How many people in your organisation are using generative AI? McKinsey’s latest research reveals a sharp rise in AI adoption, with HR and learning and development (L&D) teams increasingly using AI to enhance their processes.
As we continue to expand our use of AI, it's crucial to develop structured strategies for choosing the right tools. We must also stay vigilant about upholding ethical standards, ensuring that our approach remains fair and inclusive.
To help with this, we explore five essential questions to ask when evaluating AI tools, ensuring they are both effective and aligned with your commitment to inclusivity and fairness.
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65%.
The percentage of survey respondents who report that people in their organisation are regularly using gen AI in the latest McKinsey global research. What’s more, AI adoption in the workplace has nearly doubled in less than a year.
While marketing, product development, and IT teams have been quick to embrace AI, HR and learning and development (L&D) are catching up fast, recognising the benefits AI can bring to their strategies and workflows. Many are beginning to integrate AI into all stages of learning and assessment, from designing personalised and engaging content to enhancing delivery. AI is also being used to assess skills and knowledge, while automating routine administrative tasks, making workflows smoother and more efficient.
As many of us are still in the early stages of AI adoption, we often find ourselves without formal guidelines on how to select and use it, leading to a haphazard or scattered approach. As we continue to expand our use of AI, it’s crucial to develop more structured strategies for identifying and choosing the right solutions. And amid the excitement, we must also ensure that ethical considerations are not overlooked, maintaining a focus on fairness and inclusivity in our learning and assessments.
To help with this, we explore five essential questions to ask when evaluating AI tools, ensuring they are both effective and align with your commitment to inclusivity and fairness.
1. How diverse is the AI training data?
The foundation of any AI solution is the data it was trained on. This data - the huge mix of images, text, videos and more - guides AI learning, how the tool responds. Imagine investing in AI-driven learning and assessments only to find out that this data doesn’t reflect the diversity of your learners or the unique needs of your context.
This mismatch can lead to biased results, content that doesn’t quite fit your needs and a learning and assessment experience that fails to engage participants.
So, what should you look out for?
Ask about the variety of backgrounds, demographics, contexts, learning styles, abilities and experiences included in the AI training data.
2. How fair are the system's algorithms?
Algorithmic fairness is another crucial aspect to consider. Algorithms—the sets of rules guiding how an AI processes data and makes decisions—are central to personalising learning and evaluating learners.
Even if you’re not directly involved in developing these systems, it’s essential to discuss algorithm fairness with your vendors. Make sure they are designed to be impartial and fair, avoiding unintentional biases that could impact different groups of learners.
Find out how vendors test their algorithms to identify and address potential AI bias. For example, they might carry out fairness audits to spot and fix discriminatory patterns. You’ll want to confirm that learning and assessments don’t unfairly favour a particular cultural context or language, which could disadvantage learners from diverse backgrounds.
3. Do solutions adapt to diverse learning styles and needs?
Personalisation is a key benefit of AI-powered learning and assessment tools. But it’s not just about recognising various learning styles - it’s also about how well these solutions adapt in real-time to individual needs.
Does the AI include adaptive learning, adjusting content presentation and assessment based on a learner’s interactions? A robust system should dynamically tailor the experience, offering different formats such as videos, text, or interactive modules and adjusting the level of difficulty based on the participant's preferences and progress.
4. Do tools include accessibility features?
An AI tool can only be truly inclusive if it caters to all participants, regardless of their abilities. Accessibility features are more than just a box to tick; they’re essential for making sure everyone can fully participate in the learning and assessment experience, narrowing the digital divide.
Make sure to ask how solutions incorporate accessibility options like screen reader compatibility, text-to-speech functionality and flexible display options such as adjustable text sizes and enhanced contrast. And don’t forget to ask how they keep these up-to-date and adapt their systems based on ongoing user feedback to address evolving accessibility needs.
5. How do solutions ensure compliance with ethical standards and regulations?
Ensuring ethical and compliant AI is essential for maintaining fairness and transparency for everyone involved.
Ask vendors how they manage data protection and privacy and how they ensure their AI systems align with relevant legal and ethical guidelines. Compliance isn’t just about ticking boxes; it’s key to building trust and demonstrating a genuine commitment to fair and equitable practices.
Final thoughts
Ensuring that AI-powered learning and assessment solutions are both effective and inclusive is essential for fostering a fair and engaging learning environment. By asking the right questions about diversity in training data, algorithm fairness, adaptability, accessibility features, and compliance with regulations, you can select tools that truly meet your organisation’s needs.
It’s crucial to remember that the process doesn’t end with the initial evaluation. Both your L&D team and vendors should commit to ongoing reviews and updates to address any emerging issues and adapt to new needs. As AI technology continues to evolve, staying proactive in these assessments will help you maintain a learning environment that supports all learners effectively and equitably.
How are you planning to ensure you select inclusive AI-powered solutions for your organisation?
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