Wanna See Some Puppies?

Mark Gash asks whether we should be getting in AI’s van.

When I was a kid, I was warned of the dangers of a man with a knackered Ford Transit van pulling over at the side of the road and asking if I wanted to see some puppies. All kids want to see puppies, right? The man tells you they’re the cutest puppies you’ve ever seen. Even if you already have a dog that does everything you need a dog to do, new puppies are just so hard to resist. And all you have to do to see the puppies, is get in the van. But if you get in that van, anything could happen… So it was drummed into all 80’s kids, never get in the van - you’ve got an old dog at home, you don’t need to see the puppies.

Dirtyword was down at Learning Tech in February this year, (which in AI terms is about 300 years ago now) and it seemed like every company there was shilling their new AI-integrated learning solution that was gonna be the next big thing and revolutionise the way we all deliver training. They all wanted us to get in their AI-powered van.

6 months later and this has shown no sign of slowing down, as Artificial Intelligence continues to be rammed down our throats as the pill that will cure all L&D woes. So, it’s no surprise that training and education organisations are rushing to adopt these new generative AI technologies in lieu of continuing to deliver e-learning via tried and trusted methodologies. But should you be rushing to put a bullet in your old dog’s head, just on the promise of a fluffy new puppy?

Before you do anything rash to the e-learning equivalent of man’s best friend, it’s not a bad idea to pause and consider the implications of hastily embracing generative AI at the expense of traditional e-learning approaches.

Out with the old?

Like a faithful old labrador, traditional e-learning methodologies have been the cornerstone of digital education for decades. Pre-recorded video lectures, interactive quizzes, discussion forums, self-paced modules and Learning Management Systems (LMS) are often called out for being dull and unengaging. Yet, they still serve as the backbone of e-learning, providing a structured environment for content delivery, assessment, and learner progress tracking.

Asynchronous learning allows students to engage with materials at their own pace, while synchronous elements like webinars foster realtime interaction. Adaptive learning technologies have also been incorporated to personalise the learning experience based on individual progress and needs. These methods have effectively delivered scalable, accessible education across various subjects and skill levels. They offer consistent content delivery, clear learning objectives, and measurable outcomes, particularly valuable in corporate training and formal education settings. So if it ain’t broke, why fix it?

… and in with generative AI.

Generative AI, particularly doe-eyed large language models like GPT-3 and its successors, is touted as a potentially transformative force in education. It’s shiny and new and because AI is creating such a buzz across all industries right now, it’s got a lot of people in e-learning hot under the collar. AI systems can generate human-like text, answer questions, and even create educational content on demand. What’s not to love? The allure of generative AI in education lies in its ability to provide personalised, on-demand learning experiences. It can generate practice questions, offer explanations tailored to individual learning styles, and even simulate conversations to help learners practice language skills.

Some platforms are exploring the use of AI tutors that can provide instant feedback and guidance 24/7. The potential for scalability and customisation has caught the attention of many educational institutions and corporate training departments. As a result, there’s a growing trend of organisations looking to rapidly integrate these technologies into their learning ecosystems, sometimes at the expense of more established e-learning methods.

Here at Dirtyword, we’ve used AI to create imagery for the magazine from the beginning - it’s fast, cheap and saves time. If it wasn’t for AI, the mag would have been a non-starter, as our small team couldn’t produce the amount of visuals needed with the time and budget we have. But had we been an established magazine with artists and designers, would we have replaced them with AI and would the output quality have suffered? It’s the same question we need to ask of e-learning.

Why AI?

The integration of generative AI in education clearly offers many advantages. Firstly, it provides the prospect of unprecedented levels of personalisation. AI can adapt content and pacing to individual learners’ needs, potentially increasing engagement and retention. It can generate unlimited practice materials, allowing students to reinforce concepts through varied examples and scenarios.

Secondly, generative AI can offer immediate feedback and support. Unlike traditional e-learning systems that may have limited interactivity, AI can respond to learners’ questions in real-time, clarifying concepts and providing additional explanations as needed.

Thirdly, AI can assist in content creation, helping instructors develop courses more efficiently. It can suggest improvements to existing materials, generate assessment questions, and even create entire lesson plans based on learning objectives.

Lastly, generative AI has the potential to make education more accessible. It can provide 24/7 tutoring support, translate content into multiple languages, and offer alternative explanations for complex topics, potentially bridging gaps for learners who struggle with traditional methods.

These benefits are not to be sniffed at and go a long way to explain the enthusiasm many organisations have for rapidly adopting this technology.

Why not AI?

While the potential benefits of generative AI are amazing, it’s easy to be blinded by the promise of an L&D utopia where you get paid for writing a few prompts and chucking them at ChatGPT for it to add meat to the bones. Changing the way you do things and getting in the van comes with risks but what exactly are we looking at?

Accuracy and reliability concerns

Generative AI models can produce convincing but incorrect information, a phenomenon known as “hallucination.” In an educational context, this could lead to the spread of misinformation, potentially undermining the learning process and eroding trust in the educational institution.

Lack of critical thinking development

Over-reliance on AI-generated content and answers may stunt the development of critical thinking skills. Students might become dependent on AI for problem-solving rather than developing their own analytical abilities.

Reduction in human interaction

While AI can simulate conversation, it can’t replace the nuanced, empathetic interactions that a human teacher or trainer provides. Rushing to replace human-led instruction with AI could lead to a loss of valuable social and emotional learning experiences.

Privacy and data security issues

AI systems require vast amounts of data to function effectively. Rapid adoption without proper safeguards could lead to breaches of student privacy or misuse of sensitive educational data.

Equity and access concerns

Despite its potential to increase accessibility, the adoption of advanced AI technologies could widen the digital divide. Students without access to high-speed internet or advanced devices might be left behind.

Lack of contextual understanding

AI, despite its sophistication, may struggle to understand cultural nuances, local contexts, or specific institutional needs that human educators intuitively grasp.

Overemphasis on metrics

AI systems excel at measuring and optimising for quantifiable outcomes. This could lead to overemphasising test scores and easily measured metrics at the expense of harder-to-quantify but equally important skills like creativity and collaboration.

Ethical concerns

The use of AI in education raises ethical questions about authorship, originality, and academic integrity. Rushing to adopt these technologies without establishing clear guidelines could lead to confusion and potential misuse.

Integration challenges

Hastily implementing AI systems without proper integration with existing e-learning infrastructure could result in fragmented learning experiences and technical difficulties that frustrate both educators and learners.

Loss of valuable traditional methods

In the excitement over AI, organisations might prematurely abandon proven e-learning methodologies that have been refined over years of practice and research.

These risks highlight the need for a cautious, well-considered approach to adopting generative AI in educational settings.

Can’t we just have 2 dogs?

AI is here to stay and for many of us, we’ve already stuck our heads in the van, patted the puppy and liked what we’ve seen with no sinister consequences. But we still need to be cautious and take a balanced approach to AI adoption.

Gradual integration

Implement AI technologies incrementally, allowing time for evaluation and adjustment.

Hybrid models

Combine AI-driven tools with traditional e-learning methods, leveraging the strengths of both approaches.

Ongoing assessment

Regularly evaluate the impact of AI on learning outcomes, student engagement, and overall educational quality.

Ethical guidelines

Develop clear policies for AI use, addressing issues like data privacy, academic integrity, and appropriate AI assistance.

Educator training

Equip teachers and instructors with the skills to effectively use and monitor AI tools in their courses.

Student digital literacy

Incorporate lessons on AI capabilities and limitations, fostering critical thinking about AI-generated content.

Collaborative development

Work with AI developers to create education-specific models that align with pedagogical best practices.

Are you getting in the van or what?

While the generative AI puppy holds immense potential for transforming education, rushing to adopt it at the expense of proven methodologies carries significant risks. A thoughtful, balanced integration combining the best AI innovation with traditional e-learning approaches is probably the safest path to tread right now. So get in the van and stroke that puppy. But bring your fully-grown German Shepherd along for the ride.