Illinois People and Intelligent Infrastructures (IPII)

Strategic Research Initiative

Karrie Karahalios, Indranil Gupta: Computer Science

Campustown

About the project

IPII (pronounced “Eye-Pi”) is an interdisciplinary center created by researchers in the Computer Science Department and the I-School at the University of Illinois to interrogate the complex interactions between people, systems, and algorithms. Motivated by the recognition that human factors are crucial at every stage of functioning algorithmic systems that surround us in everyday infrastructures (e.g., in smart homes, worksplaces, hospitals, schools, transportation systems, and social media)---as well as growing demands by computing professionals, researchers, and the general public, for more trustworthy, socially accountable forms of AI — IPII will create the first environment on campus for interdisciplinary researchers to build and research intelligent systems that are genuinely “people-first” and “society-first.” IPII positions the needs, interests, and concerns of society as central to the design of new trustworthy, ethical systems.

We approach our goals from multiple perspectives. We develop fundamental algorithms and build data systems to support scalable inference and exploration of patterns generated by human behavior and by systems. We design experiments at scale to help develop new infrastructure (e.g. crowdsourcing interface design & incentives, edge computing systems and hardware; algorithm auditing tools) to gather and to support pattern discovery. We talk and work with community members to understand how algorithmic systems influence their lives. And we design socio- technical systems to suit the lives of real people.

Our work on understanding and supporting behavior of human beings and systems helps in the design of large scale systems that interconnect people and provide them with services. We interrogate the role of system affordances and algorithm design on the observed behavior. And, ultimately, we explore the societal implications of these resulting complex socio-technical systems to mould them for our daily and long term needs—at individual and group scales.

Our vision is to change the future of computing so that it is normal for researchers, users, industries, and governments to deploy complex computational algorithmic socio- technical systems that are fast, scalable, reliable, equitable to users, and that provide a creditable assurance that they are free from specific unwanted behaviors.