AIQ: How People and Machines Are Smarter Together
by Nick Polson and James Scott · 14 May 2018 · 301pp · 85,126 words
because people have made poor choices in tending the soil. There are three prime ways in which this can happen: 1. Rage to conclude. 2. Model rust. 3. Bias in, bias out. To illustrate these themes, we’ll ask for a little bit of help from a midcentury American icon: Joe DiMaggio
…
conclude, by remembering that every unverified assumption is a placeholder—an approximation to be used, for better or worse, only until more data is available. Model Rust You’ve now seen how poor assumptions, embedded into the very DNA of a model, can result in dreadful mistakes. Models aren’t always born
…
easily turn to rust. Neglect it some more, and eventually the model just rots away into nothing. Flu Trends suffered from a serious case of model rust, verging on rot. To understand why, we spoke to Dr. Rosalind Eggo, an infectious-disease researcher at the London School of Hygiene & Tropical Medicine. She
…
assumptions and bias in, bias out contraception and criminal justice system and democratization of diffusion and dissemination of enabling technological trends image classification image recognition model rust models versus reality Moravec paradox policy rage to conclude bias robot cars salaries SLAM problem (simultaneous localization and mapping) speech recognition talent and workforce twenty
…
care and medicine Medtronic Menger, Karl Microsoft Microsoft Azure modeling assumptions and deep-learning models imputation and Inception latent feature massive models missing data and model rust natural language processing and prediction rules as reality versus rules-based (top-down) models training the model Moneyball Moore’s law Moravec paradox Morgenstern, Oskar