Bias in Big Data and Artificial Intelligence - Protecting Against Algorithmic Discrimination

Explore the critical issue of bias in big data and artificial intelligence in this thought-provoking panel discussion from The Aspen Institute. Delve into how algorithms increasingly influence crucial decisions in our lives, from news consumption to mortgage approvals and health insurance rates. Examine the rampant bias and discrimination against marginalized communities caused by these systems, and consider whether machines are truly neutral or if human prejudices are embedded in their design. Investigate potential solutions, including ethical standards and regulation, to protect individuals from algorithmic bias. Learn from experts Jason Pontin, Surya Mattu, and Virginia Eubanks as they discuss topics such as the digital poorhouse, framing metaphors, moral hazards, and tools like the Allegheny Family Screening Tool. Gain insights into measuring bias, neutral and non-neutral design, automation, and the importance of diverse perspectives in technology development. Explore real-world examples and audience questions covering M Relief, Hirevue, health data applications, and regulatory frameworks to better understand and navigate the complex landscape of big data and AI-driven decision-making.

Introduction
Datadriven tools
Digital Poorhouse
Framing Metaphor
Moral Hazard
Poor Houses
Allegheny Family Screening Tool
Measuring Bias
Neutral Design
NonNeutral Design
Automation
Intention
Whos in the room
Audience Questions
M Relief
Measure Bias
Systems Engineering
Hirevue
Confidence Rises
Limitations of the Tool
Tech Literacy
Cultural Play
Health Data
Smart Toothbrush
Coordinated Entry System
Regulatory Framework