Week 9 | AI
Camilo Escobar Pazos
Created on October 24, 2024
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Transcript
Visual Culture
JR (2017) Giant Picnic. Mexican-US border installation
PLEASE TAKE THE TIME TO COMPLETE THE MEQ'S
Learning outcomes
Demonstrate knowledge and understanding in the process and contexts of interpreting visual material. Show an understanding and independent interpretation of the roles of both producer and viewer in visual communication. Apply research skills in the construction and presentation of a coherent discussion on topics relevant to the course material.
L01
L02
L03
submission week
The final submission deadline is 3rd of November at 5:00 pm. However, submitting today will ensure that you have your teachers assistance. Also, if you decide to change something in your portfolio, remember that you have up to three submission attempts.
submission week
- Cover Page (Include Student ID, Name, Cohort, Portfolio Title)
- Introduction
- Research and Discussion
- Secondary Image Visual Analysis 1
- Secondary Image Visual Analysis 2
- Primary Image Visual Analysis
- Creative Response
- Conclusion
- Bibliography
Final Submission Checklist
session 1
portfolio development
week 9
Week 9 Session 1 Objectives:Portfolio Development 1) 121s for final corrections
session 1 objectives
session 2
portfolio development
week 9
Week 9 Session 2Objectives:Portfolio Development1) 121s for final corrections 2) To submit the student portfolio in Canvas
session 2 objectives
session 3
visual culture and Artificial intelligence analysis and discussion
1) To discuss the social, cultural, and ethical dimensions of AI and digital production, and their impact on visual culture. 2) To understand the implications of AI generated visual culture.
session 3 objectives
what is Articial intelligence (ai)?
Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy.
Applications and devices equipped with AI can see and identify objects. They can understand and respond to human language. They can learn from new information and experience. They can make detailed recommendations to users and experts. They can act independently, replacing the need for human intelligence or intervention (a classic example being a self-driving car).
what is Articial intelligence (ai)?
artificial intelligence (ai) and visual culture
AI image analysis and image generation flourish in several different domains (e.g., news imagery, transport, artistic practice, private photography, the culture industry, policing). AI can (possibly) transform our conception of vision, our use of images, and image technologies’ use of us.
Visual generative media represent a novel technology with the potential to mediate public perceptions of political events, conflicts, and wars.
artificial intelligence (ai) and visual culture
Redefinition of Creativity:How AI forces us to reconsider human creativity versus machine-generated art. Impact on Traditional Art:How the rise of AI challenges traditional visual arts, with some artists embracing or rejecting AI. Future of Visual Culture:How AI-generated visuals will evolve the concept of visual culture over time—new trends, aesthetics, and platforms.
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Cultural Dimensions of AI in Visual Culture
Cultural Representation: [CLICK THE IMAGES]AI can either broaden or limit cultural representation based on its data set. Example: AI creating Western-centric visuals if trained on biased data. Hybrid Forms of Art: [CLICK]AI enables the blending of cultural elements, creating hybrid and globalized art. Shifts in Aesthetic Norms:AI introduces new visual aesthetics and styles, altering how we define "art" and "beauty."
This is the image that an AI generates when asked to create a CEO
This is the image that an AI generates when asked to create a COMPASSIONATE CEO
AI and visual culture (art)
Ai and art
“What will art after AI look like?”
Ai and art
“What will art after AI look like?”
The video you just saw explores our anxieties around human and machine creativity, at a time of intense investment in machine learning technology. To make the video, the artist Joanna Sylinska (2023) used three avatars which have been AI-generated. The avatars then have been programmed to each deliver a script responding to the following query: “What will art after AI look like?”. Blinking, smiling, and occasionally glitching, the avatars merge a friendly professional disposition with an “Uncanny Valley” look. Their narratives—written by GPT-4, ChatGPT, and the artist herself—invite a reflection on an increasingly thin line that separates original thinking from algorithmic banality, in humans and machines.
ai and culture
AI is transforming the way we experience culture by providing new ways to create, consume, and interact with media. One of the most significant impacts of AI in culture is the use of recommendation algorithms, which analyze user data and behavior to suggest content that is tailored to their preferences. This has revolutionized the way we discover new books, movies, music, and other forms of media, allowing us to explore a wider range of content than ever before. However, can an algorithm know what we like before we do? Does this have an effect on possibility?
ai and culture
AI has opened up new avenues for image generation, providing benefits such as time efficiency, enhanced realism, and endless creativity. However, there are also drawbacks to consider, including concerns about originality, ethical implications, and the reliance on training data.AI systems are only as good as the data they are trained on. If the training data contains biases, the AI will likely perpetuate these biases. This can lead to unfair outcomes, such as discrimination in hiring processes, loan approvals, and criminal justice decisions. Ensuring fairness in AI involves:
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Prompt: house in Nigeria
Prompt: a house in Indonesia
Prompt: A house in America
ethical implications of ai
Ethical and Cultural Implications Bias in Storytelling: AI systems can inadvertently encode biases present in their training data. This might skew AI-generated narratives towards certain cultural perspectives, potentially marginalising others and impacting cultural diversity in storytelling. Authenticity and Depth: While AI can generate content, there are concerns about the depth and authenticity of such narratives. AI might create technically competent stories but may struggle to capture the emotional depth and cultural subtleties that human storytellers bring to their tales. Cultural Appropriation: As AI systems generate content that draws from a wide array of cultural elements, there’s a risk of cultural appropriation, where the use of these elements can be seen as disrespectful or incorrectly represented, especially when produced without proper cultural context or understanding.
ethical implications of ai
Authorship and Ownership:Who owns AI-generated works? The user, the platform, or the AI itself? Copyright Infringement:The risk of AI borrowing or recreating existing works without credit. Deepfakes and Misinformation:Ethical concerns over AI's potential to generate deceptive visual content (e.g., deepfakes). Bias in AI:AI models can reflect societal biases (e.g., gender, race) if not carefully designed.
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Prompt: Nigerian woman
Prompt: Indonesian woman
Prompt: American woman
ethical and cultural implications
social dimensions of ai in visual culture
Accessibility and Inclusivity:AI democratizes art creation by allowing non-artists to participate. New platforms give underrepresented voices access to creative tools.Job Displacement:Discuss concerns over AI replacing human artists and designers. Creation of New Communities:AI-generated visuals foster new digital art communities (e.g., NFT artists, Instagram creatives).
social dimensions of ai in visual culture
conclusion
AI is reshaping the way visual culture is produced and consumed, with broad social, cultural, and ethical implications. The role of artists, designers, businesses and consumers will continue to adapt as AI becomes more ingrained in visual production and social life.
“Woman”-specific prompts generated the same lack of diversity and reliance on stereotypes as the “person” prompts. Most Indian women appeared with covered heads and in saffron colors often tied to Hinduism; Indonesian women were shown wearing headscarves or floral hair decorations and large earrings. Chinese women wore traditional hanfu-style clothing and stood in front of “oriental”-style floral backdrops.