Responsible AI often lives at the principle level, while engineers make concrete decisions that shape system behavior, user impact, and long-term trust. This workshop connects responsibility directly to everyday engineering work.
To win, your teams must embed responsible AI principles into concrete development decisions and workflows.
When responsible AI is not operationalized for engineers, delivery and risk management break down quickly.
• Ambiguous ownership: Engineers are unclear about their responsibility in ethical GenAI, assuming risk is handled elsewhere.
• Disconnected decisions: Technical choices are made without understanding their downstream social or user impact.
• Reactive safeguards: Safety and inclusion are addressed late, after systems are already designed or deployed.
These gaps increase ethical exposure, reduce trust, and drive costly rework.
In this hands-on workshop, your team translates responsible AI concepts into practical engineering actions through guided instruction and applied exercises.
• Define core principles of responsible AI in terms directly relevant to engineering decisions.
• Clarify the specific roles AI engineers play in ethical GenAI development.
• Map common development choices to potential social and user impacts.
• Apply safety and inclusion considerations early through structured design exercises.
• Integrate responsibility checkpoints into existing development workflows.
- Defining Core Principles of Responsible AI
- Identifying Roles of Engineers in Ethical GenAI
- Mapping Development Choices to Social Impact
- Designing for Safety and Inclusion from the Start
- Integrating Responsibility into Dev Workflows
• Explain responsible AI principles in language grounded in engineering practice.
• Understand and own their role in ethical GenAI development.
• Anticipate social and user impact when making technical design choices.
• Design systems with safety and inclusion considered from the outset.
• Embed responsible AI practices into everyday development workflows.
Who Should Attend:
Solution Essentials
Virtual or in-person
2 hours
Engineers with experience building or integrating AI systems
Structured exercises, case scenarios, and guided discussion materials