RAI Training

Summary: RAI training is designed to improve the level of awareness and skill of employees in implementing RAI.

Type of pattern: Governance pattern

Type of objective: Trustworthiness

Target users: Management teams

Impacted stakeholders: Employees, AI users, AI impacted subjects, AI consumers

Lifecycle stages: All stages

Relevant AI ethics principles: Human, societal and environmental wellbeing, human-centered values, fairness, privacy protection and security, reliability and safety, transparency and explainability, contestability, accountability

Mapping to AI regulations/standards: EU AI Act, ISO/IEC 42001:2023 Standard.

Context: If not developed and used responsibly, AI systems can pose significant risks. It is important that the employees of an organization think critically about the potential implications of AI on their work and make responsible choices during the development and use of AI systems. Doing so includes considering the potential RAI risks and impacts on various stakeholders and taking steps to mitigate those risks.

Problem: How can we improve organizational awareness and skill in RAI?

Solution: RAI training can be an effective way to help organizations ensure that they are adopting AI in a legally compliant, ethical, and responsible manner. Organizations can provide employees with knowledge and instructions on how to deal with RAI issues and reduce potential RAI risks when they develop or use AI systems. The training programs can be designed to meet specific needs of different roles within the organization and can cover a wide range of topics related to RAI. Topics can include governance for RAI, ethical operations of AI systems, trustworthy development processes, and RAI-by-design with case studies (e.g., ethical/unethical agents [1], autonomous vehicles [2]).

Benefits:

  • Increased organizational awareness: RAI training helps to provide employees with a deeper understanding and knowledge on RAI principles and best practices.
  • Increased skill: RAI training helps to sharpen the employees’ skills in developing or using AI systems responsibly.

Drawbacks:

  • Increased cost: RAI training can incur additional costs for an organization. These costs may include the cost of developing and delivering the training program, as well as any expenses related to bringing in outside experts or facilitators to provide the training.
  • Limited content: RAI involves broad knowledge and skills (e.g., principles, regulations, guidelines, methods). However, due to time constraints, RAI training may only be able to cover a subset of this content.

Related patterns:

  • RAI certification: Upon successful completion of an RAI training program, an employee or organization may be granted an RAI certificate as recognition of their RAI knowledge and commitment.
  • Code for RAI: The RAI training program can include a code of RAI as part of the curriculum.
  • Role-level accountability contract: Organizations can provide training to ensure their employees understand their accountability and responsibility when developing AI systems.

Known uses:

References:

[1] Weiss, A., et al. Using the Design of Adversarial Chatbots as a Means to Expose Computer Science Students to the Importance of Ethics and Responsible Design of AI Technologies. in IFIP Conference on Human-Computer Interaction. 2021. Springer.

[2] Furey, H. and F. Martin, AI education matters: A modular approach to AI ethics education. AI Matters, 2019. 4(4): p. 13-15.