Fairness in Networks - Information Access, Disadvantage, and Clustering

Explore fairness in social networks through this 59-minute lecture by Sorelle Friedler from Haverford College, presented at the Santa Fe Institute. Delve into the concept of information access within networks and its implications for job opportunities, public health, and safety alerts. Examine definitions of fairness in network contexts and potential interventions to promote equal information access. Investigate the complexities of clustering individuals based on their access to information. Consider motivations behind social networks, social credit systems, and job information dissemination. Analyze bias in input data, discrimination, and information cascade mechanisms. Discuss welfare definitions, individual fairness, and the balance between information access and surveillance. Gain insights into the challenges of achieving fairness in networked systems and the trade-offs involved in promoting equitable information distribution.

Introduction
Open Invitation
Motivation
Social Networks
Social Credit
Jobs Information
Bias Input Data
Discrimination
Information cascade mechanism
Welfare definitions
What we care about
What we want
Its not possible
Intuition
Individual Fairness
Questions
Information Access and Surveillance