Cognitive Systems for

Anticipatory Thinking

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Anticipatory thinking, the deliberate and divergent exploration of relevant possible futures, is a key concept in several contexts. From formal definitions of intelligence analysis to the exploration of relevant possible futures in the presence of exogenous events of our everyday lives, we rely on anticipatory thinking (AT) to evaluate the current and possible future states of the world to prepare ourselves, avoid erroneous expectations, and mitigate risk. We also use AT in our everyday lives when exogenous events compel us to use deliberate and divergent cognitive processes to explore relevant possible futures that help us prepare.

Successful AT identifies impactful future events such that opportunistic or preventative actions are taken in advance. Failures range from coming to the incorrect expectation (a failure of accuracy and/or precision) to not considering trajectories that turn out to be important (a failure of recall). Such failures limit our ability to identify and mitigate risk. Because there are many ways our preparations can succeed or fail, we are subject to surprise and exposed to risks as the future unfolds.

This community of researchers focuses on understanding, quantifying, and improving anticipatory thinking capabilities across humans and machines.


We presently see the community working on the following four topic areas, accompanied by related (but not definitive) research questions:


The assessment and evaluation of AT

    1. How are prospective cognition modality measurements related to AT?

    2. How can we assess and evaluate individual traits relevant to AT?

    3. How can we assess and evaluate for group collaboration?


Systems that augment and aid AT

    1. How can we define successful AT across tasks?

    2. How do different methodologies affect AT?

    3. How can technology platforms augment prospective cognition modalities?


Improving an individual's AT skills

    1. How can adaptive training affect AT?

    2. How does game-based learning affect the cognitive consequences needed for AT?

    3. How does proficiency in methodology interact with domain expertise to affect AT?


Domain-specific contexts for AT. Examples include (but not limited to):

    1. Insurance – Premiums are affected most by named perils, unnamed ones have little effect

    2. Strategic foresight – Identifies trends, events and change that will impact future operations of government and business to create strategic plans

    3. Emergency management – Mitigates impacts of hazards by investing in disaster infrastructure such as floodways

    4. Intelligence analysis – Uncover intentions to hypothesize future actions and respond to them

    5. Military planning – Identify courses of actions providing fast response once an engagement begins

Recommended Reading

While we want to encourage a wide variety of approaches, here are some references we expect to inform perspectives in the area.

  • Szpunar, K. K., Spreng, R. N., & Schacter, D. L. (2014). A taxonomy of prospection: Introducing an organizational framework for future-oriented cognition. Proceedings of the National Academy of Sciences, 111(52), 18414–18421.

  • Klein, G., Snowden, D., & Pin, C. L. (2011). Anticipatory Thinking. In Informed by Knowledge: Expert Performance in Complex Situations (pp. 235–246).

  • Bratman, M. (1987). Intention, Plans, and Practical Reason. Palo Alto: Center for the Study of Language and Information.

  • Geden, M., Smith, A., Campbell, J., Amos-Binks, A., Mott, B., Feng, J., & Lester, J. (2018). Towards Adaptive Support for Anticipatory Thinking. In Proceedings of the Technology, Mind, and Society (pp. 11:1--11:1). New York, NY, USA: ACM.

  • Geden, M., Smith, A., Campbell, J., Spain, R., Amos-Binks, A., Mott, B., & Lester, J. (2019). Construction and Validation of an Anticipatory Thinking Assessment. Frontiers in psychology, 10, 2749.

  • Amos-Binks, A., Dannenhauer, D. (2019, June 28). Anticipatory Thinking: A Metacognitive Capability.

Steering Committee

Dr. Adam Amos-Binks (chair)Chief AI ScientistApplied Research Associates, Inc.
Dr. Dustin DannenhauerScientistWright State Research Institute
Dr. Rogelio E. Cardona-RiveraAssistant ProfessorUniversity of Utah
Dr. Gene BrewerAssociate ProfessorArizona State University
Dr. Leilani GilpinResearcherMassachusetts Institute of Technology