A Model for Understanding the Evolving Role of Graphic Designers in the Era of Artificial Intelligence
(2023)
author(s): Stig Møller Hansen
published in: HUB - Journal of Research in Art, Design and Society
This paper examines the possible impacts of artificial intelligence (AI) on the ever-changing role of graphic designers. As its main contribution, the paper proposes a model based on the intertwining concepts of deduction, induction, and abduction. It argues that deductive and inductive tasks in graphic design can be effectively and advantageously outsourced to AI, while abductive tasks are still best performed by human graphic designers. Additionally, the power balance between humans and AI is discussed, concluding that human graphic designers must play a pivotal role in initiating and critically evaluating the results of any collaboration with AI tools. The model introduces the metaphorical notion of a "disciplinary expertise filter," which serves as a professional quality assurance for AI-based automation and augmentation in the design process. The distinction between "black box" and "clear box" AI systems is briefly discussed to provide a more nuanced understanding of AI as being "a magic tool" for graphic designers. Lastly, the paper presents six perspectives derived from the model, aiming to foster informed discussions and encourage critical reflections among graphic designers regarding their future role in the era of AI.
Aimpathy
(2023)
author(s): Amit Yungman
published in: KC Research Portal
Much research has been done to better understand the emotional experience of music; from the philosophical, artistic, psychological, and statistical approaches. In this research we conduct a cross-domain experiment based on those four disciplines, to further understand the factors that influence the emotional perception of music; and in particular the difference between the artist’s emotional conception and the audience’s perception.
In the experiment we train a novel model of an Artificial Neural Network, to predict the perceived emotion from a short musical phrase. We then feed the machine curated input, which simulates artistic choices, to explore its most significant factors in determining the perceived emotions.
In the conclusion we describe the results, as well as the possible follow-ups to the experiment, such as an emotional expression training tool for musicians.
Patterns-of-Life
(last edited: 2024)
author(s): Revuelta
This exposition is in progress and its share status is: visible to all.
In 2017, the U.S. Department of Defense announced the launch of Project Maven, also known as the Algorithmic Warfare Cross-Functional Team (AWCFT). This program aims to integrate artificial intelligence (AI) and machine learning into military operations to maintain a strategic advantage over increasingly sophisticated adversaries. The primary objective of Maven is to develop an automated analysis system capable of identifying targets and spotting suspicious activities through machine learning algorithms and advanced computer vision techniques.
One year after its launch, the DoD revealed that the program was using an AI algorithm to autonomously recognize and identify targets, marking a significant advancement towards achieving one of Maven's objectives: to develop and integrate computer vision algorithms to assist military analysts overwhelmed by a constant flow of video data.
Inspired by the Maven project, “Patterns-of-Life" offers an immersion into the perspective of a military drone, embodying the algorithmic eye of war. Trained on real combat videos collected from social networks and YouTube, the videos present a pattern recognition system to predict human behavior from movements and postures, assessing the hostile or neutral potential of a target. It thus explores the concept of "lethal autonomous targeting" by an AI system capable of differentiating between combatant actions and civilians, presented in an urban context where technology is revealed in everyday scenes.
“Patterns-of-Life” emphasizes the fundamental importance, stated in the Geneva Conventions, of distinguishing between civilians and combatants. A mission that, once, was the responsibility of commanders and soldiers, now relies on software analyzing data collected by sensors.
Patterns-of-Life invites us to reflect on the role we want technology to play in resolving conflicts and preserving innocent lives. It leads us to question the future of increasingly automated warfare and the issues of responsibility that arise. It asks: will life-or-death decisions be entirely delegated to machines? How will we recognize this shift?