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Assessing and Predicting Technology Outcomes






October 30, 2023





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Entity Types:

For profit organizations other than small businesses, Small businesses, Nonprofits (with 501(c)(3) status), Public & State controlled institutions of higher education

*Who May Submit Proposals: Proposals may only be submitted by the following: -For-profit organizations: U.S.-based commercial organizations, including small businesses, with strong capabilities in scientific or engineering research or education and a passion for innovation. -Non-profit, non-academic organizations: Independent museums, observatories, research laboratories, professional societies and similar organizations located in the U.S. that are directly associated with educational or research activities. -Institutions of Higher Education (IHEs) - Two- and four-year IHEs (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members.Special Instructions for International Branch Campuses of US IHEs: If the proposal includes funding to be provided to an international branch campus of a US institution of higher education (including through use of subawards and consultant arrangements), the proposer must explain the benefit(s) to the project of performance at the international branch campus, and justify why the project activities cannot be performed at the US campus.




Source Type:


The National Science Foundation (NSF), through the Directorate for Technology, Innovation and Partnerships (TIP), is launching a new program on Assessing and Predicting Technology Outcomes (APTO) to assess how investments in science and technology research and development will contribute to specific outcomes for the Nation. The APTO program will support a cohort of projects that will work together to complement each others research and development (R) efforts on technology outcome models to accurately describe three types of technology outcomes: technology capabilities, technology production, and technology use. These models should be able to predict future as well as past states of technology outcomes. Of particular interest are prediction models that are generalizable across multiple technology areas. The outcome of this work will help assess and evaluate the effectiveness of U.S. R investments and generate information that decision makers could use to strategize and optimize investments for advancing long-term U.S. competitiveness into the future. The APTO program serves the TIP directorates need for technology assessment to understand where the U.S. standsas a whole and in individual regionsvis--vis competitiveness in the key technology focus areas named in Sec. 10387 of the CHIPS and Science Act. TIP is interested in answers to the question of which science and technology investments would offer the greatest impact in the key technology focus areas and would be essential to the long-term national security and economic prosperity of the United States. As a key aspect of TIPs technology assessment activity, the APTO program will bring together multidisciplinary teams to help develop the data, intellectual foundations, and analytics necessary to inform decision making. The research community has accumulated important insights about the rate and direction of inventive activity[1] as an aggregate economic good, and about what decision makers can do to increase the overall production of that good. Meanwhile, industry has immense experience with creating specific technologies and planning how to reach intended technology outcomes over periods of several years. The APTO program aims to expand on this knowledge base spanning academia and industry to better understand and predict the long-term evolution of specific technologies over a period of a few years to decades, and specifically model how intentional, purposeful investments can change that evolution. APTO will fund research and development of causal models that accurately describe past and future technology outcomes, specifically the capabilities, production, and use of specific technologies. These models should be able to predict likely future outcomes for specific technologies and what intentional investments could reliably change or accelerate those outcomes by correctly capturing the various causal relationships. Building and testing these models will require significant amounts of specialized data gathered from a variety of sources, e.g., historical sources, experimentation, expert elicitation, and others. Data extraction and processing tools may need to be developed as part of that effort. APTO will support a cohort of projects that will work in collaboration on research and development of Technology Outcome Models and in development/preparation of Data Sets and related Tools. [1] The Rate and Direction of Inventive Activity, edited by R. R. Nelson, 1962. Princeton, NJ: Princeton University Press

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