Understanding the Ethics of Machine Learning and Big Data | COMPAS Case Study & Algorithm Bias

In this comprehensive presentation, we explore the critical ethical challenges surrounding machine learning and big data. From Cathy O’Neil’s analysis of 'Weapons of Math Destruction' to the biases in algorithms like COMPAS, we dive deep into how algorithms impact decision-making in areas such as criminal justice. We examine concepts like predictive parity, false positives, and the importance of transparency in AI systems. Learn how to incorporate ethics into system development and discover tools like ORCAA and Aequitas for auditing algorithms. This presentation is essential for anyone interested in AI, data science, or the responsible use of algorithms.

Key Topics Covered:
What is AI ethics, big data ethics, and data science ethics?
Analysis of 'Weapons of Math Destruction' by Cathy O’Neil.
Case Study: COMPAS predictions of recidivism and its racial bias.
The ethical dilemma of balancing predictive parity and error rates.
Tools and guidelines for ethical AI and algorithm audits.
Timestamps:
0:00 Introduction
1:20 What is Big Data Ethics?
4:10 Cathy O’Neil’s Weapons of Math Destruction
8:50 COMPAS Case Study: Bias in Criminal Justice
14:00 Challenges in Removing Bias from Algorithms
18:25 Ethical Frameworks for AI Development
21:10 Algorithm Auditing Tools
24:30 Final Thoughts on Ethical AI Practices
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