WeAreDevelopers Logo WeAreDevelopers
Sign in
For You LIVE
WeAreDevelopers LIVE • Oct 12, 2020

Algorithmic Bias- Preventing Unfairness in your Algorithms

Prathyusha Charagondla

Are your algorithms accidentally amplifying historical prejudices? Learn how to abandon technochauvinism and implement fairness by design to prevent unintended bias in your machine learning models.

Pause
Mute Enter Fullscreen
#1 about 4 min

The impact of biased training data in recruitment platforms

An automated hiring tool demonstrates how imbalanced dataset proportions reproduce existing workplace demographics and unintended gender biases.

#2 about 7 min

Defining algorithmic bias in commercial computer vision systems

Systematic algorithmic errors produce unfair outcomes and expose poor accuracy across intersectional demographics in standard classification models.

#3 about 5 min

Real-world failures in predictive policing and exam grading algorithms

Unaudited logic utilized for suspect identification and automated grade calculation causes widespread harm by enforcing unearned demographic advantages.

#4 about 1 min

Preparing for algorithmic regulation and future compliance standards

Governments will likely introduce broad compliance guidelines similar to GDPR to strictly mandate ethical machine learning management.

#5 about 2 min

Overcoming technochauvinism and evaluating algorithmic training dataset integrity

Acknowledging that technical systems are inherently fallible is the crucial prerequisite before performing exploratory data analysis to isolate biased metrics.

#6 about 3 min

Embedding fairness into algorithmic design and continuous evaluation pipelines

Implementing proactive fairness by design requires adjusting pipeline variables during staging and auditing production outputs against expected baseline parameters.

#7 about 7 min

Adopting structured ethical frameworks for trustworthy artificial intelligence

Adhering to structured institutional guidelines guarantees consistent human oversight, system robustness, and equitable impact distribution across vulnerable user populations.

#8 about 2 min

Mitigating groupthink through diverse and inclusive software engineering teams

Diverse organizations consistently leverage varied professional viewpoints to identify hidden execution assumptions and proactively prevent unintended structural consequences.

#9 about 4 min

Embedding human values and accountability into complex predictive models

Software professionals act as explicitly responsible data stewards by actively auditing intelligent systems to prevent automated systemic discrimination at a meaningful scale.

Matching moments

2:18 min

Addressing implicit human biases embedded within algorithmic datasets

Cassie Kozyrkov · World Congress 2022

4:41 min

Identifying systemic biases in algorithms and artificial intelligence tools

Emily Wright Emily Wright · Europe 2026 Virtual

3:08 min

Implementing responsible artificial intelligence frameworks to mitigate model bias

Alexander Wallner Alexander Wallner +3 · World Congress 2024

1:49 min

Mitigating algorithmic bias during AI model development

Björn Bringmann Björn Bringmann +3 · World Congress 2024

2:26 min

Addressing algorithmic bias and discrimination in decision systems

Christoph Bräunlein Christoph Bräunlein +3 · World Congress 2025

2:42 min

Mitigating data bias and explaining AI decisions

Werner Vogels Werner Vogels +1 · World Congress 2026 Europe

More from WeAreDevelopers LIVE

WeAreDevelopers LIVE - Tech Education in Two Languages thumbnail
1:00:18
6 days ago

WeAreDevelopers LIVE - Tech Education in Two Languages

Daniel Cranney, Roxy Rodriguez-Becker

WeAreDevelopers LIVE - Playing in Production thumbnail
1:06:40
13 days ago

WeAreDevelopers LIVE - Playing in Production

Andrew MacLean, Daniel Cranney, Christian Heilmann

WeAreDevelopers LIVE - Is CSS Catching Up to Flash? thumbnail
1:03:33
27 days ago

WeAreDevelopers LIVE - Is CSS Catching Up to Flash?

Chris Heilmann, Daniel Cranney, Bramus Van Damme

WeAreDevelopers LIVE - Project Chopin: Make Your Team and Agents Play Along thumbnail
1:21:17
about 1 month ago

WeAreDevelopers LIVE - Project Chopin: Make Your Team and Agents Play Along

Chris Heilmann, Daniel Cranney, Krzysztof Cieślak

Fake or News - AI Toothbrushes, Carrier Pigeon Tech & Life on Mars - Krzysztof Cieślak thumbnail
4:23
about 1 month ago

Fake or News - AI Toothbrushes, Carrier Pigeon Tech & Life on Mars - Krzysztof Cieślak

Chris Heilmann, Daniel Cranney

WeAreDevelopers LIVE - Open Source Agent Toolkits thumbnail
1:00:38
about 1 month ago

WeAreDevelopers LIVE - Open Source Agent Toolkits

Chris Heilmann, Daniel Cranney, Eddie Jaoude

Upcoming sessions on this topic

Open session

Beware of Strangers Bearing Code: Open Source Trust in the Agent Era

  • Vikram Vaswani

    Consultant

Open session

How is SWE & EM roles are changing in the age of AI

  • Amol Sharma

    Stripe

    Engineering Manager

Open session

Teaching AI Coding Agents to Build It Right the First Time

  • Sajeetharan Sinnathurai

    Microsoft

    Principal Product Manager

Open session

Autopsy of an Autonomous Incident: When the Agent Made It Worse

  • Navin Pai

    StackGen

    Director of Engineering

Open session

From Prompt Engineering to Harness Engineering: Building Observable and Governed GenAI Systems

  • Lakshmi Devi Prakash

    JPMorgan Chase

    VP, Applied AI/ML Lead

Open session

Prompt Debt: Why Your AI System Is Frozen in Time

  • Suriya Prakash B

    Red Hat

    Principal Software Engineer

Related videos

A walkthrough on Responsible AI Frameworks and Case Studies thumbnail
28:05
World Congress 2022 • over 4 years ago

A walkthrough on Responsible AI Frameworks and Case Studies

Toju Duke

Kill Switch or Moral Compass: Who Programs AI’s Conscience? thumbnail
28:54
World Congress 2025 • about 1 year ago

Kill Switch or Moral Compass: Who Programs AI’s Conscience?

Torsten Stiller

Staying Safe in the AI Future thumbnail
27:26
World Congress 2022 • over 4 years ago

Staying Safe in the AI Future

Cassie Kozyrkov

Racism fuels users experiences : why you should understand the strength of biased narratives. thumbnail
29:59
World Congress 2023 • almost 3 years ago

Racism fuels users experiences : why you should understand the strength of biased narratives.

Marcy Charollois

Trust by Design: Creating Responsible AI-Powered Services thumbnail
25:51
World Congress 2025 • about 1 year ago

Trust by Design: Creating Responsible AI-Powered Services

Christoph Bräunlein, Dr. Marc Fuchs, Eva Stepkes, Niklas Harzheim

AI & Ethics thumbnail
28:27
World Congress 2025 • about 1 year ago

AI & Ethics

PJ Hagerty

Related articles

From learning to earning

Jobs that call for the skills explored in this talk.