PeopleofSuperintelligence

Researcher

Lorien Pratt

Lorien Pratt is a researcher whose early papers explored transfer between neural networks and whose later work developed decision intelligence. Her career included work at IBM and Bellcore; she co-edited Learning to Learn in 1998 and co-founded Quantellia with Mark Zangari in 2010. She published Link in 2019, wrote about how decision intelligence bridges decisions and data in 2022, and co-authored The Decision Intelligence Handbook in 2023. As of October 2026, she is Quantellia’s Chief Scientist and writes about the human conditions organizations need to adopt AI systems.

Now at
Quantellia
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Timeline

  1. 1991–1992

    Two neural-network transfer papers

    At the 1991 National Conference on Artificial Intelligence, she coauthors “Direct Transfer of Learned Information among Neural Networks” with Jack Mostow and Candace Kamm. In 1992, she publishes “Discriminability-Based Transfer between Neural Networks” at Neural Information Processing Systems.

  2. 1998

    Editing Learning to Learn

    In 1998, she co-edits the machine-learning book Learning to Learn with Sebastian Thrun.

  3. 2010–2017

    Co-founding Quantellia

    Her career includes work at IBM and Bellcore. In 2010, she co-founds Quantellia with Mark Zangari and begins developing a platform and method to turn causal reasoning into a practical business discipline. By 2017, she is Quantellia’s cofounder and chief scientist, and her team offers machine learning, decision intelligence, and full-stack software solutions to clients worldwide.

  4. 2019

    Link and decision intelligence

    In 2019, she publishes Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World. It presents decision intelligence as going beyond AI while connecting human decision-makers across areas such as economics, big data, and analytics.

  5. January 2022

    A framework for decisions

    In January 2022, she publishes “A Framework for How Data Informs Decisions,” describing decision intelligence as a practice that bridges decisions to data.

  6. 2023

    The Decision Intelligence Handbook

    In 2023, she coauthors The Decision Intelligence Handbook with N. E. Malcolm. They present a step-by-step method to integrate technology into decisions and connect actions to desired outcomes.

  7. As of October 2026

    Chief Scientist at Quantellia

    As of October 2026, she is Quantellia’s Chief Scientist and led teams that developed transfer learning and decision intelligence. In August 2026, she writes about the human conditions organizations need to help AI practices take hold.

  1. 23% of people shaping AI who left a university for a company later returned to a universityIncludes IBM. We estimate that 468 of the 2,011 people shaping AI who left a university for a company (23%) later returned to a university after a median of 5 years, and 163 of 829 (20%) made the reverse round trip.
  2. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes IBM. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.
  3. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes IBM. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  4. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes IBM. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.

Sources and credits

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  1. Direct transfer of learned information among neural networks (1991) – National Conference on Artificial Intelligence | Metascience Observatory Explorer explore.metascienceobservatory.org. Checked 21 October 2026.
  2. Discriminability-Based Transfer between Neural Networks (1992) – Neural Information Processing Systems | Metascience Observatory Explorer explore.metascienceobservatory.org. Checked 21 October 2026.
  3. Learning to learn | Catalog Search Results | IUCAT Bloomington iucat.iu.edu. Checked 21 October 2026.
  4. Quantellia: Take Charge of Outcomes with Decision Intelligence ciotechworld.com. Checked 21 October 2026.
  5. Pulling Back the Curtain on Machine Learning Apps in Business - Lorien Pratt emerj.com. Checked 21 October 2026.
  6. 2017 U.S. Retreat Presenter Biographies futureoftalent.org. Checked 21 October 2026.
  7. Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World books.google.com. Checked 21 October 2026.
  8. A Framework for How Data Informs Decisions – Lorien Pratt's blog lorienpratt.com. Checked 21 October 2026.
  9. The Decision Intelligence Handbook: Practical Steps for Evidence-Based Decisions in a Complex World books.google.com. Checked 21 October 2026.
  10. Software Development and AI/ML Solutions quantellia.com. Checked 21 October 2026.
  11. From Invention to Adoption: Building the Human Infrastructure for Innovation in the AI Era lorienpratt.com. Checked 21 October 2026.