The recent surge in AI tools has created a fascinating technology landscape, but it has also highlighted significant challenges, one of them being linguistic bias. As a multilingual entrepreneur, I’m constantly in awe of how technology can connect people from across the globe, but I’ve also seen firsthand how these tools can inadvertently perpetuate discrimination.
Anyone who has used ChatGPT knows it’s often scarily accurate in responding to queries. Still, the question remains: can it truly grasp the richness of the diverse ways people speak? For millions of users globally who communicate through various English dialects, these tools might not just fall short but might actually reinforce harmful stereotypes or dismiss their voices altogether.
The Data That Speaks Volumes
As a business owner, understanding global diversity in language has always been a priority for me. English may be a common denominator for many, but it’s not one-size-fits-all. A recent large-scale study found that even advanced models like GPT-3.5 Turbo and GPT-4 consistently default to a limited range of Standard English (primarily Standard American or British English), leaving users who speak other equally important dialects, such as Nigerian English, African American Vernacular English (AAVE), or Indian English, unsupported.
But the issue is deeper than a model simply misunderstanding slang or colloquialisms. The research indicates that ChatGPT sometimes generates responses to non-standard dialects that include implicit bias, stereotyping, or even condescending tones. For entrepreneurs or freelancers from diverse linguistic backgrounds, the implications of this cannot be overstated. How are we supposed to rely on tools for customer service, content creation, or dynamic client communication if they fall prey to biases rooted in the data they consume?
A Breakdown of Linguistic Bias in ChatGPT
The study revealed some stark statistics that caught my attention as a business leader:
Default to Standard Forms: Over 60% of the texts fed into ChatGPT in non-standard dialects resulted in responses skewed toward American or British English conventions. Imagine trying to communicate in your own natural voice only to find the system disregards it entirely. That doesn’t just feel dismissive, it stifles our ability to maintain authentic communication.
Stereotyping Increases: When asked to generate responses using non-standard dialects, GPT-4 produced stereotypical or demeaning content 19% more frequently compared to interactions using Standard English prompts.
Comprehension Challenges: Conversations in widely spoken non-standard dialects were, on average, 9% less accurately understood than those in Standard English. For an entrepreneur serving global clients, this gap could mean miscommunication, lost deals, or poor service.
Condescension in Responses: When models attempted to adopt a user’s dialect, there were frequent instances where the tone became patronizing, rated as 15% worse by native speakers of those dialects. Imagine anyone talking down to you based on how you speak, how can you trust that system again?
What This Means for Business Owners
For people like me, building startups that often cater to diverse audiences, these findings hit close to home. Most businesses use AI tools for tasks ranging from customer support to onboarding international clients. If the AI discriminates based on language use, it can create alienation, discourage engagement, and reflect poorly on the company.
Even within international teams, linguistic bias presents an obstacle. Something as simple as writing an internal report in your natural linguistic variety might lead to alienation if the AI tools your company depends on aren’t equipped to handle dialectical differences.
How To Mitigate Linguistic Bias in AI within Your Business
This challenge requires adapting, not abandoning, technology. Here’s how entrepreneurs and business owners can avoid common pitfalls:
Choose Diverse AI Tools: Before adopting any tool, check what data sources it is trained on. Companies like Strategyzer AI and local language-focused tools provide better initial diversity accommodation.
Conduct Real-World Testing: Never assume a tool works for everyone, even within your team. Test the tool with team members who communicate in varying dialects. Their feedback is indispensable.
Enable Customization Features: Leverage tools that allow you to refine outputs. For instance, platforms like Canvanizer AI and F/MS BMC Tool offer editable outputs, so corrections are possible.
Educate Your Team About Bias: Bring the topic front and center by discussing linguistic diversity openly. Many people don’t notice bias in AI tools until it directly affects them. Awareness sharpens focus.
Mistakes You Can Avoid
Being proactive is great, but it’s just as important to steer clear of common traps in dealing with language-based tools.
- Not questioning training data: Avoid assuming that all AI models are equally impartial. For example, ChatGPT’s training heavily favors Standard English.
- Failing to localize content: Global customers will appreciate it when your material feels culturally tailored to them.
- Ignoring feedback loops: If customers or team members report issues with your outputs being inaccurate or biased, take their concerns seriously and report them directly to the AI provider.
Why This Is a Wake-Up Call for Entrepreneurs
When we talk about language bias, it’s not just a theoretical issue or an academic argument. It’s something that can and will impact markets. Every time a customer’s concerns are undermined because of how they speak, it’s a loss, not just in sales but in credibility. And if your operations rely on tools that unknowingly commit such missteps, then you’re amplifying the problem.
I’ve spent much of my career navigating multicultural environments, and if there’s one key takeaway, it’s this: Language is power. The way we acknowledge or ignore dialects shows if we are building inclusive, fair organizations. Ignoring this aspect risks alienation, making all the difference for startups looking to secure diverse customer bases in today’s interconnected economy.
For anyone building AI solutions or relying on such tools for business, this research offers a critical reminder: Strive to go beyond what’s comfortable or default. It’s not just about making the right move today. It’s about being prepared for a world where inclusivity is not optional, and where consumers scrutinize whether tools see them, hear them, and respect them entirely.
Without addressing challenges like linguistic bias in tools like ChatGPT, we risk losing customers who feel undervalued. As we adopt new solutions, the goal must be simple: give everyone a fair share of this evolving technology while building tools that recognize the power held in every voice, dialect and all.
FAQ
1. What is linguistic bias in AI language models?
Linguistic bias in AI language models refers to the tendency of these systems, such as ChatGPT, to favor certain dialects or languages over others, often defaulting to Standard English while misunderstanding or stereotyping speakers of diverse dialects like Nigerian English, AAVE, or Indian English. Learn more about linguistic bias in AI
2. How do language models like ChatGPT exhibit linguistic bias?
Studies show that ChatGPT and similar models predominantly default to Standard American or British English and may interpret non-standard dialects with less accuracy, often introducing stereotyping, demeaning content, or condescending responses. Explore findings on ChatGPT’s linguistic bias
3. What is the default behavior of ChatGPT when handling non-standard dialects?
ChatGPT tends to convert or respond in Standard English even when the input is in a non-standard dialect, disregarding the original linguistic variety. This skewed behavior has been shown to occur over 60% of the time. Check out BAIR’s study on linguistic bias
4. What are the implications of linguistic bias for businesses?
Linguistic bias in tools like ChatGPT can lead to miscommunications, stereotyping, and an unwelcoming experience for users who communicate in non-standard dialects. This can discourage customer engagement and negatively impact businesses. Read about the impact on businesses at Femaleswitch
5. How does GPT-4 perform when responding to non-standard dialects compared to GPT-3.5?
Although GPT-4 performs better in comprehension and responses to non-standard dialects, it also shows a marked increase in stereotyping compared to GPT-3.5. Explore the differences between GPT-3.5 and GPT-4
6. Can language models improve representation of non-standard dialects?
Yes, but they require training on larger, more diverse datasets that include underrepresented dialects to reduce biases and ensure fair treatment for all users. Discover more about the need for diverse AI training data
7. What are strategies to counteract linguistic bias in AI tools?
Some strategies include using diverse datasets for training, enabling customization options in AI tools, conducting real-world testing with diverse language varieties, and raising awareness about linguistic diversity. Learn about countering linguistic bias in AI
8. How can entrepreneurs address AI-related linguistic bias?
Business owners can select AI tools trained on diverse datasets, consult team members fluent in different dialects during testing, and provide feedback to AI providers about observed biases. Check out F/MS BMC Tool for inclusive AI tips
9. Does the use of AI contribute to cultural biases?
Yes, AI tools can perpetuate cultural biases, especially when they fail to accurately interpret or support diverse languages and dialects, thus limiting inclusivity and favoring dominant cultures. Learn about AI and cultural biases at ASCCC
10. What actions are researchers suggesting to mitigate linguistic bias in AI?
Researchers recommend collecting data from diverse linguistic sources and conducting evaluations by native speakers to identify and rectify biases in AI models. Read about research strategies to combat AI bias
About the Author
Violetta Bonenkamp, also known as MeanCEO, is an experienced startup founder with an impressive educational background including an MBA and four other higher education degrees. She has over 20 years of work experience across multiple countries, including 5 years as a solopreneur and serial entrepreneur. Throughout her startup experience she has applied for multiple startup grants at the EU level, in the Netherlands and Malta, and her startups received quite a few of those. She’s been living, studying and working in many countries around the globe and her extensive multicultural experience has influenced her immensely.
Violetta Bonenkamp’s expertise in CAD sector, IP protection and blockchain
Violetta Bonenkamp is recognized as a multidisciplinary expert with significant achievements in the CAD sector, intellectual property (IP) protection, and blockchain technology.
CAD Sector:
- Violetta is the CEO and co-founder of CADChain, a deep tech startup focused on developing IP management software specifically for CAD (Computer-Aided Design) data. CADChain addresses the lack of industry standards for CAD data protection and sharing, using innovative technology to secure and manage design data.
- She has led the company since its inception in 2018, overseeing R&D, PR, and business development, and driving the creation of products for platforms such as Autodesk Inventor, Blender, and SolidWorks.
- Her leadership has been instrumental in scaling CADChain from a small team to a significant player in the deeptech space, with a diverse, international team.
IP Protection:
- Violetta has built deep expertise in intellectual property, combining academic training with practical startup experience. She has taken specialized courses in IP from institutions like WIPO and the EU IPO.
- She is known for sharing actionable strategies for startup IP protection, leveraging both legal and technological approaches, and has published guides and content on this topic for the entrepreneurial community.
- Her work at CADChain directly addresses the need for robust IP protection in the engineering and design industries, integrating cybersecurity and compliance measures to safeguard digital assets.
Blockchain:
- Violetta’s entry into the blockchain sector began with the founding of CADChain, which uses blockchain as a core technology for securing and managing CAD data.
- She holds several certifications in blockchain and has participated in major hackathons and policy forums, such as the OECD Global Blockchain Policy Forum.
- Her expertise extends to applying blockchain for IP management, ensuring data integrity, traceability, and secure sharing in the CAD industry.
Violetta is a true multiple specialist who has built expertise in Linguistics, Education, Business Management, Blockchain, Entrepreneurship, Intellectual Property, Game Design, AI, SEO, Digital Marketing, cyber security and zero code automations. Her extensive educational journey includes a Master of Arts in Linguistics and Education, an Advanced Master in Linguistics from Belgium (2006-2007), an MBA from Blekinge Institute of Technology in Sweden (2006-2008), and an Erasmus Mundus joint program European Master of Higher Education from universities in Norway, Finland, and Portugal (2009).
She is the founder of Fe/male Switch, a startup game that encourages women to enter STEM fields, and also leads CADChain, and multiple other projects like the Directory of 1,000 Startup Cities with a proprietary MeanCEO Index that ranks cities for female entrepreneurs. Violetta created the “gamepreneurship” methodology, which forms the scientific basis of her startup game. She also builds a lot of SEO tools for startups. Her achievements include being named one of the top 100 women in Europe by EU Startups in 2022 and being nominated for Impact Person of the year at the Dutch Blockchain Week. She is an author with Sifted and a speaker at different Universities. Recently she published a book on Startup Idea Validation the right way: from zero to first customers and beyond, launched a Directory of 1,500+ websites for startups to list themselves in order to gain traction and build backlinks and is building MELA AI to help local restaurants in Malta get more visibility online.
For the past several years Violetta has been living between the Netherlands and Malta, while also regularly traveling to different destinations around the globe, usually due to her entrepreneurial activities. This has led her to start writing about different locations and amenities from the POV of an entrepreneur. Here’s her recent article about the best hotels in Italy to work from.