Moses Everett is Vice President of Digital Services at KQ Communications. Tapping into more than 15 years of experience in graphic design, digital marketing, web development, and social media management, Moses successfully collaborates with clients of all sizes, including start-ups, nonprofits and Fortune 500 companies. Moses earned a Bachelor of Business Administration in Marketing from Savannah State University and a certification in digital marketing strategies from the Kellogg School of Management at Northwestern University. Prior to his time at KQ, he served as the Marketing Manager for a safety technology company and worked in communications, recruitment, and marketing in K-12 education and higher education. Married to a teacher, and the son of a retired Superintendent, Moses is a passionate supporter of public education and donates his time and talents helping schools “tell their story” through branding initiatives.
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Upholding cultural understanding in the age of AI is critical.
Diverse perspectives and collaborations are key in any industry, organization, and in our communities. Too often, diverse communities are neglected, overlooked, or denied the same opportunities. A similar lack of diversity exists in STEM roles, and is negatively impacting AI training and development.
The Equal Employment Opportunity Commission report in 2024, which analyzed Census data and annual surveys, found that Hispanic or Latinx workers in the tech industry made up 10%, Black workers made up 7.4%, and women made up less than 23% between 2014 and 2022, and found more underrepresentation in management roles.
The gaps in diversity within teams can impact progress and innovation.
An example of this is with Large Language Models (LLMs), which are generating content or responses with bias.
Specifically, we have witnessed subconscious cultural bias appearing in outputs. A recent article in Nature shared findings of a study conducted by researchers at the University of California, Berkeley’s AI Research Lab that examined how two versions of GPT responded to texts written in eight widely spoken English dialects, alongside Standard American and British English. They found that the versions consistently defaulted to American spelling, and some of their findings detected stereotypes in the responses.
This is also why AI tools shouldn’t replace our teams; they must work with our strategic judgement and cultural awareness. Otherwise, the biased content you may accept will contradict the voice, language, tone, values, culture, and experiences of those the work represents.
Although AI is regarded as a tool, an ideation partner, and collaborator to help identify pain points for improving the efficiency of processes and productivity, we cannot ignore its weaknesses.
Increasing diversity in the engineering of LLMs and enhancing the development and training of LLMs, are essential and would lead to better outputs in this age of AI.
AI’s issue of bias changes what is generated to assist communication and creative work from authentically relating to and connecting with target audiences or representing the people behind the brands or organizations, especially if teams are not effectively using AI – that’s where the risk is high.
Because AI can’t automatically detect our ethnicities when we initiate a chat, our prompts must have plenty of context and details for our desired output we’re looking for. However, since bias has occurred, the work doesn’t stop when responses are given. We have to ensure AI adoption is not replacing people who bring inclusive storytelling, strategic decision-making, or creativity, just for convenience.
Diversity advances innovation in every industry.
It is important for development teams and the tech industry to prioritize the need to address disparities, as AI tools are rapidly being released, invested in, and adapted in our work. A recent study from Adobe found that 99% of creative professionals are using generative AI in their creative process. And, almost 70% of marketers have integrated AI into their operations, according to data from MarTech.
Creative teams are still driving the designs, personas, tone, and concepts of the work.
While leveraging AI tools, here are a few things to keep in mind:
- Give as much detail as possible in your prompt.
- Teach AI to avoid tropes and bias for a better output for analysis.
- Don’t forget you’re still taking the lead.
- Analyze and refine AI’s outputs.
- Don’t forget, or exclude, culture.
For marketing and communications agencies, in-house teams, or any professional in our field, it is critical as strategic creatives and brand ambassadors, corporations, or organizations, to ensure AI use doesn’t let representation, trust, and authenticity slip through the cracks.
We have to keep shining a light on cultures being overlooked and the perpetual importance of diversity in every field. Use LLMs as a tool, but they cannot erase or dominate our cultural, creative, and strategic direction.
