Data Science Ethics
02.02.2022
Bulletin
- Homework 02 due Friday
- Lab 04 due date extended: due Friday, Feb 11
- Exam 01 will be released Friday, due Tuesday 11:59pm
Today
- Questions from
ae07? - Data misrepresentation, data ethics and algorithmic bias
Guidelines for Discussion
Listen respectfully. Listen actively and with an ear to understanding others’ views.
Criticize ideas, not individuals.
Commit to learning, not debating. Comment in order to share information, not to persuade.
Avoid blame, speculation, and inflammatory language.
Avoid assumptions about any member of the class or generalizations about social groups.
Data Representation
Collecting + handling data3
Web scraping
A data analyst received permission to post a data set that was scraped from a social media site. The full data set included name, screen name, email address, geographic location, IP (Internet protocol) address, demographic profiles, and preferences for relationships. The analyst removes name and email address from the data set in effort to deidentify it.
Why might it be problematic to post this data set publicly?
How can you store the full dataset in a safe and ethical way?
You want to make the data available so your analysis is transparent and reproducible. How can you modify the full data set to make the data available in an ethical way?
Algorithmic bias: deep dive
Discussion questions
- Ezinne mentions a phenomenon called “Simpson’s Paradox”, where conclusions drawn from analyzing subgroups differ from conclusions drawn when the groups are combined. Can you demonstrate Simpson’s Paraxox with the data below? 4
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
## ✓ tibble 3.1.5 ✓ dplyr 1.0.7
## ✓ tidyr 1.1.4 ✓ stringr 1.4.0
## ✓ readr 1.4.0 ✓ forcats 0.5.1## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()berk = read_csv("data/BerkeleyAdmissionsData.csv")##
## ── Column specification ────────────────────────────────────────────────────────
## cols(
## Dept = col_character(),
## MaleYes = col_double(),
## MaleNo = col_double(),
## FemaleYes = col_double(),
## FemaleNo = col_double()
## )berkA company uses a machine learning algorithm to determine which job advertisement to display for users searching for technology jobs. Based on past results, the algorithm tends to display lower paying jobs for women than for men (after controlling for other characteristics than gender). What ethical considerations might be considered when reviewing this algorithm?5
As you start working on data analyses for the STA 199 project, internships, research, etc., what are 1 - 2 things you can do to ensure you’re doing the analysis in an ethical way?
Source: https://humansofdata.atlan.com/2019/02/dos-donts-data-visualization↩︎
Source: https://www.tylervigen.com/spurious-correlations Content warning: some examples include death or suicide.↩︎
Modified from Modern Data Science with R, 2nd Edition↩︎
Source: https://www.randomservices.org/random/data/Berkeley.html↩︎
Source: Modern Data Science with R, 2nd Edition↩︎