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P25 Dystopia or utopia? Artificial Intelligence in and for Social Innovation

P25 Dystopia or utopia? Artificial Intelligence in and for Social Innovation

Panel Chairs

Corresponding Chair and Review Group Chair:

Yanto CHANDRA –– City University of Hong Kong, Hong Kong; ychandra@cityu.edu.hk

Panel Co-Chairs:

Mila Gasco HERNANDEZ –– University at Albany, SUNY, New York

Simon TEASDALE –– Queen’s University Belfast

Echo Liang SHANG –– The Education University of Hong Kong

Shirley Qian JIN –– Utrecht University

Description

Artificial intelligence (AI) is the vocabulary of the year. Starting from Turing’s idea of machines that can think, to the first time “AI” was coined by John McCarthy in the 1950s, the first chatbot developed at MIT by Joseph Weizenbaum in the mid-1960s, to the launch of ChatGPT in late 2022, AI has come a long way. AI is not only about large language models (e.g., ChatGPT that can spit out texts after being prompted) but encompasses other systems that can be taught and learn to mimic and even surpass human capabilities –– from robots, face recognition, image classifiers, to self-driving vehicles.

But the sentiment toward AI has been rather negative in recent years with many experts fearing a dystopia where AI becomes smarter than humans and takes over jobs and replaces humans. Some even propose a moratorium that would stop AI from being developed. Others take a more positive stance believing that AI will become our friends and help us do work more efficiently after learning from how auto pilot is used in jetliners to self-driving cars that can let us enjoy the ride without worrying about driving. This augmentation-vs-automation debate (Raisch & Krakowski, 2021) will prevail until we see more instances of what AI is and what it means to humans.

The field of social innovation – where public value, social value and commercial value are combined by a single organization or entity (Ayob et al., 2016; Calo et al., 2024; Chandra & Paras, 2021; Teasdale et al., 2021) – is the best area to start discussing what AI can be. The phrase can be or might be – following Herbert Simon’s Science of the Artificial (Simon, 2019) – refers to a way of reimagining our futures through AI. Things around us, from air conditioners, cars to streets, are products of imagination by its designers. As scholars, we can reimagine what social innovation as a concept means, how it is practiced, and how it could be studied, in light of the affordances by AI.

At the intersection between social innovation and the field of public administration, there have been debates on the potential disruptive impact of AI on the labor market, industries and services and calls for “new governing mechanisms” for an inclusive AI for social good, for example, via the lens of participatory governance (Moon, 2023). There are also discussions on public value creation through AI adoption in which the adoption creates “value tensions” (e.g., nudging vs autonomy, data accessibility vs security and privacy, predictive accuracy vs discrimination and biases) (Madan & Ashok, 2023). Such tensions are likely to persist in hybrid organizations and social innovation projects that embrace AI.

Perhaps one of the most critical implications is how AI would alter co-design and co-production of goods and services (Osborne & Nasi, 2024). This applies to not only public services (Mergel et al., 2024) but also social services, social welfare projects, and organizations that aim to co-create value with its users including social enterprises and community organizations.

Consider the recent examples where robots have been used by social enterprises to enable disabled individuals to work from their home, to operate the robots in restaurants taking order, delivering to tables, and even having a chat with curious customers. This is a small example where social innovators turn AI into a solution to society’s pressing problems. We can replace the disabled in the AI story above with refugees, stigmatized individuals (e.g., ex sex workers, drug addicts, prisoners) who need a job but facing barriers to work.

Other examples include how AI could be used to help farmers in poor countries to understand weather patterns and better manage their livestock and produce better yields with precise water control. AI could also help social innovators, non-profits, and volunteers to better engage with donors and write better grant submissions.

Our premise is that when placed in the right hands and with the right intention, AI can become a resource that would have been unthinkable in the past.

Overall, social innovation is well placed to imagine the future of AI. Accordingly, we ask: What is the Future of Social Innovation Scholarship and Practice in the Age of AI?

We call the above phenomenon “Social AI”, to distinguish it from other terms for AI such as legal AI, narrow AI, reactive AI, self-aware AI, to general AI. The term “social” in social AI refers to how AI is deployed to create value that benefits society and the public.

This panel addresses the dearth of research on how, why and the extent to which AI could be used by social innovators in private, non-profit and public organizations to create either public, social and commercial value or a combination of these values. This presents an opportunity for AI x social innovation conversations at important journals as well as scholarly conversations in public management and administration and beyond.

Abstracts

We invite the submission of 500-word abstracts that center around the theme of Artificial Intelligence in and for Social Innovation. We encourage contributions that leverage a diverse array of disciplines, methods, theoretical perspectives, and data to reimagine what might be possible in the new world where social innovation, as a field and practice, is shaped by artificial intelligence.

We are open to submissions that are conceptual, review, empirical, and methodological in this area together for a fruitful discussion.

Possible topics and questions can include but are not limited to the following:

Why and how can AI be used to create public and social value that create “greater benefits” for society beyond the innovators.
Antecedents of adoption of Social AI (or its barriers) by organizations, governments and communities
Mechanisms of success and failure of social innovation projects that implement AI
The outcomes of Social AI implementation (e.g., toward beneficiaries and stakeholders, funders/donors, innovators, etc.)
New theories or perspectives for social innovation in the era of AI (e.g., co-creation/co-production, Osborne & Nasi, 2024; participatory governance, Moon, 2023; value tensions, Madan & Ashok, 2023; uncertainty, Ramoglou et al, 2024)
Methodological development in studying social innovation using AI (e.g., Bert transformers, fine tuning, customized language models, machine vision, etc.)
How work for disadvantaged/marginalized groups can be redesigned in the age of Social AI.
Policies to nurture Social AI particularly in relation to accountability (who is responsible for malfunctions or errors), fairness, justice, trustworthiness.
Ethical debates in the use of AI in and for social innovation.

Format for Abstracts

Authors should follow the standard instructions provided by the IRSPM Conference guidelines for submitting their abstracts.

References

Ayob, N., Teasdale, S., & Fagan, K. (2016). How social innovation ‘came to be’: Tracing the evolution of a contested concept. Journal of Social Policy, 45(4), 635-653.

Calò, F., Scognamiglio, F., Bellazzecca, E., & Ongaro, E. (2024). Social innovation during turbulent times: a systematic literature review and research agenda. Public Management Review, 26(6), 1706-1730.

Chandra, Y., & Paras, A. (2021). Social entrepreneurship in the context of disaster recovery: Organizing for public value creation. Public Management Review, 23(12), 1856-1877.

Chandra, Y., Shang, L. (2024). Finetuning Artificial Intelligence for Entrepreneurial Pitching Effectiveness. 64th Academy of Management 2024 Best Paper Proceedings, Chicago, USA.

Foroudi, P., Akarsu, T. N., Marvi, R., & Balakrishnan, J. (2021). Intellectual evolution of social innovation: A bibliometric analysis and avenues for future research trends. Industrial Marketing Management, 93, 446-465.

Madan, R., & Ashok, M. (2023). AI adoption and diffusion in public administration: A systematic literature review and future research agenda. Government Information Quarterly, 40(1), 101774.

Mergel, I., Dickinson, H., Stenvall, J., & Gasco, M. (2024). Implementing AI in the public sector. Public Management Review, (in press)

Moon, M. J. (2023). Searching for inclusive artificial intelligence for social good: Participatory governance and policy recommendations for making AI more inclusive and benign for society. Public Administration Review, 83(6), 1496-1505.

Osborne, S., & Nasi, G. (2024). Debate: The future of artificial intelligence for the co-design and co-production of public services—what do we know and what do we need to know? Public Money & Management, 1-3 (in press).

Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192-210.

Ramoglou, S., Schaefer, R., Chandra, Y., & McMullen, J. S. (2024). Artificial Intelligence Forces us to Rethink Knightian Uncertainty: A Commentary on Townsend et al.’s “Are the Futures Computable?”. Academy of Management Review, (in press).

Simon, H. A. (2019). The Sciences of the Artificial, reissue of the third edition with a new introduction by John Laird, MIT press.

Teasdale, S., Roy, M. J., & Hulgård, L. (2021). Power and conflict in social innovation: a field-based perspective. In A research agenda for social innovation (pp. 169-186). Edward Elgar Publishing.