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    • P7010/D1, Jun 2019 - UNAPPROVED DRAFT
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Full Description

Scope

This standard establishes wellbeing metrics relating to human factors directly affected by intelligent and autonomous systems and establishes a baseline for the types of objective and subjective data these systems should analyze and include (in their programming and functioning) to proactively increase human wellbeing.

Purpose

The Wellbeing Metrics Standard for Ethical Artificial Intelligence and Autonomous Systems enables programmers, engineers, and technologists to better consider how the products and services they create can increase human wellbeing based on a wider spectrum of measures than growth and productivity alone. Today, affective systems utilizing emotion recognizing sensors are quantified primarily by their economic value in the marketplace beyond their efficacy within certain fields (psychology, etc). While it is often understood that ethical considerations for intelligent and autonomous systems might hinder innovation by the introduction of unwanted regulation, without metrics that value mental and emotional health at both an individual and societal level, innovation is impossible to quantify. The introduction and use of these metrics for programmers and technologists means that beyond economic increase human wellbeing can be measured and better improved.

Abstract

New IEEE Standard - Active - Draft. IEEE Project 7010 Well-being Metrics for Autonomous and intelligent Systems is a standard for measuring the impact of artificial intelligence or autonomous and intelligent systems (A/IS) on humans. The overall intent of IEEE P7010 is to supports the outcome of A/IS having positive impacts on human well-being. It is the tenth of a series of standards in the P70xx series, all of which emerged from the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. The standard is grounded in scientifically valid well-being indices currently in use and based on a stakeholder engagement process. The intent of the standard is to guide product development, identify areas for improvement, manage risks, assess performance and identify intended and unintended users, uses and impacts on human well-being of A/IS products, services, and systems.