AI News, College Admissions: How AI Can Help Fight Biases artificial intelligence

A Question of “Artificial” Ethics?

AI and its inherent hidden data biases have already affected careers, interview possibilities, the ability to obtain home loans, and criminal cases.

If number of arrests is used to decide on sentencing recommendations, race plays a role, and that heavily influences these data sets.

“While building models, product managers (business analysts) and data scientists do take steps to ensure that correct/generic data…have been used to build (train/test) the model, the unintentional exclusion of some of the important features or data sets could result in bias.” Perhaps everyone in AI needs to remember that old computer credo: Garbage in, garbage out.

Predictive Analytics for Good in Higher Education: Part 1

I was offered an academic scholarship to Rhodes College, but I turned it down because they were a D III football program and I thought I could get better offers.


In his most recent book, “Think Again: How to Reason and Argue” (Penguin and Oxford University Press, 2018), Professor Sinnott-Armstrong analyzes contemporary social discourse and teaches the art of arguing as a means toward compromise and cooperation.

Through interdisciplinary projects as well as a vertically-integrated lab, students and faculty work together to better understand aspects of human motivation and human behavior, and to disseminate findings on these normative, ethical issues.” Emilia Chiscop-Head.: Professor Walter Sinnott-Armstrong, you are a renowned ethicist of Artificial Intelligence and Professor in the Duke Philosophy Department and the Kenan Institute for Ethics with secondary appointments at Duke Law School and the Department of Psychology and Neuroscience.

You mentioned that “lethal autonomous weapons systems may be more moral than traditional human-to-human engagement” because they might be able to increase effectiveness and deterrence while reducing civilian deaths.

Weapons without precise targeting cannot stop enemies without also killing lots of nearby innocent civilians, whereas more precise weapons can be used to prevent aggression without causing as much “collateral damage.” Artificial intelligence and precision in military weapons does not ensure that humans will do the right thing, but they can enable good people to stop bad people with more certainty and less cost.

The main sources of such moral errors seem to be ignorance of relevant facts, forgetting important aspects of a problem, getting confused by complexity, being overcome or misled by emotion, and bias and partiality.

But the ability of AI to avoid the main sources of error in human moral judgments suggests that AI might be able help us humans avoid many bad decisions.

This opacity becomes important, for example, if AI is used to decide bail, sentencing, or parole in criminal justice systems, because then people who are accused cannot defend themselves against adverse decisions by AI.

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