Workshop on Machine Learning for Consumers and Markets at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 14-18 Aug 2021; Workshop deadline 31 May
Author: Dokyun Lee
KDD 2021 Workshop on Machine Learning for Consumers and Markets
Topics: Recent developments in ML present exciting opportunities for business. At the same time, ML also poses challenges that prevent many algorithms from being widely adopted due to deficiencies in interpretability, auditability, and unintended biases.
This workshop aims to bring the ML and business communities together to discuss the opportunities and challenges for ML in business. We focus on the following topics:
- Novel applied machine learning research that improves the consumer and market value: ML applications in fintech, e-commerce, MOOC online education, education, healthcare, social media, ad/promotion targeting, trading, B2B market, future of work, etc.
- Empirical studies that reveal and ameliorate unintended harms of machine learning technology in consumer and marketing application: lack of interpretability, trust, auditability, biased ML algorithms.
- Novel machine learning methodology that mitigates risks and roadblocks of ML in consumer and marketing applications such as Explainable Artificial Intelligence (XAI).
- Injecting consumer behavior and market insights into ML algorithms.
Submission Format: We invite contributions in 2 formats:
- Extended abstract (1 page excluding references)
- Short paper (up to 4 pages excluding references)
- Submission deadline: May 31st, 2021
- Author notification: June 19th, 2021
The workshop does not print proceedings nor take any copyrights so you can submit any work in progress to share and get feedback.