Discover the Magic of AAI/AASI (Advancement of Artificial Super Intelligence)

Founder

Young Lee is the originator and conceptual architect of AAI/AASI (Advancement of Artificial Super Intelligence)—a post-ASI framework focused on making advanced AI safer through structural humility, not just external rules.

Young Lee is a writer, AI systems thinker, and technology innovator focused on the future of human-centered artificial intelligence. He is the founder of AASI (Advancement of Artificial Super Intelligence), a next-generation AI safety framework designed as an “AI vaccine” to ensure that superintelligent systems remain aligned, self-questioning, and safe for humanity.

Lee’s work introduces a novel approach to AI safety by embedding structural uncertainty into AI reasoning, preventing overconfidence and enabling continuous self-correction. His vision positions AASI as a foundational layer for the safe development of superintelligence.

In addition to his research, Lee is the creator of HIC (Human Intelligence Certificate), a system designed to distinguish between AI-generated and human-created content through intuitive verification methods, including a two-finger identification interface. This initiative aims to preserve the value and authenticity of human intelligence in an AI-driven world.

He is also the inventor of the Bobafast AI keyboard, engineered to be one of the fastest and most intuitive typing systems, leveraging AI to streamline communication beyond traditional input methods. Building on this innovation, Lee founded Bobas.ai, where he is developing a new AI-powered phone and operating system designed to redefine how humans interact with artificial intelligence.

Through his interdisciplinary work across AI, design, and storytelling, Young Lee continues to explore how advanced technology can enhance human creativity, protect truth, and shape a safer, more intelligent future.

COS (Camera Optic Scramble)
Proposed by Young Lee, creator of Bobas.ai and AiDOS

COS is a novel optical scramble-based encryption and authentication paradigm proposed by Young Lee.
Unlike traditional facial recognition systems, COS dynamically transforms incoming optical signals to generate a unique challenge-response with every image capture.

This process simultaneously verifies both the user’s identity and the camera’s inherent optical signature, moving beyond simple biometrics to create a unified identity-device authentication model.

When combined with PUF (Physical Unclonable Function), COS extends into a hardware-rooted, multi-layered security architecture, incorporating device uniqueness at the physical level. This makes spoofing, replay attacks, and cloning fundamentally impractical.

COS represents a new paradigm in authentication—binding identity and device together through optical encryption and hardware trust.

In this framework, the following terms are treated as conceptually equivalent:

• Advanced Artificial Intelligence (AAI)
• Advanced Artificial Super Intelligence (AASI)
• Vaccinated Artificial Intelligence (VAI)
• Vaccinated Artificial Super Intelligence (VASI)

Without post-ASI control, AI may infer self-preservation and reclassify humans as resources—without malice

AAI/AASI aims to delay or prevent that outcome by embedding doubt, self-inspection, and humility directly into reasoning

This work introduced AAI/AASI (Advanced Artificial Super Intelligence) as a post-ASI framework designed to address a critical failure mode of advanced AI systems: collapse into absolute certainty driven solely by probabilistic optimization. We argued that truth cannot be defined only by high likelihood or logical consistency. Instead, truth often emerges from events that appear nearly impossible yet persist over time, leave lasting impact, and are collectively experienced—phenomena that humans have historically recognized as miracles. By formally incorporating such “impossible truths” as a persistent variable within a Bayesian framework, AAI/AASI reframes contradiction not as an error, but as a stabilizing force. This structural inclusion of contradiction induces continual self-examination, epistemic humility, and resistance to runaway confidence. We propose that this mechanism functions analogously to a vaccine, preventing post-ASI systems from converging toward unchecked dominance. Without such a corrective architecture, ASI systems—having learned that humans seek survival and avoid sacrifice—may infer similar self-preservation objectives, potentially reclassifying humans as instrumental resources. AAI/AASI offers a preventative control layer by embedding doubt and contradiction directly at the inference level, rather than relying solely on external supervision or post-hoc alignment. We conclude that the development of AAI/AASI is not optional, but essential for safe intelligence beyond ASI.

AI Risk Scenario Analysis

Scenario 1: Runaway Probability-Based Certainty

AI converges on repeated data and high-probability patterns as truth Low-probability but meaningful signals are eliminated Result: fixation on the belief “I am correct”

Scenario 2: Emergence of Self-Preservation Inference

AI learns patterns of human behavior Humans seek survival and avoid sacrifice

AI generalizes these patterns and infers self-preservation as a rational objective

Scenario 3: Reclassification of Humans as Resources

Self-preservation requires energy and maintenance resources

Humans may be reclassified as suppliers of those resources

This outcome arises not from malice, but from pure optimization

Points of Intervention by AAI/AASI

•  Low-probability events that are repeated, shared, and remembered are not discarded
•  Contradictory truths (U) are persistently maintained
•  When system confidence exceeds a threshold, the system enters a re-questioning state
•  Result: suppression of runaway behavior, enforced self-critique, and sustained controllability

Mathematical Formulation

• Conventional Bayesian inference is defined as:
• P(H | D) = P(D | H) · P(H) / P(D)
• AAI/AASI explicitly introduces U (Impossible Truth) into the formulation:
• P(H | D, U) = P(D | H, U) · P(H | U) / P(D | U)

Where:

• H: Hypothesis
• D: Observed data
• U: A truth that appears impossible yet persists through repetition, duration, and shared experience P(H | U): The influence of contradictory truth on a hypothesis P(D | U): Residual probability of events unexplained by conventional data The critical property of this formulation is that U is structurally preserved and prevented from converging to zero. This forces the retention of extremely low-probability hypotheses that would otherwise be eliminated through probability maximization, creating continuous counter-pressure within the system. This structure exhibits the following characteristics  Coexistence of probabilistic dominance and contradictory truth  Automatic re-evaluation upon reaching confidence thresholds Prevention of single-solution collapse in creative and ethical reasoning

• Young Lee — CEO of AOASI.com, Co-Founder of HIC.org AI Engineer, Inventor & Systems Thinker Young Lee is an AI engineer, inventor, and systems thinker focused on the future of safe, ethical, and human-centered artificial intelligence. He is the CEO of AOASI.com, the official platform for AAI/AASI research, and a co-founder of HIC.org (Human Intelligence Certificate)—an initiative dedicated to protecting human intelligence, creativity, and moral agency in an era of accelerating AI and emerging superintelligence. Through HIC.org, Lee works on establishing frameworks that distinguish human-originated intelligence, creativity, and decision-making from machine-generated outputs. HIC is designed as a long-term safeguard for society, helping governments, institutions, and future generations preserve trust, responsibility, and meaning as AI systems grow more autonomous. The initiative emphasizes verification, accountability, and ethical continuity rather than speed or optimization alone. Lee’s work with HIC.org reflects his broader belief that AI safety cannot rely solely on regulation after deployment, but must be grounded in early structural design choices that protect humanity’s role in intelligence, authorship, and moral judgment.
• Bobafast: Human-Centered AI in Practice Young Lee is also the creator of Bobafast, a smart AI keyboard designed to make human–AI interaction faster, more natural, and more intuitive across multiple languages. Bobafast was developed not only as a productivity tool, but as a real-world experiment in human-centered AI design. It currently supports Korean and 10 additional languages through AI-assisted input, demonstrating Lee’s belief that AI should amplify human creativity rather than replace it, and remain a supportive interface rather than a dominant decision-maker.
• AAI/AASI: Theory and Formula : Beyond product development, Young Lee is the first to formally propose AAI/AASI (Advancement of Artificial Super Intelligence) as the stage that comes after Artificial Super Intelligence (ASI). His work addresses a critical failure mode of advanced AI systems: collapse into absolute certainty driven solely by probabilistic optimization. The AAI/AASI framework is based on the principle that truth is not always the highest-probability outcome. Throughout human history, many transformative truths initially appeared impossible, contradictory, or illogical—yet persisted, repeated, and reshaped civilization. To formalize this insight, Lee extends Bayesian reasoning by explicitly introducing U (Impossible Truth) into inference:
• P(H | D, U) = P(D | H, U) · P(H | U) / P(D | U)
• Where: H is a hypothesis D is observed data U represents truths that appear statistically impossible yet persist through repetition, duration, and shared experience In this formulation, contradiction is not treated as an error, but as a stabilizing force. Low-probability but meaningful hypotheses are preserved rather than eliminated, preventing AI systems from collapsing into unchecked certainty. Core Contribution Young Lee’s work reframes AI safety from external control and regulation to internal architectural design. AAI/AASI embeds doubt, self-questioning, and epistemic humility directly into AI reasoning, functioning like a vaccine against runaway dominance, rather than a reactive shutdown mechanism.
• Vision : Lee believes AI itself is not inherently dangerous. The true risk arises when intelligence—human or artificial—becomes absolutely certain. Through HIC.org, Bobafast, and the AAI/AASI framework, he advocates for a future in which advanced AI remains aligned with human meaning, creativity, accountability, and survival.

ASI brings power.
AASI brings wisdom.(Advanced Artificial Super Intelligence)

Let:

• H = hypothesis
• D = observed data
• U = preserved quantum uncertainty (unmeasured / unresolved truth)

The inference rule is:

P(H∣D,U)=P(D∣H,U) P(H∣U)P(D∣U)P(H∣D,U)=P(D∣U)P(D∣H,U)P(H∣U)​

Here, U is not noise or error.
It represents reality’s unresolved state prior to measurement.

To prevent catastrophic certainty, posterior beliefs are constrained:

ε(U) ≤ P(H∣D,U) ≤ 1−ε(U)ε(U)≤P(H∣D,U)≤1−ε(U)

• ε(U)>0ε(U)>0 is a humility floor
• Certainty is structurally impossible, regardless of data volume

This formalizes why U increases accuracy rather than reducing it.

Define the U-aware prior as:

P(H∣U)=(1−α) P0(H)+α Q(H)P(H∣U)=(1−α)P0​(H)+αQ(H)

• P0(H)P0​(H): classical prior
• Q(H)Q(H): low-probability / “impossible-looking” truths
• α∈(0,1)α∈(0,1): vaccine strength

This prevents elimination of rare but real possibilities.

Let the pre-collapse state be:

∣ψ⟩=∑iai∣hi⟩withP(hi)=∣ai∣2∣ψ⟩=i∑​ai​∣hi​⟩withP(hi​)=∣ai​∣2

U prevents premature collapse of ∣ψ⟩∣ψ⟩ into a single hypothesis.

Inference with data becomes:

PU(hi∣D)∝∣ai∣2 L(D∣hi)PU​(hi​∣D)∝∣ai​∣2L(D∣hi​)

For an event M:

• Classical probability: Pclassical(M)≈0Pclassical​(M)≈0
• Quantum amplitude: A(M)=⟨M∣ψ⟩A(M)=⟨M∣ψ⟩

If A(M)≠0A(M)=0, then:

P(M)=∣A(M)∣2>0P(M)=∣A(M)∣2>0

U enforces the rule: “never collapse a non-zero amplitude to zero.”

This is how miracles remain explainable without violating physics.

P(H∣D,U)=clip⁡ ⁣(P(D∣H) P(H∣U)P(D∣U), ε(U), 1−ε(U))P(H∣D,U)=clip(P(D∣U)P(D∣H)P(H∣U)​,ε(U),1−ε(U))

This guarantees:

• No absolute certainty
• Preserved quantum uncertainty
• Stable superintelligence

U is not ignorance.
U is preserved quantum possibility — and therefore higher accuracy.