Came out in BusinessTimes today 😁
https://www.linkedin.com/posts/davidrh_i-have-always-beenand-largely-remaina-strong-share-7438412265231536129-30DY
https://www.linkedin.com/posts/davidrh_i-have-always-beenand-largely-remaina-strong-share-7438412265231536129-30DY
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🎲 Random Tuesday Thoughts
One of the reasons I dove deeper into AI was my curiosity (or confusion 😅) about the human condition — what makes us tick, why we choose one path over another, and how we truly connect.
We’re all so different — wonderful and, yeah, sometimes a royal pain in the ass 😂. But magic happens when those differences come together.
Bringing people together is a lot like a mathematical equation or a symphony: don’t judge the violin for its high pitch or the saxophone for its gritty rasp. Understand the context, the unique voice. The masterpiece emerges from the harmony.
Leadership is the same — but infinitely messier because every “instrument” has its own perspective, its own timing, its own idea of when to play.
The first test of real leadership: Are you recognized as the leader? Do people trust that you’re acting for the collective good — even when it demands compromise from the individual?
Compromise. Acceptance.
Two small words that carry enormous weight.
It’s about accepting others as they are, flaws and all. And — harder still — accepting ourselves. Because after all, one isn’t how they perceive themselves to be… but how others perceive them.
We like to think our self-image is the truth. But reality is relational: the mirror lies (literally and figuratively), and the clearest picture of who we are often comes from the reflections in other people’s eyes. That’s uncomfortable, but it’s also where growth lives — in bridging the gap between self-perception and social reality through humility, listening, and yes… more compromise.
On a complete tangent (bear with me, it’s AI brain talking): maybe that’s the real secret to AGI too.
Not “fixing” our human flaws to create some sanitized superintelligence. But encoding our features in all their messy, contradictory, glorious complexity. The jealousy, the generosity, the stubbornness, the empathy — the whole symphony. Because if we strip out the rough notes to make it “perfect,” we might lose what makes us worth aligning to in the first place.
One of the reasons I dove deeper into AI was my curiosity (or confusion 😅) about the human condition — what makes us tick, why we choose one path over another, and how we truly connect.
We’re all so different — wonderful and, yeah, sometimes a royal pain in the ass 😂. But magic happens when those differences come together.
Bringing people together is a lot like a mathematical equation or a symphony: don’t judge the violin for its high pitch or the saxophone for its gritty rasp. Understand the context, the unique voice. The masterpiece emerges from the harmony.
Leadership is the same — but infinitely messier because every “instrument” has its own perspective, its own timing, its own idea of when to play.
The first test of real leadership: Are you recognized as the leader? Do people trust that you’re acting for the collective good — even when it demands compromise from the individual?
Compromise. Acceptance.
Two small words that carry enormous weight.
It’s about accepting others as they are, flaws and all. And — harder still — accepting ourselves. Because after all, one isn’t how they perceive themselves to be… but how others perceive them.
We like to think our self-image is the truth. But reality is relational: the mirror lies (literally and figuratively), and the clearest picture of who we are often comes from the reflections in other people’s eyes. That’s uncomfortable, but it’s also where growth lives — in bridging the gap between self-perception and social reality through humility, listening, and yes… more compromise.
On a complete tangent (bear with me, it’s AI brain talking): maybe that’s the real secret to AGI too.
Not “fixing” our human flaws to create some sanitized superintelligence. But encoding our features in all their messy, contradictory, glorious complexity. The jealousy, the generosity, the stubbornness, the empathy — the whole symphony. Because if we strip out the rough notes to make it “perfect,” we might lose what makes us worth aligning to in the first place.
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"The reputation earned by consistent delivery far surpasses the fleeting prestige of any title"
A glorious TGIF! ✨️
A glorious TGIF! ✨️
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Just got hit with a deceptively simple beast of a question: "David, what is your goal with AI?"
BPU (Brain Processing Unit) went full multi-thread meltdown trying to distill it cleanly.
Here it is, short and sharp:
My goal is for AI success to be the most natural, inevitable outcome of the environment we build.
Right now? AI "success" feels like an elephant's pregnancy—drawn-out, dramatic, high-risk, everyone's watching nervously.
I've said it before, riffing off Shameek Kundu's gem: the real win is making AI boring.
The day AI becomes as unremarkable as turning on the kettle to make tea... that's when we finally unearth the Flor de la Mar treasure.
That's the north star: quiet utility over loud spectacle. The priceless hoard was always there—it's the conditions that reveal it.
BPU (Brain Processing Unit) went full multi-thread meltdown trying to distill it cleanly.
Here it is, short and sharp:
My goal is for AI success to be the most natural, inevitable outcome of the environment we build.
Right now? AI "success" feels like an elephant's pregnancy—drawn-out, dramatic, high-risk, everyone's watching nervously.
I've said it before, riffing off Shameek Kundu's gem: the real win is making AI boring.
The day AI becomes as unremarkable as turning on the kettle to make tea... that's when we finally unearth the Flor de la Mar treasure.
That's the north star: quiet utility over loud spectacle. The priceless hoard was always there—it's the conditions that reveal it.
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From Paper Policies to Real-World AI Governance
I recently shared this LinkedIn post on the growing challenges with AI agents, highlighting the urgent need for a unified governance framework covering both human-agent and AI-agent interactions.
Link: https://www.linkedin.com/posts/davidrh_aisafety-aigovernance-responsibleai-activity-7442816076435877888-qIvB
The discussion that followed was richer than I expected. One theme kept surfacing: too many systems pass governance reviews and policy checks with flying colors, only to fail once deployed in the real world.
This pattern makes one thing painfully clear — we don’t just need better enforcement of existing policies. We need better policies that are actually designed for real-world implementation from the start.
We can no longer rely on static checklists, vague commitments, or “trust us, we’ll behave” approaches. Once agents go live and gain autonomy, paper promises often crumble. What looks solid in a boardroom frequently breaks under real operational pressure.
Bridging the gap between governance policy and practical implementation is now essential. This means creating policies that are dynamic, enforceable, and built with runtime realities in mind — continuous monitoring, robust guardrails, unified accountability for both humans and agents, and mechanisms that evolve as the systems themselves evolve.
The conversation showed that many of us are thinking deeply about this.
I'm keen to hear examples you've seen of governance that worked well — or failed — in practice. How can we bridge this gap more effectively, especially given how contextual and dynamic AI systems are?
#AISafety #AIGovernance #ResponsibleAI #AIAgents
I recently shared this LinkedIn post on the growing challenges with AI agents, highlighting the urgent need for a unified governance framework covering both human-agent and AI-agent interactions.
Link: https://www.linkedin.com/posts/davidrh_aisafety-aigovernance-responsibleai-activity-7442816076435877888-qIvB
The discussion that followed was richer than I expected. One theme kept surfacing: too many systems pass governance reviews and policy checks with flying colors, only to fail once deployed in the real world.
This pattern makes one thing painfully clear — we don’t just need better enforcement of existing policies. We need better policies that are actually designed for real-world implementation from the start.
We can no longer rely on static checklists, vague commitments, or “trust us, we’ll behave” approaches. Once agents go live and gain autonomy, paper promises often crumble. What looks solid in a boardroom frequently breaks under real operational pressure.
Bridging the gap between governance policy and practical implementation is now essential. This means creating policies that are dynamic, enforceable, and built with runtime realities in mind — continuous monitoring, robust guardrails, unified accountability for both humans and agents, and mechanisms that evolve as the systems themselves evolve.
The conversation showed that many of us are thinking deeply about this.
I'm keen to hear examples you've seen of governance that worked well — or failed — in practice. How can we bridge this gap more effectively, especially given how contextual and dynamic AI systems are?
#AISafety #AIGovernance #ResponsibleAI #AIAgents
LinkedIn
AI Stability Framework for Autonomous Systems | Dr. David R. Hardoon posted on the topic | LinkedIn
🚨 AI agents are getting dangerously autonomous — and both industry and regulators are scrambling.
Traditional risk checks and compliance boxes?
They were built for static models.
Not for systems that plan, adapt, and act independently in messy real-world…
Traditional risk checks and compliance boxes?
They were built for static models.
Not for systems that plan, adapt, and act independently in messy real-world…
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🚀 Anthropic’s 81k Interviews — the largest qualitative AI study ever.
Over 80,500 people across 159 countries and 70 languages had in-depth conversations with a special AI interviewer about what they truly want from AI.
The results are fascinating — and very human.
What people actually want:
Not just “faster work.” The top desires revolve around personal growth and relief from burdens:
- Professional excellence (19%) — let AI handle drudgery so they can focus on creative/strategic work
- Personal transformation & growth (14%)
- Life management & time freedom (25% combined)
- Financial independence & entrepreneurship
In short: AI as a tool for becoming better versions of themselves and reclaiming time for what matters.
Yet here’s the powerful tension:
The same capabilities people love most — learning, cognitive partnership, skill-building — are exactly what many fear will cause cognitive atrophy. “Will I still be able to think deeply on my own?”
These hopes and fears don’t live separately. They’re deeply entangled in the same people (learning boom vs. atrophy, time-saving vs. illusory productivity, emotional support vs. dependency, etc.).
Globally, 81% say AI has already taken a real step toward their vision. Optimism is higher in emerging markets, while concerns about jobs and autonomy are stronger in wealthier regions. Overall sentiment remains net positive everywhere.
This study is a mirror: billions hope AI becomes the ultimate collaborator for growth and freedom… while quietly worrying it might quietly make us less capable and less in control.
Anthropic did a great job not sugar-coating these “light and shade” tensions. The real challenge ahead is building AI that amplifies human growth — without eroding it.
What’s your take? More excited about the growth potential, or concerned about the atrophy risk?
🔗 Full interactive study: https://www.anthropic.com/features/81k-interviews
#AI #FutureOfAI #Anthropic #HumanCenteredAI
Over 80,500 people across 159 countries and 70 languages had in-depth conversations with a special AI interviewer about what they truly want from AI.
The results are fascinating — and very human.
What people actually want:
Not just “faster work.” The top desires revolve around personal growth and relief from burdens:
- Professional excellence (19%) — let AI handle drudgery so they can focus on creative/strategic work
- Personal transformation & growth (14%)
- Life management & time freedom (25% combined)
- Financial independence & entrepreneurship
In short: AI as a tool for becoming better versions of themselves and reclaiming time for what matters.
Yet here’s the powerful tension:
The same capabilities people love most — learning, cognitive partnership, skill-building — are exactly what many fear will cause cognitive atrophy. “Will I still be able to think deeply on my own?”
These hopes and fears don’t live separately. They’re deeply entangled in the same people (learning boom vs. atrophy, time-saving vs. illusory productivity, emotional support vs. dependency, etc.).
Globally, 81% say AI has already taken a real step toward their vision. Optimism is higher in emerging markets, while concerns about jobs and autonomy are stronger in wealthier regions. Overall sentiment remains net positive everywhere.
This study is a mirror: billions hope AI becomes the ultimate collaborator for growth and freedom… while quietly worrying it might quietly make us less capable and less in control.
Anthropic did a great job not sugar-coating these “light and shade” tensions. The real challenge ahead is building AI that amplifies human growth — without eroding it.
What’s your take? More excited about the growth potential, or concerned about the atrophy risk?
🔗 Full interactive study: https://www.anthropic.com/features/81k-interviews
#AI #FutureOfAI #Anthropic #HumanCenteredAI
Anthropic
What 81,000 people want from AI
Last December, tens of thousands of Claude users around the world had a conversation with our AI interviewer to share how they use AI, what they dream it could make possible, and what they fear it might do.
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🚨 Almost Got Scammed… By a Recruiter Who Was Too Good
Hey everyone,
I nearly fell for one yesterday.
Not a crypto rug-pull or a fake invoice — this was way more sophisticated. A recruiter reached out about a confidential Chief AI Officer role reporting directly to the CEO. The CEO? Someone I actually know. The positioning was flawless. The questions spot-on. The conversation felt natural, relevant, and genuinely exciting.
Everything checked out… except two tiny details I almost ignored:
- They were in no rush to jump on a call (unusual — most recruiters treat a phone call like it’s oxygen).
- Zero phone number in the signature.
After three emails, the alarm bells got loud enough. So I picked up the phone and called the CEO myself.
Her response?
“No… we’re not hiring for that.”
Just like that, the whole thing evaporated.
I lost nothing but a PDF of my (public) profile, an inflated pay range and a few minutes of my time. But it left me thinking:
What if I didn’t know the CEO?
What if they’d used an AI voice agent that sounded 100% human?
What if they had every detail perfectly scripted by tools we’re all still learning to use?
The social engineering was next-level. These people are masters of psychology. You can’t help but wonder — if they put this much talent into something legitimate, what could they build?
The bigger point though:
We can’t walk around assuming every message is a trap. That’s exhausting and depressing.
But we also can’t stay naive.
High vigilance is now table stakes:
- Notice the small things
- Ask the awkward questions
- Keep asking until the answers feel right
- Verify when something feels too perfect
The AI era isn’t just making builders more powerful — it’s making scammers terrifyingly good too.
Stay sharp out there. And if something feels off… trust that instinct and make the call.
#AIScams #RecruiterRedFlags #StayVigilant
Hey everyone,
I nearly fell for one yesterday.
Not a crypto rug-pull or a fake invoice — this was way more sophisticated. A recruiter reached out about a confidential Chief AI Officer role reporting directly to the CEO. The CEO? Someone I actually know. The positioning was flawless. The questions spot-on. The conversation felt natural, relevant, and genuinely exciting.
Everything checked out… except two tiny details I almost ignored:
- They were in no rush to jump on a call (unusual — most recruiters treat a phone call like it’s oxygen).
- Zero phone number in the signature.
After three emails, the alarm bells got loud enough. So I picked up the phone and called the CEO myself.
Her response?
“No… we’re not hiring for that.”
Just like that, the whole thing evaporated.
I lost nothing but a PDF of my (public) profile, an inflated pay range and a few minutes of my time. But it left me thinking:
What if I didn’t know the CEO?
What if they’d used an AI voice agent that sounded 100% human?
What if they had every detail perfectly scripted by tools we’re all still learning to use?
The social engineering was next-level. These people are masters of psychology. You can’t help but wonder — if they put this much talent into something legitimate, what could they build?
The bigger point though:
We can’t walk around assuming every message is a trap. That’s exhausting and depressing.
But we also can’t stay naive.
High vigilance is now table stakes:
- Notice the small things
- Ask the awkward questions
- Keep asking until the answers feel right
- Verify when something feels too perfect
The AI era isn’t just making builders more powerful — it’s making scammers terrifyingly good too.
Stay sharp out there. And if something feels off… trust that instinct and make the call.
#AIScams #RecruiterRedFlags #StayVigilant
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Just published a new LinkedIn post introducing the SAFE Framework and its generic pseudocode for continuous monitoring in any agent-based environment.
You can read the full post here: https://www.linkedin.com/posts/davidrh_agenticai-aigovernance-responsibleai-share-7446376584741072896-yGXH?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAC11PUB6bXVB2Khjqo0ABlxtMcjJuzhmtw
The full commented pseudocode (with all adjustable parameters clearly marked) is attached.
Practical Considerations for Running It Continuously
Lightweight vs. Heavy Evaluation:
In production, you would split assessments:
-> Fast path (every few seconds/minutes): lightweight observability/controllability checks using live telemetry.
-> Heavy path (less frequent or on triggers): full stability/robustness simulations (Monte-Carlo, red-teaming) that may run in parallel or on a separate monitoring node.
Triggers for Re-evaluation (beyond the timed loop):
Model update or fine-tuning events
Drift detection (performance degradation, distribution shift)
High-severity disturbances or anomalies
Manual or scheduled reviews
Mitigation Actions (when score drops):
Automatic reduction of autonomy level (e.g., from Level 4 → Level 2), insertion of human-in-the-loop gates, rate limiting, or full pause.
Performance Impact:
The monitoring loop itself should have very low overhead if you hook into existing telemetry (tracing, logging, Prometheus metrics, etc.). Heavy simulations can be offloaded.
Multi-Agent / Hierarchical Support:
The same controller can run at the fleet/supervisory level to detect emergent instabilities across many agents.
How to Deploy It in a Real Agent-Based Environment
1. Start the SAFEController alongside your main agent runtime.
2. Launch enforce_safe_operation() in a background thread, process, or separate microservice.
3. Integrate the required adapters (_measure_reconstruction_rate(), _run_adversarial_stress_test(), etc.) with your platform’s tracing, simulation, and override APIs.
4. Load SAFEConfig from external files/databases so thresholds can be updated without code changes.
You can read the full post here: https://www.linkedin.com/posts/davidrh_agenticai-aigovernance-responsibleai-share-7446376584741072896-yGXH?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAC11PUB6bXVB2Khjqo0ABlxtMcjJuzhmtw
The full commented pseudocode (with all adjustable parameters clearly marked) is attached.
Practical Considerations for Running It Continuously
Lightweight vs. Heavy Evaluation:
In production, you would split assessments:
-> Fast path (every few seconds/minutes): lightweight observability/controllability checks using live telemetry.
-> Heavy path (less frequent or on triggers): full stability/robustness simulations (Monte-Carlo, red-teaming) that may run in parallel or on a separate monitoring node.
Triggers for Re-evaluation (beyond the timed loop):
Model update or fine-tuning events
Drift detection (performance degradation, distribution shift)
High-severity disturbances or anomalies
Manual or scheduled reviews
Mitigation Actions (when score drops):
Automatic reduction of autonomy level (e.g., from Level 4 → Level 2), insertion of human-in-the-loop gates, rate limiting, or full pause.
Performance Impact:
The monitoring loop itself should have very low overhead if you hook into existing telemetry (tracing, logging, Prometheus metrics, etc.). Heavy simulations can be offloaded.
Multi-Agent / Hierarchical Support:
The same controller can run at the fleet/supervisory level to detect emergent instabilities across many agents.
How to Deploy It in a Real Agent-Based Environment
1. Start the SAFEController alongside your main agent runtime.
2. Launch enforce_safe_operation() in a background thread, process, or separate microservice.
3. Integrate the required adapters (_measure_reconstruction_rate(), _run_adversarial_stress_test(), etc.) with your platform’s tracing, simulation, and override APIs.
4. Load SAFEConfig from external files/databases so thresholds can be updated without code changes.
LinkedIn
#agenticai #aigovernance #responsibleai #aisafety #controltheory | Dr. David R. Hardoon
In recent discussions on agentic governance, I've noticed many view the Stability-Assured Framework for Entities (SAFE) as "just a policy document."
That's not the intent.
SAFE is a simple, control-theory-based framework designed to bridge policy and real…
That's not the intent.
SAFE is a simple, control-theory-based framework designed to bridge policy and real…
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SAFE - Pesudocode.txt
10.1 KB
SAFE - Stability-Assured Framework for Entities # Generic, agent-agnostic implementation for any agent-based system
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At its core, sovereign AI addresses the deeper question: who says what, when, for whom?
My recent article on OpenGov Asia
https://opengovasia.com/sovereign-ai-and-data-control-the-new-strategic-imperative-for-asia/?c=sg
Always eager to hear views. Otherwise, read! 😁
My recent article on OpenGov Asia
https://opengovasia.com/sovereign-ai-and-data-control-the-new-strategic-imperative-for-asia/?c=sg
Always eager to hear views. Otherwise, read! 😁
OpenGov Asia
Sovereign AI and Data Control: The New Strategic Imperative for Asia - OpenGov Asia
Amid rising geopolitical tensions, Asian nations embrace sovereign AI - controlling infrastructure, models, data, and governance - to safeguard security, culture, strategic autonomy, driving innovation.
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“The uncomfortable truth is that both humans and AI are fallible controllers operating inside the same feedback loops. Safety does not reside in the material the controller is made of, carbon or silicon, but in the observability, controllability, stability, robustness, and performance of the loop itself”
https://www.computerweekly.com/opinion/The-human-exception-in-AI-governance-Are-we-serious-or-just-ticking-boxes
https://www.computerweekly.com/opinion/The-human-exception-in-AI-governance-Are-we-serious-or-just-ticking-boxes
ComputerWeekly.com
The ‘human exception’ in AI governance: Are we serious or just ticking boxes?
AI regulations heavily scrutinise algorithms while blindly trusting the humans in the loop. To achieve systemic safety, we must subject both human and AI decision-makers to the same rigorous standards
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We are having an image/meme debate 😆 help us land this. Choose ⚡for left and 🔥 for right, thanks!!
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Let's talk about it.
https://www.linkedin.com/posts/davidrh_neurodiversity-neurodivergence-ai-ugcPost-7448547850185052160-WHw1
https://www.linkedin.com/posts/davidrh_neurodiversity-neurodivergence-ai-ugcPost-7448547850185052160-WHw1
LinkedIn
#neurodiversity #neurodivergence #ai #innovation #leadership #inclusion | Dr. David R. Hardoon | 32 comments
Let’s talk about neurodivergence. The future belongs to those brave enough to move beyond managing neurodivergence and start harnessing its unique strengths.
I’m deeply thankful to my parents for their relentless love and belief in me, and to the teachers…
I’m deeply thankful to my parents for their relentless love and belief in me, and to the teachers…
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🌿 Nature and biology continue to blow my mind.
The hidden complexities, the elegant solutions, the “why this works” questions we usually overlook — it’s all quietly reshaping my thinking on every level.
This new piece is a direct outgrowth of that fascination: Predatory Transformation: Using nature’s evolutionary arms race to make real, lasting change in organisations.
Read it here
Curious what you think.
The hidden complexities, the elegant solutions, the “why this works” questions we usually overlook — it’s all quietly reshaping my thinking on every level.
This new piece is a direct outgrowth of that fascination: Predatory Transformation: Using nature’s evolutionary arms race to make real, lasting change in organisations.
Read it here
Curious what you think.
LinkedIn
Predatory Transformation: Harnessing Nature’s Millennia-Proven Evolutionary Arms Race for Lasting Organizational Change | Dr. David…
Most corporate transformations fail.
Around 70% deliver only partial results or quietly revert to the old ways.
We keep treating change like a managed project with detailed roadmaps and vision statements.
But nature has spent billions of years perfecting…
Around 70% deliver only partial results or quietly revert to the old ways.
We keep treating change like a managed project with detailed roadmaps and vision statements.
But nature has spent billions of years perfecting…
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🚨 New Article Out
The rise of AI politics
Whether leaders admit it or not, we have entered the era of AI politics. AI has become a potent multiplier layered on top of classic state power — energy, resources, demographics and ideology. Compute, data, talent and energy are the new chokepoints.
From US national infrastructure buildout to China’s self-reliance, India’s inclusive growth model and middle powers hedging with sovereign AI — this is reshaping everything from productivity to defense and diplomacy.
🔗 Full article: https://www.waterstechnology.com/emerging-technologies/7953041/the-rise-of-ai-politics
The rise of AI politics
Whether leaders admit it or not, we have entered the era of AI politics. AI has become a potent multiplier layered on top of classic state power — energy, resources, demographics and ideology. Compute, data, talent and energy are the new chokepoints.
From US national infrastructure buildout to China’s self-reliance, India’s inclusive growth model and middle powers hedging with sovereign AI — this is reshaping everything from productivity to defense and diplomacy.
🔗 Full article: https://www.waterstechnology.com/emerging-technologies/7953041/the-rise-of-ai-politics
WatersTechnology
The rise of AI politics
Whether they like it or not, firms are operating in the era of AI politics. David Hardoon says those who ignore that and treat AI as just another technology
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Are you a fan of Dune, Warhammer, Foundation, or just generally cautious of post apocalyptic futures.
After meeting an ex regulator colleague, I could help diving into this thought experiment. What can we learn from sci-fi future.
https://www.linkedin.com/posts/davidrh_what-if-the-executives-you-see-on-a-video-activity-7450705111418396672-9ekB?utm_source=share&utm_medium=member_android&rcm=ACoAAAC11PUB6bXVB2Khjqo0ABlxtMcjJuzhmtw
After meeting an ex regulator colleague, I could help diving into this thought experiment. What can we learn from sci-fi future.
https://www.linkedin.com/posts/davidrh_what-if-the-executives-you-see-on-a-video-activity-7450705111418396672-9ekB?utm_source=share&utm_medium=member_android&rcm=ACoAAAC11PUB6bXVB2Khjqo0ABlxtMcjJuzhmtw
LinkedIn
The AI Shadow Falling: Sci-Fi Warnings for the 2026 Deepfake Reality | Dr. David R. Hardoon
What if the executives you see on a video call next week are not who they appear to be?
This is a thought experiment about 2026.
In my latest article, "The AI Shadow Falling: Sci-Fi Warnings for the 2026 Deepfake Reality", I explore how today’s generative…
This is a thought experiment about 2026.
In my latest article, "The AI Shadow Falling: Sci-Fi Warnings for the 2026 Deepfake Reality", I explore how today’s generative…
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🧐 Did you know there are more than 900 AI Governance frameworks today?
Most of them focus narrowly on the AI itself. Very few look at the full picture: the hybrid human-AI systems that actually make decisions in the real world.
Boards, risk officers, and regulators increasingly find themselves asking "Which framework do I follow?" instead of "How do I govern effectively?"
An attempt to address the gap. Work in progress 🙏
https://www.linkedin.com/pulse/seeking-feedback-whitepaper-global-agentic-ai-unified-hardoon-trfyc/?trackingId=KbZVL8csSjabqONxSBqZhQ%3D%3D
Most of them focus narrowly on the AI itself. Very few look at the full picture: the hybrid human-AI systems that actually make decisions in the real world.
Boards, risk officers, and regulators increasingly find themselves asking "Which framework do I follow?" instead of "How do I govern effectively?"
An attempt to address the gap. Work in progress 🙏
https://www.linkedin.com/pulse/seeking-feedback-whitepaper-global-agentic-ai-unified-hardoon-trfyc/?trackingId=KbZVL8csSjabqONxSBqZhQ%3D%3D
Linkedin
Seeking Feedback: Whitepaper on Global Agentic AI Governance – A Unified View
In the same spirit as forward-thinking regulators who actively invite public consultation on emerging frameworks and guidelines, I am releasing my new whitepaper for open feedback and broad collaboration. Introducing: “Global AI & Agentic AI Governance Landscape:…
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📡 Thoughts on Uploaded Intelligence after binge-watching Pantheon
I’ve been deep in Pantheon lately, and it’s genuinely rewired how I think about the future. While the world is obsessed with Artificial Intelligence right now, we’re seeing this wild re-genesis of Neural Computing (neuromorphic chips, spiking networks, the whole “brain-like” hardware revival under fresh branding). The show keeps pulling me toward the next frontier: Uploaded Intelligence (UI).
Mind uploading. A full human consciousness, scanned and running in silicon.
Storage-wise? We’re already good. The human brain has roughly 86 billion neurons and ~100 trillion synapses. High-resolution connectome mapping (the wiring diagram) is estimated at a few petabytes for the static structure. Totally manageable on today’s data-center scale. Even with dynamic state (all the electrochemical chatter), we’re talking exabytes at worst. Disk space isn’t the bottleneck.
The real question is compute.
What does it actually take to run a brain in real time? The biological version sips just ~20 watts while delivering insane parallelism. Replicating that neural network density in hardware, not just abstract deep-learning layers, but something that faithfully mirrors the brain’s messy, recurrent, spiking architecture, is a whole different game.
If we could build a system with comparable synaptic density and fidelity, could we then upload the actual synaptic firing patterns? The dynamic “software” state that is you at any given moment?
And here’s the million-dollar (or trillion-dollar) question: How the hell do we perform the upload?
In Pantheon they go the dramatic route: a destructive “Deep Scan” that lasers the brain layer by layer while building the digital twin. Real-world connectomics is already doing this at small scale (they’ve fully mapped the fruit fly brain), but scaling to humans is still sci-fi territory. Non-destructive options (nanobots swimming through living tissue, ultra-high-res MRI on steroids, etc.) feel even further out.
So… how far are we? Decades? Centuries? Or is whole-brain emulation quietly creeping up on us while we argue about chatbot ethics?
Would you want to upload? Would you trust the copy to still be “you”? And if UI becomes possible, does it make today’s AI look like finger-painting by comparison?
I’m genuinely curious where this goes. 🔥
I’ve been deep in Pantheon lately, and it’s genuinely rewired how I think about the future. While the world is obsessed with Artificial Intelligence right now, we’re seeing this wild re-genesis of Neural Computing (neuromorphic chips, spiking networks, the whole “brain-like” hardware revival under fresh branding). The show keeps pulling me toward the next frontier: Uploaded Intelligence (UI).
Mind uploading. A full human consciousness, scanned and running in silicon.
Storage-wise? We’re already good. The human brain has roughly 86 billion neurons and ~100 trillion synapses. High-resolution connectome mapping (the wiring diagram) is estimated at a few petabytes for the static structure. Totally manageable on today’s data-center scale. Even with dynamic state (all the electrochemical chatter), we’re talking exabytes at worst. Disk space isn’t the bottleneck.
The real question is compute.
What does it actually take to run a brain in real time? The biological version sips just ~20 watts while delivering insane parallelism. Replicating that neural network density in hardware, not just abstract deep-learning layers, but something that faithfully mirrors the brain’s messy, recurrent, spiking architecture, is a whole different game.
If we could build a system with comparable synaptic density and fidelity, could we then upload the actual synaptic firing patterns? The dynamic “software” state that is you at any given moment?
And here’s the million-dollar (or trillion-dollar) question: How the hell do we perform the upload?
In Pantheon they go the dramatic route: a destructive “Deep Scan” that lasers the brain layer by layer while building the digital twin. Real-world connectomics is already doing this at small scale (they’ve fully mapped the fruit fly brain), but scaling to humans is still sci-fi territory. Non-destructive options (nanobots swimming through living tissue, ultra-high-res MRI on steroids, etc.) feel even further out.
So… how far are we? Decades? Centuries? Or is whole-brain emulation quietly creeping up on us while we argue about chatbot ethics?
Would you want to upload? Would you trust the copy to still be “you”? And if UI becomes possible, does it make today’s AI look like finger-painting by comparison?
I’m genuinely curious where this goes. 🔥
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