ASSESS (What organizational values are leveraged for the responsible AI metrics?)

The paper emphasizes that Responsible AI metrics should begin with the satisfaction and well-being of employees. This includes assessing what wellness or well-being means to employees and how they can incentivize triple-bottom-line behavior going forward by prioritizing people and the planet before profit. It is also important to ensure that well-being initiatives are tied back to organizational values and principles. 

Another important aspect of ASSESS is defining the well-being metrics of Responsible AI. Among many existing metrics, some recommended well-being metrics to follow include the UN SDGs which contain a holistic application that provides perspective for how paradigm changes can be made, and the metrics from the World Economic Forum’s International Council (IBC) that provide a basis for Responsible AI design to help organizations assess their preparedness in the overall well-being metrics spaces. The importance of using these tools is to guarantee people and the planet are being served by our finances and not another way around. 

APPLY (How does an organization implement the principles and metrics of responsible AI?)

Risk management represents a significant avenue and obligation within the realm of Responsible AI. Consequently, addressing the unintentional outcomes of AI  remains a nascent industry. The report provided several suggestions for putting the principles and metrics of Responsible AI into practice. These recommendations include starting with one’s individual role, utilizing AI to assist in accomplishing objectives by incorporating Sustainable Development Goals (SDGs) in product/service design and aligning Responsible AI metrics with established reporting frameworks and key performance indicators (KPIs).

AMPLIFY (How does an organization scale responsible AI to company culture and widespread practices?)

A critical aspect of amplifying Responsible AI efforts involves a concentrated focus on examining elements that have a significant impact on employees, partners, or customers but are currently not adequately and meaningfully measured. Similar to other ethical AI practices, the effectiveness of well-being metrics is most pronounced when they are carefully considered during the initial design phase. The report highlighted some recommendations for organizations to scale the success of responsible AI and Well-Being metrics. These recommendations include adjusting governance to fit the size of the company’s operations and audience whether that is a start-up, larger enterprise, or non-profit, leveraging existing roles to operationalize well-being by design,  leveraging agile marketing for sustainability, and using ethical conformity assessment and the AI Ethics maturity model to leverage UN SDGs and ESGs for sustainability. 

FARI’s co-director, Carl Morch contributed to the great work of IEEE and its working group led by Adam Cutler, Milena Pribic and thanks John Havens for including FARI. The research report also provides the Well-Being Metrics Readiness Framework using well-being by design approach as a new standard for responsible innovation.

About IEEE SA

IEEE SA is a leading consensus-building organization that nurtures, develops, and advances global technologies. Providing a neutral and open platform to empower innovators across borders and disciplines, IEEE SA facilitates standards development and standards-related solutions, such as technology incubation, alliance consortia formation, open source, etc. 

Committee Members of the Research Report

Chairs:

• Adam Cutler • Milena Pribic

Committee Members:

• Uthman Ali • Kathy Baxter • Richard Benjamins • Flavio S. Correa da Silva.
• Olivia Gambelin • Ilana Golbin • John C. Havens
• Kashyap Kompella • Carl-Maria Mörch • Clara Neppel • Alice Thwaite