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The Impact of Generative AI on User Engagement and Personalisation in Digital Journaling: A Case Study
KTH, School of Electrical Engineering and Computer Science (EECS).
2024 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Effekten av generativ AI på användarengagemang och personalisering i digital journalföring : En fallstudie (Swedish)
Abstract [en]

This study explores the impact of integrating Generative Artificial Intelligence (GenAI) on user engagement and personalisation in digital journaling, specifically focusing on design qualities that enhance or detract from journaling practices. The research employed a Research through Design (RtD) approach, using mixed-methods to combine qualitative and quantitative data collection, including iterative prototype development and testing. The Artificial Intelligence (AI) features were tested in three rounds involving a total of 19 participants, who provided feedback on customisation, data privacy, AI accuracy, and performance. Key findings reveal that participants appreciated the AI’s ability to provide personalised prompts, real-time interactions, and manage analytical tasks, with a strong interest in further customisation options. However, concerns regarding data privacy and AI accuracy were also noted. The study highlights the importance of balancing technological innovation with User-Centered Design (UCD) to create meaningful and supportive journaling experiences. To advance this field, future studies could focus on creating adaptive AI that better predicts user needs, integrating personality-based and cultural customisation, and enhancing privacy and ethical standards.

Abstract [sv]

Denna studie utforskar effekten av att integrera Generative Artificial Intelligence (GenAI) på användarengagemang och personalisering i digitalt journaling, med särskilt fokus på designkvaliteter som förbättrar eller försämrar journaling-praktiker. Forskningsmetoden som användes var en RtD-ansats, där kvalitativa och kvantitativa datainsamlingsmetoder kombinerades, inklusive iterativ prototyputveckling och testning. Artificial Intelligence (AI)-funktionerna testades i tre omgångar med totalt 19 deltagare, som gav feedback om anpassning, dataintegritet, AI-precision och prestanda. Viktiga resultat visar att deltagarna uppskattade AI förmåga att tillhandahålla personliga uppmaningar, interaktioner i realtid och hantera analytiska uppgifter, med ett starkt intresse för ytterligare anpassningsalternativ. Dock noterades även oro över dataintegritet och AI-precision. Studien belyser vikten av att balansera teknologisk innovation med användarcentrerad design för att skapa meningsfulla och stödjande journaling-upplevelser. För att utveckla detta område bör framtida studier fokusera på att skapa adaptiv AI som bättre förutser användarbehov, integrera personlighetbaserad och kulturell anpassning samt förbättra integritets- och etiska standarder.

Place, publisher, year, edition, pages
2024. , p. 27
Series
TRITA-EECS-EX ; 2024:635
Keywords [en]
Human Centered AI, Human-AI Interaction, Digital Journaling, User Experience, Personalisation
Keywords [sv]
människocentrerad AI, människa-AI-interaktion, användargränssnitt, journalföring, användarupplevelse
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-353986OAI: oai:DiVA.org:kth-353986DiVA, id: diva2:1901074
External cooperation
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Available from: 2024-10-02 Created: 2024-09-25 Last updated: 2024-10-02Bibliographically approved

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CiteExportLink to record
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Citation style
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