Need for UAI–Anatomy of the Paradigm of Usable Artificial Intelligence for Domain-Specific AI Applicability

Research output: Contribution to journalResearch articleContributedpeer-review


Data-driven methods based on artificial intelligence (AI) are powerful yet flexible tools for gathering knowledge and automating complex tasks in many areas of science and practice. Despite the rapid development of the field, the existing potential of AI methods to solve recent industrial, corporate and social challenges has not yet been fully exploited. Research shows the insufficient practicality of AI in domain-specific contexts as one of the main application hurdles. Focusing on industrial demands, this publication introduces a new paradigm in terms of applicability of AI methods, called Usable AI (UAI). Aspects of easily accessible, domain-specific AI methods are derived, which address essential user-oriented AI services within the UAI paradigm: usability, suitability, integrability and interoperability. The relevance of UAI is clarified by describing challenges, hurdles and peculiarities of AI applications in the production area, whereby the following user roles have been abstracted: developers of cyber–physical production systems (CPPS), developers of processes and operators of processes. The analysis shows that target artifacts, motivation, knowledge horizon and challenges differ for the user roles. Therefore, UAI shall enable domain- and user-role-specific adaptation of affordances accompanied by adaptive support of vertical and horizontal integration across the domains and user roles.


Original languageEnglish
Article number27
Number of pages23
JournalMultimodal Technologies and Interaction
Issue number3
Publication statusPublished - Mar 2023

External IDs

WOS 000959501700001
ORCID /0000-0001-7540-4235/work/142240021


Research priority areas of TU Dresden

Subject groups, research areas, subject areas according to Destatis


  • applicable AI, artificial intelligence, cyber–physical production systems, domain-specific AI, explainable AI, human–computer interaction, industrial Internet of Things, Internet of Things, usable AI, Cyber-physical production systems, Human-computer interaction, Artificial intelligence