论文标题

关于人工智能和分布式分类帐技术的融合:范围审查和未来的研究议程

On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda

论文作者

Pandl, Konstantin D., Thiebes, Scott, Schmidt-Kraepelin, Manuel, Sunyaev, Ali

论文摘要

目前,人工智能(AI)和分布式分类帐技术(DLT)的发展导致了学术界和实践的生动辩论。 AI处理数据以执行以前认为仅适用于人类的任务。 DLT有可能在不确定环境中的一组参与者之间建立共识。在最近的研究中,这两种技术都用于相似甚至相同的系统中。示例包括设计安全的分布式分类帐或创建分布在多个节点的盟军学习系统。这可能导致技术融合,过去,这为信息技术的主要创新铺平了道路。先前的工作强调了AI和DLT收敛的几个潜在好处,但仅提供了一个有限的理论框架来描述这两种技术的即将到来的现实世界集成案例。我们的目标是通过对先前工作进行系统的文献综述并提供严格衍生的未来研究机会来做出贡献。这项工作可以帮助活跃于AI或DLT的研究人员克服其领域中的当前局限性,从业者开发系统以及两种技术的融合。

Developments in Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans. DLT has the potential to create consensus over data among a group of participants in uncertain environments. In recent research, both technologies are used in similar and even the same systems. Examples include the design of secure distributed ledgers or the creation of allied learning systems distributed across multiple nodes. This can lead to technological convergence, which in the past, has paved the way for major innovations in information technology. Previous work highlights several potential benefits of the convergence of AI and DLT but only provides a limited theoretical framework to describe upcoming real-world integration cases of both technologies. We aim to contribute by conducting a systematic literature review on previous work and providing rigorously derived future research opportunities. This work helps researchers active in AI or DLT to overcome current limitations in their field, and practitioners to develop systems along with the convergence of both technologies.

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