Analytics for Good Institute Mission
Using Data Analytics to Serve the Common Good
Founded in 2019 at the Carlson School of Management, the Analytics for Good Institute (AGI) uses data analytics to serve the common good. Through partnerships with governments, non-profit organizations, philanthropic foundations, and private companies, the Institute works to improve lives and build stronger communities by leveraging the power of data.
As an outreach initiative of the Carlson School’s Information & Decision Sciences Department, AGI is uniquely positioned to bring top-tier University resources to partner organizations that share our mission to use analytics for good. Partner organizations have included the McKnight Foundation, Hennepin County, and the City of St. Paul.
The Analytics for Good Institute aims to bring the power of analytics, artificial intelligence (AI), machine learning (ML), digital platforms, and data-driven decision-making to real-world problems while delivering societal benefits.
The Institute's genesis lies in the foundational work done by the Carlson Analytics Lab, an integral part of the MS Business Analytics (MSBA) program. The Institute adds a research dimension to the Lab's experiential learning mission, and stands on three pillars:
Benefit the Public Good
AGI serves under-served groups and supports communities through analytics that benefit the public good. Areas of effort include:
- Reducing socioeconomic disparities in affordable housing, education, transportation, healthcare, employment, income inequality, social justice, and other areas.
- Supporting best practices in sustainability and stewardship of natural resources.
Educate Student Leaders
AGI's work provides valuable experiential learning opportunities to students, made possible with the help of many partners. Collaborators include:
- For-profit companies across industries
- Cities, counties, and government agencies
- Foundations and nonprofits
Create New Knowledge
AGI works to create meaningful new knowledge and global scholarship through the support of top-tier research in cutting-edge areas of analytics. Areas of interest include:
- Fairness, transparency, and algorithmic bias issues in AI and ML
- Organizational structure and design to maximize value from analytics, AI, and ML
- The societal impact and unintended consequences of digital media, platforms, algorithms, and AI