The Complexities of AI for Social Good: An Explorative Study on Adversarial Machine Learning to Facilitate Deliberative Decision-Making in Elections.
The proliferation and pervasive use of artificial intelligence (AI) pose significant challenges to our democracies. In particular, AI leverages microtargeting political campaigns by constructing detailed user profiles and inferring people’s individual susceptibilities from their data. This capabilit...
| Publicado en: | Science & Engineering Ethics Vol. 32; no. 4; pp. 1 - 26 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Springer Nature
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=195755583&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 195755583 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 13533452 GNI jtl: Science & Engineering Ethics issn: 13533452 maglogo: N pubinfo: dt: Aug2026 vid: 32 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 195755583 10.1007/s11948-026-00598-9 ppf: 1 ppct: 25 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.8MB tig: atl: The Complexities of AI for Social Good: An Explorative Study on Adversarial Machine Learning to Facilitate Deliberative Decision-Making in Elections. aug: au: Auliya, Syafira Fitri Kudina, Olya Ding, Aaron Yi Van de Poel, Ibo affil: https://ror.org/02e2c7k09 Section Ethics and Philosophy of Technology, Department of Values, Technology, and Innovation, Faculty of Technology, Policy, and Management, TU Delft, Jaffalaan 5, 2628 BX, Delft, The Netherlands https://ror.org/02e2c7k09 Department of Engineering Systems and Services, Faculty of Technology, Policy, and Management, TU Delft, Jaffalaan 5, 2628 BX, Delft, The Netherlands sug: keyword: Adversarial machine learning Artificial intelligence Deliberative decision-making Elections Micro-targeting political campaigns Privacy Studies in Human Society Political Science ab: The proliferation and pervasive use of artificial intelligence (AI) pose significant challenges to our democracies. In particular, AI leverages microtargeting political campaigns by constructing detailed user profiles and inferring people’s individual susceptibilities from their data. This capability enables highly targeted political messaging that can substantially influence voting decisions, potentially undermining citizens’ ability to make deliberative decisions in elections. While existing research has proposed interventions to mitigate the negative impacts of political micro-targeting, many of these interventions may become less effective as AI continually yields more powerful and subliminal forms of micro-targeting. Assuming that technologies can play a role in mitigating these negative impacts of AI, we conducted an explorative study to identify the design principles of technological tools that could facilitate citizens’ deliberative decision-making in elections in the continuously levelaged AI-based political campaigns. Using Indonesia’s 2024 elections as a case study, we interviewed twenty citizens and four political actors to gain critical insights into how such technologies might be developed. Initially, we anticipated that privacy-enhancing AI, used to counterattack profiling AI used by political actors, might suffice to facilitate election deliberation. However, our findings reveal a more complex reality: addressing societal issues through technology is inherently challenging; no single solution can serve as a silver bullet. Instead, facilitating election deliberation requires integrating privacy with other conditions, including self-reflection, education, access to diverse information, critical thinking, and openness to others. These design principles might serve as concrete, actionable design principles to guide the development of technologies to enhance election deliberation. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Science & Engineering Ethics is a copyright of Springer, 2026. All Rights Reserved. item: Science & Engineering Ethics holder: Springer Nature dt: @attributes: year: 2026 holdings: @attributes: islocal: N |
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