Six Considerations for using AI in Learning & Development

Artificial intelligence (AI) has been mainstream for some time, but many consumers have only recently begun to notice its prevalence. From personalized Google searches to Amazon product recommendations, content generators, and Alexa telling us to remember sunscreen, AI is everywhere. Despite AI’s role in our everyday lives, many people are apprehensive about the technology behind it. I firmly believe that AI isn’t here to replace humans but to enhance our capabilities and free up our cognitive load so that we can create and innovate more effectively—in our personal lives, professional environment, and even in the ways we develop leaders. 

At Blueline, I’ve become known as the ‘Tech Guy.’ In my previous role, our organization used machine learning and advanced algorithms to analyze massive datasets, and then take action on those findings. Helping others understand how to effectively utilize these types of tools was a prime concern for my team. Although today’s consumer-facing AI is a different application of these systems, I believe there is incredible potential for the creative application of AI tech. We’re using it to gain an edge in developing simulations that drive business transformation—while remaining cognizant of the potential risks and ethical considerations.

The benefits of using AI to create immersive simulations

AI tools offer numerous advantages when thoughtfully applied in our simulation development process. These include:

Increases in speed and scalability 

Using AI to generate creative assets, ranging from complex characters to abstract backgrounds, has significantly reduced the time and effort required to design certain graphic components of our sims. With AI, we’re able to quickly create custom visual content that meets the specific requirements of each client in a rapid, iterative fashion. 

Accelerated agility

Our custom-built and tailored learning experiences have always been constructed with flexibility in mind so that we can pivot and adjust to new requirements as a project rolls out. The speed of AI content generation and clean up has allowed us to become even more agile in our design and delivery processes. It’s well-known that the client’s needs and business conditions often change while we’re in development. AI tools enable us to generate, refine, upscale, and smooth media files provided by clients, allowing us to leverage more source material than ever before. With these new tools at our disposal, we can outpace change and be agile in response to unexpected events.

Sparking creativity

Despite the handwringing you’ve seen online since the public release of ChatGPT, AI is not a threat to true creativity. In actuality, it’s an incubator for creative work. The random nature of AI can lead to refreshing and invigorating outcomes that inspire new ideas. I often ask myself: “I can’t use that now, but it’s interesting. How can I use that elsewhere?”

Promotion of critical thinking 

Sustainable organizational development has always required key stakeholders to engage in critical thinking to define and articulate their desired outcomes. AI tools hold our feet to the fire on this matter because the engine requires the user to provide a prompt. To create a useful prompt for a generative system, you must be thorough in thinking through what you want to create. In a team setting, I may send a few rough ideas and expect my human colleagues to fill in the gaps during the creation process. When working with generative AI, you must be very specific in requesting what you want. The act of contemplating and formulating productive prompts forces us to think more deeply and completely about what it is we want.

A few ways Blueline is using AI in learning and development

At Blueline, we’re using AI to enhance our course development and immersive simulation design process. One example is our use of an AI image generator to create human-centric art for unique scenario simulation experiences. With well-designed prompting, the tool is able to create visuals with characters that place learning in the right context and provide learners with a more immersive and engaging experience.

We’ve also integrated machine learning tools that have streamlined our video editing process, resulting in faster delivery of high-quality content. We’re also experimenting with AI voice technology to enhance diversity and representation when developing characters for our immersive simulations.

Most recently, our enhanced ExperienceBUILDER platform uses generative AI as an engine to simulate a broad range of decision-based business challenges.

As these examples show, AI is a tool that can handle some heavy lifting with the right human guidance. Our team’s experience and expertise will always be the critical component required to design and deliver complex, immersive simulations that transform businesses at speed and scale. To that end, we’ve created our own set of rules for AI use.

Six important considerations when using AI for L&D simulation design

Before we deploy AI tools in any component of learning simulation design, we address the following items:

1. Adhere to responsible attribution 

Ensuring that AI-generated content is appropriately attributed is crucial to avoiding potential legal issues and upholding ethical standards. We put the following safeguards into place in our prompts:

  • Leverage AI-generated content as a starting point and not the final solution.
  • Avoid explicitly requesting a particular artist’s or writer’s style.
  • Avoid using images that look like they have a watermark or have not been appropriately accessed.
  • Credit the source of the content when possible and acknowledge the role of the AI tool in its creation.
  • Limit the use cases for AI-generated content, and only use it where an existing alternative does not readily provide what is needed.

2. Use carefully crafted prompts 

You still need a creative vision to ask AI to do something interesting. Promptcraft is a new way of interfacing with computer systems. While we have grown used to the mouse and keyboard, how we use our words will be the future of creating output. If you provide the prompt “cat box,” you’ll get an AI-generated kitten on a box (no more, no less). But that’s not what I meant: I wanted a cat-shaped box. Creative applications require imaginative vision, thoughtful prompts, and an appropriately descriptive command of your language.

3. Avert the risk of uniformity over time 

Unique identities are at risk of diminishment over time if they rely too heavily on AI systems to generate content—this applies to brands, musicians, artists, thought leaders, and every other subject of generative AI output. Multiple companies might end up using similar commands and techniques, resulting in the loss of creative diversity. If people don’t take the time to come up with unique prompts and creative applications of the output generated, they’ll lose the human touch that makes an output distinctive to a particular organization or voice. 

4. Take heed when entering proprietary information

Massive volumes of data within organizations are folded into training, including confidential and proprietary information to which large language models should not have direct access. For example, Elon Musk wouldn’t feed ChatGPT the details of the thrust mechanism on the SpaceX rocket and ask it to develop relevant training material because that source content would become available in the public domain. To customize the delivery and organization of content that is confidential and proprietary, we can’t lean on AI until we’re able to license and train these models securely. 

5. Question whether AI can understand the complete picture

Often the greatest challenge we see as learning designers is creating content directed to teach a specific skill or subject to someone who doesn’t use it in their daily work. For example, when training customer service representatives, we can’t look at the customer service role in isolation; we need to take a deep dive across all relevant functional areas of a company to devise appropriate and effective learning material that applies to a customer service rep’s day-to-day interactions. 

Can AI achieve this level of nuance? At the moment, I think not. 

6. Be wary of over-reliance on generative AI

As tension mounts between the opportunities presented by new technology and the need for artists to control the use of their own works, new legal and regulatory frameworks related to AI will spring up. The landscape is evolving quickly, which is why I caution against changing your entire business model to rely on generative AI. You risk both liability and an interruption of business continuity. Suffice to say that if AI were to be banned tomorrow, Blueline would still be able to satisfy our clients’ requirements. 

The potential of AI in L&D

Transformative L&D is essential to the long-term success of any company, and organizations should take advantage of tools that can give them a leg up in training and development. The last significant shift in the training landscape occurred in the late 90s and early 2000s, when we moved from traditional classroom learning to virtual learning. We’re due for another disruption.

AI has the potential to revolutionize the L&D space. With AI, organizations can create highly engaging and contextualized learning experiences at scale and with speed. When learners play in the gray and engage meaningfully with learning content, they gain critical skills that can generate a tangible impact on the business. We continue to embrace new technology as a springboard for creating fresh and innovative ways to drive positive change and create a workforce that’s equipped to succeed in the face of constant flux.

Overall, Blueline’s approach to AI is cautiously optimistic. We know that emergent technology always carries inherent risk, and we need to use the mature business senses we’ve developed as consultants over the last 30 years to discern when and how to use it. 

Watch this space—we will be!

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