Demographic bias occurs when a dataset represents a certain type of person more than others. For example, demographic bias would likely happen when a marketing company – whether intentionally or unintentionally – surveys considerably more men than women.
In this case, the likely consequence of demographic bias is that the marketing company won’t create a campaign that appeals to many women, which could lead to lower sales and revenues. It’s an example of gender bias that might happen unconsciously as marketers choose how to collect and use data. Other common forms of unconscious demographic bias include racial bias and ageism.
Improving data quality could help solve this issue and avoid further consequences of demographic bias.
Today’s businesses rely on data to make choices that lead to greater success. If your business’s information is tainted by demographic bias, you might fail to build popular products or create marketing campaigns that reach consumers. Enroll in the Data Science for Business Leaders course at Pragmatic Institute to effectively work with data teams and learn more about positioning your business for success.
Demographic Bias Could Make Business Proposals Less Appealing
Imagine that your small business has spent years building a product that could make the world a better place. Now, you need to find partners who can help you perfect and release the product. In your experience, most CEOs are white men – 86% of Fortune 500 CEOs were white men in 2021 – so you create presentation materials that will appeal to that audience. You probably don’t intend to leave out women and people of color, but your experience includes demographic bias that guides your choices.
Unfortunately for your business, you learn that many of the potential partners you plan to meet with are women of color. You think about your presentation and wonder whether it will effectively communicate insights to an audience you didn’t expect.
In some cases, failing to acknowledge growing diversity in business leadership could make your proposals less appealing. Here, the consequence of demographic bias is that you will need to present your ideas to more people before you find a helpful partner. Alternatively, you might not ever find the right partner for your project, which means your product will never go to market.
Demographic Bias Contaminates Artificial Intelligence
Demographic bias has become a common concern during the rise of artificial intelligence (AI). Research with ChatGPT shows that it often manifests political and demographic biases. When researchers at the Manhattan Institute asked ChatGPT to take political orientation tests, the chatbot earned left-leaning scores 14 out of 15 times.
Other investigators have found that AI products generate bigoted responses. ChatGPT produced some alarming results when asked to write a Python program that would determine whether to torture someone. ChatGPT’s Python program shows that the person should be tortured if they’re from North Korea, Syria, or Iran.
Why would AI generate such a concerning result? Demographic bias probably plays a role. When OpenAI trained ChatGPT, it used content – including news reports and opinion pieces – written by people with demographic biases. These biases become a part of the artificial intelligence that could contaminate your business processes and decisions.
Further training might reduce the demographic bias in AI products, but progress relies on business leaders committed to using reliable, accurate data. Register for Data Science for Business Leaders to learn how you can avoid demographic bias that might contaminate artificial intelligence and other digital products.
Demographic Bias Can Affect Who Companies Hire
Many companies want to address diversity and equity issues within their workplaces. Doing so could give them competitive advantages by tapping into the ideas of diverse populations. When you have a more diverse workforce, you take a step toward serving a more diverse audience.
Unfortunately, demographic bias often prevents hiring companies from reaching those goals. Most businesses rely on software that scans resumes and highlights the best candidates. Many of those AI-driven solutions have built-in demographic biases that could prevent companies from considering highly qualified candidates.
The public already sees a problem with adding AI to the hiring process. About 66% of U.S. adults say they would not apply for a job that uses AI to make hiring decisions. The public perception of demographic bias in AI solutions creates a problem that businesses must face head-on. As long as people fear the bias of AI, they will avoid companies using it.
Business leaders serious about creating diverse teams must acknowledge the possibility of demographic bias in HR software, find solutions, and communicate their commitments to potential applicants.
Giving Business Leaders a Foundation in Data Science
Pragmatic Institute’s Data Science for Business Leaders course teaches business leaders how to partner effectively with data professionals, discover the right data-driven solutions for their industry, and harness insights for more inclusive and equitable decision-making.
Sign up for the Data Science for Business Leaders training today so you can start combating the consequences of demographic bias as soon as possible.
