AIM2025

UPDATE

The 5th AIM Conference in 2025 was a success with over 130 high-quality presentations. We would like to express our heartfelt gratitude to all the presenters, participants, and sponsors who made it possible. As we conclude the conference, we are delighted to announce this year’s award winners.

The selection process began with session chairs nominating standout papers they believed merited award consideration. In parallel, several conference co-chairs reviewed the presented papers and added their own nominations. Some award sponsors also identified noteworthy contributions during the sessions.

From this pool of Nominees, the co-chairs carefully reviewed the papers and cast their individual votes for those they deemed most deserving. These became our Finalists. Among the finalists, those receiving strong support from the co-chairs were named our Winners.

Congratulations to all Winners, Finalists, and Nominees!

WINNERS

Dominique Hanssens Best PhD Paper Award ($5,000)

1. Quantifying the Impact of AI on Productivity and Labor Demand: Evidence from U.S. Census Microdata, Sagar Baviskar et al, CMU

2. Technological Interventions to Combat Social Stigma in Mental Health Support, Zhichen Chen, et al, Boston University.

Vithala Rao Best PhD Paper Award ($5,000)

3. Artificial Intelligence Sense of Humor: Augmentation vs. Substitution in Creative Industries, Ruben R. Salas et al, Wharton,

4. Information Signals in Sponsored Search: Evidence from Google's BERT, Poet Larsen et al, USC

Steven Shugan Best Junior Faculty Paper Award ($5,000)

5. Beyond Black-Box: Enforcing Intent-Based Structure in Recommender Systems Using Predicted Intents,  Yuyan Wang et al, Stanford.

6. Emotion Sequences and Persuasive Stories: Evidence from Online Fundraising and LLM-Assisted Rewrites, Samsun Knight et al, U. of Toronto.

Cheryl and Gerard Tellis Best Junior Faculty Award ($5,000)

7. Artificial Intelligence and Workforce Skill Development: Examining the Role of Meaning, Arvind Karunakaran, et al, Stanford

8. AI Review Summary, Customer Ratings, and Performance Entrenchment, Wesley Koo et al, John Hopkins

FINALISTS

• The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilot (Doron Yeverechyahu; Raveesh Mayya; Gal Oestreicher-Singer)

• Turning the Tide: How Firms Mitigate Sociopolitical Risks Through Strategic Responses (Chen Jing; Dokyun Lee; Shuba Srinivasan; Koen Pauwels)

• Multi-Tier LLM-Based Context-Aware Framework for Extracting Sales Negotiation Tactics (Yufan (Frank) Lin; Bitty Balducci; Raymond Yang)

• Algorithmic Targeting of At-Risk Gig Workers: Evidence from Emerging Markets (Yixiang Xu)

• Generative AI and the Nature of Work (Manuel Hoffmann, Sam Boysel, Frank Nagle, Sida Peng, Kevin Xu)

• A Representative Sampling Method for Peer Encouragement Designs in Network Experiments (Yanyan Li; Sha Yang; Qing Liu)

• Artificial Intelligence, Big Data and Globalization Performance of Multinational Enterprises: Theory and Empirical Evidence (Alysson Silveira; Julie Quick; Terence Saldanha; Sunil Mithas)

• Surfing the Tech Wave: A Mindset Intervention to Boost Artificial Intelligence Adoption and Creativity (Hsuan-Che (Brad) Huang; Emily Hsu; Markus Baer)

• Weighting Graphs for Causal Inference (Khaled Boughani, Mingzheng, Sachin Gupta)

• Information Disclosure and Acceptance of Algorithmic Advice: A Field Study on Human-AI Interaction in Healthcare Gatekeeping (Shujing Sun; Lauren Xiaoyuan Lu; Susan Feng Lu; Wei Gu)

• Blessing of Reasoning: Value of LLM-Generated Explanations in Black-Box Recommender Systems (Pan Li, Yuyan Wang, Minmin Chen)

• The short-term effects of generative artificial intelligence on employment (Manuell Hoffman)

• Government Policy & Innovation Outcomes: Evidence from 2006 Chinese Domestic Innovation Initiative for AI-Automation Technologies (Albert Roh, Nan Jia, Miran Milic)

NOMINEES

• ClassChat: A Shared Generative AI Agent for Enhancing Student Dialogue, Curiosity, Critical Thinking and Peer-Led Learning (Patrick Laub; Chuljin Park; Mary-Anne Williams; Siran Zhan)

• Large Language Models Augment or Substitute Human Experts in Idea Screening (Pavel Kireyev; Brendon Rhodes; Cathy Yang; Abhishek Borah)

• Using AI-Agents in Idea Screening: When Feedback Fails and Simplicity Wins (Andrea Pescher; Christian Pescher; Jason Bell; Gerard J. Tellis; Johann Fuller)

• Eliciting Domain Expertise in the Absence of Formal Authoprity: The Case of AI Developers & Domain Experts in a Large Firm (Luca Vendraminelli, Devesh Narahanan, Arvind Karunakaran)

• Make Then Buy? Occupational Repositioning, Technology Bundling, & Processes of AI Sourcing in Large Firms Back up (Devesh Narayanan)

• Rise of Industrial AI in America: Microfoundations of the Productivity J-Curves (Kristina McElheran)

• Igniting Innovation: Evbidencve from PyTorch on Technology Control in Open Collaboration (Daniel Yue)

• Being Served in the Metaverse: A Dynamic Empirical Analysis of Customer Feedback Effects and Firm Performance Outcomes (Changxu (Victor) Li; Bart Larivière; Alexander Edeling)

• Why Do New Market Entrants Keep Disrupting Incumbents? Using AI to Identify Dimensions of Radical Innovation or Seeds of Demise in CEO Letters to Shareholders (Francesca Bonetti; Andrea Pescher; Sajeev Nair; Gerard Tellis)

• Strategic AI Readiness and Firm Valuation of Generative AI (Haonan yin, Sanjeev Dewan, Fei Ren)

• A New Estimator for Encouragement Design in Randomized Controlled Trials When the Exclusion Restriction is Villated (Zhengling Qi, Cheng Lu, Tat Chan, Zhengling Qi, Dennis Zhang, Yaran Jin, Miaoyu Yang)

• Evidence from PyTorch on Technology Control in Open Collaboration (Daniel Yue, Frank Nagle)

• Generative AI and Copyright: A Dynamic Perspective (S. Alex Yang, Angela Huyue Zhang)

• Human–Algorithmic Bias: Source, Evolution, and Impact (Xiyang Hu, Yan Huang, Beibei Li, Tian Lu)

• Designing Data Science Contests: The Role of Training vs Test Splits (Ping-Chieh Huang, Zhe Zhang, Sanjiv Erat)