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[{"key": "dc.contributor.advisor", "value": "Saarela, Mirka", "language": null, "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Kumarage, Prabha", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2025-05-14T11:30:02Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2025-05-14T11:30:02Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2025", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/102001", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "The rapid development of Generative Artificial Intelligence (GenAI) has introduced a new era of technological innovation by revolutionizing how people interact with information. Explainability is a crucial aspect to ensure transparency, accountability, and trust in these GenAI-driven systems. Interpreting and comprehending the decision-making process of GenAI models is becoming increasingly difficult as they become more complex and widespread over time. This research study aims to undertake a thorough navigation of the current state of explainability in GenAI through a two-phase literature review: an umbrella review to analyze previous reviews and an empirical review to examine empirical studies. First, the umbrella review provides an overview by analyzing the existing explainable techniques for GenAI and their limitations. The key limitations in explaining GenAI models include generalization issues, computational inefficiencies, and trade-offs between interpretability and model performance. The empirical review then examines how these GenAI explainable techniques are applied and evaluated in practical settings. A significant finding is the absence of a standardized evaluation framework to measure and compare the effectiveness of different explainability techniques. Finally, the findings of the two reviews are synthesized to identify open challenges and propose potential future directions for improving explainability in GenAI. This study highlights the importance of developing well-balanced GenAI-specific explainable techniques that align with AI regulations to ensure the responsible development of GenAI solutions. In addition, researchers, AI professionals, and policymakers seeking to improve the transparency and explainability of GenAI models can all greatly benefit from the findings.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Generatiivisen teko\u00e4lyn (GenAI) nopea kehitys on k\u00e4ynnist\u00e4nyt uuden teknologisen innovaation aikakauden mullistamalla ihmisten vuorovaikutuksen tiedon kanssa. Selitt\u00e4vyys on olennainen osa avoimuuden, vastuullisuuden ja luottamuksen rakentamista n\u00e4ihin GenAI-pohjaisiin j\u00e4rjestelmiin. GenAI-mallien p\u00e4\u00e4t\u00f6ksentekoprosessin tulkitseminen ja ymm\u00e4rt\u00e4minen on yh\u00e4 vaikeampaa, koska ne monimutkaistuvat ja laajenevat ajan my\u00f6t\u00e4. T\u00e4m\u00e4n tutkimuksen tavoitteena on perehty\u00e4 perusteellisesti GenAI:n nykyiseen selitett\u00e4vyyteen kaksivaiheisen kirjallisuuskatsauksen avulla: kattokatsaus analysoimaan aikaisempia katsauksia ja empiirinen katsaus empiirisi\u00e4 tutkimuksia. Ensin kattokatsaus tarjoaa yleiskatsauksen analysoimalla olemassa olevia selitett\u00e4vi\u00e4 GenAI:n tekniikoita ja niiden rajoituksia. T\u00e4rkeimm\u00e4t rajoitukset GenAI-mallien selitt\u00e4misess\u00e4 ovat yleistysongelmat, laskennalliset tehottomuudet sek\u00e4 tulkittavuuden ja mallin suorituskyvyn v\u00e4liset kompromissit. Seuraavaksi empiirisess\u00e4 katsauksessa tarkastellaan, kuinka n\u00e4it\u00e4 GenAI:n selitett\u00e4vi\u00e4 tekniikoita sovelletaan ja arvioidaan k\u00e4yt\u00e4nn\u00f6n ymp\u00e4rist\u00f6iss\u00e4. Yksi merkitt\u00e4v\u00e4 havainto on standardoidun arviointikehyksen puuttuminen eri selitett\u00e4vyystekniikoiden tehokkuuden mittaamiseksi ja vertailemiseksi. Lopuksi kahden katsauksen havainnot syntetisoidaan tunnistamaan avoimia haasteita ja ehdottamaan mahdollisia tulevaisuuden suuntauksia GenAI:n selitett\u00e4vyyden parantamiseksi. T\u00e4m\u00e4 tutkimus korostaa, kuinka t\u00e4rke\u00e4\u00e4 on kehitt\u00e4\u00e4 tasapainoisia GenAI-spesifisi\u00e4 selitett\u00e4vi\u00e4 tekniikoita, jotka ovat teko\u00e4lym\u00e4\u00e4r\u00e4ysten mukaisia GenAI-ratkaisujen vastuullisen kehityksen varmistamiseksi. Lis\u00e4ksi tutkijat, teko\u00e4lyammattilaiset ja p\u00e4\u00e4tt\u00e4j\u00e4t, jotka pyrkiv\u00e4t parantamaan GenAI-mallien l\u00e4pin\u00e4kyvyytt\u00e4 ja selitett\u00e4vyytt\u00e4, voivat kaikki hy\u00f6ty\u00e4 suuresti tuloksista.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2025-05-14T11:30:02Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2025-05-14T11:30:02Z (GMT). No. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "83", "language": null, "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "CC BY 4.0", "language": null, "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.title", "value": "Explainability in Generative Artificial Intelligence: A Two-Phase Review of Current Techniques, Limitations, and Open Challenges", "language": null, "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202505144243", "language": null, "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Master's Degree Programme in Artificial Intelligence", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Master's Degree Programme in Artificial Intelligence", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.copyright", "value": "\u00a9 The Author(s)", "language": null, "element": "rights", "qualifier": "copyright", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://creativecommons.org/licenses/by/4.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}, {"key": "dc.description.accessibilityfeature", "value": "unknown accessibility", "language": "en", "element": "description", "qualifier": "accessibilityfeature", "schema": "dc"}, {"key": "dc.description.accessibilityfeature", "value": "ei tietoa saavutettavuudesta", "language": "fi", "element": "description", "qualifier": "accessibilityfeature", "schema": "dc"}]
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