Welcome to the Nexus of Ethics, Psychology, Morality, Philosophy and Health Care

Welcome to the nexus of ethics, psychology, morality, technology, health care, and philosophy
Showing posts with label Sampling. Show all posts
Showing posts with label Sampling. Show all posts

Thursday, October 29, 2020

Probabilistic Biases Meet the Bayesian Brain.

Chater N, et al.
Current Directions in Psychological Science. 
2020;29(5):506-512. 
doi:10.1177/0963721420954801

Abstract

In Bayesian cognitive science, the mind is seen as a spectacular probabilistic-inference machine. But judgment and decision-making (JDM) researchers have spent half a century uncovering how dramatically and systematically people depart from rational norms. In this article, we outline recent research that opens up the possibility of an unexpected reconciliation. The key hypothesis is that the brain neither represents nor calculates with probabilities but approximates probabilistic calculations by drawing samples from memory or mental simulation. Sampling models diverge from perfect probabilistic calculations in ways that capture many classic JDM findings, which offers the hope of an integrated explanation of classic heuristics and biases, including availability, representativeness, and anchoring and adjustment.

Introduction

Human probabilistic reasoning gets bad press. Decades of brilliant experiments, most notably by Daniel Kahneman and Amos Tversky (e.g., Kahneman, 2011; Kahneman, Slovic, & Tversky, 1982), have shown a plethora of ways in which people get into a terrible muddle when wondering how probable things are. Every psychologist has learned about anchoring, conservatism, the representativeness heuristic, and many other ways that people reveal their probabilistic incompetence. Creating probability theory in the first place was incredibly challenging, exercising great mathematical minds over several centuries (Hacking, 1990). Probabilistic reasoning is hard, and perhaps it should not be surprising that people often do it badly. This view is the starting point for the whole field of judgment and decision-making (JDM) and its cousin, behavioral economics.

Oddly, though, human probabilistic reasoning equally often gets good press. Indeed, many psychologists, neuroscientists, and artificial-intelligence researchers believe that probabilistic reasoning is, in fact, the secret of human intelligence.

Saturday, March 10, 2018

Universities Rush to Roll Out Computer Science Ethics Courses

Natasha Singer
The New York Times
Originally posted February 12, 2018

Here is an excerpt:

“Technology is not neutral,” said Professor Sahami, who formerly worked at Google as a senior research scientist. “The choices that get made in building technology then have social ramifications.”

The courses are emerging at a moment when big tech companies have been struggling to handle the side effects — fake news on Facebook, fake followers on Twitter, lewd children’s videos on YouTube — of the industry’s build-it-first mind-set. They amount to an open challenge to a common Silicon Valley attitude that has generally dismissed ethics as a hindrance.

“We need to at least teach people that there’s a dark side to the idea that you should move fast and break things,” said Laura NorĂ©n, a postdoctoral fellow at the Center for Data Science at New York University who began teaching a new data science ethics course this semester. “You can patch the software, but you can’t patch a person if you, you know, damage someone’s reputation.”

Computer science programs are required to make sure students have an understanding of ethical issues related to computing in order to be accredited by ABET, a global accreditation group for university science and engineering programs. Some computer science departments have folded the topic into a broader class, and others have stand-alone courses.

But until recently, ethics did not seem relevant to many students.

The article is here.