IEEE - Wellbeing Metrics for AI (7010-2020)

IEEE 7010-2020 Wellbeing Metrics Standard for Ethical AI and Autonomous Systems

IEEE

RAI-X1-GO-I7WMEXX-2020
In Force(In Force)
StandardFundamental RightsInternational Alignment
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IEEE standard establishing wellbeing metrics for assessing impacts of AI and autonomous systems on human wellbeing.

Overview

IEEE 7010-2020 provides wellbeing metrics for AI and autonomous systems. It enables measurement of human impacts. See IEEE Ethics in Action.

Definitions

  • Wellbeing: State of being comfortable, healthy, or happy
  • Wellbeing Metrics: Quantifiable measures of human wellbeing

Governance and Institutional Framework

  • IEEE Standards Association: Publisher
  • P7010 Working Group: Development team

Key Focus Areas

  1. Physical wellbeing indicators
  2. Psychological wellbeing metrics
  3. Social wellbeing measures
  4. Environmental wellbeing factors
  5. Economic wellbeing assessment

Implementation Framework

  • Metric selection
  • Data collection methodology
  • Analysis framework
  • Reporting requirements

Monitoring and Evaluation

  • Ongoing measurement
  • Trend analysis

Penalties, Liability, and Appeals

Voluntary standard for assessment.

Relationship to Other Instruments

  • Part of IEEE 7000 series
  • Complements IEEE 7000-2021

International Alignment

International standard for wellbeing assessment.

Implementation Timeline

DateMilestoneStatus
2020Standard publishedCompleted

Compliance Checklist

RequirementDescriptionDeadline
Metric ImplementationDeploy wellbeing metricsOngoing

Sources and References

DocumentTypeLink
IEEE 7010-2020StandardIEEE
Plain English

The IEEE 7010-2020 standard offers a framework for measuring how artificial intelligence (AI) and autonomous systems impact human wellbeing, applying to any organization or team developing or deploying these technologies who wishes to assess their ethical footprint.

Published in 2020, this standard is designed to help product managers, founders, and in-house teams understand and quantify the human effects of their AI systems. While voluntary, it provides a structured approach to ethical AI development by focusing on five key areas of wellbeing: physical, psychological, social, environmental, and economic. For those who choose to adopt it, the core "obligation" involves a systematic process: - Selecting relevant wellbeing metrics from the standard's guidance. - Establishing clear methodologies for collecting the necessary data. - Developing an analytical framework to interpret the collected data. - Fulfilling reporting requirements to document findings and demonstrate impact.

The standard became effective immediately upon its publication, meaning organizations can implement its guidelines on an ongoing basis. Crucially, as an IEEE standard, it carries no direct legal penalties or enforcement mechanisms. Its "teeth" are primarily reputational and ethical; adopting it signals a commitment to responsible AI, which can be vital for building user trust and meeting stakeholder expectations in an increasingly regulated landscape.

A practical pitfall for teams is the sheer breadth of "wellbeing" and the challenge of consistently collecting meaningful data across all five categories. While the standard provides guidance, translating these broad concepts into actionable, measurable metrics and integrating them into product development cycles requires significant effort and commitment. Teams might find themselves grappling with how to quantify subjective experiences or indirect environmental and economic impacts, making thorough implementation a complex, ongoing endeavor rather than a one-time checklist item.

Plain-English rewrite by Regulations.ai — not legal advice. Verify against the official text.

What you must do — compliance checklist

0 / 7 marked complete

Plain-English obligations under IEEE - Wellbeing Metrics for AI (7010-2020). Not legal advice — verify against the official text before relying on it.

  1. #1RecommendedCompliance Checklist⏰ Ongoing

    Applies to: Organizations applying the IEEE 7010 standard.

    “Deploy wellbeing metrics”
  2. #2RecommendedImplementation Framework⏰ Before assessment begins

    Applies to: Organizations applying the IEEE 7010 standard.

    “Metric selection”
  3. #3RecommendedImplementation Framework⏰ Before data collection begins

    Applies to: Organizations applying the IEEE 7010 standard.

    “Data collection methodology”
  4. #4RecommendedImplementation Framework⏰ Before data analysis

    Applies to: Organizations applying the IEEE 7010 standard.

    “Analysis framework”
  5. #5RecommendedImplementation Framework⏰ Before reporting

    Applies to: Organizations applying the IEEE 7010 standard.

    “Reporting requirements”
  6. #6RecommendedMonitoring and Evaluation⏰ Ongoing

    Applies to: Organizations applying the IEEE 7010 standard.

    “Ongoing measurement”
  7. #7RecommendedMonitoring and Evaluation⏰ Ongoing

    Applies to: Organizations applying the IEEE 7010 standard.

    “Trend analysis”

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