From da8a8f1e0175700d453be444fd7973a1039a8fcc Mon Sep 17 00:00:00 2001
From: Katie Wetstone <46792169+klwetstone@users.noreply.github.com>
Date: Mon, 1 Jul 2024 00:39:55 -0400
Subject: [PATCH] Add positive examples (#175)
* update readme in _common_body
* update readme and index.md to preview
* list spacing
* final README updates
* test bullet formatting
* test css changes
* undo css testing
* add positive examples
* categorize examples as positive or negative
* remove repeat gorilla story
* adjust section description
* add a few more positive examples
* update md files
* tweak README
* add more positive examples
* more examples
* tweak readme
* remove extra css
* revert markdown files
* fully revert examples.md
---
deon/assets/examples_of_ethical_issues.yml | 118 ++++++++++++---------
docs/md_templates/_common_body.tpl | 31 +++---
docs/md_templates/examples.tpl | 4 +-
docs/render_templates.py | 2 +-
4 files changed, 88 insertions(+), 67 deletions(-)
diff --git a/deon/assets/examples_of_ethical_issues.yml b/deon/assets/examples_of_ethical_issues.yml
index a9fad18..4c03b61 100644
--- a/deon/assets/examples_of_ethical_issues.yml
+++ b/deon/assets/examples_of_ethical_issues.yml
@@ -1,138 +1,156 @@
- line_id: A.1
links:
- - text: Facebook uses phone numbers provided for two-factor authentication to target users with ads.
+ - text: ✅ A voiceover studio is now required to get informed consent from a performer before using their likeness in AI-generated content.
+ url: https://variety.com/2024/biz/news/sag-aftra-ai-voiceover-studio-video-games-1235866313/
+ - text: ⛔ Facebook uses phone numbers provided for two-factor authentication to target users with ads.
url: https://techcrunch.com/2018/09/27/yes-facebook-is-using-your-2fa-phone-number-to-target-you-with-ads/
- - text: African-American men were enrolled in the Tuskegee Study on the progression of syphilis without being told the true purpose of the study or that treatment for syphilis was being withheld.
+ - text: ⛔ African-American men were enrolled in the Tuskegee Study on the progression of syphilis without being told the true purpose of the study or that treatment for syphilis was being withheld.
url: https://en.wikipedia.org/wiki/Tuskegee_syphilis_experiment
- - text: OpenAI's ChatGPT memorized and regurgitated entire poems without checking for copyright permissions.
+ - text: ⛔ OpenAI's ChatGPT memorized and regurgitated entire poems without checking for copyright permissions.
url: https://news.cornell.edu/stories/2024/01/chatgpt-memorizes-and-spits-out-entire-poems
- line_id: A.2
links:
- - text: StreetBump, a smartphone app to passively detect potholes, may fail to direct public resources to areas where smartphone penetration is lower, such as lower income areas or areas with a larger elderly population.
+ - text: ⛔ StreetBump, a smartphone app to passively detect potholes, may fail to direct public resources to areas where smartphone penetration is lower, such as lower income areas or areas with a larger elderly population.
url: https://hbr.org/2013/04/the-hidden-biases-in-big-data
- - text: Facial recognition cameras used for passport control register Asian's eyes as closed.
+ - text: ⛔ Facial recognition cameras used for passport control register Asian's eyes as closed.
url: http://content.time.com/time/business/article/0,8599,1954643,00.html
- line_id: A.3
links:
- - text: Personal information on taxi drivers can be accessed in poorly anonymized taxi trips dataset released by New York City.
+ - text: ✅ DuckDuckGo enables users to anonymously access ChatGPT by *not* collecting user IP addresses along with queries.
+ url: https://www.theverge.com/2024/6/6/24172719/duckduckgo-private-ai-chats-anonymous-gpt-3-5
+ - text: ⛔ Personal information on taxi drivers can be accessed in poorly anonymized taxi trips dataset released by New York City.
url: https://www.theguardian.com/technology/2014/jun/27/new-york-taxi-details-anonymised-data-researchers-warn
- - text: Netflix prize dataset of movie rankings by 500,000 customers is easily de-anonymized through cross referencing with other publicly available datasets.
+ - text: ⛔ Netflix prize dataset of movie rankings by 500,000 customers is easily de-anonymized through cross referencing with other publicly available datasets.
url: https://www.wired.com/2007/12/why-anonymous-data-sometimes-isnt/
- line_id: A.4
links:
- - text: In six major cities, Amazon's same day delivery service excludes many predominantly black neighborhoods.
+ - text: ⛔ In six major cities, Amazon's same day delivery service excludes many predominantly black neighborhoods.
url: https://www.bloomberg.com/graphics/2016-amazon-same-day/
- - text: Facial recognition software is significanty worse at identifying people with darker skin.
+ - text: ⛔ Facial recognition software is significanty worse at identifying people with darker skin.
url: https://www.theregister.co.uk/2018/02/13/facial_recognition_software_is_better_at_white_men_than_black_women/
- line_id: B.1
links:
- - text: Personal and financial data for more than 146 million people was stolen in Equifax data breach.
+ - text: ✅ MediCapt, which documents forensic evidence in conflict regions, effectively protects sensitive information using encryption, limited access, and security audits.
+ url: https://phr.org/issues/sexual-violence/medicapt/
+ - text: ⛔ Personal and financial data for more than 146 million people was stolen in Equifax data breach.
url: https://www.nbcnews.com/news/us-news/equifax-breaks-down-just-how-bad-last-year-s-data-n872496
- - text: Cambridge Analytica harvested private information from over 50 million Facebook profiles without users' permission.
+ - text: ⛔ Cambridge Analytica harvested private information from over 50 million Facebook profiles without users' permission.
url: https://www.nytimes.com/2018/03/17/us/politics/cambridge-analytica-trump-campaign.html
- - text: AOL accidentally released 20 million search queries from 658,000 customers.
+ - text: ⛔ AOL accidentally released 20 million search queries from 658,000 customers.
url: https://www.wired.com/2006/08/faq-aols-search-gaffe-and-you/
- line_id: B.2
links:
- - text: The EU's General Data Protection Regulation (GDPR) includes the "right to be forgotten."
+ - text: ✅ The EU's General Data Protection Regulation (GDPR) includes the "right to be forgotten."
url: https://www.eugdpr.org/the-regulation.html
- line_id: B.3
links:
- - text: FedEx exposes private information of thousands of customers after a legacy s3 server was left open without a password.
+ - text: ⛔ FedEx exposes private information of thousands of customers after a legacy s3 server was left open without a password.
url: https://www.zdnet.com/article/unsecured-server-exposes-fedex-customer-records/
- line_id: C.1
links:
- - text: When Apple's HealthKit came out in 2014, women couldn't track menstruation.
+ - text: ✅ Code for America programmatically cleared >140,000 eligible criminal records by collaborating with multiple relevant stakeholders like policymakers, advocacy groups, and courts.
+ url: https://codeforamerica.org/programs/criminal-justice/automatic-record-clearance/
+ - text: ⛔ When Apple's HealthKit came out in 2014, women couldn't track menstruation.
url: https://www.theverge.com/2014/9/25/6844021/apple-promised-an-expansive-health-app-so-why-cant-i-track
- line_id: C.2
links:
- - text: word2vec, trained on Google News corpus, reinforces gender stereotypes.
+ - text: ✅ A study by Park et al shows how reweighting can mitigate racial bias when predicting risk of postpartum depression.
+ url: https://doi.org/10.1001/jamanetworkopen.2021.3909
+ - text: ⛔ word2vec, trained on Google News corpus, reinforces gender stereotypes.
url: https://www.technologyreview.com/s/602025/how-vector-space-mathematics-reveals-the-hidden-sexism-in-language/
- - text: Women are more likely to be shown lower-paying jobs than men in Google ads.
+ - text: ⛔ Women are more likely to be shown lower-paying jobs than men in Google ads.
url: https://www.theguardian.com/technology/2015/jul/08/women-less-likely-ads-high-paid-jobs-google-study
- line_id: C.3
links:
- - text: Misleading chart shown at Planned Parenthood hearing distorts actual trends of abortions vs. cancer screenings and preventative services.
+ - text: ⛔ Misleading chart shown at Planned Parenthood hearing distorts actual trends of abortions vs. cancer screenings and preventative services.
url: https://www.politifact.com/truth-o-meter/statements/2015/oct/01/jason-chaffetz/chart-shown-planned-parenthood-hearing-misleading-/
- - text: Georgia Dept. of Health graph of COVID-19 cases falsely suggests a steeper decline when dates are ordered by total cases rather than chronologically.
+ - text: ⛔ Georgia Dept. of Health graph of COVID-19 cases falsely suggests a steeper decline when dates are ordered by total cases rather than chronologically.
url: https://www.vox.com/covid-19-coronavirus-us-response-trump/2020/5/18/21262265/georgia-covid-19-cases-declining-reopening
- line_id: C.4
links:
- - text: Strava heatmap of exercise routes reveals sensitive information on military bases and spy outposts.
+ - text: ⛔ Strava heatmap of exercise routes reveals sensitive information on military bases and spy outposts.
url: https://www.theguardian.com/world/2018/jan/28/fitness-tracking-app-gives-away-location-of-secret-us-army-bases
- line_id: C.5
links:
- - text: Excel error in well-known economics paper undermines justification of austerity measures.
+ - text: ✅ NASA's Transform to Open Science initiative is working to make research more reproducible and accessible.
+ url: https://nasa.github.io/Transform-to-Open-Science/
+ - text: ✅ Medic's Community Health Tooklit supports health workers in hard-to-reach areas. The toolkit is fully open source on Github for anyone to view or collaborate.
+ url: https://communityhealthtoolkit.org/
+ - text: ⛔ Excel error in well-known economics paper undermines justification of austerity measures.
url: https://www.bbc.com/news/magazine-22223190
- line_id: D.1
links:
- - text: In hypothetical trials, language models assign the death penalty more frequently to defendants who use African American dialects.
+ - text: ✅ Amazon developed an experimental AI recruiting tool, but did not deploy it because it learned to perpetuate bias against women.
+ url: https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G
+ - text: ⛔ In hypothetical trials, language models assign the death penalty more frequently to defendants who use African American dialects.
url: https://arxiv.org/abs/2403.00742
- - text: Variables used to predict child abuse and neglect are direct measurements of poverty, unfairly targeting low-income families for child welfare scrutiny.
+ - text: ⛔ Variables used to predict child abuse and neglect are direct measurements of poverty, unfairly targeting low-income families for child welfare scrutiny.
url: https://www.wired.com/story/excerpt-from-automating-inequality/
- - text: Amazon scraps AI recruiting tool that showed bias against women.
- url: https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G
- - text: Criminal sentencing risk asessments don't ask directly about race or income, but other demographic factors can end up being proxies.
+ - text: ⛔ Criminal sentencing risk asessments don't ask directly about race or income, but other demographic factors can end up being proxies.
url: https://www.themarshallproject.org/2015/08/04/the-new-science-of-sentencing
- - text: Creditworthiness algorithms based on nontraditional criteria such as grammatic habits, preferred grocery stores, and friends' credit scores can perpetuate systemic bias.
+ - text: ⛔ Creditworthiness algorithms based on nontraditional criteria such as grammatic habits, preferred grocery stores, and friends' credit scores can perpetuate systemic bias.
url: https://www.whitecase.com/publications/insight/algorithms-and-bias-what-lenders-need-know
- line_id: D.2
links:
- - text: Apple credit card offers smaller lines of credit to women than men.
+ - text: ✅ A study by Garriga et al uses ML best practices to test for and communicate fairness across racial groups for a model that predicts mental health crises.
+ url: https://www.nature.com/articles/s41591-022-01811-5
+ - text: ⛔ Apple credit card offers smaller lines of credit to women than men.
url: https://www.wired.com/story/the-apple-card-didnt-see-genderand-thats-the-problem/
- - text: Google Photos tags two African-Americans as gorillas.
- url: https://www.forbes.com/sites/mzhang/2015/07/01/google-photos-tags-two-african-americans-as-gorillas-through-facial-recognition-software/#12bdb1fd713d
- - text: With COMPAS, a risk-assessment algorithm used in criminal sentencing, black defendants are almost twice as likely as white defendants to be mislabeled as likely to reoffend.
+ - text: ⛔ With COMPAS, a risk-assessment algorithm used in criminal sentencing, black defendants are almost twice as likely as white defendants to be mislabeled as likely to reoffend.
url: https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
- text: -- Northpointe's rebuttal to ProPublica article.
url: https://www.documentcloud.org/documents/2998391-ProPublica-Commentary-Final-070616.html
- text: -- Related academic study.
url: https://www.liebertpub.com/doi/pdf/10.1089/big.2016.0047
- - text: Google's speech recognition software doesn't recognize women's voices as well as men's.
+ - text: ⛔ Google's speech recognition software doesn't recognize women's voices as well as men's.
url: https://www.dailydot.com/debug/google-voice-recognition-gender-bias/
- - text: Google searches involving black-sounding names are more likely to serve up ads suggestive of a criminal record than white-sounding names.
+ - text: ⛔ Google searches involving black-sounding names are more likely to serve up ads suggestive of a criminal record than white-sounding names.
url: https://www.technologyreview.com/s/510646/racism-is-poisoning-online-ad-delivery-says-harvard-professor/
- - text: -- Related academic study.
- url: https://arxiv.org/abs/1301.6822
- - text: OpenAI's GPT models show racial bias in ranking job applications based on candidate names.
+ - text: ⛔ OpenAI's GPT models show racial bias in ranking job applications based on candidate names.
url: https://www.bloomberg.com/graphics/2024-openai-gpt-hiring-racial-discrimination/
- line_id: D.3
links:
- - text: Facebook seeks to optimize "time well spent", prioritizing interaction over popularity.
+ - text: ✅ Facebook seeks to optimize "time well spent", prioritizing interaction over popularity.
url: https://www.wired.com/story/facebook-tweaks-newsfeed-to-favor-content-from-friends-family/
- - text: YouTube's search autofill suggests pedophiliac phrases due to high viewership of related videos.
+ - text: ⛔ YouTube's search autofill suggests pedophiliac phrases due to high viewership of related videos.
url: https://gizmodo.com/youtubes-creepy-kid-problem-was-worse-than-we-thought-1820763240
- - text: A widely used commercial algorithm in the healthcare industry underestimates the care needs of black patients because it optimizes for spending as a proxy for need, introducing racial bias due to unequal access to care.
+ - text: ⛔ A widely used commercial algorithm in the healthcare industry underestimates the care needs of black patients because it optimizes for spending as a proxy for need, introducing racial bias due to unequal access to care.
url: https://www.science.org/doi/10.1126/science.aax2342
- line_id: D.4
links:
- - text: Patients with pneumonia with a history of asthma are usually admitted to the intensive care unit as they have a high risk of dying from pneumonia. Given the success of the intensive care, neural networks predicted asthmatics had a low risk of dying and could therefore be sent home. Without explanatory models to identify this issue, patients may have been sent home to die.
- url: http://people.dbmi.columbia.edu/noemie/papers/15kdd.pdf
- - text: GDPR includes a "right to explanation," i.e. meaningful information on the logic underlying automated decisions.
+ - text: ✅ GDPR includes a "right to explanation," i.e. meaningful information on the logic underlying automated decisions.
url: hhttps://academic.oup.com/idpl/article/7/4/233/4762325
+ - text: ⛔ Patients with pneumonia with a history of asthma are usually admitted to the intensive care unit as they have a high risk of dying from pneumonia. Given the success of the intensive care, neural networks predicted asthmatics had a low risk of dying and could therefore be sent home. Without explanatory models to identify this issue, patients may have been sent home to die.
+ url: http://people.dbmi.columbia.edu/noemie/papers/15kdd.pdf
- line_id: D.5
links:
- - text: Google Flu claims to accurately predict weekly influenza activity and then misses the 2009 swine flu pandemic.
+ - text: ✅ OpenAI posted an explanation of how ChatGPT is trained to behave, its limitations, and future directions for improvement.
+ url: https://openai.com/index/how-should-ai-systems-behave/
+ - text: ⛔ Google Flu claims to accurately predict weekly influenza activity and then misses the 2009 swine flu pandemic.
url: https://www.forbes.com/sites/stevensalzberg/2014/03/23/why-google-flu-is-a-failure/#6fa6a1925535
- line_id: E.1
links:
- - text: Dutch Prime Minister and entire cabinet resign after investigations reveal that 26,000 innocent families were wrongly accused of social benefits fraud partially due to a discriminatory algorithm.
+ - text: ✅ RobotsMali uses AI to create children's books in Mali's native languages, and incorporates human review to ensure that all AI-generated content is accurate and culturally sensitive.
+ url: https://restofworld.org/2024/mali-ai-translate-local-language-education/
+ - text: ⛔ Dutch Prime Minister and entire cabinet resign after investigations reveal that 26,000 innocent families were wrongly accused of social benefits fraud partially due to a discriminatory algorithm.
url: https://www.vice.com/en/article/jgq35d/how-a-discriminatory-algorithm-wrongly-accused-thousands-of-families-of-fraud
- - text: Sending police officers to areas of high predicted crime skews future training data collection as police are repeatedly sent back to the same neighborhoods regardless of the true crime rate.
+ - text: ⛔ Sending police officers to areas of high predicted crime skews future training data collection as police are repeatedly sent back to the same neighborhoods regardless of the true crime rate.
url: https://www.smithsonianmag.com/innovation/artificial-intelligence-is-now-used-predict-crime-is-it-biased-180968337/
- line_id: E.2
links:
- - text: Software mistakes result in healthcare cuts for people with diabetes or cerebral palsy.
+ - text: ✅ Healing ARC uses a targeted, race-conscious algorithm to counteract documented inequities in access to heart failure care for Black and Latinx patients.
+ url: https://catalyst.nejm.org/doi/full/10.1056/CAT.22.0076
+ - text: ⛔ Software mistakes result in healthcare cuts for people with diabetes or cerebral palsy.
url: https://www.theverge.com/2018/3/21/17144260/healthcare-medicaid-algorithm-arkansas-cerebral-palsy
- line_id: E.3
links:
- - text: Google "fixes" racist algorithm by removing gorillas from image-labeling technology.
+ - text: ⛔ Google "fixes" racist algorithm by removing gorillas from image-labeling technology.
url: https://www.theverge.com/2018/1/12/16882408/google-racist-gorillas-photo-recognition-algorithm-ai
- - text: Microsoft's Twitter chatbot Tay quickly becomes racist.
+ - text: ⛔ Microsoft's Twitter chatbot Tay quickly becomes racist.
url: https://www.theguardian.com/technology/2016/mar/24/microsoft-scrambles-limit-pr-damage-over-abusive-ai-bot-tay
- line_id: E.4
links:
- - text: Generative AI can be exploited to create convincing scams like "virtual kidnapping".
+ - text: ⛔ Generative AI can be exploited to create convincing scams like "virtual kidnapping".
url: https://www.trendmicro.com/vinfo/us/security/news/cybercrime-and-digital-threats/how-cybercriminals-can-perform-virtual-kidnapping-scams-using-ai-voice-cloning-tools-and-chatgpt
- - text: Deepfakes—realistic but fake videos generated with AI—span the gamut from celebrity porn to presidential statements.
+ - text: ⛔ Deepfakes—realistic but fake videos generated with AI—span the gamut from celebrity porn to presidential statements.
url: http://theweek.com/articles/777592/rise-deepfakes
diff --git a/docs/md_templates/_common_body.tpl b/docs/md_templates/_common_body.tpl
index c46a089..115924d 100644
--- a/docs/md_templates/_common_body.tpl
+++ b/docs/md_templates/_common_body.tpl
@@ -34,27 +34,30 @@ Dig into the checklist questions to identify and navigate the ethical considerat
For more configuration details, see the sections on [command line options](#command-line-options), [supported output file types](#supported-file-types), and [custom checklists](#custom-checklists).
-# Background and perspective
+# What is `deon` designed to do?
-We have a particular perspective with this package that we will use to make decisions about contributions, issues, PRs, and other maintenance and support activities.
+We created `deon` to help data scientists across the sector be more intentional in their choices, and more aware of the ethical implications of their work. We use that perspective to make decisions about contributions, issues, PRs, and other maintenance and support activities.
-First and foremost, our goal is not to be arbitrators of what ethical concerns merit inclusion. We have a [process for changing the default checklist](#changing-the-checklist), but we believe that many domain-specific concerns are not included and teams will benefit from developing [custom checklists](#custom-checklists). Not every checklist item will be relevant. We encourage teams to remove items, sections, or mark items as `N/A` as the concerns of their projects dictate.
-Second, we built our initial list from a set of proposed items on [multiple checklists that we referenced](#checklist-citations). This checklist was heavily inspired by an article written by Mike Loukides, Hilary Mason, and DJ Patil and published by O'Reilly: ["Of Oaths and Checklists"](https://www.oreilly.com/ideas/of-oaths-and-checklists). We owe a great debt to the thinking that proceeded this, and we look forward to thoughtful engagement with the ongoing discussion about checklists for data science ethics.
+1. 🔓 **Our goal is not to be arbitrators of what ethical concerns merit inclusion**. We have a [process for changing the default checklist](#changing-the-checklist), but we believe that many domain-specific concerns are not included and teams will benefit from developing [custom checklists](#custom-checklists). Not every checklist item will be relevant. We encourage teams to remove items, sections, or mark items as `N/A` as the concerns of their projects dictate.
-Third, we believe in the power of examples to bring the principles of data ethics to bear on human experience. This repository includes a [list of real-world examples](http://deon.drivendata.org/examples/) connected with each item in the default checklist. We encourage you to contribute relevant use cases that you believe can benefit the community by their example. In addition, if you have a topic, idea, or comment that doesn't seem right for the documentation, please add it to the [wiki page](https://github.com/drivendataorg/deon/wiki) for this project!
+2. 📊 This checklist is designed to provoke conversations around **issues where data scientists have particular responsibility and perspective**. It's not up to data scientists alone to decide what the ethical course of action is. This has always been a responsibility of organizations that are part of civil society. Conversations should be part of a larger organizational commitment to doing what is right.
-Fourth, it's not up to data scientists alone to decide what the ethical course of action is. This has always been a responsibility of organizations that are part of civil society. This checklist is designed to provoke conversations around issues where data scientists have particular responsibility and perspective. This conversation should be part of a larger organizational commitment to doing what is right.
+3. 💬 Items on the checklist are **meant to provoke discussion** among good-faith actors who take their ethical responsibilities seriously. We are working at a level of abstraction that cannot concretely recommend a specific action (e.g., "remove variable X from your model"). Because of this, most of the items are framed as prompts to discuss or consider. Teams will want to document these discussions and decisions for posterity.
-Fifth, we believe the primary benefit of a checklist is ensuring that we don't overlook important work. Sometimes it is difficult with pressing deadlines and a demand to multitask to make sure we do the hard work to think about the big picture. This package is meant to help ensure that those discussions happen, even in fast-moving environments. Ethics is hard, and we expect some of the conversations that arise from this checklist may also be hard.
+4. 🌎 We believe in the **power of examples** to bring the principles of data ethics to bear on human experience. This repository includes a [list of real-world examples](http://deon.drivendata.org/examples/) connected with each item in the default checklist. We encourage you to contribute relevant use cases that you believe can benefit the community by their example. In addition, if you have a topic, idea, or comment that doesn't seem right for the documentation, please add it to the [wiki page](https://github.com/drivendataorg/deon/wiki) for this project!
-Sixth, we are working at a level of abstraction that cannot concretely recommend a specific action (e.g., "remove variable X from your model"). Nearly all of the items on the checklist are meant to provoke discussion among good-faith actors who take their ethical responsibilities seriously. Because of this, most of the items are framed as prompts to discuss or consider. Teams will want to document these discussions and decisions for posterity.
+5. 🔍 We believe the primary benefit of a checklist is **ensuring that we don't overlook important work**. Sometimes it is difficult with pressing deadlines and a demand to multitask to make sure we do the hard work to think about the big picture. This package is meant to help ensure that those discussions happen, even in fast-moving environments.
-Seventh, we can't define exhaustively every term that appears in the checklist. Some of these terms are open to interpretation or mean different things in different contexts. We recommend that when relevant, users create their own glossary for reference.
+6. ❓ We can't define exhaustively every term that appears in the checklist. Some of these **terms are open to interpretation** or mean different things in different contexts. We recommend that when relevant, users create their own glossary for reference.
-Eighth, we want to avoid any items that strictly fall into the realm of statistical best practices. Instead, we want to highlight the areas where we need to pay particular attention above and beyond best practices.
+7. ✨ We want to avoid any items that strictly fall into the realm of statistical best practices. Instead, we want to highlight the areas where we need to pay particular attention **above and beyond best practices**.
-Ninth, we want all the checklist items to be as simple as possible (but no simpler), and to be actionable.
+8. ✅ We want all the checklist items to be **as simple as possible** (but no simpler), and to be actionable.
+
+## Sources
+
+We built our initial list from a set of proposed items on [multiple checklists that we referenced](#checklist-citations). This checklist was heavily inspired by an article written by Mike Loukides, Hilary Mason, and DJ Patil and published by O'Reilly: ["Of Oaths and Checklists"](https://www.oreilly.com/ideas/of-oaths-and-checklists). We owe a great debt to the thinking that proceeded this, and we look forward to thoughtful engagement with the ongoing discussion about checklists for data science ethics.
# Using this tool
@@ -195,9 +198,9 @@ We're excited to see so many articles popping up on data ethics! The short list
- [Technology is biased too. How do we fix it?](https://fivethirtyeight.com/features/technology-is-biased-too-how-do-we-fix-it/)
- [The dark secret at the heart of AI](https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/)
-## Where things have gone wrong
+## Data ethics in the real world
-To make the ideas contained in the checklist more concrete, we've compiled [examples](http://deon.drivendata.org/examples/) of times when things have gone wrong. They're paired with the checklist questions to help illuminate where in the process ethics discussions may have helped provide a course correction.
+To make the ideas contained in the checklist more concrete, we've compiled [examples](http://deon.drivendata.org/examples/) of times when tradoffs were handled well, and times when things have gone wrong. They're paired with the checklist questions to help illuminate where in the process ethics discussions may have helped provide a course correction.
We welcome contributions! Follow [these instructions](https://github.com/drivendataorg/deon/blob/main/CONTRIBUTING.md) to add an example.
@@ -208,4 +211,4 @@ There are other groups working on data ethics and thinking about how tools can h
- [Aequitas](https://dsapp.uchicago.edu/aequitas/) ([github](https://github.com/dssg/aequitas))
- [Ethical OS Toolkit](https://ethicalos.org/)
- [Ethics & Algorithms Toolkit: A risk management framework for governments](http://ethicstoolkit.ai/)
-- Ethics and Data Science ([free ebook](https://www.amazon.com/dp/B07GTC8ZN7/ref=cm_sw_r_cp_ep_dp_klAOBb4Z72B4G)) and ([write-up](https://medium.com/@sjgadler/care-about-ai-ethics-what-you-can-do-starting-today-882a0e63d828))
+- Ethics and Data Science ([free ebook](https://www.amazon.com/dp/B07GTC8ZN7/ref=cm_sw_r_cp_ep_dp_klAOBb4Z72B4G)) and ([write-up](https://medium.com/@sjgadler/care-about-ai-ethics-what-you-can-do-starting-today-882a0e63d828))
\ No newline at end of file
diff --git a/docs/md_templates/examples.tpl b/docs/md_templates/examples.tpl
index 31808e3..c330f5c 100644
--- a/docs/md_templates/examples.tpl
+++ b/docs/md_templates/examples.tpl
@@ -1,7 +1,7 @@
-# Where things have gone wrong
+# Data ethics in the real world
-To make the ideas contained in the checklist more concrete, we've compiled examples of times when things have gone wrong. They're paired with the checklist questions to help illuminate where in the process ethics discussions may have helped provide a course correction.
+To make the ideas contained in the checklist more concrete, we've compiled **examples** of times when tradoffs were handled well, and times when things have gone wrong. Examples are paired with the checklist questions to help illuminate where in the process ethics discussions may have helped provide a course correction. Positive examples show how principles of `deon` can be followed in the real world.
{{ links_table }}
\ No newline at end of file
diff --git a/docs/render_templates.py b/docs/render_templates.py
index 0c12f6a..d62c417 100644
--- a/docs/render_templates.py
+++ b/docs/render_templates.py
@@ -55,7 +55,7 @@ def make_table_of_links():
for r in refs:
refs_dict[r["line_id"]] = r["links"]
- template = """Checklist Question | Examples of Ethical Issues
+ template = """Checklist Question | Examples
--- | ---
{lines}
"""