Real World Implications of Bias in Coding & Machine Learning

Explore the real-world implications of bias in coding and machine learning in this 45-minute conference talk from PASS Data Community Summit. Delve into the misconception that computers can't be biased, and understand how human experiences and assumptions seep into applications, surveys, and web forms. Learn to identify bias in code, develop inclusive programming practices, and implement quick tips to ensure your applications cater to all users, not just those who resemble you. Discover the impact of biased algorithms, machine bias, and data-driven prejudices through real-world examples. Gain insights on questioning assumptions, practicing inclusive design, and creating more effective web forms and user evaluations. Equip yourself with the knowledge to create truly inclusive and world-changing applications.

Introduction
What is bias
Computers cant be biased
Machine bias
Not making assumptions
Glow Eve
Pool Float
Bad Data
Image Searches
Data Driven Bias
Other Real World Implications
Soap is a Problem
Biased Algorithms
Who is the Average User
Questioning Assumptions
Inclusive Design
oxo Kitchen Products
Web Forms
Questions
Focus Groups
Evaluations