AI-based component management system for structured content creation, annotation, and publication

Abstract: The ever-mutable regulations and laws, over-information, and the exponential change of digital technologies require large complex entities, companies, and public administrations to continually adapt their production and information processes. Indeed, they increasingly need to update and to inform employees and users in an immediate, efficient, and timely manner (Bostrom 2006; Harari 2018; Yaneer Bar-Yam 2004). To this end, following the principles of human centered design (Norman and Draper 1986), authors should decline information according to the user profile and create different versions of the same content.However, content management systems (CMS) that support the vast majority of large complex websites (Barker 2016), flatten text (often in multiple languages), regulations, images, videos and quantitative variables (dates, numerical parameters, geographic location) in a linear document. The content is managed in a digital format that loses all structure, prevents reuse, and takes no advantage of the originally modular nature of the information. This causes an uncontrollable growth of touch points to be maintained and updated, and a fragmentation of information sources inevitably doomed to abandonment and inconsistency.Challenges grow exponentially with the organization scale and with information complexity: using CMS and traditional web tools only, the most likely result is a corpus so intricate, specialized and self-contradictory as to be not only ineffective, but even harmful (Vian 2020). This catastrophic and widespread state is caused by the degree of information complexity, which has vastly exceeded the capability of traditional CMSs.In this paper we describe the regulatory, technological and economic requirements and the system of software, organizational and cultural solutions that emerged at the University of Genoa (UniGe) as a result of the successful development of a content service platform (CSP), powered by intelligent tools and aimed at addressing the aforementioned issues.We have designed and deployed a CSP that leverages the granularity of information to transform it into structured and reusable data following a single-sourcing and component content management paradigm (Andersen and Batova 2015). The CSP manages and annotates multimedia content, translates text, and catalogues images and videos based on their semantic content using state-of-the-art machine learning methods. The integration of human processes and intelligent tools facilitates the decoupling of information and technology choices, and triggers a content structuring process that better serves current user’s needs and prepares UniGe knowledge base for future advances in the semantic web (Berners-Lee, Hendler, and Lassila 2001).The system we present is part of the UniGe CSP and is being used to publish notices, news and events on about 200 websites about education and research, including the main website. In particular the CSP: manages and publishes structured and granular content for multiple channels, user profiles and devices is integrated with services from the Google Cloud AI ecosystem for image recognition and automatic text translation features a user-friendly graphical interface that simplifies the editorial process is provided with digital rights tools, to assign different roles within the editorial staff and to enable editors on specific profiles or touchpoints serves all output data in machine readable formats for reuse in other applications.In spite of strong internal resistance, the institution was highly committed to the success of the project, which span almost seven years and called for the involvement of about 20 full-time equivalents of an interdisciplinary, dedicated and highly skilled team. The adoption of the system in UniGe involved the entire course of business processes, entailed profound technological and cultural transformations and received strong appreciation and support. On one hand, its advent has highlighted the pressing needs for digital transformation in a typical large Italian public organization, and the excellent and tangible results obtained with a strategy relying on the integration of human processes and intelligent systems. On the other hand, the fragile political conditions necessary for such integration signal that the collective acceptance and cultural transformation required by digital technology is at least as important as the technological framework.Our findings strongly support hybrid systems, where intelligent methods sustain, enhance and complement the capabilities of humans, giving them control over the process and its final outcome and a clear picture of the benefits achieved. In this intermediate phase of building a hybrid human-AI, human acceptance is indeed a necessary condition for the success of digital transformation processes (Chen et al. 2020).

Keywords: Component Content Management, Complexity Management, Ux Design, Single-Sourcing Authoring, Artificial Intelligence, Machine Learning

DOI: 10.54941/ahfe1001009

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