ARTIFICIAL INTELLIGENCE IN AUGMENTATIVE AND ALTERNATIVE COMMUNICATION SYSTEMS - A LITERATURE-BASED ASSESSMENT AND IMPLICATIONS OF DIFFERENT CONVERSATION PHASES AND CONTEXTS
Even though AAC systems and corresponding AI approaches have been investigated in the extant research, they still show remarkable drawbacks, resulting in a low prevalence among speech-impaired individuals. As the suggestions and adaptions proposed by AI within AAC systems may show insufficiencies in certain situations (e.g., unreliable suggestions, low conversational rates, unauthentic adaptions towards the users), we aim to take a more up-close look at the conversations, especially the conversational contexts and conversation phases in which the supporting AI is applied. Therefore, we have conducted a Systematic Literature Review as well as Literature Analysis. Thereby, we could reveal that there are indeed several gaps within the extant research on AI regarding the coverage of the conversational context “informativeness” and the conversation phases “beginning” and “closing”. To dismantle the existing communication barriers that speech-impaired individuals suffer from, several implications for investigating AI in the context of AAC systems are derived and proposed for future (IS) research.
Konadl, Daniel; Wörner, Janik; Luttner, Lucas; and Leist, Susanne, "ARTIFICIAL INTELLIGENCE IN AUGMENTATIVE AND ALTERNATIVE COMMUNICATION SYSTEMS - A LITERATURE-BASED ASSESSMENT AND IMPLICATIONS OF DIFFERENT CONVERSATION PHASES AND CONTEXTS" (2023). ECIS 2023 Research Papers. 309.