Overview:
This workshop explores image generation with AI tools while examining responsible practices. Participants will learn techniques for prompting and editing through a hands-on exercise. The discussion will cover responsible use of AI, including reviewing data, privacy, copyright, fake news, biases, agency, accountability, authorship, and legal implications.

Human creativity and artistic skills have always been much appreciated and admired traits. With easy access to generative AI tools, our perception of art and the artist is rapidly transforming. In this workshop, we will explore image generation with AI and examine issues of responsible practice. After a brief introduction to AI image generation concepts and tools, we will work through a guided exercise to learn different techniques of prompting and editing.  Through this hands-on exercise, we will learn to identify and discuss the implications of the technology with the following pointers:

• Reviewing the data an image generator is trained on

• Privacy and Identity - Who owns the copyright to your face?

• Does AI steal like an artist?

• Fake news and misinformation - Interpretations of AI-generated images.

• Is it possible to create a perfect AI model, free of human biases?

• Agency, Accountability, Authorship: “AI did it, not me!”

• Evolving legal implications of images

Program:

• Conceptual introduction to AI image generation process (15 min) 

• Demo, followed by a creative exercise (45 min) 

• Discussion (30 min)

Facilitator Profile:

Chandni Naidu is a designer and artist with a keen interest in learning, creativity, and society. Her past work includes the design of multi-sensory interactions for accessible learning, and data visualizations for better awareness and engagement with social issues. She can be reached at chandni[dot]naidu[at]proton[dot]me and her website is www.chandninaidu.com.

Overview:
This workshop will explore the intricacies of dataset creation, ethical considerations, and their implications on labor dynamics within the AI landscape. The workshop aims to cover the following areas of focus:

1. Data Annotation and Labeling: Discussing methods and challenges associated with annotating and labeling data to establish ground truth for machine learning algorithms.

2. Ethical Considerations: Exploring the ethical implications of data annotation, particularly in cases where it involves qualitative judgements, and discussing strategies for ethical data handling.

3. Quality Assurance: Addressing the importance of quality assurance processes in ensuring the accuracy and reliability of labeled datasets, and discussing techniques for minimizing errors and bias.

4. Impact on Labor Dynamics: Examining the role of human annotators and data workers in the data annotation process, and discussing issues related to job security, fair compensation, and working conditions in the context of precarious labor.

5. Algorithmic Bias and Fairness: Analyzing how biases in labeled datasets can propagate through machine learning algorithms, leading to unfair or discriminatory outcomes, and discussing approaches for mitigating bias and promoting fairness in AI systems.

6. Regulatory Compliance: Exploring legal and regulatory frameworks governing data annotation and labeling practices, and discussing compliance requirements related to data privacy, consent, and transparency.

Program:

• Introduction, Welcome, and Ice-breakers: (10 minutes)

• Introductory Talk: (30 minutes)

• Introduction to the Tasks: (5 minutes)

• Team Division and Breakout Rooms: (5 minutes)

• Biobreak (10 minutes)

• Data Labeling Tasks: (20 minutes)

• Discussion and Evaluation of Labeling Tasks: (20 minutes)

• Conclusion and Wrap-up (10 minutes)

Facilitator Profile:

Currently honored as the recipient of the Creative Media Award from the Mozilla Foundation, Arnab Chakravarty is engaged in crafting a game that delves into the human toll of AI, delving into the profound notion that machines may forever remain distant from the nuanced essence of what we consider intrinsically human.

In his prior role as a post-doctoral research fellow at ITP and as an artist-in-residence at CMU, Arnab conceptualized and built to a game centered around the 7th Amendment, showcased at Federal Hall and featured in a notable publication. Beyond these pursuits, he serves as the technical director of Broken Ghost Immersives, a theater collective seamlessly blending elements of escape rooms, immersive theater, board games, role-playing, and video games. The collective's theatrical works showcase live performances, digital elements, and a responsive story shaped entirely by the decisions of its audience.

His work has been featured and  supported by the Mozilla Foundation, India Art Fair, British Library, Goethe Institute, Frank-Ratchye STUDIO for Creative Inquiry, FAB:Learn, No:Quarter, MakerFaire, Consumer Reports, Kochi Bienalle, and NYC Media Lab. Website: https://chaky.works 

Group discussion and closing reflections on 'Creative and Responsible AI for Well-being' facilitated by Dr. Gopinaath Kannabiran