Over five billion people worldwide actively engage with AI, Metaverse, bots, machine-to-machine connected solutions, 5G, AR/VR, cryptocurrency, and blockchain. This conference will explore how digital, social, and mobile technologies affect business models, customer behavior, management strategies, public policy, and social changes at large. Exemplar topics include:

AI automation augmentation/ Metaverse/ Cryptocurrency/ Robotics AI adoption and user behavior/AI voice-mining for promo and recommendations/ AIML with social media data/ Multi-modal algorithms for images, voice, and video data/ Bot trading and AI advisor in financial markets/AI for ad creatives and publishers/ AI applications in worker training, hiring, supervising, HR management, business strategies/ ML applications in fintech, pharma, and e-commerce/ Deepfake algorithms, privacy and ethics of new technologies/ Data breach and security/ Blockchain applications/ Future of work and unemployment/ Big data IoT, 5G, AR, and VR applications/ Public policy and regulation of AI technologies/ AI algorithm bias, interpretable ML/ Machine learning for causal inference/ ML and deep learning for statistics methods/ Machine learning for empirical IO/ Deep reinforcement learning for microeconomics theory / Healthcare applications of ML/ Multi-armed bandits for online advertising and pricing/ Contextual MAB for personalized dynamic recommendations/ AIML in B2C and B2B markets, COVID detection/prevention/treatment

Confirmed Keynote Speakers (tentative):

Tat Chan (WUSL)

Kosuke Uetake (Yale)

Daria Dzyabura (NES and Skolkovo Moscow School of Management)

John Hauser (MIT)

John Horton (MIT)

Nan Jia (USC)

Xueming Luo (Temple)

Puneet Manchanda (UMich)

Sridhar Narayanan (Stanford)

Daniel Rock (Wharton)

Param Vir Singh (CMU)

Vineet Kumar (Yale)

K Sudhir (Yale)

Raphael Thomadsen (WUSL)

Catherine Tucker (MIT)

Shunyuan Zhang (Harvard)

Submission logistics: Submit either a 3-page abstract, full paper, or 10 PPT slides to AIML2022Conf@gmail.com, Xueming.Luo@temple.edu, szhang@hbs.edu

Submission deadline: October 1, 2022. Acceptance notification date: November 1, 2022 (Acceptance of submission requires one co-author to register and present at the conference)

This annual conference was hosted at Chicago Booth in 2014, NYU Stern in 2015 and 2017, Stanford GSB in 2016, CMU Tepper in 2018, Temple in 2019, and on Zoom in 2020 and 2021. It has attracted a vibrant group of professors, industry people, and PhD students working on cutting-edge AI/ML models and data in inter-disciplinary fields. This conference serves as an intellectual bridge between computer science, economics, statistics, marketing, management, finance, strategy, IS, healthcare, education, public policy, and others.

Please note: By registering for this conference, you agree to follow all HBS COVID-19 guidelines. For the latest COVID-19 guidance, please visit the Keep HBS Healthy visitor page.