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Research on the collaborative driving mechanism of science and technology for social good based on evolutionary game
Ruan Rongbin, Zhu Zuping, Chen Wan
Science Research Management ›› 2026, Vol. 47 ›› Issue (6) : 88-100.
PDF(1711 KB)
PDF(1711 KB)
Research on the collaborative driving mechanism of science and technology for social good based on evolutionary game
As a key action to realize the benefits of science and technology, address major social issues, and empower vulnerable and special groups in society, driving science and technology for social good holds significant importance in responding to the demands of stakeholder groups and improving people’s well-being. This study constructed an evolutionary game model of consumers, enterprises and the government in collaborative driving science and technology for social good, analyzed the strategic choices of each game subject and the stability of the equilibrium point of the game system, and carried out the numerical simulation analysis by using Matlab 2024a, to investigate the evolutionary path of behavioral strategy of each subject in the context of changes of key parameters. As results shown, in the process of collaborative driving science and technology for social good, the final evolution of the three-party game subjects’ stable strategy is consumers’ participation in science and technology for social good, enterprises’ active implementation of science and technology for social good, and the government’s rigorous governance of science and technology for social good; different parameter values of the three-party subjects’ initial strategy selection probability, the government’s level of rewards and penalties, enterprises’ commercial and reputational gains, consumers’ gains, and the three-party subjects’ loss can significantly affect the behavioral strategy evolution. That is, the increase in the three-party subjects’ initial strategy selection probability, the reinforcement of the government’s level of rewards and penalties, the improvement of enterprises’ commercial and reputational gains, the enhancement of consumers’ gains, and the increase in the losses caused by the three-party subjects’ negative strategies all contribute to the evolutionary system reaching an ideal stable state. The study has enriched the exploration of mechanism for collaborative driving science and technology for social good and will provide theoretical and practical reference to the evolution of strategic choices of consumers, enterprises and the government in positive directions.
science and technology for social good / multi-agent / evolutionary game / numerical simulation
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人工智能的“多手问题”，越来越高的自主性和学习能力以及研发和应用中的“道德运气”因素共同造成了人工智能事故的道德责任归因难题。现有方案多少存在理论上的不足，也不能很好的用于实际问题的解决。而人工智能事故的统计结果和人工智能的研发机构组成表明，企业作为一股中坚力量，在加速推进人工智能技术的发展和产业落地方面贡献突出，但是也加剧了人工智能的伦理风险。无论是从学术的还是从现实的角度来看，人工智能相关企业都不应该被免除道德责任。另外，在相关法律和行业标准还没有及时更新和制定的阶段，软性的激励和惩戒手段将会在伦理规制层面发挥很好的补充和实践作用。因此，制定道德层面的具体规制措施会是引导企业积极承担道德责任的有效进路。
“The problem of many hands” of AI, increasing autonomy and learning ability, and “moral luck” in development and application of AI cause the moral responsibility dilemma of AI. The existing strategies are not perfect enough and can not be used to solve the practical problems well. The statistical results of AI accidents and the composition of AI research institutions show that enterprises play a very important role in accelerating the development of AI technology and industry landing, but also aggravate the ethical risks of AI. Therefore, from both an academic and a practical point of view, AI companies should not be exempt from moral responsibility. In addition, in the relevant laws and industry standards have not been updated or formulated in a timely manner, so soft incentives and punishment measures will play a complementary role in ethical regulation. To formulate specific regulatory measures on the moral level will be an effective way to guide enterprises to actively undertake moral responsibilities.
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In this study, we explored the capacity for two promising macrophytes, Typha domingensis and Typha elephantina, to be used for the surveillance of contamination by six metals, i.e., Cu, Fe, Mn, Ni, Pb, and Zn, in the mountainous area of Taif City in Saudi Arabia. Regression models were generated in order to forecast the metal concentrations within the plants’ organs, i.e., the leaves, flowers, peduncles, rhizomes, and roots. The sediment mean values for pH and the six metals varied amongst the sampling locations for the respective macrophytes, indicating that similar life forms fail to indicate equivalent concentrations. For instance, dissimilar concentrations of the metals under investigation were observed within the organs of the two rooted macrophytes. The research demonstrated that the segregation of metals is a regular event in all the investigated species in which the metal concentrations vary amongst the different plant constituent types. In the current study, T. domingensis and T. elephantina varied in their capacity to absorb specific metals; the bioaccumulation of metals was greater within T. domingensis. The relationships between the observed and model-estimated metal levels, in combination with high R2 and modest mean averaged errors, offered an appraisal of the goodness of fit of most of the generated models. The t-tests revealed no variations between the observed and model-estimated concentrations of the six metals under investigation within the organs of the two macrophytes, which emphasised the precision of the models. These models offer the ability to perform hazard appraisals within ecosystems and to determine the reference criteria for sediment metal concentration. Lastly, T. domingensis and T. elephantina exhibit the potential for bioaccumulation for the alleviation of contamination from metals.
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This study examines blockchain technologies and their pivotal role in the evolving Metaverse, shedding light on topics such as how to invest in cryptocurrency, the mechanics behind crypto mining, and strategies to effectively buy and trade cryptocurrencies. While it contextualises the common queries of \"why is crypto crashing?\" and \"why is crypto down?\", the research transcends beyond the frequent market fluctuations to unravel how cryptocurrencies fundamentally work and the step-by-step process on how to create a cryptocurrency. Contrasting existing literature, this comprehensive investigation encompasses both the economic and cybersecurity risks inherent in the blockchain and fintech spheres. Through an interdisciplinary approach, the research transitions from the fundamental principles of fintech investment strategies to the overarching implications of blockchain within the Metaverse. Alongside exploring machine learning potentials in financial sectors and risk assessment methodologies, the study critically assesses whether developed or developing nations are poised to reap greater benefits from these technologies. Moreover, it probes into both enduring and dubious crypto projects, drawing a distinct line between genuine blockchain applications and Ponzi-like schemes. The conclusion resolutely affirms the staying power of blockchain technologies, underlined by a profound exploration of their intrinsic value and a reflective commentary by the author on the potential risks confronting individual investors.
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