According to a recent survey, 42% of working professionals are concerned that artificial intelligence (AI) is going to replace many human workers in the workplace soon. But more than 63% of those surveyed said that they are actually more concerned that human bias and prejudices such as race, religion, or demographics will corrupt the data used to teach AI systems, including systems implemented for training purposes.
It seems that there are, indeed, ethical matters to consider for training materials developed, executed, and driven via AI. Below are some of the ethical matters you’ll want to consider when implementing AI-driven training.
Potential In-Built Racism, Sexism, and Other Biases
AI-driven programs and algorithms are built with the intended purpose of learning and executing code automatically and (for the most part) autonomously. However, it’s important to remember that AI-driven systems are still built and executed with man-made historical data or code and that these AI-driven systems are still provided with information created by real human beings. And human beings aren’t inherently neutral and do have innate biases.
So, it’s important to consider how your AI-driven training technology will recognize faces, voices, learning behaviors and already acquired knowledge, assessments, and how each learner will ultimately be evaluated. It’s critical that each learner is provided with unbiased learning opportunities and assessments and that his or her overall evaluations and learner profiles aren’t biased toward one gender, race, religion, age, social status, other demographic criteria, etc.
Unequal Distribution of Learning Content and Opportunities
If your AI-driven training technology isn’t devoid of the encoded biases mentioned above, it will unintentionally begin unequally distributing learning content and opportunities.
For instance, if some of your AI-driven learning assessments favor answers that are biased toward men of a certain race and age, those learners might be offered more advanced learning opportunities and more interesting learning content more quickly while other learners are still being offered regurgitations of the same type of learning material and learning topics repeatedly.
Consequently, while one group of learners is advancing and perhaps acquiring more leadership skills and guidance, other groups of learners are left behind and have unimpressive learning profiles and might end up becoming less engaged with their overall learning activities.
How Regular Interactions with AI Encourage Learning and Everyday Behavior
Sometimes AI-driven technologies can work so well that it’s easy for learners to forget that they’re even interacting with a machine or robot. And this can lead to learners becoming impatient or overly dependent on technology when they’re learning something new or attempting to be innovative.
They will come to always expect immediate responses to all their questions and will always expect immediate feedback and results, regardless of whether they’re in an AI-driven environment. And then they will come to expect such immediacy from their managers, trainers, and peers, too—all of which might lead to more tension, stress, and anxiety in the workplace, as well as incomplete or unsuccessful projects.
As you implement AI-driven training technology across your organization, be sure to carefully consider the ethical matters it incites listed above.