Generative AI and the Unseen Bias of Digital Literacy
- S B
- Jan 1
- 3 min read
Efficiency. Optimization. Productivity.
In today’s workplace, these are the words linked to GenAI tools, carrying the promise of relieving employees from the “monotony of day-to-day tasks” and boosting creativity. While this is undoubtedly promising, an oversized elephant remains in the room — Digital Literacy Bias.
Digital literacy refers to using digital tools to find, create, and communicate information. We introduce bias when we assume employees are fluent with the technology and can interact with it effectively. This is particularly pronounced across demographics like age, education, and location, where access to digital tools and training is unevenly distributed. The rise of GenAI tools is a prime example, as those who create these technologies often forget that others must learn how to use them.
However, while cost savings and process optimization remain at the forefront of project proposals, buried deep within — if mentioned at all — is the topic of upskilling employees on prompt engineering, a crucial aspect of digital literacy in the age of AI.
Having worked extensively with data visualization and AI solutions, I’ve witnessed the effects of this bias long before GenAI came along. Working with technologies like RShiny for visualization, I quickly learned that no matter how technically impressive or visually appealing my plots were, the solutions were useless if users found them confusing or difficult to engage with. Good user experience design, along with adequate training workshops and enthusiastic business champions, were key to getting employees to adopt these solutions.
With GenAI, where the stakes seem to be higher as employees worry about being replaced by AI agents, the ask is greater. Not only must employees interact with the systems, but they must also guide and validate them, often through skillful prompting.
Think of it like this: We once viewed typing as a specialized skill, taught in dedicated classes. Today, it’s as fundamental as reading and writing. Prompt engineering is on a similar trajectory. However, we’re not there yet, and the stakes are high. There’s a significant difference between prompting for the best skincare product and prompting to optimize your workflow or even safeguard your job.
Bridging the Gap: Addressing Digital Literacy Bias in AI Adoption
To avoid leaving employees behind and to truly unlock the potential of generative AI, companies need to:
Invest in prompt engineering training programs.
Create mentorship opportunities for employees.
Develop clear guidelines and best practices for prompt creation.
Let’s not let digital literacy bias become another barrier to success in the age of AI. Instead, let’s embrace this opportunity to build a future where AI is used responsibly and inclusively. As Marie Curie wisely said, “Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.”
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"AI is the tool, but the vision is human." — Sophia B.
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I’m exploring how generative AI is reshaping storytelling, science, and art — especially for those of us outside traditional creative industries.
About the Author
Sophia Banton works at the intersection of AI strategy, communication, and human impact. With a background in bioinformatics, public health, and data science, she brings a grounded, cross-disciplinary perspective to the adoption of emerging technologies.
Beyond technical applications, she explores GenAI’s creative potential through storytelling and short-form video, using experimentation to understand how generative models are reshaping narrative, communication, and visual expression.
