Topic Research: AI in eLearning Predictions The End of SMEs?

Does AI in eLearning Topic Research belong in the SME Parade?

With generative Artificial Intelligence (AI) creating content quickly at lightning speed, organizations can achieve unprecedented efficiencies, but the risks of AI innovation and loss of real-world understanding still loom on the horizon. How do we deal with this change, achieving the right balance between the efficiency of AI and the irreplaceable value of human expertise?

The Emergence of Subject Matter Knowledge in Training

For years, organizations have relied on Human Resource Professionals (SMEs) to create training materials. These professionals bring deep domain knowledge and guide content creation, but this traditional approach comes with significant challenges. Organizations often struggle with limited availability of expertise, high consulting costs, and the time-consuming nature of information transfer. These constraints often create bottlenecks in the development of content, which slows down the entire training process.

Advantages of Generative AI in eLearning

Generative AI brings huge benefits to eLearning content creation by speeding up the process and making it more efficient. It can edit content in minutes and quickly generate different versions to suit different learning styles. AI also lowers costs by reducing the need for expensive subject matter experts and automating tasks like translation. It keeps things consistent throughout, ensuring consistent tone and wording while following good design practices. AI is also highly scalable, making it easy to adapt content for different levels and update learning materials quickly. Also, it can collect and cite information from multiple sources, ensuring that the content is well-integrated and reliable.

Challenges in AI Topical Research

While AI offers many benefits to eLearning, it comes with some challenges and risks. One major concern is accuracy, as AI can sometimes produce factual errors or outdated information, which requires thorough fact-checking. Human supervision is also required to ensure quality, especially in capturing industry-specific information and avoiding overly generic content. AI has technical limitations as well, such as a lack of emotional intelligence, functional intelligence, and difficulty in creating complex or interactive visualizations. The tacit knowledge that human experts bring from experience may also be missed. Using AI can require significant setup, clear guidelines, and may face resistance from native content creators accustomed to manual processes.

Enter STORM: AI-Powered Knowledge Curation

In an amazing development that is sending waves through the Learning and Development (L&D) sector, Artificial Intelligence is poised to revolutionize the way we create training materials. With Stanford University’s innovative STORM technology leading the way, we are seeing a fundamental shift in the way organizations approach content technology and content creation.

Stanford’s STORM, which stands for Synthesis of Topic Outline through Retrieval and Interdisciplinary Questioning, represents a much-needed shift in the way we approach subject knowledge. This open source AI tool automates information classification through a complex process that includes topic identification, information retrieval, and multi-viewing. The system works by simulating conversations between various professional agents, ensuring comprehensive coverage of topics while maintaining accuracy and reliability.

The Power of STORM Interactive SI

Building on the core technology, Co-STORM introduces a new collaborative feature. Think of it as a virtual round table where AI experts and humans work together to explore and understand topics in depth. This collaborative environment enables real-time information integration and dynamic evaluation of complex subjects, making it particularly useful for the development of training materials. Users can watch AI-driven conversations or actively participate by asking questions and directing the conversation to specific areas.

A Changing Subject Study of Training Content

STORM’s impact on the development of training materials is huge. The experience of Dr. Philippa Hardman’s technology demonstrates its incredible efficiency, producing comprehensive summaries of peer-reviewed research and industry reports in just three minutes. This level of speed and efficiency cannot be achieved with traditional SME consulting methods.

Using STORM I was able to create a coherent summary of peer-reviewed research, industry reports, and other reliable resources on a specific subject in ~3 minutes.
– Dr Philippa Hardman

However, STORM’s value goes beyond just speed. The technology is at the forefront of integrating information from multiple reliable sources, ensuring that the subject research of the training material is complete and well organized. By integrating diverse perspectives and maintaining relevant citations, the Stanford AI assistant creates content that meets high academic standards while saving valuable time and resources.

Balancing AI and Human Technology

Although STORM shows great promise, it is important to acknowledge the challenges and considerations in using AI to train content development. The risk of AI bias—where the AI ​​produces information that makes sense but is incorrect—requires careful human vigilance. Content validation and fact-checking are still important steps in the development process.

The role of human expertise is not diminished; rather, it is developing. Instead of spending hours researching and compiling information, human experts can focus on validating content, adding real-world context, and ensuring that training materials align with organizational needs and learning objectives.

Looking to the Future of AI in eLearning

The evolution of STORM and similar technologies points to a future where the creation of training content is more accessible and efficient. Organizations can reduce their reliance on traditional SME consulting while maintaining high quality standards. This change would democratize access to expertise, allowing smaller organizations to create comprehensive training services that were previously inaccessible due to budget constraints.

Forecasting Clear Skies Ahead

As we face this technological climate, organizations should carefully consider how to integrate AI-enabled tools like STORM into their training development processes. The key lies in finding the right balance between the AI’s capabilities to leverage while maintaining the quality and authenticity that a human expert brings to the training material. Rather than viewing AI as a replacement for Content Experts, we should see it as a powerful tool that enhances and accelerates the content development process.

How we navigate the technology climate today will change the outlook for training and development in the future. By thoughtfully and strategically adopting AI tools, organizations can create training programs that are not only a breeze but also efficient, effective, and efficient—while retaining the human touch that makes learning shine.