This is demonstrated by the wave of nostalgic photos that recently hit social networks, the first showcases of the latest exploits of DALL-E, Midjourney, Leonardo AI… Classy photos, for example, directly from the 80s, cuts au bol , braids and bell-bottoms for all the students in line, all… as imperfect as the original photos. Artificial intelligence has simply ”learned to identify the codes of the very first images digitized in the 2000s and therefore taken in the 1980s, and to imitate them”, describes Marjolaine Marie Aria Ray, from the Lattice laboratory (CNRS – École normalie supérieure – Sorbonne-Nouvelle ). And thus reproduce small defects such as, for example, graininess or red eyes. “This makes the images even more difficult to detect visually,” admits Tina Nikoukhah, media security researcher at GetReal Labs.
How is nostalgia influencing the design of AI-generated images on social media platforms?
Interview: The Evolution of Nostalgia in AI-Generated Images
Q: Today, we’re exploring an interesting trend in artificial intelligence and image generation. Can you explain what’s driving this wave of nostalgic photos on social media?
Marjolaine Marie Aria Ray: Certainly! The resurgence of nostalgic images, particularly those mimicking the styles of the 1980s, is primarily influenced by AI technologies like DALL-E, Midjourney, and Leonardo AI. These platforms have been programmed to recognize and replicate the distinct visual characteristics of early digital images, which often come with imperfections.
Q: What specific features are these AI systems reproducing from the 1980s images?
Marjolaine Marie Aria Ray: AI has learned to identify typical elements from the earlier digital photography era—think of cuts au bol hairstyles, braids, and bell-bottoms, which were iconic back then. They don’t just replicate compositions; they also mimic small defects and anomalies—like graininess or red-eye effects—that were common in photographs from that time period. This attention to detail draws viewers in with a sense of authenticity.
Q: Tina, as a media security researcher, could you share the implications of these advances in AI-generated imagery? What challenges do they pose?
Tina Nikoukhah: The implications are significant. As these technologies improve, it becomes increasingly difficult to distinguish between genuine photographs and AI-created images. This raises concerns around misinformation and the potential for deception in media. For instance, if someone were to create a fake nostalgic image that looks convincingly real, it could mislead audiences.
Q: Are there practical ways that individuals and industries can address these challenges?
Tina Nikoukhah: Absolutely. One practical approach is to invest in image verification software that utilizes machine learning algorithms to detect AI-generated content. Additionally, educating the public about the existence of these technologies and their capabilities is crucial. Awareness can empower individuals to think critically about what they see online.
Q: How do you see the future of AI-generated images evolving, particularly in the creative industries?
Marjolaine Marie Aria Ray: I believe we will see a continuous blurring of lines between human creativity and AI capabilities. Artists and marketers will likely leverage these tools to evoke nostalgia or create entirely new visual experiences. However, it will also challenge creators to differentiate their work from AI-generated content, fostering a shift in how we value originality.
Q: Lastly, for our readers who may want to experiment with these AI technologies, what advice would you give them?
Marjolaine Marie Aria Ray: My advice would be to embrace creativity while being mindful of ethical considerations. Play around with different prompts in AI platforms to see how they can be used to enhance your artistic vision. However, always consider the implications of sharing AI-generated content and strive for transparency about its origins. This not only builds trust with your audience but also contributes positively to the discourse around AI and art.
Conclusion
This conversation underscores the profound impact AI technologies have on our understanding and manipulation of nostalgia in imagery. As we continue to navigate this evolving landscape, awareness, education, and ethical considerations will be key in shaping our visual culture.