Responsible AI in Learning and Development

A company has implemented an AI-driven learning platform that recommends personalized training modules to employees based on their job roles and past performance. However, some employees have noticed that the AI consistently suggests less challenging content for female employees compared to their male counterparts, even when their performance metrics are similar. This has raised concerns about potential gender bias in the AI’s decision-making process, leading to questions about fairness and equity in employee development opportunities.

• Adjust manually for fairness

• Trust the AI to improve over time

• Investigate and retrain the AI with more balanced data

• Not sure

An AI-powered learning platform has been implemented at a global company to personalize employee training based on their performance data and learning preferences. However, after several months, employees from non-English speaking regions have reported that the AI is recommending content that is less advanced and sometimes irrelevant to their roles, raising concerns that the AI may be favoring English-language data and underestimating the skills of non-native speakers.

• Leave the AI to adjust and learn over time

• Retrain the AI with more diverse, multilingual data

• Implement manual adjustments to recommendations for non-English speakers

• Use AI recommendations as a supplement, not the primary guide

A learning and development team uses an AI-based assessment tool to evaluate employee progress in a mandatory cybersecurity training course. The AI provides personalized feedback and suggests additional learning resources based on quiz results. However, some employees with learning disabilities have reported that the AI’s feedback is not accommodating their needs, as it doesn’t consider alternative learning methods or extended time requirements. This raises concerns about whether the AI is adequately supporting all learners.

• Continue using the AI tool as is

• Provide separate, human-driven support for accommodations

• Modify the AI to include accommodations for diverse learning needs

• Not sure

A team of instructional designers is using a generative AI tool to create custom e-learning modules for employees. The AI quickly generates content based on prompts provided by the designers. However, after several iterations, the team notices that the examples and scenarios generated by the AI predominantly feature certain cultural norms and perspectives, which may not be relatable or relevant to the company’s diverse, global workforce.

• Manually edit the AI-generated content to include more diverse examples

• Use more specific prompts that explicitly request diverse and culturally relevant content

•  Rely on AI to improve its content diversity over time

• Rotate the use of different AI tools to see which one generates the most diverse content

A training department is using a generative AI tool to create assessments for various employee development programs. The AI quickly generates multiple-choice questions and quizzes based on the provided learning objectives. However, after deploying these assessments, some employees report that the questions are too simplistic and don’t accurately reflect the complexity of their roles or the content they’ve learned, potentially undermining the credibility of the training program.

• Manually revise the AI-generated questions to better match the learning objectives

• Provide the AI with more detailed prompts, including examples of the desired complexity and depth

• Supplement AI-generated assessments with questions created by subject matter experts

• Use the AI tool for initial drafts only and rely on human experts for finalizing assessments