A future‐oriented approach to the selection of artificial intelligence technologies for knowledge platforms
本文提出一种结合德尔菲调查与多准则分析的方法，用于为创新知识平台选择人工智能技术，以增强其创造力促进功能，并规划至2030年的发展路径。
Abstract This article presents approaches used to solve the problem of selecting AI technologies and tools to obtain the creativity fostering functionalities of an innovative knowledge platform. The aforementioned selection problem has been lagging behind other software‐specific aspects of online knowledge platform and learning platform development so far. We linked technological recommendations from group decision support exercises to the platform design aims and constraints using an expert Delphi survey and multicriteria analysis methods. The links between expected advantages of using selected AI building tools, AI‐related system functionalities, and their ongoing relevance until 2030 were assessed and used to optimize the learning scenarios and in planning the future development of the platform. The selected technologies allowed the platform management to implement the desired functionalities, thus harnessing the potential of open innovation platforms more effectively and delivering a model for the development of a relevant class of advanced open‐access knowledge provision systems. Additionally, our approach is an essential part of digital sustainability and AI‐alignment strategy for the aforementioned class of systems. The knowledge platform, which serves as a case study for our methodology has been developed within an EU Horizon 2020 research project.