White House report on embedding civil rights principles into algorithms.
Table of Contents:
PREFACE……………………4
- The Assumption: Big Data is Objective…….6
- Challenge 1: Inputs to an Algorithm………..7
- Challenge 2: The Design of Algorithmic Systems and Machine Learning…………………..8
CASE STUDIES IN THE USE OF BIG DATA…….10
Big Data and Access to Credit……………….11
- The Problem: Many Americans lack access to affordable credit due to thin or non-existent credit files. ..11
- The Big Data Opportunity: Use of big data in lending can increase access to credit for the financially underserved. …….11
- The Big Data Challenge: Expanding access to affordable credit while preserving consumer rights that protect against discrimination in credit eligibility decisions…12
Big Data and Employment……………………13
- The Problem: Traditional hiring practices may unnecessarily filter out applicants whose skills match the job opening. ……..13
- The Big Data Opportunity: Big data can be used to uncover or possibly reduce employment discrimination. ….14
- The Big Data Challenge: Promoting fairness, ethics, and mechanisms for mitigating discrimination in employment opportunity. …………………15
Big Data and Higher Education……………..16
- The Problem: Students often face challenges accessing higher education, finding information to help choose the right college, and staying enrolled. ………………….16
- The Big Data Opportunity: Using big data can increase educational opportunities for the students who most need them. .17
- The Big Data Challenge: Administrators must be careful to address the possibility of discrimination in higher education admissions decisions.18
Big Data and Criminal Justice………………..19
- The Problem: In a rapidly evolving world, law enforcement officials are looking for smart ways to use new technologies to increase community safety and trust. ………..19
- The Big Data Opportunity: Data and algorithms can potentially help law enforcement become more transparent, effective, and efficient……19
- The Big Data Challenge: The law enforcement community can use new technologies to enhance trust and public safety in the community, especially through measures that promote transparency and accountability and mitigate risks of disparities in treatment and outcomes based on individual characteristics…..21
LOOKING TO THE FUTURE………………………..22
To read the report, click here.
Top DSC Resources
- Article: What is Data Science? 24 Fundamental Articles Answering This Question
- Article: Hitchhiker’s Guide to Data Science, Machine Learning, R, Python
- Tutorial: Data Science Cheat Sheet
- Tutorial: How to Become a Data Scientist – On Your Own
- Categories: Data Science – Machine Learning – AI – IoT – Deep Learning
- Tools: Hadoop – DataViZ – Python – R – SQL – Excel
- Techniques: Clustering – Regression – SVM – Neural Nets – Ensembles – Decision Trees
- Links: Cheat Sheets – Books – Events – Webinars – Tutorials – Training – News – Jobs
- Links: Announcements – Salary Surveys – Data Sets – Certification – RSS Feeds – About Us
- Newsletter: Sign-up – Past Editions – Members-Only Section – Content Search – For Bloggers
- DSC on: Ning – Twitter – LinkedIn – Facebook – GooglePlus
Follow us on Twitter: @DataScienceCtrl | @AnalyticBridge