Date: 10/5/2025

Panelists: Margaret Spence, Alyssa Chuck

Tags: AI workgroup, AI, compliance, risk, talent development 

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AI Generated Summary: 

The group explored AI risks and compliance, discussing the outputs from large language models and the importance of proper prompting and verification when using generative AI tools.

AI Risk Assessment and Compliance

The meeting focused on discussing AI risks and compliance, with panelists Margaret Spence and Alyssa Chuck sharing their insights on the outputs from large language models (LLMs) regarding generative AI risks. Margaret noted that the input prompt was insufficiently detailed, while Alyssa highlighted the robustness of the responses and emphasized the importance of basic AI literacy. Both agreed that the LLMs missed significant risks, with Alyssa expressing concern about the lack of citations to European AI policies. The discussion also touched on the need for better vendor vetting and the potential pitfalls of relying on free, easily accessible AI tools like ChatGPT. The session concluded with conversations about AI's impact on various fields, including design work with Canva AI, and plans for new membership types and educational initiatives focused on AI training and project sharing.

Generative AI and Information Retrieval

The group discussed the use of generative AI and search engines for information retrieval. Margaret emphasized the importance of effective prompting and highlighted that different AI models, such as ChatGPT and Perplexity, provide varying levels of useful information. She suggested asking AI models what one should know about a topic as a strategy to receive relevant guidance. Alyssa noted the distinction between generative AI and search engines, pointing out that search engines often lead users to external sources like Wikipedia, which may not be suitable for research purposes. Margaret warned about AI hallucinations and suggested double-checking AI-generated content by searching for the information on Google to verify its accuracy and originality. Steve Yudewitz noted that even when AI is asked to double-check its responses, it may still make mistakes. The group also discussed the need for critical thinking when using AI tools and the importance of verifying sources, especially when dealing with copyrighted material.

AI Adoption and Bias Challenges

Margaret and Alyssa discussed their experiences with different AI models, finding Gemini the most practical and Claude the least reliable. They emphasized the importance of understanding AI laws and regulations, particularly for talent development professionals who are being asked to train others on these models. Margaret highlighted the need for organizations to strike a balance between AI guardrails and learning opportunities, as excessive restrictions can hinder AI adoption. They also discussed the challenges of unconscious bias in AI prompts and outputs, with Margaret sharing data on how women and neurodiverse individuals are disproportionately affected by AI disruptions in the workplace.

Bias Mitigation in Generative AI

The group discussed strategies for mitigating bias in generative AI, with Margaret emphasizing the importance of questioning AI outputs and Alyssa suggesting the use of thumbs up/down buttons with detailed explanations. George announced the formation of three breakout rooms focused on different AI tools (ChatGPT, Gemini, and Claude), and helped participants select their preferred rooms. After the breakout sessions, the conversation ended with a brief Q&A session followed by an optional networking period.

AI Evolution and Human Touch

The group discussed the impact of AI on various fields, with Margaret emphasizing that Claude will continue to be a leading tool for coding and writing due to its superior capabilities. They explored how AI tools like ChatGPT, Copilot, and others are evolving and potentially replacing traditional software and search engines. The conversation also touched on the importance of representation in AI-generated content and the need for sensitivity in AI applications, as highlighted by Victoria Brenes and Alyssa. The conversation ended with a reflection on the value of human touch in communications, with members emphasizing the irreplaceable role of human interaction and personalization.

Canva AI 

The group discussed using Canva AI for design work, with several members sharing their experiences and tips. Alyssa explained how to effectively use Canva AI for images by providing simple, metaphor-based prompts, while Margaret revealed that Claude is now integrated with Canva as its backend.

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Date: 8/30/2025

Panelists: Barb Potter, Dr. Victoria Brown

Tags: AI workgroup, AI, talent development 

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AI Generated Summary: 

The AI workgroup kickoff meeting focused on exploring and leveraging AI tools for talent development professionals. During the meeting, participants discussed various aspects of AI usage, including prompt engineering, ethical considerations, and technical limitations, while breakout rooms were organized for more focused discussions.

AI Tools for Talent Development

Panelists discussed their impressions of large language model outputs, noting that while the information was basic, it provided a good starting point for those new to AI. They identified missing concepts such as content acceleration, ideation nuances, and bias sources in AI. The panelists also shared their experiences with prompt engineering and the limitations of AI in creating new ideas versus regurgitating patterns. The conversation ended with a discussion on refining AI definitions and the importance of context in AI outputs.

AI Prompt Strategies and Ethics

The group discussed how prompts influence AI responses, with Barb Potter and Dr. Brown sharing their experiences using AI tools like ChatGPT. They noted that AI can learn user preferences and styles but emphasized the importance of starting with personal input and iterating. Dr. Brown highlighted that AI could reflect user search patterns and suggested being critical of AI-generated content, while Barb shared strategies for crafting effective prompts, including being specific about audience and format. The discussion concluded with Dr. Brown and Steve Yudewitz stressing the need for due diligence when using AI, such as verifying sources and ensuring accuracy.

AI Tools Breakout Room Organization

The meeting focused on organizing participants into breakout rooms for discussions on AI tools, with George Romagosa and Steve explaining the process and assigning rooms to Barb, Dr. Brown, and Victoria Brenes. After the breakout sessions, participants reconvened for a general discussion and QA session

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Date: 4/8/24

Presenter: John Kilroy

Tags: instructional design, AI

AI Generated Summary:

This Zoom meeting was for an audience of instructional designers and focused on the transition from instructional designer to digital learning professional.

The meeting was hosted by the Digital Learning Institute (DLI). The speaker, the founder of DLI, discussed the institute’s mission to elevate standards in digital education and online learning.

DLI’s Offerings and Background: The speaker provided background information about the Digital Learning Institute (DLI), including its university-accredited courses in digital learning design and the diverse backgrounds and global locations of its students.

The main sections of the meeting included:

• Skills 1st Agenda:

• • The speaker emphasized the importance of reskilling and upskilling, driven by factors like AI and the diversification of the workforce.

  • By 2030, 50% of workers are expected to need reskilling, and 44% of jobs will require it (Source: World Economic Forum).

  • The challenge for learning professionals is to address this reskilling demand by designing agile and engaging learning experiences.

  • The discussion highlighted a shift towards a "skills-first" approach, focusing on capabilities and potential, rather than just roles or career paths.

  • Learning programs should aim to develop both broad and deep skills, including transferable skills like collaboration, communication, and digital literacy, to future-proof both individuals and organizations.

  • • Reskilling and Upskilling: The agenda begins with the recognition that a significant portion of the workforce will need to acquire new skills due to the impact of AI and the changing nature of work.

    • Addressing the Reskilling Challenge: Learning professionals are tasked with creating learning experiences that are not only effective but also agile and can be delivered rapidly to meet the demands of a changing job market.

    • Shift to a Skills-First Approach: This involves a fundamental change in how organizations view talent development, moving away from focusing on specific job roles or career paths to instead prioritizing the capabilities and potential of individuals.

    • Designing Learning Programs Around Capabilities: Learning programs should be designed to cultivate the skills that organizations need to be agile, adaptable, and future-proof.

    • Developing Broad and Deep Skills: The agenda emphasizes the importance of developing both specialized skills (depth) and a wide range of transferable skills (breadth), such as collaboration, communication, and digital literacy.

• Transition from Instructional Designer to Digital Learning Designer:

• • The speaker explored the evolving roles in the learning and development field, noting the emergence of roles like learning engineer and learning scientist.

  • These roles require a blend of learning science, engineering, and computer science.

  • The speaker also introduced DLI’s design framework, which aims to simplify the design process for learning experiences across various delivery modes, including blended, hybrid, and fully digital learning.

  • • The framework seeks to address the increasing complexity of designing learning experiences across different modes of delivery.

    • The speaker mentioned that the framework includes templates.

    • The speaker planned on sharing the full framework and templates with the participants.  

• Examples and AI:

• • AI in Learning Design: The discussion covered how AI is being used in learning design, including AI tutors that offer personalized learning and feedback. It also addressed AI's broader role in creating personalized learning experiences.

  • Data and Privacy: The speaker stressed the importance of tackling issues related to data and privacy, such as student concerns about how their data is used and whether it will affect their grades. The speaker also noted that younger learners tend to be more open to sharing their data compared to older learners.

  • Quality Assurance: The meeting highlighted the necessity of quality assurance and applying learning science principles when using AI-generated content.

  • AI Prompting and Frameworks: The speaker provided an AI prompting worksheet and introduced the CARE framework (Context, Action, Results, Examples) for effective prompt engineering.

  • Addressing Concerns about AI: The speaker acknowledged that some subject matter experts are resistant to AI, fearing it might replace them. The speaker offered strategies for introducing AI tools, such as piloting them for specific tasks and working with current technology providers..

  • The framework seeks to address the increasing complexity of designing learning experiences across different modes of delivery

  • The speaker mentioned that the framework includes templates.

  • The speaker planned on sharing the full framework and templates with the participants.