The Impact of Artificial Intelligence on the Graphic Design Industry

doi:10.7176/ads/104-01

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…It is being incorporated into various disciplines, such as psychology, healthcare, graphic design etc. (Luxton, 2014;Yu et al, 2018;Mustafa, 2023). The combination of AI and psychology allows for new ways of understanding human behavior and preferences while also having a better understanding of AI's capabilities and its inaccuracies (Ashton & Franklin, 2022).…”

Section: Why Is This Important/significant?mentioning

confidence: 99%

Utilizing Machine Learning Algorithms Trained on AI-generated Synthetic Participant Recent Music-Listening Activity in Predicting Big Five Personality Traits

Solaiyappan,

Mohamdjawad,

et al. 2023

Preprint

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The recent rise of publicly available artificial intelligence (AI) tools such as ChatGPT hasraised a plethora of questions among users and skeptics alike. One major question asks, "Has AIgained the ability to indistinguishably mimic the psychology of its organic, human counterpart?".Since music has been known to be a positive predictor of personality traits due to the individuality ofpersonal preference, in this paper we use machine learning (ML) algorithms to analyze thepredictability of AI-generated or 'synthetic' participants' Big 5 personality traits (Openness,Conscientiousness, Extraversion, Agreeableness, and Neuroticism) using their recent music listeningactivity and motivations for listening to music. Recent music listening history for syntheticparticipants is generated using ChatGPT and the corresponding audio features for the songs arederived via the Spotify Application Programming Interface (Beats per minute, Danceability,Instrumentals, Happiness, etc). This study will also administer the Uses of Music Inventory toaccount for synthetic participants’ motivations for listening to music: emotional, cognitive, andbackground. The dataset will be trained and tested on scaler-model combinations to identify thepredictions with the least mean absolute error using ML models such as Random Forest, DecisionTree, K-Nearest Neighbors, Logistic Regression, and Support Vector Machine. Both regression(continuous numeric value) and classification (Likert scale option) prediction methods will be used.An Exploratory Factor Analysis (EFA) will be conducted on the audio features to find a latentrepresentation of the dataset that machine learning is also trained and tested on. A full literaturereview showed this is the first study to use both Spotify API data, rather than self-reported musicpreference, and machine learning, in addition to traditional statistical tests and regression models, topredict the personality of a synthetic college student demographic. The findings of this study showChatGPT struggles to mimic the diverse and complex nature of human personality psychology andmusic taste. This paper is a pilot study to a broader ongoing investigation where the findings ofsynthetic participants are compared to that of real college students using the same inventories forwhich data collection is ongoing.

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Section: Why Is This Important/significant?mentioning

confidence: 99%

Utilizing Machine Learning Algorithms Trained on AI-generated Synthetic Participant Recent Music-Listening Activity in Predicting Big Five Personality Traits

Solaiyappan,

Mohamdjawad,

et al. 2023

Preprint

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Investigating the role of artificial intelligence in immersive visual design: A case study in Nanjing

Chen,

2024

Proceedings of the 2024 7th International Conference on Computer Information Science and Artificial Intelligence

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Inteligencia Artificial en Illustrator. Percepción y exploración en estudiantes de diseño gráfico

Escudero Fernández

2024

epsir

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Introducción: El presente estudio ha tenido como finalidad detectar la percepción de los estudiantes de la inteligencia artificial generativa en el entorno educativo trabajando con programas habituales dentro de la docencia de diseño gráfico e implementándose en la asignatura Maquetación del grado de Diseño Gráfico Digital. Metodología: Para analizar la posibilidad de integración en futuros cursos se ha empleado la metodología de análisis un diseño no experimental, mediante estadística descriptiva simple y exploratoria. Resultados: Muestran una valoración positiva la inserción de la inteligencia artificial generativa en su aprendizaje y perciben su práctica como positiva para su posterior uso en el ámbito profesional. Discusión: El uso de la inteligencia artificial integrada en programas que conocen como Illustrator, facilita la implementación en las asignaturas de diseño y facilita el aprendizaje guiado de estas tecnologías, que ya se están empleando en el sector productivo de diseño. Conclusiones: Un porcentaje elevado de estudiantes no han implementado en la fase de ideación de la actividad estas nuevas herramientas tecnológicas, lo que sugiere una tendencia natural a emplear técnicas y herramientas conocidas. Los profesores deben integran de manera natural la IAGen para dotar a los estudiantes de competencias tecnológicas que serán necesarias en su futuro profesional.

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The Impact of Artificial Intelligence on the Graphic Design Industry

Cited by 3 publications

References 7 publications

Utilizing Machine Learning Algorithms Trained on AI-generated Synthetic Participant Recent Music-Listening Activity in Predicting Big Five Personality Traits

Utilizing Machine Learning Algorithms Trained on AI-generated Synthetic Participant Recent Music-Listening Activity in Predicting Big Five Personality Traits

Investigating the role of artificial intelligence in immersive visual design: A case study in Nanjing

Inteligencia Artificial en Illustrator. Percepción y exploración en estudiantes de diseño gráfico

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