Did you know that the worldwide AI market is now predicted to grow by $120 billion by 2025? With so much buzz in the air, it’s no surprise that 63% of companies plan to increase or maintain AI and machine learning spending in 2023.

AI holds immense potential to reshape the learning landscape. It allows us to tailor learning experiences to individual needs, offer instant feedback, and even anticipate future learning requirements. But, as with all powerful tools, it’s essential to use AI responsibly.

As we approach 2024, AI integration in learning technologies isn’t just a concept of the future – it’s happening right now. So, how can we ensure we’re using AI ethically in our learning strategies?

Addressing Challenges of Ethical AI in Learning

AI has become such a common buzzword these days – it’s everywhere, from our workplaces to our everyday lives – it hardly needs an introduction.

The technology is flipping traditional educational models on their heads; the usual classroom training at work just won’t cut it anymore. Some organizations are already embracing AI to enhance skill development through personalized learning, using chatbots or virtual assistants and utilizing predictive analytics to identify skill gaps and anticipate training needs.

But, even as AI becomes a regular feature in some workplaces, quite a few professionals are still on the fence about including it in their learning and development plans.

Here at Hive Learning, we’re very much aware of the common concerns and hurdles linked to AI. Let’s explore some of the most common concerns around using AI as part of your L&D strategies and how to mitigate them.

Job Security

According to a report by the World Economic Forum, by 2025, AI and automation could displace 85 million jobs worldwide. So, as AI continues to advance and becomes more skilled, some of us are starting to wonder, “How can we humans, who are occasionally prone to error, ever compete?”

In truth, AI is more likely to enhance and automate existing jobs rather than eliminate them. Even with the advancements of Gen AI, human abilities like critical thinking, emotional intelligence, and objective reasoning are still vital.

While AI is undoubtedly making strides with its automation abilities and analytical prowess, it falls short in one area where we humans truly shine – our inherent capacity for creativity and innovation. Take, for example, designing a learning program. While AI can certainly build a program based on predefined parameters, it’s us humans who bring the creative spark. AI lacks an understanding of the unique needs of a diverse workforce that resonates on a human level.

At Hive Learning we follow the ‘AHAH’ principle, which stands for AI-assisted, Human-led, AI-resourced, Human-checked. This approach underscores the balance between AI assistance and human leadership. While AI lends a hand and provides resources, humans are still at the helm, overseeing the processes. It’s a mixed approach that amplifies the benefits of AI while preserving the invaluable human touch.

Bias is Inherent in AI

AI systems are trained on data that reflects the biases of the real world. If not properly managed, the systems can reinforce existing biases. As some of us are already familiar with, social media uses algorithms to feed content to us by analyzing the content we have already consumed. Similarly, AI models produce results based on those that already exist. 

One of the most common ways bias can find its way into AI is when the data used reflects biases prevalent in society. It might not accurately represent certain groups or carry prejudiced perspectives. So, although the data might include accurate correlations, AI algorithms might not factor in ethical considerations. 

A well-known example of bias in AI involved a tech firm that developed an AI tool for vetting resumes. The tool was trained on data from past applicants to determine what made a “good” hire. The catch was that the company’s workforce was predominantly male, leading the AI to assume that being female was a negative trait. Since AI doesn’t have a contextual understanding of the world and simply identifies patterns, it can’t consciously correct these errors. 

This is another example where human intervention is invaluable; if humans are reviewing the results produced by AI, biases creeping into the workplace become a lot less likely. Organizations have a moral responsibility to eliminate algorithmic biases and prioritize humans.


A poll by the Pew Research Center revealed that many Americans who know about AI are worried about how companies might use it. Especially after seeing the popularity of ChatGPT, they’re apprehensive. In fact, 81% expressed concerns about potential misuse of their data, while 80% were worried about their data being used in ways they didn’t intend.

So, how can we ensure that the data collected is used responsibly and ethically?

AI is already proving its power to transform our work and life, but it’s crucial to tread carefully. Whenever you use AI software, consider the information you’re giving it very thoughtfully. Keep in mind that once you input data into an AI tool, it could potentially be accessed by anyone on the internet. It’s an open model online, so steer clear of sharing sensitive or proprietary data.

We need to establish clear guidelines and regulations for the use of AI in learning. This includes implementing robust data protection measures and conducting regular audits to ensure compliance.

Using AI in learning in a way that is ethical and secure

Navigating the new era of AI brings valid concerns around data security, but let’s turn to some insights from an expert in the field. Fabrizio Conrado, Chief Product Officer at Hive Learning, shares his thoughts on embracing this transformative technology:

“AI is the biggest revolution we’ll see in our lifetime and that can be very daunting. As individuals, we often struggle to grasp the broader perspective of our history of human innovation. Yet, if we glance back at similar periods of rapid change, some clear patterns emerge: Be brave, and delve deeply into these new technologies to discern both the risks and rewards. Experiment with various ideas in a secure environment with real users, and then implement them gradually, yet swiftly. At Hive Learning, we’re fortunate to have a robust innovation ecosystem that provides us access to experts, tools, users, and clients, all of which help us accelerate this process!”

So, how can we embrace AI in a secure environment? The answer lies in creating a culture of security. This involves educating all stakeholders about the importance of data security and providing them with the tools and resources they need to protect their data.

Moreover, we need to adopt a transparent approach to AI. This means communicating how AI systems work and how they use and protect data. Transparency not only builds trust but also allows your learners to make informed decisions about their learning.

At Hive Learning, we understand the importance of ethical and secure AI. That’s why our AI-powered learning solutions not only enhance learning but also prioritize data security and ethical use.


The ethical considerations of emerging learning technologies are substantial, but they’re not unbeatable. With a proactive and responsible approach, we can harness these technologies in a manner that’s both ethical and secure. 

Organizations are now presented with a unique opportunity to pioneer AI-powered learning strategies; it’s crucial to seize this opportunity to stay ahead of the curve. After all, if we’ve learned anything from history, it’s that ground-breaking technologies and innovation can significantly boost an organization’s growth and success. 

So, are you prepared to welcome AI into your learning strategy? Team up with us at Hive Learning, and let’s collectively shape the future of learning.

More Articles

What is Agile Good For?

Chris Hall, Senior L&D Manager at MacMillan Cancer Support has joined us in a guest blog series to share his experience rolling...

Discovering Multimodal AI in Learning and Development

In recent months, you may have heard the phrase ‘multimodal AI’ in Learning & Development, you also might not - and that’s...

Implementing Agile Strategies: A Guide for L&D...

Hive Learning’s recent session with Natal Dank offered a deep dive into Agile L&D strategies with a focus on Natal’s newest...

Webinar Highlights: Embracing Agility: Transforming...

Remember when smartphones were the hot new thing and everyone was scrambling to get one? That’s where we are with AI today....

Book a demo today

Discover the power of Hive Learning:
Simplify, Streamline, and Succeed