The intermingling between Artificial Intelligence and Community Well-being: a few perspectives on the possibilities

By Bogdana (Bobi) Rakova

There is a growing overarching challenge of overly simplifying complex dynamic social problems that threatens to reinforce certain misconceptions about their true nature. An interdisciplinary worldview helps us recognize the need for a multifaceted approach to understanding the complexity of interactions between Artificial Intelligence (AI) and community well-being. They are intangible and are often perceived in different ways depending on the context within which we are accessing them. Still, it is critical for us to engage in understanding them better and especially explore how they interact. This is the goal of the Springer publication Intersections of AI and Community Well-Being Special Issue for the International Journal of Community Well-Being [1].

“An interdisciplinary worldview helps us recognize the need for a multifaceted approach to understanding the complexity of interactions between Artificial Intelligence (AI) and community well-being.”

As the visual anthropologist, semiotician, and cyberneticist Gregory Bateson would say, some questions are not meant to be answered but they show us new perspectives about the relations between all involved actors [2]. In putting together this Special Issue, the editorial team seeks to help community organizers, academics, researchers, instructors, policy makers, AI practitioners, administrators, governmental and nongovernmental staff, and others, understand the interactions between AI and community well-being. The Special Issue aims to explore this space through the lens of three main focus areas:

the formation of a means of measuring and assessing the impacts of AI on community well-being,
the engagement of communities in the development, deployment and management of AI, and
the creation of AI that improves community well-being and safeguards communities from social, ecological, economic and other threats such as climate change, dismantling of democracy, destabilizing economic inequality, and decimation of natural resources.

Measurement Frameworks

The AI algorithms and prototypes built in academic settings are often very different from real world scenarios. In very practical terms, applying AI in the real world involves resolving many challenges which are often not in scope for AI research and experiments done in traditional academic settings. There’s a high value placed on measurement in Western society. People in any industry or business management setting often say that if you can't measure something, you can't improve it. However, in regards to AI, it is not often straightforward what exactly we are measuring, how and who is going to make the measurement, how measurements are used and who is accountable for mismeasurement. Moreover, Goodhart's law - “when a measure becomes a target, it ceases to be a good measure” - speaks to the unintended consequences of picking a measure which is trying to reduce a complex dynamic system into a metric. In regards to well-being, what could be metrics frameworks that allow practitioners to measure the impact of AI systems on community well-being? As a first step, they help to define the concept we aim to measure.

“In very practical terms, applying AI in the real world involves resolving many challenges which are often not in scope for AI research and experiments done in traditional academic settings.”

One could define well-being broadly as “people’s living conditions and quality of life today (current well-being), as well as the resources that will help to sustain people’s well-being over time (natural, economic, human and social capital)” [3]. Furthermore, AI could be defined broadly as ”autonomous or intelligent software when installed into other software or hardware systems that are able to exercise independent reasoning, decision-making, intention forming, and motivating skills according to self-defined principles” which is the definition used in the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems [4]. Several of the articles in the Special Issue speak to the challenges and opportunities for establishing community well-being metrics frameworks in the realms of recommender systems, social media news feeds, and other kinds of AI-enabled systems [5,6].

Community Engagement in AI Development

Sociotechnical and participatory action researchers have increasingly given attention to the field of fairness, accountability, and transparency of algorithmic systems, proposing methodological frameworks [7] and technical as well as community-based situated interventions [8, 9]. The contributors to the Special Issue go a long way in trying to understand and reimagine community engagement in AI systems especially in their design and development. Disentangling the perceived challenges experienced by specific communities such as Indigenous Peoples and informal caregivers, the authors seek to examine the ways in which AI is being developed and used currently and point to mechanism design and methodological insights that can bring about positive outcomes contributing to community inclusion, equity and data justice [10, 11, 12].

AI’s Role in the Protection of Community Well-Being

As our lives become more and more inextricably woven with technology, it is urgent for us to have a critical approach to how AI could be employed to protect and empower the flourishing of communities. A few of the contributors to the Special Issue embark on a journey to help the readers understand the neurophysiological experience of people in public urban spaces through the use of AI [6], while others investigate the role of AI in improving community well-being within current models of economic growth [13]. Finally, two Special Issue contributors also suggest biomimicry as a means for the development of AI drawn from art projects involving a type of fungus commonly known as slime mold (physarum polycephalum) [14].

“As our lives become more and more inextricably woven with technology, it is urgent for us to have a critical approach to how AI could be employed to protect and empower the flourishing of communities.”

In conclusion, these three focus areas are the subject of the fascinating contributions within the Springer publication Intersections of AI and Community Well-Being Special Issue for the International Journal of Community Well-Being. I hope these glimpses of what’s in the publication have inspired you to intermingle with these questions yourself. Furthermore, you can find an overview of all contributions in the introductory article for the Special Issues and reach out to me to learn more.

Bogdana (Bobi) Rakova

Bobi is the chief guest editor of the Springer publication Intersections of AI and Community Well-Being Special Issue for the International Journal of Community Well-Being. She is working on designing AI systems that empower participation and inclusion through governance frameworks for AI, AI impact assessments, and multi-stakeholder collaboration frameworks. Bobi is part of the Happiness Alliance NGO, the Responsible AI team at Accenture, as well as a research fellow at the Partnership on AI. In addition, Bobi gave a lightning talk at All Tech Is Human: San Francisco in September 2019 that you can watch here.

References:

[1] Special Issue International Journal of Community Well-being - https://www.springer.com/journal/42413

[2] Gregory Bateson. 2000. Steps to an ecology of mind: Collected essays in anthropology, psychiatry, evolution, and epistemology. University of Chicago Press.

[3] Organization for Economic Cooperation and Development (OECD) (2018). Going digital in a multilateral word. Paris: OECD Publishing. Retrieved September 30, 2020 from https://www.oecd.org/going-digital/C-MIN-2018-6-EN.pdf Accessed 3 Dec 2020.

[4] IEEE Standards Association. (2018). The IEEE global initiative on ethics of autonomous and intelligent systems. https://ethicsinaction.ieee.org/ Accessed 3 Dec 2020.

[5] Stray, J. (2020). Aligning AI Optimization to Community Well-Being. International Journal of Community Well-Being, 1-21. https://link.springer.com/article/10.1007/s42413-020-00086-3

[6] Ducao, A., Koen, I., Guo, Z., Frank, J., Willard, C., & Kam, J. (2020). Multimer: Modeling Neurophysiological Experience in Public Urban Space. International Journal of Community Well-Being, 1-26. https://link.springer.com/article/10.1007/s42413-020-00082-7

[7] Selbst, A. D.; Boyd, D.; Friedler, S. A.; Venkatasubramanian, S.; and Vertesi, J. 2019. Fairness and abstraction in sociotechnical systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency, 59–68. ACM.

[8] Zhang, A. X., Hugh, G., & Bernstein, M. S. (2020, October). PolicyKit: Building Governance in Online Communities. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology (pp. 365-378). https://arxiv.org/pdf/2008.04236.pdf

[9] Katell, M., Young, M., Dailey, D., Herman, B., Guetler, V., Tam, A., ... & Krafft, P. M. (2020, January). Toward situated interventions for algorithmic equity: lessons from the field. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (pp. 45-55). https://dl.acm.org/doi/abs/10.1145/3351095.3372874

[10] Ruster, L. P., & Brown, G. (2020). Termination for Cultural Misalignment: Setting up Contract Terms to Ensure Community Well-Being in the Development of AI. International Journal of Community Well-Being, 1-15. https://link.springer.com/article/10.1007/s42413-020-00081-8

[11] Pettini, A. (2020). Real-Time Assessment of the Burden on the Community of Informal Caregivers. A Pilot Study. International Journal of Community Well-Being, 1-15. https://link.springer.com/article/10.1007/s42413-020-00083-6

[12] Hollander, J. B., Potts, R., Hartt, M., & Situ, M. (2020). The Role of Artificial Intelligence in Community Planning. International Journal of Community Well-Being, 1-15. https://link.springer.com/article/10.1007/s42413-020-00090-7

[13] Narayan, R. (2020). Leveraging Digital Intelligence for Community Well-Being. International Journal of Community Well-Being, 1-20. https://link.springer.com/article/10.1007/s42413-020-00085-4

[14] Solomon, L. H., & Baio, C. (2020). An Argument for an Ecosystemic AI: Articulating Connections across Prehuman and Posthuman Intelligences. International Journal of Community Well-Being, 1-26. https://link.springer.com/article/10.1007/s42413-020-00092-5

All Tech Is Human .orgDecember 14, 2020Comment