GeoVerse Lab
← AI & Computing Sciences Division

AI Safety & Alignment Center

Researches AI alignment, mechanistic interpretability, robustness, and evaluation methods - including RLHF, red-teaming, and scalable oversight - to ensure advanced AI systems remain safe, controllable, and beneficial when deployed in high-stakes scientific and societal settings.

⚙️ GeoVerse System Administration Division🖥️ AI & Computing Sciences Division🔬 Basic Sciences Division⚡ Intelligent Geophysical Exploration Division🛢️ Resource & Energy Engineering Division🌍 Applied Geoscience Solutions Division💼 Economics, Policy & Strategy Division🎓 Education & Training Development Division🚀 Innovation & International Collaboration Division
Machine Learning CenterNatural Language Processing CenterComputer Vision CenterHigh-Performance Computing CenterQuantum Computing CenterGenerative AI & Foundation Models CenterReinforcement Learning & Agents CenterAI Safety & Alignment CenterAI for Science CenterRobotics & Embodied AI Center
Norbert Wiener🔑
⭐ Center Chief
Norbert Wiener
Center Head
💡 Cybernetics founder, early warnings on AI risk
Auguste Kerckhoffs🔑
1835–1903
Auguste Kerckhoffs
Researcher
💡 Formulated Kerckhoffs's Principle — a system must remain secure even if everything about it except the key is public knowledge — the foundational security-engineering assumption underlying adversarial robustness and red-teaming evaluation of AI systems
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
W. Ross Ashby🔑
1903–1972
W. Ross Ashby
Researcher
💡 Founded cybernetic control theory (Law of Requisite Variety, the Homeostat), establishing how a regulator must model a system's variety to control it — the systems-theoretic root of AI alignment
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Bruno de Finetti🔑
1906–1985
Bruno de Finetti
Researcher
💡 Founded the subjectivist (Bayesian) theory of probability and the exchangeability theorem, and defined calibration as the criterion for a good subjective probability forecaster — foundational to evaluating whether an AI system's confidence estimates are trustworthy
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Lev Pontryagin🔑
1908–1988
Lev Pontryagin
Researcher
💡 Founded optimal control theory (Pontryagin's Maximum Principle), the mathematical framework for steering a dynamical system toward a goal under constraints — directly relevant to the theory of maintaining control/corrigibility over autonomous AI agents
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
John Forbes Nash Jr.🔑
1928–2015
John Forbes Nash Jr.
Researcher
💡 Founded non-cooperative game theory and the Nash equilibrium, the formal framework for analyzing strategic interaction between agents — the game-theoretic foundation of AI safety debate and multi-agent oversight protocols
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Immanuel Kant🔑
1724–1804
Immanuel Kant
Researcher
💡 Founded deontological ethics (the Categorical Imperative — act only on principles universalizable and treating persons as ends, not merely means), one of the two dominant ethical frameworks (alongside utilitarianism) debated for encoding constraints in AI systems
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
John Rawls🔑
1921–2002
John Rawls
Researcher
💡 Founded modern theory of distributive justice (justice as fairness, the veil of ignorance, the difference principle), the philosophical foundation most cited in algorithmic fairness research for defining what a 'fair' AI decision procedure should achieve
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Hans Jonas🔑
1903–1993
Hans Jonas
Researcher
💡 Formulated the 'imperative of responsibility' — that the unprecedented power of modern technology demands a new ethics of long-term, precautionary responsibility to future generations, foundational to AI governance frameworks
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Donald O. Hebb🔑
1904–1985
Donald O. Hebb
Researcher
💡 Proposed the theory that neurons wire together via correlated activity ('cells that fire together wire together'), founding the study of how distributed representations encode concepts — the theoretical root of interpreting learned features in neural networks
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Leonid Hurwicz🔑
1917–2008
Leonid Hurwicz
Researcher
💡 Founded mechanism design theory, showing how to design incentive structures so that self-interested agents' rational behavior reveals their true preferences and produces desired outcomes — directly foundational to inverse reinforcement learning and incentive alignment
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Frank P. Ramsey🔑
1903–1930
Frank P. Ramsey
Researcher
💡 Founded subjective expected-utility theory, providing the axiomatic basis for representing an agent's preferences as a utility function derivable from choices — the mathematical foundation of reward modeling from human feedback
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Charles Perrow🔑
1925–2019
Charles Perrow
Researcher
💡 Founded Normal Accident Theory — that catastrophic failures are inevitable in tightly coupled, complex systems regardless of safeguards — a foundational framework for analyzing systemic risk in complex, opaque AI systems
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
J. C. R. Licklider🔑
1915–1990
J. C. R. Licklider
Researcher
💡 Founded the vision of 'man-computer symbiosis' — humans and machines cooperating with complementary strengths under meaningful human oversight — the foundational framework for trustworthy, human-compatible AI system design
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Robert W. Floyd🔑
1936–2001
Robert W. Floyd
Researcher
💡 Founded formal program verification (Floyd-Hoare logic, assigning preconditions/postconditions to prove program correctness), the mathematical foundation for formally verifying that safety-critical AI systems satisfy specified properties
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center
Herman Kahn🔑
1922–1983
Herman Kahn
Researcher
💡 Founded systematic future/scenario analysis for low-probability, catastrophic risks ('thinking about the unthinkable'), pioneering the methodology of existential-risk analysis later applied to advanced AI
🖥️ AI & Computing Sciences DivisionAI Safety & Alignment Center