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AI is evolving at an incredible rate, specifically video generation. Theoretically, AI software will soon be able to take an instructor's face and generate a video of them giving a full lecture. What are the possible implications/uses/consequences/controversies that can stem from the technology evolving to this point?

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•Integration of AI tools may speed up development processes.

•Stand alone tools will be adopted by faculty to bypass development processes.

•If the development is collapsed or squeezed out of the development cycle, then is the role of instructional designers going to be focused on humanizing education

What does humanizing mean in this context?

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Does the job description of future Instructional and Media designers include use of AI/ML tools? Knowledge of Python?

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What does your job as an instructional designer look like in the age of AI? What new skills do you need to be successful?

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Evaluating issues of intellectual property and confidentiality. For example, is my content and intellectual property protected if I utilize certain AI tools? What are the best practices to ensure my intellectual property is protected? Is my confidentiality protected?

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Debate Topic: Is Artificial Intelligence Making Higher Education Obsolete?

Overview:

The accessibility and affordability of Artificial Intelligence (AI) learning platforms are transforming the educational landscape. Proponents argue that AI can deliver personalized, on-demand learning for a fraction of the cost of traditional universities. This raises the question: is Higher Education becoming irrelevant in the face of AI-powered learning?

Arguments for AI Replacing Higher Education:

Cost: AI platforms offer significantly cheaper access to a vast amount of knowledge.

Accessibility: Learning becomes flexible and available anytime, anywhere.

Personalization: AI tailors learning to individual needs and pace, potentially leading to faster and more efficient knowledge acquisition.

Arguments for the Continued Importance of Higher Education:

Human Interaction: Universities provide valuable in-person interaction with professors and peers, fostering critical thinking, communication, and teamwork skills – crucial for success in the workforce.

Credentials: Degrees from accredited institutions hold weight in the job market and are often required for certain professions.

Structured Learning: Universities offer a structured learning environment that provides guidance and deadlines, beneficial for some students who thrive with such a framework.

Specialized Fields: For specialized fields, universities offer in-depth research opportunities and access to cutting-edge facilities not readily available through AI platforms.

The Future of Education:

The debate is not necessarily a binary choice. The future of education might involve a blended model that leverages the strengths of both AI and traditional methods:

AI-powered learning can personalize foundational knowledge acquisition.

Universities can focus on developing critical thinking, communication, and social skills that complement AI learning.

HigherEd institutions may specialize in offering accredited degrees and fostering groundbreaking research alongside AI platforms.

Debate Prompt: Consider the arguments for both sides and weigh in: Will AI make Higher Education obsolete, or will the two find a way to co-exist and create a more powerful learning experience?

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Teaching AI Literacy to students: What to do with the content AI spits out (It's even at the top of my google searches!)

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Moving from Exploration to Adoption:
Generative AI has garnered much attention from various disciplines, including instructional design, due to its possible 'transformative' potential. In our endeavor to benefit from these tools, it is important to take into account various factors such as:

Motivation: What problems are we trying to address with the use of generative AI?

Outcomes: What does/would the use of a tool look like in practice? What was the process and the final result?

Effectiveness: Are we ready to take the next step and adopt certain tools? What criteria should be used to make the final decision?

We will discuss real-world examples of AI implementation in instructional design. Discuss both the successes and the challenges faced. Highlight practical tips for managing expectations and maximizing efficiency.

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Navigating Challenges and Limitations of AI

How can we ensure that AI enhances rather than undermines the quality of education? As AI technology continues to advance, it brings with it several challenges and limitations that we must navigate such as:

Technocentrism:

AI/Innovation Fatigue: Burnout resulting from the continuous need to adapt to new AI tools and technologies.

Sustainability: Using an avatar or AI assistant to attend meetings or allow you to multitask sounds great- but what happens when everybody does it? Are we considering AI tools through this filter?

Gullibility: Acceptance of AI outputs without critical evaluation.

Misperceptions of How LLMs Work: Misunderstandings about large language models, such as thinking they have a database, memory, as well as anthropomorphism.

Misuse of ChatGPT: For instance, using chatgpt as an AI detector, production of low quality content.

Education Value Questions: What happens when AI is used simultaneously on both ends of the academic experience - by students for generating assignments, and instructors to grade and give feedback on assignments?

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How does AI affect accessibility in general? Does it make accessibility easier or harder?

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How can AI tools improve the accessibility of media content for people with disabilities

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Using AI to help write rough draft scripts for educational online videos.

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What potential tools in AI could revolutionize educational video production.

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The Dehumanization of Learning Experiences and lack of Faculty Presence.

Does the use of AI create less of a connection between faculty and students? Is there a loss of the human touch? How can AI leverage the faculty members time and efficiency to better enhance the course and allow faculty time to actively engage with their students.

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Using AI as a Research Partner to Bounce Ideas with. I learn better when I discuss ideas with someone. When reading research I ask GPT to read the same pdf and I initiate a discussion with it, kind of inquiry based learning. I also relate the new information to other ideas I have explored in the past to create new associations. This process can be added to courses for students to use AI to learn faster and about more topics. This process can be tweaked by the students to make it their own and personalize it.

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Best practices for disclosing and documenting/citing use of AI - instructors, students, etc.

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AI-driven feedback tools/autograding tools used by educators, especially in large class settings.

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Potential risks of overreliance on AI tools in education.

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How AI can be used for student-educator collaboration in co-designing personalized learning journeys or adaptive learning experiences for students.

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The role of the instructional designer in the era of AI: knowledge, skills, and values

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Using AI to provide better, more robust feedback to students (for example, on performance-based assessments)

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Exploring ways we can use AI to use course content to help students study more effectively

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Discussion: Rethinking Assignments.

Assignments may have to evolve to focus more on measuring critical thinking creativity, decision making where students justify why they followed a certain thought process. By designing complex projects that integrate presenting their thought process and decisions they took may be one way to mitigate AI doing the work for the students.

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Discussion: Understanding AI's Role and Potential

Integrating AI into the curriculum involves using it as a tool to enhance learning rather than viewing it as a threat. The discussion can center on using demonstrations and employing AI-based tools for simulations or data analysis. It is also important for both students and faculty to become aware of AI capabilities, limitations, ethical concerns, and potential biases.

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I would like to have a discussion around the topic of helping faculty overcome their resistance to adopting using AI. Some examples of resistance include:

I don't think it is ethical for me to use Gen AI in my course development because I am "cheating" by asking a computer to do my work.

Using Gen AI to create scripts, assignments, learning objectives, etc. is not my writing so it sounds different.

I don't have time to learn the new tools.

etc.

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Protecting and securing access for voice clones or digital twins we might create during our media production process.

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Would like to know more about how to use AI to rate user satisfaction during a course.

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AI tools to create formative assessments

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More easily create customized "choose your own adventure" style scenarios and situational response-style learning.

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Generate math, plots, diagrams, and code. Sources: (1) hand-drawn, (2) from text or voice input.

https://mathpix.com

https://simpletex.net

https://docs.google.com/presentation/d/1EiGxC8xxFmSUsdzoC6YALCuj2qm_5BACqVpTjBq6XQo/edit?usp=sharing

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Best Practices for Integrating AI in Learning and Instructional Design

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Popular AI Applications in Instructional Design

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Top AI Tools for Instructional Design and Creativity

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Creating Custom AI Applications and GPTs

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Leveraging AI for Personalized Learning

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Addressing Bias, Privacy, and Transparency in Educational AI 