Source: https://www.linkedin.com/feed/update/urn%3Ali%3Ashare%3A6593725739252670464
#AI #ML #DL #DataScience: #Causality, #Interpretability, #Explainability & #Causal #Assumptions:
#Princeton Presentations on #Quantitative #Modeling:
ModelRiskArbitrage.com:
On #MisMeasurement of Key #Constructs and #ModelRisks Underpinning Global Survival:
A Lot Rides on the #Modelers #Assumptions as Most Trained #Quantitative Modelers may already Recognize.
However Many NOT Trained in #SocioTechnical #QuantitativeModeling such as in #ComputerScience #Telecommunications #NetworkSecurity and #ElectricalEngineering MUST come up to speed with such #Foundations. This is all the more critical when their work underpins #Core #NationalSecurity & #NationalPolicy Issues such as #Core #National and #Global #Information #Infrastructures (#NII, #GII).
Over span of last 25-years or so, such #Critical #Disconnects in #AI #ML #DL R&D are evident across ‘disciplinary’ #SILOS of #academia, #research, #policy, & #practices in #HardSciences such as #ComputerScience & #InformationSystems (and related AI-ML-DL Research) and #SocialSciences such as #Social #Behavioral #Cognitive #Pschology and #HumanLearning.
Having Survived 70%-80% #SystemsFailure Rates Despite Exponential IT Advancements and #GlobalFinancialCrisis, #Lessons Learned MUST Help Us Avert a #HumanMade Global Nuclear Crisis.
