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Stefan Conrady
Managing Partner, Bayesia USA & Singapore
Keynote by Olivier Sibony: Noise — A Flaw in Human Judgment Abstract: Imagine that two doctors in the same city give different diagnoses to identical patients—or that two judges in the same courthouse give markedly different sentences to people who have committed the same crime. Suppose that different interviewers at the same firm make different decisions about indistinguishable job applicants—or that when a company is handling customer complaints, the resolution depends on who happens to answer the phone. Now imagine that the same doctor, the same judge, the same interviewer, or the same customer service agent makes different decisions depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical. In Noise, Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein show the detrimental effects of noise in many fields, including medicine, law, economic forecasting, forensic science, bail, child protection, strategy, performance reviews, and personnel selection. Wherever there is judgment, there is noise. Yet, most of the time, individuals and organizations alike are unaware of it. They neglect noise. With a few simple remedies, people can reduce both noise and bias, and so make far better decisions. Packed with original ideas, and offering the same kinds of research-based insights that made Thinking, Fast and Slow and Nudge groundbreaking New York Times bestsellers, Noise explains how and why humans are so susceptible to noise in judgment—and what we can do about it. About the Presenter: Olivier Sibony is... (More)
Stefan Conrady
Managing Partner, Bayesia USA & Singapore
Cybersecurity Risk Assessment with Bayesian Networks

Risk assessment is challenging when data is unavailable, hard to obtain, or costly to process. Organizations often request estimates from experts instead. This talk demonstrates how to integrate cybersecurity data with expert estimates using Bayesian Networks. Cybersecurity analysts, resource managers, and executives can use Bayesian Network models to perform risk assessments, select security controls, and prioritize which suspicious events to investigate first. System administrators can configure autonomous sources of data including vulnerability scanners and cybersecurity event monitoring systems to automatically update these hybrid network models alongside inputs from risk analysts and executives.

About the Presenter
Corey Neskey has been providing analyses, architecting secure environments, and leading security program implementations in IT security and risk since 2011. His career started with informing executive decision-making using algebraic data analyses for explanation, simulation, and attribution (i.e., intelligence analysis, forensics, SOC, CIRT), and optimization. His toolset expanded to more descriptive and predictive methods (i.e., machine learning/AI for risk assessment, vulnerability prioritization, event correlation). He is now developing skills for integrating these analytical areas and expanding beyond algebraic methods and static probability calculus to using Bayesian network models.

https://youtu.be/JOBd4EX8cZ0
Stefan Conrady
Managing Partner, Bayesia USA & Singapore
Dr. Lionel Jouffe presents the key innovations of BayesiaLab 10 at the 2021 BayesiaLab Conference.