Implementing Safe Use of AI in Your Business - A Strategic Framework

The workshop will be held on MS Teams with a limited number of participants to ensure everyone has the chance to ask questions and to support a more personalised learning experience.

This course provides a strategic blueprint for ensuring Safe, ethical, privacy-focused, transparent, and unbiased AI governance in any organisation . Below is a summary of the course content -

Who Should Attend:

• Training providers and colleges, e.g. managing directors, IT leads, heads of centre, curriculum leads, any individual leading on AI or Sipporting AI use in a business.
• Employer providers
• Leaders in technology, data, risk, compliance, learning and development or workforce strategy
• Policy-makers
• Any professional wanting to support safe AI implementation or ethics in a business.

1. Strategic Application of AI in Decision-Making

• Strategies for Integrating AI into Decision-Making Processes
• Understanding the Role of AI in Data-Driven Decision Making
• Approaches to Leveraging AI for Enhanced Decision Support

2. The 5 Pillars of AI Governance

Pillar 1, Safety - Ensuring Safety in AI Practices

- Understanding the Importance of Safety in AI

- Approaches to Safety in Diverse AI Contexts

- Case Studies: Safety Failures and Successes in AI

Pillar 2, Ethics - Understanding the ethical considerations of AI

- Ethical principles in AI: Fairness, transparency, accountability, and privacy

- Implications of biased data and algorithmic bias

- Strategies for addressing ethical considerations in AI usage

Pillar 3, Privacy - Data privacy and security considerations

- Understanding the Importance of Data Privacy and Compliance in AI

- Strategies for Ensuring Data Security in AI Applications

- Approaches to Risk Mitigation and Data Protection in AI Usage

Pillar 4, Transparency - Implementing Transparency in AI

- The Role of Transparency in Building Trust in AI

- Strategies for Enhancing Transparency in AI Practices

- Case Studies: Transparency Challenges and Solutions in AI

Pillar 5, Bias - Mitigating Bias via inclusivity and fairness in AI usage

- Identifying and mitigating bias in AI systems and data

- Ensuring diverse and representative training data

- Evaluating AI models for fairness and inclusivity

3. Completion

There will be a short quiz/assessment (self marked) at the end of the workshop to enable attendees to assess their own learning and ask questions for any areas or knowledge needing clarification.

There will be a final Q+A session at the end of the workshop to support attendees fully with next steps and full comprehension.

CPD Credential

Those completing the course will receive a digital credential from R People and City & Guilds confirming attendance, and the knowledge and skills gained during the course. Digital badges can be shared on social media.