MAP-2.1—The specific task, and methods used to implement the task, that the AI system will support is defined (e.g., classifiers, generative models, recommenders).

AI actors define the technical learning or decision-making task(s) an AI system is designed to accomplish, or the benefits that the system will provide. The clearer and narrower the task definition, the easier it is to map its benefits and risks, leading to more fulsome risk management.

Organizations can document the following

• To what extent has the entity clearly defined technical specifications and requirements for the AI system?
• To what extent has the entity documented the AI system’s development, testing methodology, metrics, and performance outcomes?
• How do the technical specifications and requirements align with the AI system’s goals and objectives?
• Did your organization implement accountability-based practices in data management and protection (e.g. the PDPA and OECD Privacy Principles)?
• How are outputs marked to clearly show that they came from an AI?

AI Transparency Resources

• Datasheets for Datasets.
• WEF Model AI Governance Framework Assessment 2020.
• WEF Companion to the Model AI Governance Framework- 2020.
• ATARC Model Transparency Assessment (WD) – 2020.
• Transparency in Artificial Intelligence - S. Larsson and F. Heintz – 2020.

Leong, Brenda (2020). The Spectrum of Artificial Intelligence - An Infographic Tool. Future of Privacy Forum.

Brownlee, Jason (2020). A Tour of Machine Learning Algorithms. Machine Learning Mastery.