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BayesiaLab & LawFree Seminar for Law Practitioners:

Bayesian Networks — Artificial Intelligence for Judicial Reasoning 

Regus — 1050 Connecticut Ave NW, Suite 500, Washington, DC 20036
Tuesday, January 21, 2020, 2:00 p.m.–5:00 p.m.

BayesiaLab

"Bayesian networks are the natural language of jurisprudence. They can subsume laws, evidential reasoning, and causal inference. To this day, however, law practitioners have been using a kind of ersatz code — human language."

In this workshop for law professionals, we present a unified, normative framework for judicial reasoning by implementing the Bayesian network formalism with the BayesiaLab 9 software. This provides a visual and explainable approach to Artificial Intelligence that supports core reasoning tasks in the practice of law, such as:

Probabilistic Evidential Reasoning

  • Probabilistic reasoning with many pieces of evidence
  • Handling the Prosecutor's Fallacy (Fallacy of the Transposed Conditional)
  • Quantifying the importance of evidence (Mutual Information)
  • Quantifying the conflict in evidence (Bayes Factor)
  • Analysis of evidence consistency 
  • Using joint probability as a measure of plausibility
  • Detecting anomalies and deceit
  • Reconstructing foreseeability

Causal Inference

  • Formal and intuitive treatment of causation, prevention, omission, and omission of prevention
  • Analysis of proximate causes
  • Evaluation of bias claims and discrimination (dealing with Simpson's Paradox)
  • Causal inference for estimating effects from observational data and expert knowledge
  • Counterfactual causal analysis ("Had it not been for...")
  • Computing the "most relevant explanation" of an observed outcome
  • Contribution/attribution analysis for allocating damages between multiple defendants

Decision Support & Optimization

  • Developing adversarial reasoning strategies
  • Quantifying outcome uncertainty (Entropy)
  • Modeling jury perception
  • Estimating overall case risk for optimum settlement/plea timing

Seminar Format, Technology, and Materials

  • BayesiaLab SeminarIn this seminar, we alternate slides presentations and group discussions of case studies using BayesiaLab as the reasoning platform.
  • The number of participants is limited to 24.
  • There will be one 10-minute break at approx. 3:30 p.m.
  • You will receive all presentation slides in PDF format.
  • You can download all Bayesian network models used in the seminar.

Requirements

  • This seminar is intended exclusively for law practitioners, i.e., lawyers, attorneys, judges, corporate counsels, law clerks, arbitrators, plus law students and law school faculty.
  • No mathematical, statistical, or programming skills are required as background. 
  • Even though the seminar is free of mathematical formulas and statistical jargon, it is a fast-paced and intellectually challenging program. So, your full concentration over three hours will be required.

Additional Resources

About the Instructor

Stefan ConradyStefan Conrady has over 20 years of corporate experience in with leading automotive brands, such as Mercedes-Benz, BMW, and Rolls-Royce Motor Cars. Stefan is a native of Ulm, Germany, but his career has spanned the globe, having lived and worked in Chicago, New York, Munich, and Singapore, just to name a few. In his most recent corporate assignment, he was heading the Analytics & Forecasting group at Nissan North America.

Today, in his role as Managing Partner of Bayesia USA and Bayesia Singapore, he is recognized as a thought leader in applying Artificial Intelligence for research, analytics, and reasoning. Stefan's tutorials, seminars, and lectures on Bayesian Networks are widely followed by scientists who embrace AI innovations to improve decision-making. In this context, Stefan has recently co-authored a book with Lionel Jouffe, Bayesian Networks & BayesiaLab — A Practical Introduction for Researchers.

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