
Explore our seminars, learn directly from AI safety researchers, and find the guidance and support your career or project needs to make a real impact.
Our speakers have worked or collaborated with
Apart Research
Google DeepMind
OpenAI
MIRI
Future of Life Institute
Center for AI Safety
LASR Labs
SaferAI
Pour Demain
BlueDot Impact
AI Governance Club (BlueDot)
Cambridge AI Safety Hub
ML4Good
Kairos
AI Risk Explorer
ORCG
PauseAI
BAISH
AI Safety México
AI Safety Colombia
AI Safety Barcelona
CEGIA
Women4AISafety
DLR
Max Planck
IIT
Princeton
TUM
UPM
UPC
UPV
UBA
Universidad de los Andes
UNAM
Universidad Politécnica de Yucatán
ITK Engineering
Mercado Libre
Sezzle
TShaped
Jaime entered AI safety through a hackathon and now leads Apart Research. Discover how to build a real career in AI safety from scratch.

Can AI deceive us in its own reasoning? Pablo presents CoT Red-Handed, exploring the limits and solutions for monitoring AI chains of thought.

Alejandro Tlaie analyzes how AI agents autonomously hack systems in real environments, evaluating urgent challenges in governance, auditing, and cybersecurity.

Janeth, coordinator of AI Safety Mexico, maps the regional ecosystem and reviews projects like VIGÍA to drive AI safety in Spanish.

Joaquín analyzes the limits of 'AI safety via debate' against models with asymmetric capabilities, showing how protocol design can enforce AI honesty.

Dani analyzes the Mythos/Glasswing case, addressing the risks of AI capability proliferation and the political urgency raised by PauseAI.

Mariana Hungría examines Digital Linguistic Bias as a governance problem: what it means that large language models fail to adequately represent the Spanish-speaking world.

Eitan, AI safety researcher and co-founder of BAISH, on building a career in this field from Buenos Aires.

An industry insider's look at whether recent state restriction episodes mark the start of government control over frontier AI.

Melissa is a mathematician with a master's degree in Systems Engineering, presenting her research on bias detection in supervised models and language models, with particular attention to contextual biases in the Spanish language.

José Gelves, director of AI Safety Colombia, explains why the real bottleneck in AI safety isn't technical research, but the lack of generalist talent and institutional coordination.

Guillem Bas, Head of Projects at the AI Risk Explorer (AIRE), explains how the systematic collection and synthesis of public evidence makes it possible to monitor AI risks rigorously.

Tobias Martin, communicator and researcher at MIRI, explains how to find and create opportunities in AI safety as a Spanish speaker, in a field so new that it is still full of gaps to fill.

Andrés Lage Freire, an AI governance engineering specialist, explains why probabilistic models need deterministic boundaries once they move from proposing to acting, through a separation of powers inspired by Montesquieu.
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