Actionable Strategies for AI Impact Assessments

This module equips you with actionable strategies to conduct AI impact assessments, ensuring ethical, legal, and social considerations are integrated into every stage of your AI projects.
Format

Online
Course

Expert

Shalaleh
Rismani

Live session date

May 7 , 2025

Live session time

12:30 - 3:00PM

Individual preparatory work

1 Hour

Price

$225 + Tax

About the module

In today's fast-paced economy, the ability to develop and deliver innovative services and products swiftly is a critical competitive advantage. However, the rapid integration of AI technology can introduce unforeseen risks and negative impacts, which may be harmful or even illegal. This module on Responsible AI Impact Assessments will provide an in-depth overview of algorithmic harms and guide you through each stage of an AI impact assessment framework equipping you with the knowledge and tools to conscientiously and responsibly plan and manage AI projects. Additionally, in this module you will outline how impact assessments compare to other frameworks and examine their role in establishing appropriate AI governance mechanisms and complying with upcoming regulations.

Learning Outcomes

Identify how impact assessments are an important tool in establishing AI governance mechanisms and meeting upcoming regulations. 
Describe different types of harms from algorithmic systems, specifically AI systems.
Outline different stages of an impact assessment process.
Highlight the key activities that need to take place in different stages of an impact assessment.
Discuss how impact assessments can be considered throughout an AI system/product’s  life cycle.
Consciously plan how an impact assessment could be considered in implementation of a responsible AI strategy in various AI projects. 

Who is this module for?

All AI professionals, including executive leaders, Data Scientists, ML/AI engineers, AI developers, AI product managers, AI consultants and investors.

Tailored for participants with an interdisciplinary background or interest, who have a foundational understanding of AI systems, including their creation and diverse applications.

Course Lessons

Shalaleh Rismani

Shalaleh Rismani is a PhD candidate in Electrical and Computer Engineering at McGill University and Mila, where she conducts interdisciplinary research in the Responsible Autonomy and Intelligent Systems Ethics Lab. Her work centers on human-AI interaction and system safety, developing actionable frameworks to identify and characterize factors that could lead to algorithmic harm in AI systems. Focusing on the early stages of AI system design, her research aims to equip developers and stakeholders with practical tools to address potential sources of harm before they emerge in real-world applications. 
In addition to her research, Shalaleh is a responsible AI consultant at Mila, contributing to various educational and research initiatives, including creating an Open Resource Learning Guide for teaching responsible AI research practices for machine learning researchers and hosting a workshop on psychological impact of AI systems to inform Canadian policy. She also serves as the Executive Director of the Open Roboethics Institute, advancing education on the social and ethical implications of robotics and embodied AI systems.
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