In recent years, artificial intelligence (AI) has become increasingly common in the way we do business. From virtual assistants to recruitment, streamlining production processes and due diligence, AI is powering how we get things done.

The 2021 Appen State of AI report was released to educate business people on how to leverage AI across industries and keep pace with the rapid adoption of the technology. Data from the report suggests that the rapid growth of the AI industry threatens to leave behind the organizations that haven’t yet invested in their own AI initiatives. From then to now, there is an increase in companies utilizing AI to streamline their internal and customer-facing processes, and applications. Implementing AI continues to help businesses achieve results faster and more efficiently by eliminating human error, automating repetitive tasks, sifting and analyzing data, and providing decision-making capabilities.

Yet, as companies turn to AI to transform the workplace, they must also ensure that their people are using AI technology in an ethical, not to mention legal, way. There are many concerns for companies using AI to consider — one of the biggest is the privacy and security of people’s data. However, there are other complications to also consider.

AI produces results depending on how the data is designed and what data it uses. This could lead to decisions that are intentionally or unintentionally biased. AI can be used in facial recognition equipment or online tracking and profiling of individuals. In addition, AI enables merging pieces of information a person has given into new data, leading to results the person would not expect. A company can use a person’s data to predict behavior and adapt their message. It also needs to be clarified to consumers if they interact with AI or a person.

And that is just the beginning. As AI gets more sophisticated and AI tools proliferate, the need to ensure companies manage this ever-evolving technology has become evident.

AI Ethics: Topics for Training and Development

Understanding regulatory guidelines is crucial to any employee AI compliance training initiative. There’s been a real uptick in legislation worldwide to protect people’s data and manage AI use. Data privacy begins with the E.U.’s General Data Protection Regulation (GDPR), which led to a flurry of other laws, such as the California Consumer Privacy Act and Brazil’s General Personal Data Protection Law. Countries are also starting to tackle their approaches to managing AI. From President Biden’s executive order on AI to the E.U.’s upcoming AI Act, countries are creating regulations to manage the ever-evolving technology.

And more regulations are likely to come, especially as industry professionals raise concerns about AI and its potential dangers, calling for increased regulation. Over 50,000 signatories signed a letter in March 2023 urging an immediate halt in developing “giant” AIs and establishing robust AI governance systems.

As Sam Altman, OpenAI’s CEO, said when he appealed to the U.S. Congress to regulate the new technology, “I think if this technology goes wrong, it can go quite wrong. And we want to be vocal about that. We want to work with the government to prevent that from happening.”

Even if some of these regulations aren’t where you’re based, your company will still need to comply with these regulations if they conduct business in those locations and overall for best practice. Your employees need to be updated on how users’ data is collected, stored and used, and they should be aware of the company’s data protections.

This brings us to transparency, a critical element for ethical AI. AI systems are often not very transparent. The algorithms that power them are complex. However, your workforce needs to understand how AI tools work — with a focus on the training data and how the system makes its decisions.

Addressing the potential bias of AI, specifically generative AI tools like ChatGPT, is another critical element of AI workforce training. It’s tricky because it can be hard to detect, but if fairness and accountability are clearly communicated to all employees, it’s possible to generate ethical AI content. This would involve clear guidelines and a diverse group of people who could regularly review the AI-generated content for bias.

AI Ethics in L&D

AI is becoming increasingly prevalent in learning and development (L&D) initiatives, transforming employee training and skill development. Learning can be personalized, chatbots can be employed, materials can be analyzed and enhanced, and content, including videos, can be created and curated. It can all add up to a seamless and effective learning experience. However, many L&D professionals are realizing that implementing AI in training can come with several ethical issues that they must contend with.

The first issue is the possibility for bias depending on the data the AI systems are trained on. These biases can perpetuate inequality, reinforce these ideas within the organization and lead to discrimination in training.

However, this can be addressed: It starts with “cleaning” the data that trains the AI algorithms. This essentially means identifying the potential sources of bias in the data collection process, which could exclude or overrepresent certain groups, or from the data labelling process, which may involve inconsistent standards.

Best practices include establishing standards and policies for the data and the data cleaning process. It’s essential to have transparency in AI decision-making processes so organizations can identify and correct biases and provide fair treatment for all learners. Audits of the AI systems should be conducted regularly.

Similarly, AI-powered assessment models should be continuously monitored and calibrated to ensure they’re free of discrimination. This can be done by incorporating agreed-upon validation methods. In this way, organizations can provide a level playing field for all learners.

AI-powered learning content, customized to learner’s personal preferences, can undoubtedly lead to more dynamic learning experiences. But organizations must also ensure that their AI-powered learning applies to all employees. This is doable by considering all of your employees’ varying needs and preferences, and being aware of various cultural perspectives and backgrounds. Accessible features like closed captions, transcripts and alternative learning formats can also ensure inclusivity.

Moving Forward

L&D professionals must share clear guidelines for AI usage, audits of AI systems and oversight of AI initiatives with their people. Transparency of how AI is used in the organization can go a long way in building trust. However, ensuring responsible and ethical AI use across the organization is not simple to achieve. Learning leaders can start by raising the level of awareness across the organization, encouraging ongoing training and fostering a culture of open dialogue in AI compliance. Also, remember to continuously monitor and evaluate your L&D initiatives so you can be ready as the technology evolves. One thing you can be sure of is that it will.