Webinar Series - Welcome to the Chance Age

AI and Stochastic Data have enabled a new way to measure Chance: The ChanceOmeter. Have no idea what stochastic data is? Then this series is for you!

You may play with the ChanceOmeters above on your phone by using the QR code if you are viewing this on a computer or clicking the link directly if you are on your phone.

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Three live presentations by Dr. Sam Savage

Dr. Sam L. Savage is the Executive Director of ProbabilityManagement.org, a 501(c)(3) nonprofit devoted to standardizing the communication and calculation of uncertainty. The organization has received funding from Chevron, Kaiser Permanente, Highmark Health, Lockheed Martin, PG&E, and others, and Harry Markowitz, Nobel Laureate in Economics was a co-founding board member. Dr. Savage is author of The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty (John Wiley & Sons, 2009, 2012) and Chancification: Fixing the Flaw of Averages (2022). He is the inventor of the Stochastic Information Packet (SIP), an auditable data array for conveying uncertainty. He is an Adjunct in Civil and Environmental Engineering at Stanford University.

The world is uncertain…

yet we manage it with averages—producing systematic errors known as the Flaw of Averages. Avoid these pitfalls with this webinar series.

Across these three webinars, the series moves from Ideas to Language to Infrastructure, showing how Coherent Stochastic Data form the foundation of the Chance Economy.

The first installment, Give Chance a Chance, covers the ChanceOmeter and the basic concepts for reasoning about uncertainty.
The second, AI’s Native Tongue: The Language of Chance, shows how AI can generate stochastic data, enabling direct calculations with uncertainty itself.
The final installment, The Probability Power Grid, brings it all together—describing the full technology stack required to operate in the Chance Economy.

No statistics is assumed. However, for those with extensive training in the field, these webinars will repair the damage.