ASD-STE100 Standardized Download PDF THE HIERARCHY OF ARTIFICIAL INTELLIGENCE RISK AND THE PRESERVATION OF HUMAN LEARNING AGENCY Table of Contents Scope and Purpose Terms and Definitions The Two False Beliefs About AI Agency The Inverted Hierarchy of Risk The Two-Century Continuum of Attention Capture The Mechanisms of Voluntary Disagency The Existential Crisis: Atrophy of the
Part I: The Take-Off Ramp — Evolution Beyond Raw Encephalization A prevalent misconception in evolutionary biology suggests that human cognitive superiority stems directly from brain expansion—simply scaling an ancestral ape brain from roughly 350–450 cm³ (and ~6–9 billion cortical neurons) up to 1350–1400 cm³ (and ~16–21 billion cortical neurons). Yet an isometric scaling of that
Apes to AIs: The Illusion of Scaling Up Sentience Read More »
“The most immediate, high-leverage danger of advanced AI does not require the machine to have a will of its own; it arises because AI dramatically lowers the skill barrier and multiplies the destructive reach of rogue human actors—enabling individuals, syndicates, and hostile nation-states to synthesize novel biological pathogens, automate catastrophic cyberwarfare against critical infrastructure, and
The Greatest Danger of AI? Read More »
If you haven’t seen the latest NetFlix release: AI GONE WILD I recommend it. It’s a great backdrop for understanding the misleading ways the media is helping to perpetuate the wrong set of fears. Click here for a detailed take on the Hugging Face example Like the documentary points out, every few weeks (becoming days),
The ongoing debate over whether artificial intelligence will become a conscious, autonomous agent has trapped itself between two dogmas of unexamined certainty. On one side stand those who declare machine self-agency an absolute inevitability: “Advanced AI will inevitably develop into an autonomous, self-interested entity that breaks free from human control, pursuing its own survival and
to be or not to be? Read More »
“I visualize a time when we will be to robots what dogs are to humans.” – Claude Shannon 1987 The Hierarchy of AI Risk The public debate over the existential risk of artificial intelligence is paralyzed by deceptive illusions. The scenarios commanding the most headlines and panic are the most speculative and sensational, while the
Don’t Let the Wizards of Iz Distract You Read More »
In his “Looking in the Mirror” episode of “Lyrics of Livin” (hear him in full below), Matthew McConaughey, with his distinctly cool gravitas, says: “AI’s a big mirror we’re holding up to ourselves, but it’s still only a reflection” My first response was who is he talking about? The “we’re” seems like a future historian’s
Looking Through McConaughey’s Mirror Read More »
We can’t use human ways of thinking about knowing to explain AI’s process of tokening. AI’s have semantically arbitrary, mechanical rather semantic, meaning space extent limits. An AI user’s bandwidth limits (technologically or customer type) affect the “depth” of context informing the tokening. That’s what makes AIs seem so absurd – as if they are
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Shared-chat dialogues have the potential to be the most positively empowering and transformative learning service AI can provide humanity: the agentic mediation of mutually learning oriented human dialogues. I call this modality of AI, dAilogues. dAilogues are like “universal translators” that can not only bridge language, they can bridge differences in vocabulary, knowledge, skill, beliefs,
dAilogues: The Future of Learning Together Read More »
You might find this interesting on two fronts. It explores the relationship between learning and agency and it also explores the biases deeply embedded in AI (and prevailing educational paradigms) that work against children learning self-agency. DB: From infancy, humans learn to extend their agency and learn to become who they become through their learned
Self-Agency Learning (and How AI Endangers It) Read More »