Challoumis, Constantinos (2025): Harnessing Sociological Insights For Equitable AI Development And Economic Policies.
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Abstract
The deployment of artificial intelligence (AI) plays an increasingly prominent role in the economy and society. With AI-enabled systems now constituting a powerful force in shaping economies and societies, their development necessitates policy interventions and transformations. This is particularly important as revenues from AI solutions grow exponentially and have begun to outpace the rate of investment in other digital technologies. At the same time, public considerations of AI development so far have gained limited traction in the strategy-setting of governments and firms. Addressing inequality and bias as part of AI development do not come standard, and alternative configurations of AI have myriad paths towards potential futures. Therefore, it is possible to intervene and contest ongoing pathways of development, contributing to more informed and ethical engagements with technologies and future realities.
Item Type: | MPRA Paper |
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Original Title: | Harnessing Sociological Insights For Equitable AI Development And Economic Policies |
Language: | English |
Keywords: | AI, economic policies |
Subjects: | Z - Other Special Topics > Z0 - General Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology Z - Other Special Topics > Z1 - Cultural Economics ; Economic Sociology ; Economic Anthropology > Z10 - General |
Item ID: | 123876 |
Depositing User: | constantinos challoumis |
Date Deposited: | 14 Mar 2025 08:03 |
Last Modified: | 14 Mar 2025 08:03 |
References: | Zajko, M. (2020). Conservative AI and social inequality: Conceptualizing alternatives to bias through social theory. S. Roberts, J. & N. Montoya, L. (2022). Contextualizing Artificially Intelligent Morality: A Meta-Ethnography of Top-Down, Bottom-Up, and Hybrid Models for Theoretical and Applied Ethics in Artificial Intelligence. Leavy, S., O'Sullivan, B., & Siapera, E. (2020). Data, Power and Bias in Artificial Intelligence. Floridi, L., Cowls, J., C. King, T., & Taddeo, M. (2020). How to Design AI for Social Good: Seven Essential Factors. ncbi.nlm.nih.gov Tena-Meza, S., Suzara, M., & Alvero, A. J. (2021). Coding with Purpose: Learning AI in Rural California. Hsu, Y. C., ‘Kenneth’ Huang, T. H., Verma, H., Mauri, A., Nourbakhsh, I., & Bozzon, A. (2022). Empowering local communities using artificial intelligence. ncbi.nlm.nih.gov Roche, C., J. Wall, P., & Lewis, D. (2022). Ethics and diversity in artificial intelligence policies, strategies and initiatives. ncbi.nlm.nih.gov |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/123876 |