Building Ethics and Diversity in AI

Share this Session:
Share on facebook
Share on twitter
Share on linkedin

Presented by Appen

Appen collects and labels images, text, speech, audio, video, and other data used to build and continuously improve the world’s most innovative arti­ficial intelligence systems.

  • Session Description
  • Presenters
  • Additional Resources

Bias in machine learning is a significant concern as technology gets increasingly ubiquitous across many industries. Some types of bias can be attributed to limits in design and tooling; however, the bias in the training data itself is a general phenomenon. Skewed training data propagates into discriminatory AI models that amplify human prejudices.

Building a data labeling framework that uses a diverse set of crowd workers to collect and label the data can help reduce bias.

Meeta Dash

VP of Product at Appen As VP Product at Appen Meeta is building a machine learning data annotation platform focused on Computer Vision, Autonomous Vehicles,

Login to View Content

Login Or Register

Event Registration

Almost there!

We need to confirm your email.

You're Almost thEre!

Check your Email for Confirmation and Login Instructions

You will receive an email confirming your registration – please click on the link in the email to confirm.

Login instructions will also be provided in the email. If you don’t get the email, please let us know at info@cognilytica.com.