Abstract:This essay draws from game design to improve the prospects of democratic deliberation during government consultation with the public. The argument begins by reviewing the problem of low-quality deliberation in contemporary discourse, then explains how games can motivate participants to engage in demanding behaviors, such as deliberation. Key design features include: the origin, governance, and oversight of the game; the networked small groups at the center of the game; the objectives of these groups; the purpo… Show more
“…Finally, another study presented a visual analytics technique for interactive data labeling that applies gamification and explainable AI concepts to support complex classification tasks [46]. Several studies by Chen (2020) [44][45][46] utilized elements of "gamification for a specific purpose", albeit with completely different topics and objectives than our study.…”
Section: Gamification and Artificial Intelligencementioning
confidence: 96%
“…Another study argued that games can enhance the possibilities for democratic deliberation during government consultation with the public. Key design features developed in this context include game origin, management, and oversight; networked small groups at the center of the project; and artificial intelligence and automated metrics to measure deliberation [45]. Finally, another study presented a visual analytics technique for interactive data labeling that applies gamification and explainable AI concepts to support complex classification tasks [46].…”
Section: Gamification and Artificial Intelligencementioning
AI fairness is an essential topic as regards its topical and social-societal implications. However, there are many challenges posed by automating AI fairness. Based on the challenges around automating fairness in texts, our study aims to create a new fairness testing paradigm that can gather disparate proposals on fairness on a single platform, test them, and develop the most effective method, thereby contributing to the general orientation on fairness. To ensure and sustain mass participation in solving the fairness problem, gamification elements are used to mobilize individuals’ motivation. In this framework, gamification in the design allows participants to see their progress and compare it with other players. It uses extrinsic motivation elements, i.e., rewarding participants by publicizing their achievements to the masses. The validity of the design is demonstrated through the example scenario. Our design represents a platform for the development of practices on fairness and can be instrumental in making contributions to this issue sustainable. We plan to further realize a plot application of this structure designed with the gamification method in future studies.
“…Finally, another study presented a visual analytics technique for interactive data labeling that applies gamification and explainable AI concepts to support complex classification tasks [46]. Several studies by Chen (2020) [44][45][46] utilized elements of "gamification for a specific purpose", albeit with completely different topics and objectives than our study.…”
Section: Gamification and Artificial Intelligencementioning
confidence: 96%
“…Another study argued that games can enhance the possibilities for democratic deliberation during government consultation with the public. Key design features developed in this context include game origin, management, and oversight; networked small groups at the center of the project; and artificial intelligence and automated metrics to measure deliberation [45]. Finally, another study presented a visual analytics technique for interactive data labeling that applies gamification and explainable AI concepts to support complex classification tasks [46].…”
Section: Gamification and Artificial Intelligencementioning
AI fairness is an essential topic as regards its topical and social-societal implications. However, there are many challenges posed by automating AI fairness. Based on the challenges around automating fairness in texts, our study aims to create a new fairness testing paradigm that can gather disparate proposals on fairness on a single platform, test them, and develop the most effective method, thereby contributing to the general orientation on fairness. To ensure and sustain mass participation in solving the fairness problem, gamification elements are used to mobilize individuals’ motivation. In this framework, gamification in the design allows participants to see their progress and compare it with other players. It uses extrinsic motivation elements, i.e., rewarding participants by publicizing their achievements to the masses. The validity of the design is demonstrated through the example scenario. Our design represents a platform for the development of practices on fairness and can be instrumental in making contributions to this issue sustainable. We plan to further realize a plot application of this structure designed with the gamification method in future studies.
“…Most studies in this cluster focus on data analysis from eConsultation platforms [43,46,47]. Additionally, exploration into game design principles to enhance eConsultation initiatives [55] and optimize AI utilization in governance through eConsultation platform data [45] is noted.…”
Section: Eparticipation Actorsmentioning
confidence: 99%
“…Studies related to the "Deliberative" effect: Eleven articles explore various techniques and technologies to enhance participation quality, ranging from chatbots for organizing arguments [77] to applications facilitating ePetition drafting [61] and virtual reality approaches [71]. Additionally, analyses of online consultation platform designs concerning discussion quality principles are included in the literature [41,79], while there is a study proposing an innovative platform based on game design principles [55]. Challenges encountered in online consultation initiatives aimed at fostering qualitative discussions for policy formulation are also documented [81].…”
Section: Eparticipation Effectsmentioning
confidence: 99%
“…Paper ID Deliberative [42,48,55,61,64,65,69,71,79,81,86] Democratic [41,44,50,54,65,81,85] Civic Engagement [41,44,47,[49][50][51][53][54][55]58,60,63,65,66,[68][69][70]74,76,[78][79][80][81][82][83]85,86]…”
Electronic Participation (eParticipation) enables citizens to engage in political and decision-making processes using information and communication technologies. As in many other fields, Artificial Intelligence (AI) has recently started to dictate some of the realities of eParticipation. As a result, an increasing number of studies are investigating the use of AI in eParticipation. The aim of this paper is to map current research on the use of AI in eParticipation. Following PRISMA methodology, the authors identified 235 relevant papers in Web of Science and Scopus and selected 46 studies for review. For analysis purposes, an analysis framework was constructed that combined eParticipation elements (namely actors, activities, effects, contextual factors, and evaluation) with AI elements (namely areas, algorithms, and algorithm evaluation). The results suggest that certain eParticipation actors and activities, as well as AI areas and algorithms, have attracted significant attention from researchers. However, many more remain largely unexplored. The findings can be of value to both academics looking for unexplored research fields and practitioners looking for empirical evidence on what works and what does not.
BACKGROUND
Public deliberation is a qualitative research method that has successfully been used to solicit lay people’s perspectives on health ethics topics, but questions remain as to whether this traditionally in-person method translates into the online context. The MindKind Study conducted public deliberation sessions to gauge the concerns and aspirations of young people in India, South Africa, and the United Kingdom in regard to a prospective mental health databank. This paper details our adaptations to and evaluation of the public deliberation method in the online context, especially in the presence of a digital divide.
OBJECTIVE
The purpose of this paper is to assess the quality of online public deliberation and share emerging learnings in a remote disseminated qualitative research context.
METHODS
We convened participants for 2 hours of structured deliberation over an online video conferencing platform. We provided participants with multimedia informational materials describing different ways to manage mental health data. We analyzed the quality of online public deliberation in variable resource settings on the basis of (1) equal participation, (2) respect for the opinions of others, (3) adoption of a societal perspective, and (4) reasoned justification of ideas. In order to assess the depth of comprehension of informational materials, we used qualitative data pertaining directly to the material provided.
RESULTS
The sessions were broadly of high quality, although some sessions suffered from unstable internet connection and resulting multimodal participation, complicating our ability to perform a quality assessment. English-speaking participants displayed a deep understanding of complex informational materials. We found that participants were particularly sensitive to linguistic and semiotic choices in informational materials. A more fundamental barrier to understanding was encountered by participants who utilized materials translated from English.
CONCLUSIONS
Although online public deliberation may produce similar quality outcomes to in-person public deliberation, researchers who utilize remote methods should plan for technological and linguistic barriers when working with a multinational population. Our recommendations to researchers include budgetary planning, logistical considerations, and ensuring participants’ psychological safety.
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