AI Governance
Published by O'Reilly Media, Inc.
Principles and Practices for AI Stakeholders
- Learn how to build a governance framework for the development and implementation of AI within your organization.
- Understand the role of AI governance in addressing ethical considerations, regulatory compliance, accountability and effectiveness.
- Understand the distinct roles of different teams involved in the development and implementation of AI, and the responsibilities they must fulfill within an AI governance framework.
- Learn techniques to foster a positive AI culture within your organization, empowering both technical and non-technical stakeholders to contribute to development.
This comprehensive course on AI governance will equip professionals with the knowledge and tools needed to develop and implement an effective AI governance framework within their organization. Through emerging trends, discussion and presentations, participants will understand the core principles of AI governance and why they are growing ever more important against the backdrop of the latest state-of-the-art techniques. As organizations continue to leverage AI for process augmentation and automation, it is increasingly important to ensure that development and implantation is responsible, safe and effective. This course will culminate in a discussion of how best to foster a positive AI culture within an organization, ensuring that any governance is suitable, well-received and has positive uptake. This course will empower business leaders to ensure effective and responsible AI utilization at all stages of the development lifecycle and throughout the organization.
What you’ll learn and how you can apply it
- To understand the purpose of AI governance in organizational AI adoption.
- To identify the key regulatory frameworks that may need to be considered when building an AI governance framework.
- To understand the use and purpose of different types of tools that can be use to implement and manage an AI governance framework.
- To distinctly identify the different stages of the AI lifecycle, who is involved, the potential risks and how they can be mitigated through governance.
- To be aware of the tools and techniques that can be used to develop and measure AI implementations for safety, transparency and performance.
- Learn techniques that can be used to create a positive AI culture within your organization.
This live event is for you because...
- You are a leader within an organization responsible for the strategy, development and implementation of AI. - You may or may not be technical, but want to equip yourself with the tools necessary to ensure your teams implement AI that is safe, responsible and trustworthy.
- Example roles: Chief Technology Officer, Head of Engineering, Legal Council, AI Project Manager, Head of Compliance
Prerequisites
Recommended Follow-up
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
What is AI governance (40 minutes)
- Introduction/bio
- The goals of AI governance
- What does governance look like?
- Who is governance for?
Break (5 minutes)
Developing a Governance Framework (50 minutes)
- Defining ethical principles and goals
- Identifying legal and regulatory obligations
- Accountability and responsibility
- Identifying risk
- Tools and reporting
Break (5 minutes)
Responsible AI development (65 minutes)
- Defining success
- AI lifecycle
- Transparency and explainability
- Measuring success
Break (5 minutes)
Fostering a positive AI culture (45 minutes)
- Inclusivity and collaboration
- Building knowledge and skills
- Learning from failure
Break (5 minutes)
Conclusion (20 minutes)
- Recap
- The future of AI and AI governance
Your Instructor
Jonny Davis
Jonny Davis has spent his career working in data science consultancy, specialising in delivering applied AI solutions to organisation across a wide variety of industries and regions. Originally focusing on Natural Language Processing (NLP) at Accenture, he led the NLP expert group and was also involved in defining parts of their Responsible AI Framework, underpinning client trust in their AI development.
Through consulting and engagement with a wide variety of cross-industry clients, Jonny gained a keen interest in communication and explainability. He is a regular blogger on Medium where he writes articles to explore and understand complex topics, from confirmation bias in AI to constitutional AI. He has also spoken at several conferences on data-driven decision making and ensuring machine learning is correctly utilised in organisations. He had a BSc in Physics from Imperial College London.
Skills covered
- AI Governance
- Governance