Eliminating Bias in AI Training for Small Business Owners 

Artificial intelligence (AI) tools can be a game-changer for small businesses – helping automate tasks, improve customer service, and make faster decisions.  

But like any tool, AI isn’t perfect. AI can make unfair or inaccurate decisions if it’s trained on biased or incomplete data. That’s where the issue of AI bias comes in. 

What is AI bias? 

AI bias happens when an artificial intelligence system produces results that are unfair, inaccurate, or skewed toward a particular group of people. This usually stems from the data the AI was trained on. If that data is limited, outdated, or reflects human biases, the AI will learn and repeat those patterns. 

For small business owners, this can lead to unintended consequences like turning off potential customers, making bad hiring decisions, or missing out on valuable opportunities. 

AI bias example #1 

Let’s say a small business owner decides to use an AI-powered chatbot to help with their business. Its purpose is to answer customer questions online.  

However, if the chatbot was trained mostly on interactions from customers who speak English as a first language, the chatbot may have trouble understanding people who use different dialects or have limited English skills. This could frustrate international or non-native-speaking customers, which could potentially drive them away and cost you sales. 

AI bias example #2 

It’s often necessary for small business owners to wear many hats – including filling the role of HR when hiring new employees.  

In this example, a small business owner decides to free up time by using an AI tool to help screen job applications.  

But if the AI tool was trained using past hiring data that reflects unconscious bias (such as mostly hiring men or people with English names), it may begin favouring certain candidates over others – even if the alternate candidate is just as qualified. This kind of bias not only hurts diversity but can also lead to missed talent opportunities.  

Where does AI bias come from? 

AI learns from the data it is given and the choices made by the people who designed it. This means that, generally, AI bias is not intentional. But it can sneak in at different parts of the AI’s development. Knowing where AI bias stems from can help small business owners choose the right kind of tools and ask informed questions.  

Biased training data 

Most AI systems learn by studying massive amounts of data. That said, if that data does not represent the full range of people or situations that your business is designed to help, then the AI may develop a narrow or unbalanced understanding of the world.  

Bias can come from: 

• Underrepresentation of certain groups (e.g., women, minorities, older people). 

• Outdated information that no longer reflects current behaviours or values. 

• Stereotypes embedded in language or images the AI was trained on. 

The role of human decision-making in AI training 

Even before the data is used, bias can creep in through the choices made by developers. These decisions include: 

• What data to collect (and what to leave out). 

• Which features or patterns the AI should focus on. 

• How data is labelled or interpreted by humans during training. 

For example, if a developer assumes that past hiring patterns are a reliable indicator of “success,” they may unknowingly reinforce past biases like favouring certain names, educational backgrounds or career paths. Or, if a marketing AI is trained to target “ideal” customers based on a narrow dataset, it might exclude potentially valuable audiences.  

Why AI bias matters for small business owners 

Using AI in your business can help speed things up, saving you time and helping you to grow your business. However, if the technology is biased, then it can create more problems than it solves.  

Impact on customers and reputation 

All customers expect fair, honest, inclusive treatment, whether they’re messaging a chatbot or speaking with someone face to face. If an AI tool gives inconsistent or incorrect information, misidentifies customer needs, or simply doesn’t understand what a customer is trying to tell it, the situation can escalate quickly.  

For example, if your online chatbot only understands standard English and struggles with different accents or slang, it could alienate culturally diverse or non-native English-speaking customers.  

Over time, these small errors will eventually erode trust, hurt your business’s reputation and could eventually lead to negative reviews.  

Legal and ethical considerations 

AI bias can have legal repercussions, too. If an AI tool makes decisions that result in unfair treatment (like screening out job applicants based on gender, ethnicity, marital status or age) your business could be held accountable under anti-discrimination laws, even if the bias was unintentional. 

Using AI ethically and responsibly is just as much about doing the right thing as staying compliant and protecting your business from potential lawsuits. 

How small business owners can identify and avoid AI bias 

According to research from the Department of Industry, Science and Resources, more and more Australian businesses are jumping on board with AI. However, the number of businesses that are adopting AI (35%) is still outweighed by those who are unsure of how to use AI (23%) and those who are not planning on using AI (42%).  

The industry with the highest rate of total non-adoption and unawareness was agriculture, forestry and fishing. Only 6% of businesses in this sector were adopting AI. Manufacturing and education had the highest rate of adoption, with 45% each.  

These statistics go to show that there is still a lot of hesitancy around AI adoption. This seems to be because of a lack of education and tailored information for different sectors. This can have serious repercussions for certain sectors.  

A lack of education and information means that people are less likely to adopt AI. This could put them at a disadvantage compared to their competitors who are using AI. But what it also means is that those who do begin to use AI may do so without comprehending the challenges and risks involved.  

While many different businesses can benefit from integrating AI, it’s necessary to have some understanding of the tools you plan on implementing. If you are planning on using AI in your small business, then it’s important to know what kinds of questions to ask and how to move forward responsibly and ethically.  

Ask the right questions when choosing AI tools 

Before adopting any AI tool, it’s important to ask vendors or developers a few key questions. You don’t need to be a tech wizard, just focus on how the tool was built and tested.  

Here’s a simple checklist to help get you started: 

1. How was the AI trained? Ask what kind of data was used. If the vendor can’t give a clear answer, it may be a red flag. 

2. Was the training data diverse and representative?  Make sure the data reflects the real variety of people, behaviours, and situations relevant to your business, not just one narrow group. 

3. Has the model been tested for bias?  Vendors should be able to explain what steps they’ve taken to reduce bias and how they’re monitoring for fairness. 

4. Can I adjust or control how the AI behaves?  Some tools offer settings or customisation options. Ask if you can fine-tune the tool based on your audience or values. 

5. What happens when the AI gets something wrong?  Check whether there’s a fallback plan – like human review –  and how errors are tracked or fixed. 

Start small and monitor outcomes 

Whenever you roll out something new within your business, it’s usually best to take small steps and monitor progress. AI is the same. 

When introducing AI into your business, start with a small, manageable use case. This might be a chatbot on your website or a tool for sorting customer emails. 

As you roll it out, keep a close eye on how it behaves. Watch for patterns that might suggest bias, such as: 

• Certain types of customers receiving unhelpful or cold responses. 

• Some job applicants never making it past the first filter. 

• Ads being shown to only one kind of audience. 

This kind of iterative approach can help to make sure that any problems are weeded out early. This ensures that bad habits are not reinforced.  

Get feedback from customers 

Your customers and employees are your best source of truth. If something feels wrong, they will notice – and it’s important that you’re there to listen to them.  

Encourage feedback from both staff and customers and invite them to share their experiences. This kind of input can help you spot subtle issues the AI might miss, while also giving you the chance to fix minor problems before they become unmanageable.  

Embracing AI responsibly 

AI has the power to help small businesses work smarter, connect with more customers, and make better decisions – but only if it’s used thoughtfully and responsibly. AI in bias is not always obvious, but it can have serious consequences for your brand and bottom line.  

By asking the right questions, starting small and being open to feedback, you can take advantage of the benefits AI has to offer while avoiding the pitfalls.  

This information is general only and does not take into account your objectives, financial situation or needs. It should not be relied upon as advice. As with any insurance, cover will be subject to the terms, conditions and exclusions contained in the policy wording. 

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