Description

Unlock the creative potential of generative AI while navigating ethical and legal challenges in this theory-based course. Learn the strengths and limitations of AI, from content creation to breaking through creative block, and gain insights into bias and plagiarism.

In today's world, artificial intelligence (AI) is changing the way we create content. AI models like ChatGPT and DALL-E 2 are becoming increasingly sophisticated, enabling us to generate high-quality text and images at an unprecedented speed and scale. As a result, it's essential for creatives to understand how to leverage these tools effectively. In this course, you will learn the fundamentals of generative AI and how to use it ethically and responsibly. You will discover the strengths and limitations of these models and when to use them for content creation. You will also explore various applications of AI in the creative industries and the legal and ethical implications of using these tools. The course begins with an introduction to generative AI and an overview of popular models such as ChatGPT and DALL-E 2. You will then delve into the strengths and limitations of AI, including its ability to create content quickly, revise content, and break through creative block. You will also learn about the limitations of AI, including the finite nature of training data, issues of accuracy, plagiarism, and bias, and the need for human modification. By the end of the course, you will have a solid understanding of the role of AI in content creation and the ethical considerations that come with using these tools. You will be able to navigate the strengths and limitations of AI and make informed decisions about when and how to use it.

What You Will Learn

Navigate risks and limitations of AI
Master prompt engineering techniques for quality output
Understand key legal concepts for professional usage
Address AI bias to improve creative work
Develop AI guidelines for team best practices
Embrace transparency for unique human perspective

Audience

This course is designed for creatives, marketers, and anyone interested in learning how to use generative AI tools for content creation. No prior experience with AI is required, as the course covers the fundamentals of AI and the capabilities and limitations of generative AI. However, a basic understanding of digital media tools and technology is recommended. You should also have access to a computer and a stable internet connection.

Approach

The course learning approach is based on a theory-driven framework, providing a comprehensive understanding of the concepts and applications of generative AI. The course also includes hands-on experiences, case studies, and real-world examples to enhance the learners' skills and knowledge.

Key Features

Guidance on developing AI guidelines and understanding financial implications * Learn to navigate ethical and legal challenges in generative AI * Determine when to leverage your human perspective, and when to take advantage of AI's strengths

Github Repo

https://github.com/PacktPublishing/ChatGPT-and-DALL-E-Sell-Your-Creative-Thinking-with-AI

About the Author

AI Daily LLC

AI Daily is a collective of creatives and technologists with a passion for teaching responsible use of artificial intelligence. With over a decade of experience at leading tech firms and agencies, our experts are well-equipped to help learners of all levels stay current with the latest AI advances and seamlessly integrate them into their workflow. From complex ethical and conceptual issues to technical know-how, our courses cover all aspects of generative AI for creative use, featuring tools such as ChatGPT, DALL-E 2, and Midjourney. Hannah Peterson is a multidisciplinary creative director based in Los Angeles, CA. She has been fortunate enough to work with some of the top brands in the world in tech, entertainment, and CPG including Amazon, Meta, Microsoft, Disney, Motortrend, NBC Universal, FOX Networks, Western Digital, Stanley, Black & Decker, Nature's Bakery, and Tullamore Dew. Her expertise is in branding, advertising, and packaging. Inspired by recent innovations in artificial intelligence, she founded AI Daily as a way to help bridge the gap between creativity and technology. AI Daily's mission is to empower creative professionals with guidance to integrate AI into their daily workflow.

Course Outline

1. Introduction

In this section, we will be introduced to the course and the topics that will be covered throughout. We will begin by exploring the basics of AI and its relationship with creativity. We will then delve into the world of Open AI and deep learning, providing an overview of how these technologies work. Finally, we will introduce you to the deep learning models that power many AI systems, including GPT-3, GPT-3.5, and GPT-4.

1. Welcome to the Course

In this video, we will welcome you to the course and provide an overview of what you can expect to learn. We will discuss the importance of AI in today's world and how it is shaping the future of many industries.

2. Why AI Can't Replace Creatives (But We Should Still Learn It)

In this video, we will explore the relationship between AI and creativity. We will discuss why AI can never fully replace human creativity but why it is still essential for creatives to understand and learn about AI.

3. Introduction to Open AI and Deep Learning

In this video, we will provide an introduction to Open AI and deep learning. We will explain the basics of how these technologies work and their applications in the real world.

4. ChatGPT Demo (Optional)

In this video, we will provide a demo of ChatGPT, a deep learning model used for generating human-like text. This video is optional for those who are already familiar with ChatGPT.

5. DALL-E 2 Demo (Optional)

In this video, we will provide a demo of DALL-E 2, a deep learning model used for generating images from text descriptions. This video is optional for those who are already familiar with DALL-E 2.

6. GPT-3, GPT-3.5, and GPT-4: Meet the Deep Learning Models Behind the Scenes

In this video, we will introduce you to the deep learning models that power many AI systems, including GPT-3, GPT-3.5, and GPT-4. We will discuss their capabilities and how they are used in various applications.

2. When (And When Not) to Use AI

In this section, we will explore the strengths and limitations of using generative AI and when it's appropriate to utilize it in content creation.

1. The Strengths and Limitations of Generative AI

In this video, we will discuss the advantages and disadvantages of using generative AI for content creation.

2. Strength 1: Creating Content in Mass, Quickly

In this video, we will explore how generative AI can be used to create large amounts of content in a short amount of time.

3. Strength 2: Revising Your Original Content

In this video, we will look at how generative AI can help you revise and improve your existing content.

4. Strength 3: Breaking Through Creative Block

In this video, we will discuss how generative AI can be a useful tool for overcoming creative blocks and generating new ideas.

5. Introduction to Limitations

In this video, we will introduce the limitations of using generative AI for content creation.

6. Limitation 1: The Training Data Is Finite

In this video, we will discuss the limitation that the training data used to train generative AI models is finite, which can impact the quality of the output.

7. Limitation 2: Output Is Not Reliably Accurate

In this video, we will examine the limitation that generative AI output is not always accurate or reliable.

8. Limitation 3: Output Can Be Plagiarized and Biased

In this video, we will discuss the limitation that generative AI output can be plagiarized and biased, which can be problematic in certain contexts.

9. Limitation 4: AI Work Will Need to Be Modified

In this video, we will look at the limitation that AI-generated content will often need to be modified or edited by humans.

10. Limitation 5: Apps Can Go Down

In this video, we will examine the limitation that generative AI apps and services can go down, causing disruptions in content creation workflows.

11. Limitation 6: AI Works in a Vacuum

In this video, we will discuss the limitation that generative AI works in a vacuum and does not have an understanding of the broader cultural or social context in which it's used.

3. Prompt Engineering

In this section, we will delve into the art of prompt engineering. We will explore the various tips and techniques that can help you create effective prompts that can improve the quality and relevance of your AI-generated content.

1. The Art of the Prompt

In this video, we will discuss the importance of crafting good prompts for your AI models. We will also explore the key elements of an effective prompt and provide some tips on how to make your prompts more precise and relevant.

2. Tip #1: Be Specific

In this video, we will discuss the first tip for prompt engineering, which is to be specific in your prompts. We will talk about why specificity is important and provide some examples of specific prompts.

3. Tip #2: Reference a Style

In this video, we will explore the second tip for prompt engineering, which is to reference a style in your prompts. We will discuss the importance of referencing a particular style and provide some examples of prompts that reference a style.

4. Tip #3: Give Context

In this video, we will discuss the third tip for prompt engineering, which is to give context in your prompts. We will explore why context is important and provide some examples of prompts that give context.

5. Tip #4: Adjust with Feedback

In this video, we will explore the fourth tip for prompt engineering, which is to adjust your prompts based on feedback. We will discuss the importance of feedback and provide some tips on how to use feedback to improve your prompts.

4. AI and Bias

In this section, we will explore the issue of bias in AI systems. We will discuss why AI systems can be biased, provide examples of biased AI, and explore some ways to address bias in creative work.

1. Why Are AI Systems Biased?

In this video, we will discuss why AI systems can be biased. We will explore the various factors that can contribute to bias in AI systems, including biased training data and biased algorithms.

2. Examples of Biased AI

In this video, we will provide some examples of biased AI systems. We will explore how bias can manifest in different types of AI systems and provide some real-world examples of biased AI.

3. How to Address AI Bias in Creative Work

In this video, we will explore some ways to address bias in creative work that involves AI systems. We will discuss the importance of being aware of bias and provide some tips on how to mitigate bias in your AI-generated content.

5. Ask an Attorney: Understanding the Legal Landscape of Generative AI

In this section, we will explore the legal landscape of generative AI and its impact on creative professionals. We will discuss key legal concepts and how they apply to generative AI, including ownership, authorship, trademark law, and ethics. You will also learn about intentional plagiarism and the legalities surrounding style references.

1. Overview of Key Legal Concepts (As They Apply to Creative Professionals)

In this video, we will provide an overview of the key legal concepts related to generative AI that creative professionals should be aware of. You will learn about copyright law, fair use, and how they apply to generative AI.

2. Ownership, Authorship, and Trademark Law

In this video, we will delve deeper into the concepts of ownership, authorship, and trademark law. You will learn about the legal rights of creators and how they can protect their work in the realm of generative AI.

3. Ethics and Legalities of Style References

In this video, we will explore the ethics and legalities surrounding the use of style references in generative AI. You will learn about the importance of citing sources and how to avoid potential legal issues.

4. Intentional Plagiarism

In this video, we will discuss intentional plagiarism and its consequences in the world of generative AI. You will learn how to recognize and avoid intentional plagiarism, and how to protect your work from being plagiarized by others.

6. The Importance of Transparency

In this section, we will discuss the importance of transparency in the development and use of generative AI. You will learn about the ethical considerations of using AI in creative work, and how to develop AI guidelines to ensure transparency and accountability.

1. Developing AI Guidelines

In this video, we will discuss how to develop AI guidelines for your creative work. You will learn about the key components of AI guidelines, including transparency, accountability, and ethical considerations. You will also learn about the importance of involving all stakeholders in the development of AI guidelines.

7. Financial Implications

In this section, we will dive into the financial aspects of generative AI and how it impacts creative professionals. We will discuss the costs associated with developing and using generative AI tools, such as app subscriptions and additional training resources. We will also explore how to reframe creative selling points in the context of generative AI.

1. Cost of Apps and Subscriptions

In this video, we will discuss the financial costs of generative AI tools. We will cover the costs associated with using these tools, such as app subscriptions and licensing fees. We will also explore the financial implications of using these tools in your creative work.

2. Additional Training and Resources

In this video, we will explore the additional training and resources necessary to use generative AI effectively. We will discuss the importance of continued learning and professional development in the field of generative AI and provide tips for finding and accessing these resources.

3. Revisiting Creative Selling Points

In this video, we will revisit the creative selling points of generative AI and explore how to communicate these benefits to clients and stakeholders. We will discuss the unique advantages of generative AI, including increased efficiency, creativity, and scalability.

8. Selling Your Creative Thinking

In this section, we will explore how to leverage generative AI in the creative selling process. We will discuss the difference between ideas and execution and how to present your ideas effectively. We will also examine a real-world case study of Heinz using generative AI in their marketing campaign.

1. The Idea Versus The Execution

In this video, we will discuss the difference between ideas and execution in the creative process. We will explore the importance of communicating your ideas effectively and how to leverage generative AI to enhance the execution of these ideas.

2. Putting It All Together: Heinz Case Study

In this video, we will examine a real-world case study of Heinz using generative AI in their marketing campaign. We will explore the benefits and challenges of using generative AI in a creative campaign and provide insights into how to use generative AI effectively in your own work.

3. Conclusion

In this video, we will summarize the key concepts and topics covered in this course. We will provide a final reflection on the importance of generative AI in the creative field and how to navigate its ethical, legal, and financial implications.

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ChatGPT and DALL-E: Sell Your Creative Thinking with AI

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