StakeholdersMassachusetts Institute of Technology (MIT) - Institute for Data, Systems, amd Society...

Massachusetts Institute of Technology (MIT) – Institute for Data, Systems, amd Society (IDSS)

World-renowned Massachusetts Institute of Technology (MIT) is widely known for cutting-edge research in many disciplines, ranging from pure science to social sciences and humanities

MIT’s Institute for Data, Systems, and Society (IDSS) sits at a landmark intersection of several usually disparate disciplines. IDSS takes a holistic and data-driven approach to analyzing complex, high-impact systems in society.

IDSS research is rooted in three core analytical disciplines and aims to address broad overarching challenges inherent to highly interconnected and data-rich systems. IDSS researchers work in a broad range of applications, including five key research domains of expertise.

Analytical disciplines

Statistics and data science

While mechanistic models may exist for some physical systems, they often overlook how users of these systems actually make decisions.  The key issue is how to generate reliable and actionable algorithms and models from diverse data with only partial information about the underlying processes.

Information and decision theory

Information and decision theory is a broad discipline that includes research in: systems and controls, optimization and game theory, networks, and inference and statistical data processing.

Human and institutional behavior

Research into the behaviors of humans and institutions looks at nontraditional aspects of modeling these behaviors as they relate to particular societal issues. This includes the behavior of individuals, groups, and institutions as it impacts upon the operation and behavior of systems. Aspects of this field are anchored in the social sciences, e.g., economics, sociology, psychology, political science, management and policy. Topics include: rational decision theory, behavioral decision theory, organizational behavior, and public policy design.

Overarching challenges

There are many challenges in developing and modeling data-driven systems, regardless of domain or discipline. IDSS research is unified in its efforts to address these challenges:

  • Resilience and systemic risk
  • System design and architecture
  • Sustainability and Policy
  • Data-to-decisions
  • Research domains

IDSS has five key research domains of expertise:

Stakeholder Details

For more information, visit:

idss.mit.edu/

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