Episode 32 with Jeremy Tuttle: Balancing Innovation and Practicality when using AI in Instructional Design

In the ever-evolving field of instructional design, the integration of generative AI is becoming increasingly significant. The latest podcast episode featuring Jeremy Tuttle, Director of Learning Design at Niche Academy, delves into the practical applications, challenges, and ethical considerations of using AI tools like ChatGPT and Adobe Illustrator in educational contexts. Jeremy’s firsthand experiences provide invaluable insights into the current and future landscape of AI in learning design.

One of the primary topics discussed in the episode is the application of ChatGPT for text generation. While ChatGPT excels at generating realistic scenarios, Jeremy points out that creating effective learning materials still demands significant human intervention. The time-consuming process of editing and fact-checking AI-generated content often outweighs the benefits of using the tool for direct content creation. Instead, ChatGPT proves to be more useful for generating scenarios that help learners think through various situations. This highlights the need for a balanced approach where AI supports but does not replace human creativity and expertise.

The conversation also explores the challenges of using AI for image generation in Adobe Illustrator. Jeremy explains that while AI can produce visually appealing images, the intricacies of editing these images to meet specific design needs can be cumbersome. AI-generated images often come with a multitude of layers and groups, making it difficult to achieve the desired simplicity and style. This underscores the importance of human intervention in refining AI-generated content to ensure it aligns with the specific requirements of instructional design.

Drawing parallels between the current state of AI integration and the early days of UX/UI design, Jeremy discusses the balance required between innovation and practicality. The initial open possibilities of generative AI will eventually be refined into best practices, much like how customizable web pages of the MySpace era evolved into today’s streamlined interfaces. This historical perspective provides valuable context for understanding the ongoing refinement of AI applications in instructional design.

Looking ahead, the episode explores future trends such as learner personalization and chatbots. While these AI-driven tools hold great potential, their effectiveness hinges on understanding user needs and feedback. Jeremy emphasizes the critical role of user feedback in shaping the future of AI integration, ensuring that AI tools are developed in ways that genuinely enhance the learning experience.

The ethical dimensions of using AI in creative fields are another significant focus of the episode. The necessity of artists’ consent and fair compensation when their work is used in AI training pools is a pressing issue. Jeremy draws a provocative analogy to the Napster era, questioning the implications of AI-generated art on the value of creativity. This discussion advocates for stronger protections to ensure that art continues to thrive in the age of AI, highlighting the need for ethical standards and legislation to safeguard artists’ rights.

A noteworthy case involving Air Canada’s chatbot serves as a cautionary tale about the risks of relying on AI for authoritative information. The chatbot’s failure to provide accurate information led to a legal ruling against the company, illustrating the potential pitfalls of AI in critical contexts. This example underscores the importance of verifying AI-generated content to ensure its accuracy and relevance, particularly in professional and educational settings.

The episode also touches on the mental effort involved in creative tasks and whether AI-driven tools enhance or hinder true creativity. Jeremy questions the value of using AI for efficiency if it compromises the quality and intentionality of human-produced work. This discussion extends to the realm of instructional design, where the quality of learning materials must be maintained despite the increasing use of AI.

In terms of video creation, AI tools like Adobe Premiere’s Remix tool offer practical benefits. The Remix tool allows for seamless adjustment of music lengths in video projects, saving time and effort for instructional designers. However, the episode highlights that while AI can assist with certain tasks, the overall quality and effectiveness of instructional design still rely heavily on human expertise.

As the episode concludes, Jeremy expresses his hope for stronger legislation around the training material for large language models and other generative software. The protection of artists’ work and the preservation of the human element in art are crucial considerations as AI continues to evolve. This episode serves as a compelling exploration of the intersection between technology and artistry, advocating for a thoughtful and ethical approach to AI integration in instructional design.

In summary, this podcast episode offers a comprehensive overview of the innovations, challenges, and ethical considerations of using generative AI in instructional design. Jeremy Tuttle’s insights provide a nuanced perspective on the current and future landscape of AI in education, emphasizing the importance of balancing innovation with practicality and maintaining ethical standards to protect the value of creativity.