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Record STMT-WF9B6D9Advisory

Prioritizing People and Planet as the Metrics for Responsible AI Ethically Aligned Design for Business

Framework ProfessionalGlobaladopted

This paper by the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems provides guidance for businesses and policymakers on incorporating well-being metrics—such as ESG standards and UN Sustainable Development Goals (SDGs)—into the design and lifecycle of artificial intelligence systems (AIS). It advocates for 'Well-being by Design' as a core metric for responsible AI to prioritize human well-being and environmental sustainability over solely financial indicators. The document outlines practical steps for assessing, applying, and scaling these metrics across organizations of varying sizes.

Summary and content fields are drawn from the document text and are pending editorial review.

Who issued it

Institute of Electrical and Electronics EngineersProfessional · US
Lead issuer
Legal forceAdvisory
Under whose authorityProfessional
Judged fromfull text

Who it governs

CompaniesNational governmentAI developers and providersAI deployers and usersResearchers and academics

Business leaders, technology developers, and policymakers looking to integrate responsible AI and well-being metrics into organizational strategy and system design.

Sectors
Cross-sectorResearch and science · autonomous and intelligent systems

What the document contains

What's covered

The document covers the integration of well-being, ESG, and UN Sustainable Development Goal metrics into the design, development, and scaling of autonomous and intelligent systems to ensure human and environmental flourishing.

What's missing

Binding legal enforcement mechanisms, mandatory penalties for non-compliance, and technical source code implementation details.

Key takeaways
  • Traditional business metrics focused purely on financial growth risk causing unintended human or environmental harm when developing AI systems.
  • Organizations should adopt a 'Well-being by Design' approach by integrating UN Sustainable Development Goals (SDGs) and ESG metrics at the outset of AIS design.
  • Assessing organizational readiness and leveraging existing human resources, compliance, and corporate social responsibility structures can facilitate the adoption of responsible AI metrics.
  • Implementing well-being metrics requires cross-functional training, risk management, and the use of frameworks such as IEEE Std 7010 and IEEE Std 7000.
  • Scaling responsible AI practices across an organization involves tailoring governance structures to company size, championing internal evangelists, and fostering a positive safety culture.
Principles it states
Prioritizing people and planet as metrics for responsible AIContinuous and sustainable physical, mental, and social flourishing of individuals, communities, and populationsHuman-centric, value-based design
Outline
· 1 Introduction
· Assess: What organizational values are leveraged for Responsible AI metrics?
· Apply: How does an organization implement the principles and metrics of Responsible AI?
· Amplify: How does an organization scale its work to grow and measure the success of Responsible AI metrics?
· Conclusion
· Well-Being Metrics Readiness Framework
· Committee Members
Issued2022
Length9,076 words
FormatNot recorded
Scopeglobal

How it scores

Pending review

Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.

Accountability

3/5

Clear responsibility for AI outcomes

Establish clear stakeholders/owners of the metrics with individuals that will help drive the initiative forward and take responsibility.

AMPLIFY

screening score · 2026-10-23

Human Oversight

2/5

Humans remain in control of consequential decisions

AI systems are designed to operate with varying levels of autonomy.

1 Introduction

screening score · 2026-10-23

Privacy

2/5

Protection of personal data and private life

For instance, when the European Union’s (EU) General Data Protection Regulation (GDPR) first came into existence, many people fought against having to use it.

WHAT ORGANIZATIONAL VALUES ARE LEVERAGED FOR RESPONSIBLE AI METRICS?

screening score · 2026-10-23

Transparency

3/5

Openness about how AI systems work and are used

Transparency underlies Target 12.6 of the SDGs to encourage companies to adopt sustainable practices and integrate sustainability information into their reporting cycle.

APPLY:

screening score · 2026-10-23

Enforcement

1/5

Consequences and compliance mechanisms with real force

Conformity assessment will be mandatory for high risk applications in the EU.

AMPLIFY

screening score · 2026-10-23

Impact Assessment

4/5

Required assessment of an AI system's risks/impacts before or during use

Compliance functions may use impact assessments (environmental, and human rights, among others) to assess both positive and negative impacts that specific technology, processes, and initiatives may have in the enterprise.

WHAT ORGANIZATIONAL VALUES ARE LEVERAGED FOR RESPONSIBLE AI METRICS?

screening score · 2026-10-23

Topics

Physical AI Governancecore
responsible_ai well_being_metrics esg sustainable_development_goals ethical_design