Compose Diverse and Interdisciplinary ML-Team new

Overview

Sustainability Dimension	Governance
ML Development Phase	ML Demand Specification
ML Development Stakeholders	Business Stakeholder

Description

“Compose Diverse and Interdisciplinary ML-Team” describes the required composition of the ML project teams, as diverse and interdisciplinary teams foster creativity and mitigate biases (Burgdorf et al., 2022). Organizations shall keep the ML development process closely aligned to ethics and actively reflect upon critical voices by engaging in dialogue (Barocas & Boyd, 2017). Diverse teams are characterized by a different range of experiences and different social as well as domain-specific insights. This enables the development of not only innovative approaches necessary for solving challenging problems, but also the ones essential for mitigating social risks (Burkhardt, 2019; Johnson et al., 2021). Hence, business stakeholders must account for such an ML Team composition early in the ML Demand Specification phase (Barocas & Boyd, 2017).

Sources

• Burgdorf, K., Rostamzadeh, N., Srinivasan, R., & Lena, J. (2022). Looking at Creative ML Blindspots with a Sociological Lens (arXiv:2205.13683). https://doi.org/10.48550/arXiv.2205.13683
• Barocas, S., & Boyd, D. (2017). Engaging the ethics of data science in practice. Communications of the ACM, 60(11), 23–25. https://doi.org/10.1145/3144172
• Burkhardt. (2019). Leading your organization to responsible AI | McKinsey. https://www.mckinsey.com/capabilities/quantumblack/our-insights/leading-your-organization-to-responsible-ai
• Johnson, M., Albizri, A., & Harfouche, A. (2021). Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing. Information Systems Frontiers. https://doi.org/10.1007/s10796-021-10137-5