Digitally Assisted Collective Governance of Smart City Commons - ARTIO

智慧城市共享的数字辅助集体治理 - ARTIO

• 批准号: MR/W009560/1
• 负责人: Evangelos Pournaras
• 金额: $ 180.71万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FW009560%2F1
• 关键词: Digitally; Assisted; Collective; Governance; Smart

The aim of this fellowship programme is to design a socially responsible collective governance for Smart City commons: shared pool of urban resources (transport, parking space, energy) managed and regulated digitally. Smart City commons exhibit unprecedented complexity and uncertainties: transport systems integrate electric, shared and autonomous vehicles, while distributed energy resources highly penetrate energy systems. How can we manage Smart City commons in a sustainable and socially responsible way to tackle long-standing problems such as traffic jams, overcrowded parking spaces or blackouts? Failing to digitally coordinate collective decisions promptly and at large-scale has tremendous economic, social and environmental impact. Coordinated decisions require a digital (r)evolution, a new paradigm on where we decide, how we decide and what we decide.But which are limiting factors? 1.Online decision-making often disconnects citizens from the physical urban space for which decisions are made: choices are less informed and vulnerable to social media misinformation, while decision outcomes may show lower legitimation. What if collective choices could be made more locally as digital geolocated testimonies, creating opportunities for community interactions and deliberation? 2.Voting system design is another origin of poor collective decisions, with majority voting often failing to achieve consensus or fair and legitimate outcomes. What if we expanded the design space of voting systems with alternative voting methods, e.g. preferential, to encompass social values? While such methods have so far been costly and limited to low-cognitive exercises, negating their social value over majority voting, decision-support systems based on artificial intelligence (AI) emerge as game-changer. 3.With an immense computational and communication complexity, large-scale coordination of inter-dependent collective decisions remains a timely grand challenge. What if coordination could be digitally assisted and emerge as a result of smart aggregate information exchange, achieving privacy and efficiency?To address these challenges, I will combine Internet of Things, human-centred AI and blockchain technology with social choice theory and mechanism design. Using IoT devices, urban points of interest can be turned into digital voting centres within which conditions for a more informed decision-making will be verified in the blockchain, e.g. proving citizens' location. A novel ontology of voting features will provide the basis to predict voting methods that generate fair and legitimate outcomes. Using collective and active reinforcement learning techniques on the blockchain, human and machine collective intelligence will be combined to achieve a trustworthy coordination of collective decisions at large scale.In collaboration with high-profile partners from government/industry, I will demonstrate the applicability of these approaches via 4 innovative impact cases. 1.Using the developed solutions, citizens will geolocate problems and vote for transport planning solutions. 2.They will also vote on spot to implement participatory budgeting projects. 3.A smart parking system will be enhanced with load-balancing capabilities to alleviate crowded and polluted city centres. 4.Via citizens' coordination of transport modality, an urban traffic control system will be optimized for an equitable shift to public/sharing transport, while preserving low-carbon transport zones.These Smart City blueprints will open up new avenues for deeper understanding of digitally assisted collective governance. To master this inter-disciplinary research area and develop myself into a future leader, I will visit world-class leaders and, together with my team, enrol in novel training activities. Two esteemed mentors and an advisory board will further support me. I will engage with the broader community of citizens and policy-makers by organizing workshops and hackathons.

该奖学金计划的目的是为智慧城市共同体设计一个对社会负责的集体治理：数字化管理和监管的城市资源（交通，停车位，能源）共享池。智慧城市公共空间呈现出前所未有的复杂性和不确定性：交通系统集成了电动、共享和自动驾驶汽车，而分布式能源高度渗透到能源系统中。我们如何以可持续和对社会负责的方式管理智慧城市公共空间，以解决交通拥堵、停车位拥挤或停电等长期存在的问题？如果不能迅速、大规模地对集体决策进行数字化协调，将对经济、社会和环境产生巨大影响。协调决策需要数字化（r）进化，需要一种关于我们在哪里决定、如何决定以及决定什么的新范式。但哪些是限制因素？1.在线决策往往使公民与决策所针对的城市物理空间脱节：选择不那么知情，容易受到社交媒体错误信息的影响，而决策结果可能显示出较低的合法性。如果集体选择可以更本地化地作为数字地理定位的证词，为社区互动和审议创造机会呢？2.投票制度设计是糟糕的集体决策的另一个根源，多数投票往往无法达成共识或公平合法的结果。如果我们扩大投票系统的设计空间，采用其他投票方法，例如优先投票，以涵盖社会价值？虽然到目前为止，这些方法成本高昂，且仅限于低认知练习，否定了其相对于多数投票的社会价值，但基于人工智能（AI）的决策支持系统成为游戏规则改变者。3.由于巨大的计算和通信复杂性，相互依赖的集体决策的大规模协调仍然是一个及时的重大挑战。如果协调可以通过数字化方式辅助，并通过智能聚合信息交换而出现，从而实现隐私和效率，那会怎么样？为了应对这些挑战，我将把联合收割机物联网、以人为中心的AI和区块链技术与社会选择理论和机制设计相结合。使用物联网设备，城市的兴趣点可以变成数字投票中心，在那里，更明智的决策的条件将在区块链中得到验证，例如证明公民的位置。一种新的投票特征本体将为预测产生公平和合法结果的投票方法提供基础。在区块链上使用集体和主动强化学习技术，将人类和机器的集体智慧结合起来，实现大规模集体决策的可靠协调。我将与来自政府/行业的知名合作伙伴合作，通过4个创新影响案例来展示这些方法的适用性。1.使用开发的解决方案，公民将地理定位问题和交通规划解决方案投票。2.他们还将现场投票实施参与式预算项目。3.智能停车系统将增强负载平衡能力，以缓解拥挤和污染的市中心。4.通过市民对交通方式的协调，城市交通控制系统将得到优化，以公平地转向公共/共享交通，同时保留低碳交通区。这些智慧城市蓝图将为深入理解数字辅助集体治理开辟新的途径。为了掌握这一跨学科的研究领域，并将自己发展成为未来的领导者，我将拜访世界级的领导者，并与我的团队一起参加新颖的培训活动。两位受人尊敬的导师和一个咨询委员会将进一步支持我。我将通过组织研讨会和黑客马拉松，与更广泛的公民和政策制定者社区接触。

项目成果

SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation

• DOI: 10.1109/acsos-c58168.2023.00021
• 发表时间: 2023-07
• 期刊: 2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)
• 作者: Zeinab Nezami;Evangelos Pournaras;Amir Borzouie;Jie Xu

Collective privacy recovery: Data-sharing coordination via decentralized artificial intelligence

• DOI: 10.1093/pnasnexus/pgae029
• 发表时间: 2023-01
• 期刊: PNAS Nexus
• 作者: Evangelos Pournaras;M. Ballandies;S. Bennati;Chien-fei Chen

Collective Learning for Energy-centric Flexible Job Shop Scheduling

• DOI: 10.1109/isie51358.2023.10228029
• 发表时间: 2023-06
• 期刊: 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE)
• 作者: A. Narayanan;Evangelos Pournaras;P. Nardelli

Machine Learning, Optimization, and Data Science - 9th International Conference, LOD 2023, Grasmere, UK, September 22-26, 2023, Revised Selected Papers, Part I

机器学习、优化和数据科学 - 第九届国际会议，LOD 2023，英国格拉斯米尔，2023 年 9 月 22-26 日，修订后的选定论文，第一部分

• DOI: 10.1007/978-3-031-53969-5_1
• 发表时间: 2024
• 作者: Majumdar S

Democracy by Design: Perspectives for Digitally Assisted, Participatory Upgrades of Society

• DOI: 10.1016/j.jocs.2023.102061
• 发表时间: 2023-05-19
• 期刊: JOURNAL OF COMPUTATIONAL SCIENCE
• 影响因子: 3.3
• 作者: Helbing，Dirk;Mahajan，Sachit;Pournaras，Evangelos
• 通讯作者: Pournaras，Evangelos