Ai+ Training

Course curriculum

AI is seemingly everywhere. It powers the technology that helps us move around in the world, entertain ourselves, work productively, and access necessary resources and services. The pressure on business leaders to incorporate AI into their systems and products is enormous. However, successful implementation is difficult. Reportedly, 85% of AI projects fail to bring their intended results to the business. The recent Zillow debacle highlighted the enormous financial risks of implementing AI systems poorly, not only in terms of revenue impact, but also in reputational damage, loss of morale, and loss of jobs. So, how do we move forward with AI responsibly and effectively? That process starts with the system's design. This talk will draw on information from the following two frameworks – IEEE 7000-2021: IEEE Standard Model Process for Addressing Ethical Concerns during System Design, and Section A of the Technical Best Practices from the Foundation for Best Practices in Machine Learning. In melding the more technically focused IEEE framework with the more business-oriented section from the Technical Best Practices framework, this talk aims to provide participants with practical and actionable guidance on designing effective and ethical AI products. The talk will focus on the initial stage of the AI product lifecycle. Specifically, we’ll focus on the following areas of the AI design process: team composition and roles, problem statement and solution mapping, integrating context, organizational capacity, and defining the product and outcomes. Participants will leave this session with a broad understanding of two prevailing ethical design frameworks and a practical understanding of the initial steps organizations can take to design ethical and effective AI systems.