EIRINI MALLIARAKI
ABOUT
eirinimalliaraki@gmail.com
Twitter, Linkedin, Substack
Technologist, researcher, and former founder. I build tools, programmes, and infrastructure at the intersection of AI, frontier science, and public-good innovation. I trained as a design engineer at Imperial College London and the Royal College of Art. Before that, a BSc in Finance from the Athens University of Economics and Business.
Three preoccupations have shaped the past decade: how intelligence emerges and travels across minds, machines, and ecosystems; what infrastructure a field needs to translate knowledge into action; and what it means to build systems that regenerate rather than extract. I've pursued all three — across startups, research labs, national AI institutes, and philanthropy.
I’m based in London, and my email is always open to ethersamplers, epistemic humorists, and ungoogleable souls.
Other curiosities: Complex systems & memetic engineering · Extended cognition · Theorising entanglement · Radical social futures · New learning environments · Community praxis · The Arctic · Soulmaking Dharma · Planetarity · Post-human design · Collective imagination · The surreal · Science Roadmapping
CV
COLLECTIVE INTELLIGENCE DESIGN @ NESTA
COLLECTIVE INTELLIGENCE DESIGN @ NESTA
Collective intelligence
Artificial Intelligence
2021
DESCRIPTION
I designed and managed an internal crowdsourced forecasting program called Nestadamus, to help Nesta more accurately forecast and prepare for organisational risk. We are using the wisdom of the crowd, i.e., Nesta employees, to: increase our accuracy in assessing and forecasting risks; provide a forum that gives everyone an impactful way to voice their perspectives; uncover blind spots; and establish a process with feedback and accountability for risk assessment.
Crowdsourced forecasting is the ongoing collection of predictions (typically in the form of a probability) from a large, diverse group of people, which are then aggregated into a “crowd” or “consensus” forecast about a future event. This consensus probability can be tracked and used as ongoing insights for decision-making. Groups of super-forecasters have been found to be more accurate than experts, and similar efforts have been repeatedly proven in the public and private sectors around the world.
Also authored the winning €2.7M EU Commission bid for HACID — a participatory AI system that combines human and machine intelligence for climate adaptation decision-making. Co-authored publications for the Red Cross, OECD and ACM.