How to Develop an Ethically Sound Compliance Training Program Rooted in AI

September 27, 2023 | What's Hot | 7 min read

There are many ways that you can leverage artificial intelligence (AI) to enhance the effectiveness and efficiency of your compliance training program. AI can help streamline training processes, personalize learning experiences, and improve overall outcomes – just to name a few of the benefits.

The best way to get started? Dive right in. According to my colleague Asha Palmer, SVP Compliance Solutions at Skillsoft:

“Inching into Generative AI and hoping that the 'water’ will get ‘warmer' or ‘easier to tolerate' is not the right answer.

We must jump in.
We must let our employees jump in.
We must let our companies jump in.”

Let’s talk about some of the ways that you might incorporate AI into your own compliance training today.

Personalized Learning Paths

Here at Skillsoft, we use AI to help deliver personalized learning through content curation, individual learning paths, skill level, and role. AI algorithms are adept at assessing learners’ strengths and weaknesses and creating personalized training paths that cater to their specific needs. In fact, by analyzing a learner’s progress and performance, AI can recommend relevant courses or modules to help them fill knowledge gaps.

Content Recommendation

A gap analysis can help compliance leaders to identify the competency, knowledge, or skills that your employees lack at any given time. AI-powered content recommendation engines can then suggest relevant compliance materials, documents, videos, or quizzes based on the learner's role, industry, and learning history.

Natural Language Processing (NLP)

NLP is often used to develop chatbots or virtual assistants that answer learner questions in real-time, providing on-demand support during training. It can also analyze and understand written compliance documents and regulations, making it easier to extract key information and updates.

Skillsoft recently announced the general availability of Skillsoft CAISY Conversation AI Simulator, a generative AI based tool for simulating business and leadership conversational skills. CAISY provides employees with a safe space to practice important business conversations by playing the role of the other person within the conversation and then providing personalized feedback.

Gamification and Engagement

AI can enhance engagement by incorporating gamification elements like leaderboards, badges, and challenges within compliance training programs.

Check out how Skillsoft is using leaderboards to power workforce transformation.

Predictive Analytics

AI can analyze historical compliance data to predict potential compliance violations or identify areas where employees are more likely to make mistakes. This can help organizations proactively address issues. Predictive analytics can also forecast future compliance training needs and recommend actions to mitigate risks.

Automation of Administrative Tasks

GenAI solutions have allowed Skillsoft to enhance our productivity and deliver better learning experiences. Our internal AI team utilizes AI to implement new features in our learning platform, and our marketing and customer success teams are actively exploring new ways in which AI-generated content can drive efficiency and increase effectiveness. We’ve also started to leverage AI to accelerate our own curriculum development.

Ethical considerations with ai-driven compliance training

While AI has plenty of applications within a compliance training program, there are some ethical considerations that must be taken into account before going “all in” on the technology.

According to Palmer, even as we dive in on GenAI, it’s likely we’ll need floaties. She said, “You must first understand the risks associated with the water: How deep is it? Do you know how to swim? Are there other hazards? Is there a lifeguard?

But once you have a good idea of the guardrails you’ll need to put in place related to GenAI within your organization, you will be ready to take on any challenges. These might include the potential for bias, the importance of transparency, and the need for human review.

Subscribe to the Skillsoft Blog

We will email when we make a new post in your interest area.

Select which topics to subscribe to:

Bias and Fairness

AI algorithms may inherit biases that are present in training data, potentially leading to unfair or discriminatory outcomes. Avoid this by regularly auditing your data to ensure fairness in training and assessment.

Transparency and Explainability

Transparency and openness can help promote ethical behavior and create a culture where employees are more willing to report ethical concerns. Learners and other stakeholders have a right to understand how AI algorithms make decisions or recommendations. And ensuring the transparency and explainability of AI processes can foster trust and accountability.

Consent and Opt-Out

Learners should have the option to opt out of AI-driven features if they have concerns about privacy or other ethical issues. Organizations must respect learners' choices and preferences.

Accountability

Clear lines of accountability should be established for AI-driven compliance training programs. Organizations should define who is responsible for AI system oversight, maintenance, and addressing ethical issues that may arise.

Privacy and Data Security

Privacy and security are a top concern when using any data technology. A study conducted by Cyberhaven showed that 4% of employees had pasted confidential information into ChatGPT and that 11% of all total information pasted into ChatGPT is sensitive in some way.

Team members must be aware of the sensitivity of data they are using in conjunction with GenAI systems and be aware that the submission of such data to a GenAI system could lead to a data breach.

Furthermore, data collected during AI-driven compliance training, such as learner performance data and interaction history, should be handled with care and in compliance with privacy regulations (e.g., GDPR, CCPA). Transparency in data collection and use is crucial.

Evaluation and Validation

Information accuracy is a key problem in the use of GenAI. GenAI systems are designed to create content that sounds truthful. However, there is no way for the technology to confirm that the content is actually true. This can lead to all sorts of problems.

The only way to address this issue is to fact-check the outputs of your GenAI systems. Team members should not use GenAI to create or publish content on subjects in which they do not have expertise. In cases where team members lack relevant expertise, they should:

  • Consult an expert in this area
  • Take other precautions to conduct due diligence on the outputs of the system

Copyright Infringement and Disclosure of Trade Secrets

If you are not careful with the information you share with GenAI, you may inadvertently disclose some of your organization’s trade secrets. For example, an employee submitting product information into a GenAI system to respond to an RFP is one way that trade secrets might be leaked.

Copyright issues are also a concern. If a team member asked ChatGPT to “write a blog post in the style of Oprah Winfrey” and ChatGPT used actual excerpts from things Oprah said, this would amount to plagiarism. Similarly, if a design team asked for “images in the style of Banksy” and the images were not differentiable from a Banksy painting, this might constitute theft of intellectual property.

Avoiding Discrimination

Ensure that the data used to train the AI is diverse and representative. A lack of diversity in your data can lead to AI that does not reflect the values and ethics of an organization. AI systems should not discriminate against individuals based on characteristics such as race, gender, age, or disability. Make every effort to ensure that AI algorithms do not inadvertently reinforce or amplify biases. Also keep in mind that different cultures may have varying perspectives on AI usage, data sharing, and privacy. Organizations with a global presence should consider cultural differences in their AI implementation.

Ethical Training Content

The content of compliance training programs, including AI-generated material, should adhere to ethical principles and not promote unethical behavior or discrimination.

Employee Concerns

Organizations should address employee concerns about AI in compliance training and provide channels for reporting ethical issues or violations related to AI usage.

Check out Skillsoft’s new ChatGPT courses, meant to teach the abilities and limitations of AI.

Addressing these ethical considerations is essential to create a responsible and trustworthy AI-driven compliance training program that aligns with legal requirements, ethical principles, and organizational values.

Make it a point to stay informed about evolving AI ethics guidelines and best practices so that you may adapt your training program accordingly.