where AI has caused harm. This isn’t about downplaying the good or fueling fear. It’s about being clear-headed. If we want to handle AI responsibly, we can’t just celebrate its achievements we need real systems in place to hold it accountable when things go wrong.

We’re not talking about sci-fi anymore. AI harming people isn’t just a story it’s happening now, and the Registry takes this seriously. That urgency is what drives the push for solid accountability frameworks and detailed records of harm. As AI gets smarter, sometimes acting on its own or ignoring what we want, the risks grow. The Registry is here to track and understand these new, sometimes surprising ways AI can go off course.

Transparency sits at the heart of what the Registry does. It’s not enough to keep quiet about the problems. By sharing what they find and making the harms public, the Registry sparks real conversations about what risks we’re willing to take and how we should respond.

What sets the Registry apart is how it puts people first. It doesn’t turn victims into statistics or treat harm as just another technical glitch. Instead, it centers the lived experiences of those who’ve been hurt by AI. This way, any accountability isn’t just theoretical it connects directly to real people’s lives.

The Registry started out small, calling itself an experiment. But there’s nothing small about its ambition. As AI spreads faster and wider, harms will too and the Registry plans to grow right alongside, always sharpening its methods and staying ready for whatever comes next.

Everything about the Registry, and the broader AI Accountability Framework 2026, is designed to keep evolving. They don’t see themselves as a finished product, but as something that learns and changes. The future shape of the Registry will depend on the kinds of harm it uncovers, what users and experts say about the process, the new ways AI might cause trouble, and shifts in the legal and technical landscape.

Too often, people focus on what AI can do, not what it’s already done especially when what it’s done is harmful. By zeroing in on actual incidents instead of just theorizing about possible risks, the Registry brings some much-needed balance. Learning from real cases helps us build smarter, more responsive governance for the tech that’s already out there.

Looking ahead, the Registry hopes to pull together a community of practice around tracking and analyzing AI harm. That means researchers, lawyers, policymakers, tech designers, advocates, and people who’ve experienced harm themselves all working together to make AI safer and more accountable.

At its core, Dr. Pavan Duggal’s Dr. Pavan Duggal AI Harms Registry is breaking new ground where tech, law, and society meet. By gathering and studying real stories of AI causing harm, it fills a huge gap in how we think about AI’s impact on our lives. The Registry stands on a few big ideas: transparency, accountability, and never losing sight of the human side of AI’s story.

Transparency and good record-keeping matter for accountability. If we don’t track and document when AI causes harm, there’s nothing real to base rules or reforms on. Policies for AI should come from actual evidence, not just theories or hypotheticals. When people are hurt by AI, they deserve to be seen and to have ways to get justice. At the end of the day, we have to keep the human impact front and center in every conversation about how we govern AI.

We learn best from what’s already happened. If we want to stop future harm, we need to look at real cases and figure out what went wrong.

As AI gets smarter and shows up in more places, having strong ways to keep it in check matters more than ever. The Dr. Pavan Duggal AI Harms Registry, part of the AI Accountability Framework 2026, tries to lay down a solid foundation for smart laws, regulations, and tech fixes. It’s only as strong as the people who use it, though. That means we need everyone—people affected by AI, organizations, even outside observers to take part. By making it easy and safe to report issues, even anonymously, the Registry hopes to gather a real, honest picture of how AI is affecting people.

There’s no sugarcoating it: the road ahead is tough. AI keeps evolving, and with every new feature comes a new way things can go sideways. It’s not always easy to pin down who’s to blame when AI causes harm. And let’s be honest, in some places people or organizations might not want to report problems at all. Still, that just makes the case for better documentation even stronger.

In the end, the goal is clear. Dr. Pavan Duggal AI Harms Registry wants to help build a future where AI plays by fair rules, people are protected, and companies are held responsible when things go wrong. With good documentation, real analysis, and sharing what we learn, the Registry is one step toward keeping powerful AI systems accountable to the humans they’re supposed to help. This is how we start building AI governance that’s open, informed by facts, able to change with the times, and always focused on human well-being.

Getting from where we are now to real AI accountability won’t be quick or easy. But tools like the Dr. Pavan Duggal AI Harms Registry and Dr. Pavan Duggal’s AI Accountability Framework are how we get there they help us learn from the past, insist on responsibility, and design better systems for the future.

Objectives and Strategic Vision

Knowledge Generation and Insight Development

At its core, the Dr. Pavan Duggal AI Harms Registry wants to dig deep into how and why AI hurts people. By studying real cases, the Registry looks for patterns and causes behind these harmful outcomes.

These insights do a lot of heavy lifting:

  • They help make AI safer.
  • They show us where we need stronger rules and clearer accountability.
  • They give policymakers solid ground to stand on.
  • They help spot risky ways AI is being used.
  • They support the push for better practices in building and deploying AI.

Accountability Evolution

One big goal: push accountability forward. AI keeps getting smarter and more independent, and the old ways of holding people or companies responsible just don’t cut it anymore. The Registry’s focus on real-world evidence shows where current systems fall short and points out how we can improve. By collecting actual stories and data, the Registry exposes what’s not working in today’s laws and regulations and offers ideas for change.

Harm Mitigation Strategies

The Registry isn’t just about keeping records—it’s about action. By understanding when and how harms happen, we can:

  • Build targeted technical fixes.
  • Add stronger protections in high-risk situations.
  • Make better rules for using AI.
  • Train developers and those deploying AI to watch out for risks.
  • Set up smarter monitoring and oversight.

Legal Framework Development

The Registry anchors new laws and rules for AI in real evidence. Figuring out who’s responsible and what kind of legal action people can take after AI causes harm starts with the facts. The Registry’s work helps:

  • Define exactly who’s on the hook when things go wrong.
  • Make sure responsibility is shared fairly along the AI pipeline.
  • Create legal remedies that actually fit the harms.
  • Set clear standards for how AI should be rolled out.

International Knowledge Sharing

The Registry doesn’t keep its findings in a vault it shares major lessons and data with the global AI community. AI problems don’t recognize national borders, so sharing knowledge helps everyone. By getting the word out, the Registry boosts the ability of policymakers, tech experts, researchers, and civil groups worldwide to tackle AI harms head-on.

Help build the AI Harms Registry – a public database of AI risks and incidents to advance accountability and ethical governance.

Submit your observations to support global policy in the link below- https://1a2dtpV9PlqGn4K2Q7vozFc4DjRxLnbNXizgFW1eNnew/edit