---
title: Designing with Extended Intelligence 
page_type: course
track: Exploration
course_type: Workshop
feature_img: /assets/images/2023-24/year-1/t-2/designing-with-extended-intelligences.png
img_caption: Credit | 4x upscale of ‘a press photo of a bright maker lab full of students hacking programming and building physical prototypes --ar 3:2 --v 5.2’ (Copyright Midjourney, Christian Ernst)
faculty:
    - christian-ernst
    - pietro-rustici
ects: 2
---

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## Syllabus

The course offers designers and makers a comprehensive introduction to the field of generative artificial intelligence (AI). The program focuses on empowering participants with the knowledge and skills required to extract mainstream AIs (such as GPT or DALL-E) into external interfaces. 

Course Contents:

- Showcase of Salient Projects: The instructors will showcase their most salient and relevant projects that demonstrate the creative possibilities of generative AI for designers and makers.

- Introduction to Generative AI: Participants will gain a clear understanding of the concept of generative AI, its principles, and its applications. They will learn about algorithms, models, and techniques used in generative AI.

- Exploring OpenAI: Students will be introduced to OpenAI, a powerful platform for developing AI-based applications. They will learn how to access and utilize OpenAI tools to leverage generative AI for their own projects.

- Web-Based Application Development: The course will provide hands-on training in developing a small application using generative AI algorithms. Participants will learn how to create a web-based application that connects to OpenAI and generates unique designs based on user inputs.

- Design Considerations and Ethics: The course will also address the ethical considerations associated with generative AI. Participants will learn about responsible AI usage, ethical design principles, and the importance of considering privacy and bias while utilizing generative AI for their projects.

By the end of this short course, participants will have developed a solid foundation in generative AI and gained practical experience in creating their own web-based application utilizing OpenAI. They will be equipped to explore the endless possibilities of generative AI in their future design and making endeavors.

**Keywords: Generative Artificial Intelligence, AI-Driven Web Applications, Rapid Prototyping**

### Learning Objectives

- Gain a clear understanding of the concept of generative AI, its principles, and its applications.
- Learn about algorithms, models, and techniques used in generative AI.
- Develop practical skills in utilizing OpenAI tools for generative AI projects.
- Acquire hands-on experience in developing a web-based application using generative AI algorithms.
- Understand the ethical considerations and responsible usage of generative AI.
- Develop a solid foundation in generative AI for future design and making endeavors.

### Methodological Strategies

- Introductory lectures to build an understanding of the problem space
- Group project execution phase to apply learnings on a chosen topic 
- Academic understanding
- Hands-on/ tactile experience
- Learning by application
- Collaborative project execution
- Iterative Design, Design Thinking

## Schedule

=== "Day 1"

    - Introduction, who we are. Pietro, Chris + DOTTOD
    - Projects showcase 
    - Introduction to the class assignment
    - Group making and hardware setup (helping students to get started)

=== "Day 2"

    - The evolution of LLMs and diffusion models
    - Understanding how to query LLMs
    - Introduction to the anatomy of a web app and to API calls
    - Follow-up support for the class assignment

=== "Day 3"

    - Project Execution in Group Work
    - Students presentation

## Deliverables

A fully functional web demo, linking multimodal inputs and outputs with generative AI, based on a strong conceptual foundation. 15-minute presentations of the latter, demonstration of the former. Course documentation on the students’ blogs summarizing project outcome and personal reflection. 

## Grading Method

| Percentage  | Description                         |
| ----------- | ------------------------------------|
| 20%         | Participation                       |
| 30%         | Prototype and Conceptual Quality    |
| 30%         | Presentation                        |
| 20%         | Reflection                          |

!!! ects "European Credit Transfer and Accumulation System (ECTS)"

    {{ ects }} ECTS

## Additional Resources

- [Dottod I: gallery of cybernetic interpretations](https://www.dottod.net/) | Project
- [Dottod II: Icon's replicants](https://furnitures.dottod.net/) | Project
- [Del Complex / Del Complex Incident Report September 2023](https://xiosky.com/delmedia/media/archival_media/Del_Complex_Incident_Report_7_September_2023.pdf) | Project
- [Communicative Agents for Software Development](https://arxiv.org/pdf/2307.07924.pdf) Paper
- [The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"](https://arxiv.org/abs/2309.12288) | Paper
- [The Zizi Show](https://www.jakeelwes.com/project-zizi-show.html) | Project
- [Large Language Models as Optimizers](https://arxiv.org/abs/2309.03409) | Paper
- [Decomposing Language Models Into Understandable Components](https://www.anthropic.com/index/decomposing-language-models-into-understandable-components) | Article
- [Infinite Images and the latent camera](https://mirror.xyz/herndondryhurst.eth/eZG6mucl9fqU897XvJs0vUUMnm5OITpSWN8S-6KWamY) | Article

## Faculty

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