The Agentic Economy
David Rothschild, Markus Mobius, Jake Hofman, Eleanor Dillon, Daniel G. Goldstein, Nicole Immorlica, Sonia Jaffe, Brendan Lucier, Aleksandrs Slivkins, Matthew Vogel
May 2025
Jake Hofman
Senior Principal Researcher
Papiers de Collaboration
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Effects of LLM-based Search on Decision Making: Speed, Accuracy, and Overreliance
Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein, Jake Hofman
CHI 2025 | April 2025
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ChatBench: From Static Benchmarks to Human-AI Evaluation
Serina Chang, Ashton Anderson, Jake Hofman
April 2025
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Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
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Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
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Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity
Alexia Cambon, Brent Hecht, Benjamin Edelman, Donald Ngwe, Sonia Jaffe, Amy Heger, Mihaela Vorvoreanu, Sida Peng, Jake Hofman, Alex Farach, Margarita Bermejo-Cano, Eric Knudsen, James Bono, Hardik Sanghavi, Sofia Spatharioti, David Rothschild, Daniel G. Goldstein, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, Michael Schwarz, Jaime Teevan
MSR-TR-2023-43 | December 2023
Publié par Microsoft
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A Sports Analogy for Understanding Different Ways to Use AI
Jake Hofman, Daniel G. Goldstein, David Rothschild
Harvard Business Review | December 2023
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Math Education with Large Language Models: Peril or Promise?
Harsh Kumar, David Rothschild, Daniel G. Goldstein, Jake Hofman
SSRN Electronic Journal | December 2023
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An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability
Sam Zhang, Patrick R. Heck, Michelle N. Meyer, Christopher F. Chabris, Daniel G. Goldstein, Jake M. Hofman
Proceeding of the National Academy of Sciences | August 2023, Vol 120(33)
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Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment
Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein, Jake Hofman
July 2023
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Investigating Perceptual Biases in Icon Arrays
Cindy Xiong, Ali Sarvghad, Daniel G. Goldstein, Jake Hofman, Çağatay Demiralp
CHI 2022 | April 2022
Honorable Mention
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Putting scientific results in perspective: Improving the communication of standardized effect sizes
Yea-Seul Kim, Jake Hofman, Daniel G. Goldstein
CHI 2022 | April 2022
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Round Numbers Can Sharpen Cognition
Huy Anh Nguyen, Jake Hofman, Daniel G. Goldstein
CHI 2022 | April 2022
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Integrating explanation and prediction in computational social science
Jake Hofman, Duncan J Watts, Susan Athey, Filiz Garip, Thomas L Griffiths, Jon Kleinberg, Helen Margetts, Sendhil Mullainathan, Matthew J Salganik, Simine Vazire, Alessandro Vespignani, Tal Yarkoni
Nature | June 2021, Vol 595(7866): pp. 181-188
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Manipulating and Measuring Model Interpretability
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
CHI 2021 | May 2021
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Datamations: Animated Explanations of Data Analysis Pipelines
Xiaoying Pu, Sean Kross, Jake Hofman, Daniel G. Goldstein
April 2021
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How good is good enough for COVID19 apps?
Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake Hofman, Elissa M. Redmiles
May 2020
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How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results
Jake Hofman, Daniel G. Goldstein, Jessica Hullman
CHI 2020 | April 2020
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Expanding The Scope Of Reproducibility Research Through Data Analysis Replications
Jake Hofman, Daniel G. Goldstein, Siddhartha Sen, Forough Poursabzi-Sangdeh
The Web Conference Workshop on Innovative Ideas in Data Science (IID) | April 2020
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Perspective annotation for numerical representations
Jake Hofman, Miro Dudík, Daniel G. Goldstein
December 2018
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Split-door criterion: Identification of causal effects through auxiliary outcomes
Amit Sharma, Jake Hofman, Duncan Watts
Annals of Applied Statistics | December 2018, Vol 12(4): pp. 2699-2733
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Explanation, Prediction, And Causality: Three Sides Of The Same Coin?
Duncan Watts, Emorie D Beck, Elisa Jayne Bienenstock, Jake Bowers, Aaron Frank, Anthony Grubesic, Jake Hofman, Julia M. Rohrer, Matthew Salganik
October 2018
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To Put That in Perspective: Generating Analogies that Make Numbers Easier to Understand
Christopher Riederer, Jake Hofman, Daniel G. Goldstein
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems | April 2018
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Prediction and explanation in social systems
Jake Hofman, Amit Sharma, Duncan Watts
Science | February 2017, Vol 355: pp. 486-488
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Improving Comprehension of Numbers in the News
Pablo J. Barrio, Daniel G. Goldstein, Jake Hofman
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems | May 2016
ISBN: 978-1-4503-3362-7
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Exploring Limits to Prediction in Complex Social Systems: Predicting Cascade Size on Twitter
Travis Martin, Jake Hofman, Amit Sharma, Ashton Anderson, Duncan Watts
Proceedings of the 25th International Conference on World Wide Web | April 2016
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Online and Social Media Data As an Imperfect Continuous Panel Survey
Fernando Diaz, Michael Gamon, Jake Hofman, Emre Kiciman, David Rothschild
PlosONE | January 2016, Vol 11
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The Structural Virality of Online Diffusion
Sharad Goel, Jake Hofman, Duncan Watts, Ashton Anderson
Management Science | July 2015, Vol 62(1): pp. 180-196
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Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
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A Large-scale Exploration of Group Viewing Patterns
Allison J.B. Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
TVX '14 Proceedings of the 2014 ACM international conference on Interactive experiences for TV and online video | June 2014
ISBN: 978-1-4503-2838-8
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Online And Social Media Data As A Flawed Continuous Panel Survey
Fernando Diaz, Michael Gamon, Jake Hofman, Emre Kiciman, David Rothschild
MSR-TR-2014-159 | May 2014
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Mining Large-scale TV Group Viewing Patterns for Group Recommendation
Allison J.B. Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
MSR-TR-2013-114 | November 2013
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The Agentic Economy
David Rothschild, Markus Mobius, Jake Hofman, Eleanor Dillon, Daniel G. Goldstein, Nicole Immorlica, Sonia Jaffe, Brendan Lucier, Aleksandrs Slivkins, Matthew Vogel
May 2025
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Effects of LLM-based Search on Decision Making: Speed, Accuracy, and Overreliance
Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein, Jake Hofman
CHI 2025 | April 2025
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ChatBench: From Static Benchmarks to Human-AI Evaluation
Serina Chang, Ashton Anderson, Jake Hofman
April 2025
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Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
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Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
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Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity
Alexia Cambon, Brent Hecht, Benjamin Edelman, Donald Ngwe, Sonia Jaffe, Amy Heger, Mihaela Vorvoreanu, Sida Peng, Jake Hofman, Alex Farach, Margarita Bermejo-Cano, Eric Knudsen, James Bono, Hardik Sanghavi, Sofia Spatharioti, David Rothschild, Daniel G. Goldstein, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, Michael Schwarz, Jaime Teevan
MSR-TR-2023-43 | December 2023
Publié par Microsoft
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A Sports Analogy for Understanding Different Ways to Use AI
Jake Hofman, Daniel G. Goldstein, David Rothschild
Harvard Business Review | December 2023
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Manipulating and Measuring Model Interpretability
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
CHI 2021 | May 2021
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How good is good enough for COVID19 apps?
Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake Hofman, Elissa M. Redmiles
May 2020
-
Perspective annotation for numerical representations
Jake Hofman, Miro Dudík, Daniel G. Goldstein
December 2018
-
Split-door criterion: Identification of causal effects through auxiliary outcomes
Amit Sharma, Jake Hofman, Duncan Watts
Annals of Applied Statistics | December 2018, Vol 12(4): pp. 2699-2733
-
To Put That in Perspective: Generating Analogies that Make Numbers Easier to Understand
Christopher Riederer, Jake Hofman, Daniel G. Goldstein
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems | April 2018
-
Mining Large-scale TV Group Viewing Patterns for Group Recommendation
Allison J.B. Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
MSR-TR-2013-114 | November 2013
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The Agentic Economy
David Rothschild, Markus Mobius, Jake Hofman, Eleanor Dillon, Daniel G. Goldstein, Nicole Immorlica, Sonia Jaffe, Brendan Lucier, Aleksandrs Slivkins, Matthew Vogel
May 2025
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Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
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Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
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Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity
Alexia Cambon, Brent Hecht, Benjamin Edelman, Donald Ngwe, Sonia Jaffe, Amy Heger, Mihaela Vorvoreanu, Sida Peng, Jake Hofman, Alex Farach, Margarita Bermejo-Cano, Eric Knudsen, James Bono, Hardik Sanghavi, Sofia Spatharioti, David Rothschild, Daniel G. Goldstein, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, Michael Schwarz, Jaime Teevan
MSR-TR-2023-43 | December 2023
Publié par Microsoft
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A Sports Analogy for Understanding Different Ways to Use AI
Jake Hofman, Daniel G. Goldstein, David Rothschild
Harvard Business Review | December 2023
-
Expanding The Scope Of Reproducibility Research Through Data Analysis Replications
Jake Hofman, Daniel G. Goldstein, Siddhartha Sen, Forough Poursabzi-Sangdeh
The Web Conference Workshop on Innovative Ideas in Data Science (IID) | April 2020
-
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
-
-
-
Effects of LLM-based Search on Decision Making: Speed, Accuracy, and Overreliance
Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein, Jake Hofman
CHI 2025 | April 2025
-
ChatBench: From Static Benchmarks to Human-AI Evaluation
Serina Chang, Ashton Anderson, Jake Hofman
April 2025
-
Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
-
Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
-
Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity
Alexia Cambon, Brent Hecht, Benjamin Edelman, Donald Ngwe, Sonia Jaffe, Amy Heger, Mihaela Vorvoreanu, Sida Peng, Jake Hofman, Alex Farach, Margarita Bermejo-Cano, Eric Knudsen, James Bono, Hardik Sanghavi, Sofia Spatharioti, David Rothschild, Daniel G. Goldstein, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, Michael Schwarz, Jaime Teevan
MSR-TR-2023-43 | December 2023
Publié par Microsoft
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Math Education with Large Language Models: Peril or Promise?
Harsh Kumar, David Rothschild, Daniel G. Goldstein, Jake Hofman
SSRN Electronic Journal | December 2023
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Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment
Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein, Jake Hofman
July 2023
-
Putting scientific results in perspective: Improving the communication of standardized effect sizes
Yea-Seul Kim, Jake Hofman, Daniel G. Goldstein
CHI 2022 | April 2022
-
Round Numbers Can Sharpen Cognition
Huy Anh Nguyen, Jake Hofman, Daniel G. Goldstein
CHI 2022 | April 2022
-
Investigating Perceptual Biases in Icon Arrays
Cindy Xiong, Ali Sarvghad, Daniel G. Goldstein, Jake Hofman, Çağatay Demiralp
CHI 2022 | April 2022
Honorable Mention
-
How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results
Jake Hofman, Daniel G. Goldstein, Jessica Hullman
CHI 2020 | April 2020
-
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
-
-
-
Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
-
Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
-
-
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Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
-
Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
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-
-
Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
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Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
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An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability
Sam Zhang, Patrick R. Heck, Michelle N. Meyer, Christopher F. Chabris, Daniel G. Goldstein, Jake M. Hofman
Proceeding of the National Academy of Sciences | August 2023, Vol 120(33)
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Integrating explanation and prediction in computational social science
Jake Hofman, Duncan J Watts, Susan Athey, Filiz Garip, Thomas L Griffiths, Jon Kleinberg, Helen Margetts, Sendhil Mullainathan, Matthew J Salganik, Simine Vazire, Alessandro Vespignani, Tal Yarkoni
Nature | June 2021, Vol 595(7866): pp. 181-188
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Manipulating and Measuring Model Interpretability
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
CHI 2021 | May 2021
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Datamations: Animated Explanations of Data Analysis Pipelines
Xiaoying Pu, Sean Kross, Jake Hofman, Daniel G. Goldstein
April 2021
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How good is good enough for COVID19 apps?
Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake Hofman, Elissa M. Redmiles
May 2020
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How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results
Jake Hofman, Daniel G. Goldstein, Jessica Hullman
CHI 2020 | April 2020
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Expanding The Scope Of Reproducibility Research Through Data Analysis Replications
Jake Hofman, Daniel G. Goldstein, Siddhartha Sen, Forough Poursabzi-Sangdeh
The Web Conference Workshop on Innovative Ideas in Data Science (IID) | April 2020
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Explanation, Prediction, And Causality: Three Sides Of The Same Coin?
Duncan Watts, Emorie D Beck, Elisa Jayne Bienenstock, Jake Bowers, Aaron Frank, Anthony Grubesic, Jake Hofman, Julia M. Rohrer, Matthew Salganik
October 2018
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Prediction and explanation in social systems
Jake Hofman, Amit Sharma, Duncan Watts
Science | February 2017, Vol 355: pp. 486-488
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Improving Comprehension of Numbers in the News
Pablo J. Barrio, Daniel G. Goldstein, Jake Hofman
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems | May 2016
ISBN: 978-1-4503-3362-7
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Exploring Limits to Prediction in Complex Social Systems: Predicting Cascade Size on Twitter
Travis Martin, Jake Hofman, Amit Sharma, Ashton Anderson, Duncan Watts
Proceedings of the 25th International Conference on World Wide Web | April 2016
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Online and Social Media Data As an Imperfect Continuous Panel Survey
Fernando Diaz, Michael Gamon, Jake Hofman, Emre Kiciman, David Rothschild
PlosONE | January 2016, Vol 11
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The Structural Virality of Online Diffusion
Sharad Goel, Jake Hofman, Duncan Watts, Ashton Anderson
Management Science | July 2015, Vol 62(1): pp. 180-196
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Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
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A Large-scale Exploration of Group Viewing Patterns
Allison J.B. Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
TVX '14 Proceedings of the 2014 ACM international conference on Interactive experiences for TV and online video | June 2014
ISBN: 978-1-4503-2838-8
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Online And Social Media Data As A Flawed Continuous Panel Survey
Fernando Diaz, Michael Gamon, Jake Hofman, Emre Kiciman, David Rothschild
MSR-TR-2014-159 | May 2014
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Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
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Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
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-
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How good is good enough for COVID19 apps?
Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake Hofman, Elissa M. Redmiles
May 2020
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Mining Large-scale TV Group Viewing Patterns for Group Recommendation
Allison J.B. Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
MSR-TR-2013-114 | November 2013
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The Agentic Economy
David Rothschild, Markus Mobius, Jake Hofman, Eleanor Dillon, Daniel G. Goldstein, Nicole Immorlica, Sonia Jaffe, Brendan Lucier, Aleksandrs Slivkins, Matthew Vogel
May 2025
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Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment
Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein, Jake Hofman
July 2023
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How good is good enough for COVID19 apps?
Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake Hofman, Elissa M. Redmiles
May 2020
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Perspective annotation for numerical representations
Jake Hofman, Miro Dudík, Daniel G. Goldstein
December 2018
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Explanation, Prediction, And Causality: Three Sides Of The Same Coin?
Duncan Watts, Emorie D Beck, Elisa Jayne Bienenstock, Jake Bowers, Aaron Frank, Anthony Grubesic, Jake Hofman, Julia M. Rohrer, Matthew Salganik
October 2018
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ChatBench: From Static Benchmarks to Human-AI Evaluation
Serina Chang, Ashton Anderson, Jake Hofman
April 2025
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Datamations: Animated Explanations of Data Analysis Pipelines
Xiaoying Pu, Sean Kross, Jake Hofman, Daniel G. Goldstein
April 2021
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Effects of LLM-based Search on Decision Making: Speed, Accuracy, and Overreliance
Sofia Eleni Spatharioti, David Rothschild, Daniel G. Goldstein, Jake Hofman
CHI 2025 | April 2025
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Putting scientific results in perspective: Improving the communication of standardized effect sizes
Yea-Seul Kim, Jake Hofman, Daniel G. Goldstein
CHI 2022 | April 2022
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Round Numbers Can Sharpen Cognition
Huy Anh Nguyen, Jake Hofman, Daniel G. Goldstein
CHI 2022 | April 2022
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Investigating Perceptual Biases in Icon Arrays
Cindy Xiong, Ali Sarvghad, Daniel G. Goldstein, Jake Hofman, Çağatay Demiralp
CHI 2022 | April 2022
Honorable Mention
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Manipulating and Measuring Model Interpretability
Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake Hofman, Jennifer Wortman Vaughan, Hanna Wallach
CHI 2021 | May 2021
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How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results
Jake Hofman, Daniel G. Goldstein, Jessica Hullman
CHI 2020 | April 2020
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Expanding The Scope Of Reproducibility Research Through Data Analysis Replications
Jake Hofman, Daniel G. Goldstein, Siddhartha Sen, Forough Poursabzi-Sangdeh
The Web Conference Workshop on Innovative Ideas in Data Science (IID) | April 2020
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To Put That in Perspective: Generating Analogies that Make Numbers Easier to Understand
Christopher Riederer, Jake Hofman, Daniel G. Goldstein
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems | April 2018
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Improving Comprehension of Numbers in the News
Pablo J. Barrio, Daniel G. Goldstein, Jake Hofman
Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems | May 2016
ISBN: 978-1-4503-3362-7
-
Exploring Limits to Prediction in Complex Social Systems: Predicting Cascade Size on Twitter
Travis Martin, Jake Hofman, Amit Sharma, Ashton Anderson, Duncan Watts
Proceedings of the 25th International Conference on World Wide Web | April 2016
-
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake Hofman, Duncan Watts
Proceedings of the Sixteenth ACM Conference on Economics and Computation | June 2015
ISBN: 978-1-4503-3410-5
-
A Large-scale Exploration of Group Viewing Patterns
Allison J.B. Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
TVX '14 Proceedings of the 2014 ACM international conference on Interactive experiences for TV and online video | June 2014
ISBN: 978-1-4503-2838-8
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Microsoft New Future of Work Report 2024
Jenna Butler, Mihaela Vorvoreanu, Rebecca Janssen, Abigail Sellen, Nicole Immorlica, Adam Troy, Advait Sarkar, Alex Farach, Alex Chouldechova, Alexandra Olteanu, Alexia Cambon, Arjun Radhakrishna, Asta Roseway, Ben Zorn, Brent Hecht, Daniel G. Goldstein, Dhruv Joshi, Ed Cutrell, Emre Kiciman, Gonzalo Ramos, Gustavo Soares, Hanna Wallach, Ian Drosos, Jack Williams (johnwilliams), Jacki O'Neill, Jake Hofman, Jaime Teevan, Javier Hernandez, Jennifer Wortman Vaughan, Jina Suh, John Tang, Justin Edwards, Kalika Bali, Kori Inkpen, Krishna Madhavan, Laylah Bulman, Leon Reicherts, Lev Tankelevitch, Longqi Yang, Martez Mott, Millicent Ochieng, Mercy Muchai, Nancy Baym, Najeeb Abdulhamid, Nicolai Marquardt, Ken Hinckley, Michael Bentley, Dave Brown, Hugo Romat, Nathalie Henry Riche, Samuel Maina, Shamsi Iqbal, Siân Lindley, Stephanie Nyairo, Su Lin Blodgett, Sumit Gulwani, Sunayana Sitaram, Vu Le
MSR-TR-2024-56 | December 2024
Publié par Microsoft
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Microsoft New Future of Work Report 2023
Jenna Butler, Sonia Jaffe, Nancy Baym, Mary Czerwinski, Shamsi Iqbal, Kate Nowak, Sean Rintel, Abigail Sellen, Mihaela Vorvoreanu, Najeeb G. Abdulhamid, Judith Amores, Reid Andersen, Kagonya Awori, Maxamed Axmed, danah boyd, James Brand, Georg Buscher, Dean Carignan, Martin Chan, Adam Coleman, Scott Counts, Madeleine Daepp, Adam Fourney, Daniel G. Goldstein, Andy Gordon, Aaron L Halfaker, Javier Hernandez, Jake Hofman, Jenny Lay-Flurrie, Vera Liao, Siân Lindley, Sathish Manivannan, Charlton Mcilwain, Subigya Nepal, Jennifer Neville, Stephanie Nyairo, Jacki O'Neill, Victor Poznanski, Gonzalo Ramos, Nagu Rangan, Lacey Rosedale, David Rothschild, Tara Safavi, Advait Sarkar, Ava Scott, Chirag Shah, Neha Parikh Shah, Teny Shapiro, Ryland Shaw, Auste Simkute, Jina Suh, Siddharth Suri, Ioana Tanase, Lev Tankelevitch, Adam Troy, Mengting Wan, Ryen W. White, Longqi Yang, Brent Hecht, Jaime Teevan
MSR-TR-2023-34 | December 2023
Publié par Microsoft
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Early LLM-based Tools for Enterprise Information Workers Likely Provide Meaningful Boosts to Productivity
Alexia Cambon, Brent Hecht, Benjamin Edelman, Donald Ngwe, Sonia Jaffe, Amy Heger, Mihaela Vorvoreanu, Sida Peng, Jake Hofman, Alex Farach, Margarita Bermejo-Cano, Eric Knudsen, James Bono, Hardik Sanghavi, Sofia Spatharioti, David Rothschild, Daniel G. Goldstein, Eirini Kalliamvakou, Peter Cihon, Mert Demirer, Michael Schwarz, Jaime Teevan
MSR-TR-2023-43 | December 2023
Publié par Microsoft
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Online And Social Media Data As A Flawed Continuous Panel Survey
Fernando Diaz, Michael Gamon, Jake Hofman, Emre Kiciman, David Rothschild
MSR-TR-2014-159 | May 2014
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Mining Large-scale TV Group Viewing Patterns for Group Recommendation
Allison J.B. Chaney, Mike Gartrell, Jake Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
MSR-TR-2013-114 | November 2013
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A Sports Analogy for Understanding Different Ways to Use AI
Jake Hofman, Daniel G. Goldstein, David Rothschild
Harvard Business Review | December 2023
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Math Education with Large Language Models: Peril or Promise?
Harsh Kumar, David Rothschild, Daniel G. Goldstein, Jake Hofman
SSRN Electronic Journal | December 2023
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An illusion of predictability in scientific results: Even experts confuse inferential uncertainty and outcome variability
Sam Zhang, Patrick R. Heck, Michelle N. Meyer, Christopher F. Chabris, Daniel G. Goldstein, Jake M. Hofman
Proceeding of the National Academy of Sciences | August 2023, Vol 120(33)
-
Integrating explanation and prediction in computational social science
Jake Hofman, Duncan J Watts, Susan Athey, Filiz Garip, Thomas L Griffiths, Jon Kleinberg, Helen Margetts, Sendhil Mullainathan, Matthew J Salganik, Simine Vazire, Alessandro Vespignani, Tal Yarkoni
Nature | June 2021, Vol 595(7866): pp. 181-188
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Split-door criterion: Identification of causal effects through auxiliary outcomes
Amit Sharma, Jake Hofman, Duncan Watts
Annals of Applied Statistics | December 2018, Vol 12(4): pp. 2699-2733
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Prediction and explanation in social systems
Jake Hofman, Amit Sharma, Duncan Watts
Science | February 2017, Vol 355: pp. 486-488
-
Online and Social Media Data As an Imperfect Continuous Panel Survey
Fernando Diaz, Michael Gamon, Jake Hofman, Emre Kiciman, David Rothschild
PlosONE | January 2016, Vol 11
-
The Structural Virality of Online Diffusion
Sharad Goel, Jake Hofman, Duncan Watts, Ashton Anderson
Management Science | July 2015, Vol 62(1): pp. 180-196
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