Guest Articles

AI Washing: Drying, Folding Up, and Putting Away This Threat to the Growth of AI

AI washing erodes trust in artificial intelligence. Learn how false AI claims harm innovation and why transparency is critical.

Artificial intelligence has already had a positive effect on several industries, but unfortunately, this popularity and success have caused some wrongdoers to attempt to capitalize on the AI boom in unethical and illegitimate ways. One such practice is known as “AI washing,” and it is arguably one of the biggest threats to the continued growth of AI.

AI washing is most easily understood by comparing it to the similar practice of greenwashing, in which companies misrepresent their products as being more eco-friendly than they actually are. Similarly, AI washing involves making false representations of a product or service’s use of artificial intelligence technology. Through this deceit, businesses are riding the wave of AI hype without offering their customers the benefits.

Understanding AI washing

One of the most common examples of AI washing takes advantage of many consumers’ lack of knowledge about artificial intelligence with misleading product descriptions. For example, a business could claim that traditional algorithms are artificial intelligence, yet because of the similarities between the two technologies, the average consumer might not realize they are being misguided.

Some businesses are guilty of a form of AI washing in which they exaggerate the scale of the capabilities or use of AI as it relates to their business. For example, a company might claim to offer “AI-powered services” when, in reality, it only uses artificial intelligence in ways incidental to its business. Even though these businesses do use AI to some extent, they have still misled the consumer into believing that their use is more extensive than it actually is.

Other businesses may claim to use artificial intelligence without substantially implementing it into their business. Some have claimed to use AI without using it at all, while others claim to use it while it’s still in its early stages of development and has no noticeable effects.

Why AI washing is bad for everyone

The most obvious consequences of AI washing are for consumers who have been misled by companies and their deceitful marketing. Because of the intense hype around artificial intelligence, consumers may use a company’s claims regarding its use of AI to inform their purchasing decisions, spending their hard-earned money — sometimes at a premium — purchasing products or services with the expectation of higher levels of performance. When AI-washed products don’t deliver, consumers’ wallets suffer.

There are more than just direct victims of AI washing, though, as companies that make false claims about artificial intelligence are effectively stealing from the real innovators. Any investments in or purchases from a company representing themselves with AI washing are funds that could have been going to a company that genuinely supports and uses artificial intelligence.

However, perhaps the most detrimental impact of AI washing is that it erodes the public’s trust in the technology itself. AI washing conditions consumers and stakeholders to expect underperformance, fueling their reluctance to embrace genuine AI innovations due to feeling so often disappointed by products mislabeled as artificial intelligence. Especially in a time when AI technology is still “emerging” and people are learning to live with it, restoring and preserving this trust should be a top concern.

Stopping the practice of AI washing

To combat the harmful practice of AI washing, we must strive to increase transparency and honesty in the artificial intelligence space. Although the number of businesses participating in this predatory practice is, thankfully, quite small, the harm it causes to those who are actually using artificial intelligence for legitimate, beneficial purposes is disproportionate and must be stopped.

One approach the industry itself can take to support this increased transparency and honesty is establishing certification bodies to self-regulate claims made about artificial intelligence. These organizations could create benchmarks by which AI technologies can be evaluated, giving consumers and investors a better way to verify the capabilities of AI products and the validity of AI claims. This creates a trusted mark of authenticity that can be used to inform investment decisions.

Others have suggested that more formal regulation and legislation is the solution to curbing the negative effects of AI washing, such as regulatory bodies like the SEC implementing restrictions on companies making AI claims to ensure that there are no deceptive practices. By imposing stringent verification processes and penalties for false claims, jurisdictions can discourage companies from this deceitful practice.

That being said, the most powerful way we can combat the negative effects of AI washing is by improving education about this harmful practice. People who are informed about the features and benefits of genuine AI technology will be more able to identify fraudulent claims and not fall victim to the deceit of AI washing. Thus, by fostering a conversation around the use of artificial intelligence, proponents of the technology can create a landscape where people are less likely to fall victim to the deceit.

AI washing is one of the biggest obstacles to the widespread embrace of AI as a force of positive change. By making false claims about artificial intelligence technology and its capabilities, businesses that AI wash their products and services are undermining the work of those who genuinely want to make a positive difference with this innovation. 

Through legislation, self-regulation, and education, we can curb the negative effects of this harmful practice and create an ecosystem conducive to the use of AI for good.

Explore AITechPark for top AI, IoT, Cybersecurity advancements, And amplify your reach through guest posts and link collaboration.

Related posts

CCMSI Saves Employers $300 Million in Workers’ Compensation Claims with AI

Gia Sawko

Struggling with ROI in AI? A Lesson in Scale from AI Leaders

Alexis Fournier

Evaluating AI for Retail Pricing

Matthew Pavich