Summer is upon us, and for some, it’s the season of working with summer interns. Recently, I had a conversation about GenAI tools and how their outputs can range from impressive to terrible. The bottom line: we can’t blindly trust these outputs, and varying degrees of human oversight are needed. This experience reminds me of working with summer interns and it inspired me to compare them with AI tools. This blog post explores the similarities, highlighting the good, the bad, and the ugly.
1. The Good
- Easy Idea Generation: AI tools rapidly generate content on any topic imaginable. This rapid ideation helps kick-start the creative process, leading to more innovative and engaging learning experiences. This is similar to having a dialogue with a summer intern to bounce ideas off and get a fresh perspective. For L&D professionals, this means having a constant stream of fresh ideas to develop learning initiatives.
- Combatting Blank Canvas Syndrome: Creating content from scratch can be daunting. The instant generation of workshop outlines, facilitator guides, and activities by AI can really save time in the development process, helping instructional designers move from concept to creation. Imagine having an intern who is able to draft outlines and map out initial concepts, helping instructional designers overcome the dreaded “blank canvas syndrome.”
- Scalability and Customization: AI excels in producing vast amounts of content tailored to specific learning outcomes, subject domain areas, and learner demographics. This scalability and customization mean that learning experiences can be more closely aligned with individual learner needs. It’s akin to having a summer intern who can tailor their research and outputs to meet the specific requirements of different projects, enhancing the personalized learning experience for the target learners.
- Enhanced Writing Assistance: AI is particularly adept at writing scenarios, branching exercises, quiz questions, learning objectives, summaries, and key points. This feature can improve the written quality of learning materials and provide copy editing help. Similarly, interns are often asked to provide writing and editing assistance, supporting the development of clear, concise, and engaging content.
2. The Bad
- Generic Content: One major drawback is AI’s tendency to produce generic content that may not resonate with all audiences. The lack of depth, personal tone, and specificity can make it challenging to engage learners meaningfully. It’s like receiving a basic report from an intern that needs substantial refinement to add the necessary details, examples, and relevance.
- Redundancy Issues: AI-generated content often suffers from redundancy, with the same phrases or ideas repeated unnecessarily. This can lead to learning materials that are less effective and more tedious to engage with (and a dead giveaway that it is written by AI). This is akin to an intern who, despite their enthusiasm, may not yet have the experience to write concisely.
- Copyright and Privacy Concerns: AI systems can inadvertently generate content that infringes on copyright or compromises privacy. Navigating these legal and ethical considerations requires careful audit, guidelines, and governance. Similarly, an intern might unknowingly use copyrighted material or mishandle sensitive information, necessitating vigilant supervision.
3. The Ugly
- Risk of False Information: AI’s capability to generate content based on existing information sources means there is a risk of perpetuating false information or “hallucinations” – instances where AI presents fabricated data as fact. This parallels an intern misinterpreting information or making errors in their research, leading to inaccurate outputs.
- Cultural and Bias Challenges: Many AI systems are trained on data that reflect cultural biases or are overly North American-centric. This can lead to content that lacks cultural relevance or sensitivity, potentially alienating or misrepresenting learners from diverse backgrounds. It’s like having an intern who, despite their best efforts, may not yet have the global perspective needed to create inclusive and culturally sensitive content.
- Regression over Time: Currently, roughly 14% of online content is AI-generated, and this will increase over time. There is a concern that the AI-generated output might degrade as it trains on more AI-generated content, potentially leading to a regression in content quality. This is similar to an intern learning from outdated or incorrect materials, leading to diminishing returns in their work quality over time.
Mitigation Strategies
To mitigate the bad and the ugly of GenAI, here are a few strategies for L&D to consider:
- Implement Robust Governance Frameworks: Developing clear guidelines for AI use in content creation, including copyright compliance, data privacy, and ethical considerations.
- Blend AI with Human Expertise: Human oversight is needed in every step of the content generation process. While AI can be efficient in content generation, human expertise and experience is the quality control we must use to ensure content output that is relevant, accurate, and culturally sensitive.
- Regularly Review and Update AI Models: Whenever you have access to the data source, it’s not just good practice but essential to ensure the data remains diverse, accurate, and up-to-date. This regular maintenance helps mitigate biases, reduce the risk of false information, and improve the overall effectiveness of the AI-generated content.
- Foster Cultural Sensitivity and Inclusion: Put together a stakeholder group with a diversity of gender, age, domain knowledge, cultural background, and life experiences. Actively and periodically seek input from this group to identify and correct biases in AI-generated content, and to build trust in your organization from the bottom up.
AI-generated content holds immense promise for L&D; however, realizing its full potential requires careful consideration of its limitations and challenges. Just as interns need guidance, mentorship, and oversight to produce their best work, AI tools require thoughtful integration and human supervision. By striking a balance between innovation and oversight, L&D professionals can leverage AI to create impactful, engaging, and inclusive learning experiences. Treat your GenAI tool as you would a summer intern: with clear expectations, continuous feedback, and a collaborative approach to harness its full potential.
