NIST AI RMF Playbook
AI RMF Playbook > Map > MAP 3.1

MAP 3.1: Potential benefits of intended AI system functionality and performance are examined and documented.

About:
AI systems have enormous potential to improve quality of life, enhance economic prosperity and security costs. Organizations are encouraged to define and document system purpose and utility, and its potential positive impacts and benefits beyond current known performance benchmarks.

It is encouraged that risk management and assessment of benefits and impacts include processes for regular and meaningful communication with potentially affected groups and communities. These stakeholders can provide valuable input related to systems' benefits and possible limitations. Organizations may differ in the types and number of stakeholders with which they engage.

Other approaches such as human-centered design (HCD) and value-sensitive design (VSD) can help AI teams to engage broadly with individuals and communities. This type of engagement can enable AI teams to learn about how a given technology may cause positive or negative impacts, that were not originally considered or intended.

Suggested Actions:
- Utilize participatory approaches and engage with system end users to understand and document AI systems' potential benefits, efficacy and interpretability of AI task output.
- Maintain awareness and documentation of the individuals, groups, or communities who make up the system's internal and external stakeholders.
- Verify that appropriate skills and practices are available in-house for carrying out participatory activities such as eliciting, capturing, and synthesizing user, operator and external feedback, and translating it for AI design and development functions.
- Establish mechanisms for regular communication and feedback between relevant AI actors and internal or external stakeholders related to system design or deployment decisions.
- Consider performance to human baseline metrics or other standard benchmarks.
- Incorporate feedback from end users, and potentially impacted individuals and communities about perceived system benefits .

Transparency and Documentation:
### Organizations can document the following
- Have the benefits of the AI system been communicated to end users?
- Have the appropriate training material and disclaimers about how to adequately use the AI system been provided to end users?
- Has your organization implemented a risk management system to address risks involved in deploying the identified AI system (e.g. personnel risk or changes to commercial objectives)?

### AI Transparency Resources
- Intel.gov: AI Ethics Framework for Intelligence Community - 2020. [URL](https://www.intelligence.gov/artificial-intelligence-ethics-framework-for-the-intelligence-community)
- GAO-21-519SP: AI Accountability Framework for Federal Agencies & Other Entities. [URL](https://www.gao.gov/products/gao-21-519sp)
- Assessment List for Trustworthy AI (ALTAI) - The High-Level Expert Group on AI - 2019. [LINK](https://altai.insight-centre.org/), [URL](https://digital-strategy.ec.europa.eu/en/library/assessment-list-trustworthy-artificial-intelligence-altai-self-assessment)

References:
Roel Dobbe, Thomas Krendl Gilbert, and Yonatan Mintz. 2021. Hard choices in artificial intelligence. Artificial Intelligence 300 (14 July 2021), 103555, ISSN 0004-3702. [URL](https://doi.org/10.1016/j.artint.2021.103555)

Samir Passi and Solon Barocas. 2019. Problem Formulation and Fairness. In Proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* '19). Association for Computing Machinery, New York, NY, USA, 39-48. [URL](https://doi.org/10.1145/3287560.3287567)

Vincent T. Covello. 2021. Stakeholder Engagement and Empowerment. In Communicating in Risk, Crisis, and High Stress Situations (Vincent T. Covello, ed.), 87-109. [URL](https://ieeexplore.ieee.org/document/9648995)

Yilin Huang, Giacomo Poderi, Sanja Šćepanović, et al. 2019. Embedding Internet-of-Things in Large-Scale Socio-technical Systems: A Community-Oriented Design in Future Smart Grids. In The Internet of Things for Smart Urban Ecosystems (2019), 125-150. Springer, Cham. [URL](https://link.springer.com/chapter/10.1007/978-3-319-96550-5_6)

Eloise Taysom and Nathan Crilly. 2017. Resilience in Sociotechnical Systems: The Perspectives of Multiple Stakeholders. She Ji: The Journal of Design, Economics, and Innovation, 3, 3 (2017), 165-182, ISSN 2405-8726. [URL](https://www.sciencedirect.com/science/article/pii/S2405872617300758)