Artificiell intelligens (AI) har blivit alltmer betydelsefull i dagens samhälle, med växande tillämpningar inom olika kreativa områden. Denna kandidatuppsats syftar till att undersöka de potentiella fördelarna och riskerna som AI erbjuder för kreativa yrken inom media. Genom analys av åtta intervjuer studerar arbetet hur AI-verktyg, såsom ChatGPT, DALL·E och Midjourney, kan effektivisera arbetsprocesser, öka tidsåtgången för kreativt arbete och främja inspiration, samtidigt som det granskar de förknippade utmaningarna, såsom rättigheter, stereotyper, deepfake och påverkan på arbetsmöjligheter. Resultaten visar att användningen av AI medför både för- och nackdelar för kreativt arbete och antyder att denna trend kommer att fortsätta i framtiden. Även om potentialen för AI-teknik är stor, förväntas mänsklig kreativitet fortfarande att ha en avgörande roll i det kreativa arbetet. Avhandlingen avslutas med att betona samhällets och individernas ansvar att aktivt delta i utvecklingsprocessen och säkerställa att lämpliga lagar och regler finns på plats för att förhindra missbruk av olika AI-system inom den kreativa sektorn. / Artificial intelligence (AI) has become increasingly significant today with growing applications in various creative fields. This bachelor thesis aims to explore the potential benefits and risks AI offers to creative professions within media. Through the analysis of eight interviews, the study investigates how AI tools, such as ChatGPT, DALL·E, and Midjourney, can streamline work processes, enhance creative work, and foster inspiration while also examining the associated challenges, such as rights, stereotypes, deepfakes, and the impact on work opportunities. The findings demonstrate that AI usage presents both advantages and disadvantages for creative work and suggests that this trend will continue in the future. While the potential of AI technology is vast, the industry is expected to undergo significant transformations. The thesis concludes by emphasizing the responsibility of society and individuals to actively participate in the development process, ensuring that appropriate laws and regulations are in place to prevent the misuse of various AI systems in the creative sector.

The rapid advancement of artificial intelligence has led to the emergence of deepfake, digital media that has been manipulated to replace a person's likeness with another. This technology has seen significant improvements, becoming easier to use and producing results increasingly difficult to distinguish from reality. This development has raised ethical discussions surrounding its deceiving nature. Furthermore, deepfakes have had a considerable impact and application on social media, enabling their spread. Despite this, the public discourse on social media, along with its societal and personal values associated with deepfakes, remains underexplored. This study addresses this gap by examining social media discourse and perception surrounding the prominent ethical concerns of deepfakes, and situating these concerns within the broader landscape of AI ethics. Through a qualitative method resembling netnography, 320 posts from Reddit and Youtube were thematically analyzed through a passive observation, along with their respective comment section. The findings reveal various concerns, surrounding misinformation and consent to deeper fears about deepfakes' role in fostering distrust, as well as more abstract apprehensions regarding the technology's abuse and harmful applications. These concerns further revealed how generalized established AI ethical principles might be interpreted in the deepfake context, also showing how and why these principles might be violated by this technology. Particularly it revealed terms how principles such as dignity, transparency, privacy and non-maleficence might be diverged in deepfake applications.

L’utilisation croissante de l’information audiovisuelle devant les tribunaux de droit pénal international indique une trajectoire qui oblige à considérer plus attentivement les enjeux soulevés par ce type de preuve à partir de sa collecte, sa conservation jusqu’à son utilisation dans le cadre d’un procès. Ces enjeux peuvent être variés et se rattacher à la véracité, l’authenticité et l’intégrité du contenu d’une telle information. Dans le cadre de ce mémoire, nous plaidons, au moins, pour une approche rigoureuse dans l’évaluation de la preuve audiovisuelle, et ce, tout au long du processus judiciaire d’une affaire devant la CPI, ou au plus, pour un encadrement objectif des règles applicables à la preuve audiovisuelle, et ce, en s’écartant du principe général de souplesse et de flexibilité fortement ancré dans la culture de l’administration de la preuve devant cette institution, pour adopter une approche stricte et rigoureuse. Laquelle favoriserait, d’une part, l’application du critère préalable de fiabilité lors de la phase de l’introduction d’un élément de preuve audiovisuel, et d’autre part, l’application d’une méthode d’évaluation de la preuve audiovisuelle basée sur le modèle d’admission. La présence d’une phase préalable d’analyse substantielle des éléments sensibles, tels que les éléments de preuve audiovisuels, n’implique pas forcément une perte du pouvoir discrétionnaire des juges à renvoyer l’évaluation des éléments de preuve introduits à la fin du processus. L’enjeu fondamental réside dans le fait que le critère préalable de fiabilité et le modèle d’admission permettraient de tempérer le pouvoir discrétionnaire des juges et favoriseraient une analyse plus diligente et rigoureuse des éléments de preuve audiovisuels. À notre avis, cette démarche devra être initiée par les juges des chambres préliminaires et de première instance, en leur qualité de juges de faits et de la preuve, et se concrétiser sur le terrain par les premiers et différents intervenants impliqués dans le processus judiciaire de cette institution. / The increasing use of audiovisual information before international criminal courts is indicative of a trajectory that calls for a closer look at the issues raised by this type of evidence, from its collection and preservation to its use in court. These issues can be varied and relate to the veracity, authenticity and integrity of the content of such information. In this research Paper, we argue for at least a rigorous approach to the evaluation of digital evidence, throughout the judicial process of a case before the ICC, or at most, an objective framing of the rules applicable to digital evidence, departing from the general principle of flexibility strongly rooted in the culture of the administration of evidence before this institution, in favor of a strict and rigorous approach. This would favor the application of the preliminary criterion of reliability when introducing audiovisual evidence, and the application of a method for evaluating audiovisual evidence based on the admission model. The presence of a substantial preliminary analysis phase for sensitive elements, such as digital evidence, does not necessarily imply a loss of judicial discretion to defer the evaluation of the evidence produced to the end of the process. What is fundamentally at stake is the fact that the prior reliability criterion and the admission model would temper judicial discretion and encourage a more diligent and rigorous analysis of digital evidence. In our opinion, this approach should be initiated by the judges of the preliminary and trial chambers, in their capacity as judges of fact and evidence, and implemented in the field by the first and various stakeholders involved in the judicial process of this institution.

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<p dir="ltr">The rapid development of machine learning techniques makes it possible to manipulate or synthesize video and audio information while introducing nearly indetectable artifacts. Most media forensics methods analyze the high-level data (e.g., pixels from videos, temporal signals from audios) decoded from compressed media data. Since media manipulation or synthesis methods usually aim to improve the quality of such high-level data directly, acquiring forensic evidence from these data has become increasingly challenging. In this work, we focus on media forensics techniques using the metadata in media formats, which includes container metadata and coding parameters in the encoded bitstream. Since many media manipulation and synthesis methods do not attempt to hide metadata traces, it is possible to use them for forensics tasks. First, we present a video forensics technique using metadata embedded in MP4/MOV video containers. Our proposed method achieved high performance in video manipulation detection, source device attribution, social media attribution, and manipulation tool identification on publicly available datasets. Second, we present a transformer neural network based MP3 audio forensics technique using low-level codec information. Our proposed method can localize multiple compressed segments in MP3 files. The localization accuracy of our proposed method is higher compared to other methods. Third, we present an H.264-based video device matching method. This method can determine if the two video sequences are captured by the same device even if the method has never encountered the device. Our proposed method achieved good performance in a three-fold cross validation scheme on a publicly available video forensics dataset containing 35 devices. Fourth, we present a Graph Neural Network (GNN) based approach for the analysis of MP4/MOV metadata trees. The proposed method is trained using Self-Supervised Learning (SSL), which increased the robustness of the proposed method and makes it capable of handling missing/unseen data. Fifth, we present an efficient approach to compute the spectrogram feature with MP3 compressed audio signals. The proposed approach decreases the complexity of speech feature computation by ~77.6% and saves ~37.87% of MP3 decoding time. The resulting spectrogram features lead to higher synthetic speech detection performance.</p>