Data Governance, Ethics and Privacy
zhugedali321
Session2_CUSPBiasPresentation09132022.pdf
Understanding Source of Bias and Fairness in Data Science
Professor Manny Patole
September 13, 2022
Our Conversation Bias and Fairness in Data Science
● A story
● A few definitions
● An unintended consequence
● A conversation
“If we took every science book, and every fact, and destroyed them all, in a thousand years they’d all be back, because all the same tests would [produce] the same results.” - Ricky Gervais
Fact is indisputable. Truth is acceptable. “It’s easy to lie with statistics, but it’s hard to tell the truth without them.” - Charles Wheelan
A fact is something that’s indisputable, based on empirical research and quantifiable measures Facts are proven through: ● Calculation ● Experience Defined by event in
the past ● Repetition
Truth is different, include fact as well as belief. Groups may accept things as true because: ● Close to their comfort zones ● Accepted easily into their comfort
zones ● Reflect their preconceived
notions of reality. Why is it important to collect facts and not truths?
Why should this important to you?
The law of unintended consequences is a frequently-observed phenomenon in which any action has results that are not part of the actor's purpose. The superfluous consequences may or may not be foreseeable or even immediately observable and they may be beneficial, harmful or neutral in their impact.
- Robert K. Merton
Plagiarism
Plagiarism is a type of cheating that involves the use of another person's ideas, words, design, art, music, etc., as one's own in whole or in part without acknowledging the author or obtaining his or her permission. Plagiarism is not just restricted to written text, but is applicable to other works such as ideas, design, art, and music.
- Northern Illinois University (2020)
What is the connection between Plagiarism, Power, and Justice?
What do you owe to… Your colleagues? Your instructors?
Your communities?
