2025 Final Project Brief

1. Brief

Design and develop an independent AI-driven art project that integrates programming technologies and artistic concepts. Deliver a fully functioning project (e.g., generative art, interactive media) along with supporting materials including a dataset, creative logbook, and academic paper. The project emphasizes technical implementation, creative expression, and interdisciplinary integration of AI, programming, and art.

Presentation: Individual

Core Deliverables: Functioning AI-driven art project, creative logbook, 3500–4000 Chinese characters academic paper (excluding references), and presentation.

2. Key Submission Requirements

All deliverables are mandatory and must meet the following specifications to avoid grade deductions:

•   Functioning AI-driven Art Project: Operational generative art or interactive media (e.g., executable program, web-based interactive work, offline installation files).

•   Dataset: Complete dataset (raw + preprocessed files) with detailed description of source, scale, and preprocessing steps.

•   Creative Logbook: Comprehensive documentation of individual learning and creative process (format: Word/PDF, no word limit but must cover required content).

•   Academic Paper: 3500–4000 Chinese characters (excluding references), following professional academic standards.

•   Presentation: PowerPoint-based presentation (3 minutes in total; pre-recorded video acceptable) to be delivered on 21/28/29 November.

3. Learning Outcomes (LOs)

Align your work with the following outcomes to meet assessment expectations (supplementary LOs marked with *):

•   LO1: Understanding programming skills (e.g., processing, p5.js) and AI technologies (e.g., generative models, interactive AI tools) for practical project implementation.

•   *LO2: Apply programming skills to create digital artworks (e.g., code-generated visual patterns, algorithmic animations) and interactive media (e.g., user-triggered AI art responses, AI generative art), forming technical support for artistic expression.

•   *LO3: Design and implement a complete AI-driven art project that systematically integrates programming, AI, and artistic expression—ensuring technical routes match creative concepts, and functional outcomes reflect artistic connotations.

•   LO4: Integrate artistic concepts with technical implementation, realizing creative expression through AI-driven methods (e.g., using AI to extend traditional art styles, converting abstract ideas into visual/audio outputs).

•   LO5: Systematically document the project process (via logbook) and summarize key outcomes (via academic paper), demonstrating reflective thinking and interdisciplinary application capabilities.

•   LO6: Analyze and address technical and creative challenges in AI art projects, and reflect on the practical value and limitations of AI in artistic creation.

•   *LO7: Critically assess the ethical implications (e.g., copyright of AI-generated content, originality attribution, data privacy) and societal impact (e.g., influence on traditional artistic creation models, accessibility of art to the public) of AI in the arts.

4. Weighting

This project accounts for 50% of your total course grade, with each deliverable contributing  to the final score (specific grading criteria will be provided separately). Note: Performance on supplementary LOs (LO2/3/7) will be evaluated through the logbook, academic paper, and  presentation.

5. Deliverables Details

5.1 Creative Logbook

Document the entire individual learning and creative process, with supplementary requirements for new LOs:

•   Project aims & objectives: Clear definition of the project’s core purpose and expected outcomes (link to LO3: explain how the project integrates programming, AI, and art).

• Research & analysis:

◦   Literature review on AI art (including ethical discussions of AI in arts, to align with LO7)

◦   Case studies of similar projects (emphasize how they applied programming to create digital art/interactive media, link to LO2)

◦   Analysis of technical feasibility (verify if programming/AI tools can support artistic expression, link to LO3)

•   Mind-map: Visualization of project structure, technical routes (e.g., programming modules, AI model workflow), and creative directions (link to LO3).

•   Idea generation: All proposed creative concepts (include how programming/AI will support each idea, link to LO2), including discarded or revised ideas with reasoning.

• Experiments & development:

◦   Detailed records of technical experiments (e.g., using Python to write generative art code, testing interactive logic—link to LO2)

◦   Creative iterations (track how programming/AI adjustments optimize artistic effects— link to LO3)

◦   Problems encountered (e.g., ethical dilemmas in using open-source AI datasets—link to LO7)

•   Proposed direction: Finalized project plan and implementation roadmap (clearly state how to achieve LO2/3/7).

5.2 Functioning AI-driven Art Project

• Submission format: Executable files (e.g., Python/JS scripts for generative art,

Processing/ TouchDesigner/ Audrino projects for interactive media), web links (for browser-based interactive work), or offline demonstration materials (with operation guide).

•   Core requirement (link to LO2/3): The project must be fully functional, with clear evidence of programming application (e.g., custom code for interaction) and AI-art integration (e.g., AI generates art based on user input).

•   Supporting materials: Include a simple operation manual (1–2 pages) explaining how to run/experience the project, and mark which parts reflect LO2 (programming-driven creation) and LO3 (triple integration).

5.3 Essay

Follow professional academic paper format, with content curated from the logbook and presentation slides, and layout matching the project theme. Highlight supplementary LOs in the following sections:

•   Abstract (150–200 Chinese characters): Summary of project background, objectives (including LO2/3/7), methods, outcomes, and reflections.

•   Introduction: Project background, research significance (include the value of integrating programming/AI/art, and the need for ethical assessment—link to LO3/7), and literature review.

•   Project Objectives: Clear statement of technical and creative goals, with explicit alignment to LO2 (programming application), LO3 (triple integration), and LO7 (ethical assessment).

• Tools & Technologies: Detailed description of programming languages if used (e.g.,

Python, Processing—link to LO2), AI models (e.g., Stable Diffusion, TensorFlow or etc— link to LO3), and software/tools used (e.g., Photoshop, TouchDesigner or etc).

•   Artistic Ideas: Interpretation of the project’s artistic connotation, style positioning, and creative inspiration (explain how programming/AI realizes these ideas—link to LO2/3).

• Challenges & Solutions:

◦   2 key technical/creative challenges (e.g., AI Generative Art—link to LO2)

。 EthicaI chaIIenges (e.g., how to address copyright concerns of AI-generated art—Iink to LO7)

。 Specific soIutions impIemented.

•   Project Outcomes:

。 Quantitative resuIts (e.g., project operation efficiency, dataset scaIe)

。 QuaIitative outcomes (e.g., artistic expression effect, audience feedback—Iink to LO2/3)

。 EthicaI assessment resuIts (e.g., how the project avoids copyright risks—Iink to LO7).

• RefIections:

。 SeIf-assessment of project strengths and weaknesses (incIuding performance on LO2/3/7)

。 Insights on AI’s roIe in artistic creation

。 Recommendations for addressing ethicaI issues in future AI art projects (Iink to LO7).

•   References: Standard academic citations (no Iess than 5 references, incIuding at Ieast 1

Iiterature on AI art ethics—Iink to LO7).

5.4 Presentation

Structure the PowerPoint (3mins) to highIight key project content and suppIementary LOs:

•   Project Overview: Name, participant information (names, student IDs, roIes), and 1- sentence core purpose (Iink to LO3).

• Creative & TechnicaI Foundation:

。 Artistic inspiration

。 Research basis (incIude AI art ethics research—Iink to LO7)

。 SeIected tooIs/technoIogies (expIain how programming/AI support art—Iink to LO2/3)

•   ImpIementation Process:

。 Key deveIopment stages (e.g., programming for interactive functions—Iink to LO2)

。 Experiments and iterative improvements (Iink to LO3)

。 EthicaI considerations during deveIopment (Iink to LO7)

•   Project Demonstration: Live or video demonstration of the functioning project (highIight programming-driven features and AI-art integration—Iink to LO2/3).

• Outcomes & RefIections:

。 Summary of resuIts (incIuding ethicaI assessment—Iink to LO7)

。 SeIf-assessment (aIignment with LO2/3/7)

。 Future improvement directions.

•   Q&A: Open discussion on project-related topics (prepare to answer questions about programming application, triple integration, and ethical issues—link to LO2/3/7).

6. AI Usage Category

Continue to follow Category II – Use only with full acknowledgement:

•   Authorized AI usage: AI tools for literature summary, draft creation (artworks, code snippets), data preprocessing, etc.

•   Mandatory requirement: Clearly acknowledge AI usage in the logbook, academic paper, and presentation. Example: “We used Stable Diffusion 3/ Jimeng to generate initial image drafts (prompt: ‘abstract landscape with Chinese ink wash style’), and all drafts were artistically revised and integrated into the interactive project. We also used ChatGPT to draft Python code snippets for image preprocessing, which were manually adjusted to match our artistic needs (aligned with LO2).”

•   Consult the course coordinator/teacher in advance if unsure about the eligibility of any AI tool (especially for tools involving ethical risks—link to LO7).

7. Remarks

•   Final Submission Deadline: 1 December 2025, 23:59 (all deliverables except presentation; presentation to be delivered on 21/28/29 November as scheduled).

• Format & Platform. All materials must be submitted via Moodle. Accepted formats:

◦ Logbook/Paper/Dataset Description: Word/PDF

◦ Functioning Project: ZIP-compressed executable files/links (with operation guide)

◦ Dataset: ZIP-compressed raw + preprocessed files

◦ Presentation: PPT/PDF (pre-recorded video in MP4 format if applicable)

• Cover Page & File Naming:

◦   Paper/Logbook/Dataset Description: Must include a cover page with project title, participant names, student IDs, and a note of “Alignment with LOs: LO1-7” .

◦   File naming rule: “[Project Title][Name][Student ID]_[Deliverable Type]” (e.g., “AI Ink Wash Landscape_Zhang San_2023001_Report”).

◦   Group submission: Each member submits the same set of materials with their own name and student ID in the file name.

• File Compression: Compress all deliverables (excluding presentation video) into one ZIP

file (size ≤ 200 MB) for submission. Label the ZIP file as “[Project Title][Group/Individual][All Student IDs]_Final Submission” .

• Source Files: Include all programming files (e.g., in-class exercise codes, project

experiment scripts—link to LO2) in the compressed file, labeled as “Source Files” with a README explaining each file’s function.