"How can A/IS creators influence A/IS goals to ensure well-being, and what can A/IS creators learn or borrow from existing models in the well-being and other arenas?
## BackgroundAnother way to incorporate considerations of well-being is to include well-being measuresin the development, goal setting, and trainingof the A/IS systems themselves.Identified metrics of well-being could be formulated as auxiliary objectives of the A/IS. As these auxiliary well-being objectives will be only a subset of the intended goals of the system, the architecture will need to balance multiple objectives. Each of these auxiliary objectives may be expressed as a goal, set of rules, set of values, or as a set of preferences, which can be weighted and combined using established methodologies from intelligent systems engineering.For example, an educational A/IS tool could not only optimize learning outcomes, but also incorporate measures of student social and emotional education, learning, and thriving.A/IS-related data relates both to the individual— through personalized algorithms, in conjunction with affective sensors measuring and influencing emotion, and other aspects of individual well-being —and to society as large data sets representing aggregate individual subjective and objective data. As the exchange of this data becomes more widely available via establishing tracking methodologies, the data can be aligned within A/IS products and services to increase human well-being. For example, robots like Pepper are equipped to share data regarding their usage and interaction with humans to the cloud. This allows almost instantaneous innovation, as once an action is validated as useful for one Pepper robot, all other Pepper units (and ostensibly their owners) benefit as well. As long as this data exchange happens with the predetermined consent of the robots’ owners, this innovation in real time model can be emulated for the large-scale aggregation of information relating to existing well-being metrics.A/IS creators can also help to operationalize well-being metrics by providing stakeholders with reports on the expected or actual outcomes of the A/IS and the values and objectives embedded in the systems. This transparency will help creators, users, and third parties assess the state of well-being produced by A/IS and make improvements in A/IS. In addition, A/IS creators should consider allowing end users to layer on their own preferences, such as allowing users to limit their use of an A/IS product if it leads to increased sustained stress levels, sustained isolation, development of unhealthy habits, or other decreases to well-being.Incorporating well-being goals and metrics into broader organizational values and processes would support the use of well-being metrics as there would be institutional support. A key factor in industrial, corporate, and societal progress is cross-dissemination of concepts and models from one industry or field to another. To date, a number of successful concepts and models exist in the fields of sustainability, economics, industrial design and manufacturing, architecture and urban development, and governmental policy. These concepts and models can provide a foundationfor building a metrics standard and the use of wellbeing metrics by A/IS creators, from conception and design to marketing, product updates, and improvements to the user experience.
## RecommendationCreate technical standards for representing goals, metrics, and evaluation guidelines for well-being metrics and their precursors and components within A/IS that include:
Ontologies for representing technological requirements.
A testing framework for validating adherence to well-being metrics and ethical principles such as [IEEE P7010™ Standards Project for Wellbeing Metric for Autonomous and Intelligent Systems](https://standards.ieee.org/project/
html).above as well as others as a basis for a wellbeing metrics standard for A/IS creators. (See page 191, Additional Resources: Additional Resources: Standards Development Models and Frameworks)
The development of a well-being metrics standard for A/IS that encompasses an understanding of well-being as holistic and interlinked to social, economic, and ecological systems.
## Further Resources
A.F.T Winfield, C. Blum, and W. Liu. “[Towards an Ethical Robot: Internal Models, Consequences and Ethical Action Selection](https://link.springer.com/chapter/
1007/978-3-319-10401-0_8),” in Advances in Autonomous Robotics Systems. Springer, 2014, pp. 85–96
R. A. Calvo, and D. Peters. Positive Computing: Technology for Well-Being and Human Potential._ _Cambridge MA: MIT Press,
Y. Collette, and P. Slarry. [Multiobjective Optimization: Principles and Case Studies ](https://link.springer.com/book/
1007%2F978-3-662-08883-8)(Decision Engineering Series). Berlin, Germany:Springer,
doi:
1007/978-3-662-08883-
J. Greene, et al. “Embedding Ethical Principles in Collective Decision Support Systems,” in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence_, _4147–
Palo Alto, CA: AAAI Press,
L. Li, I. Yevseyeva, V. Basto-Fernandes, H. Trautmann, N. Jing, and M. Emmerich,“Building and Using an Ontology of Preference-Based Multiobjective Evolutionary Algorithms.” In 9th International Conference on Evolutionary Multi-Criterion Optimization—Volume 10173 (EMO O. Schütze, M. Wiecek, Y. Jin, and C. Grimme, Eds., Vol.
Springer-Verlag, Berlin, Heidelberg, 406-421,
PositiveSocialImpact: Empowering people, organizations and planet with information and knowledge to make a positive impact to sustainable development,
D.K. Ura, Bhutan’s Gross National Happiness Policy Screening Tool."p.79-81