What is AI Washing?
AI washing is a deceptive marketing strategy where companies exaggerate or falsely claim the use of artificial intelligence (AI) in their products or services. This tactic aims to exploit the growing interest in AI to make offerings appear more innovative and advanced than they truly are. For instance, a business might advertise its chatbot as “Powered by the latest AI technology” when, in reality, it simply matches keywords with pre-written responses.
While AI washing is fundamentally deceptive, it’s important to recognize that sometimes this misrepresentation is unintentional. Marketers might overstate the role of AI due to a lack of understanding of the technology.
Origins of AI Washing
The term “washing” in marketing refers to aligning a product or service with current trends to make it more appealing. This concept is rooted in one of the meanings of whitewashing: presenting a sanitized or misleading version of something to create a favorable impression.
How AI Washing Works
Companies engaged in AI washing often use vague language and AI-related jargon to capitalize on the general public’s limited understanding of AI. For example, they might describe a product as “AI-powered” because it automates workflows or claim their cloud service uses machine learning (ML) simply because it can analyze data.
The key issue is that many functions attributed to AI can be achieved with static programmed instructions. To genuinely be “Powered by AI,” artificial intelligence must be an integral part of the product or service’s operation.
Why Companies Engage in AI Washing
Companies may engage in AI washing to:
- Increase consumer and investor interest.
- Enhance brand value.
- Inflate the perceived value of a product/service.
- Justify higher pricing.
- Distract from a product’s shortcomings or limitations.
- Stay competitive in a fast-moving market.
- Create the perception of being more advanced than competitors.
Avoiding AI Washing Vendors
To avoid companies that engage in AI washing, it’s crucial to look for vendors that use the term “AI” accurately in both their internal and customer-facing communications. Consider the following steps:
- Check for detailed glossaries: Look for vendors whose websites and white papers include a glossary of AI-related terms.
- Examine the management team: If a company claims to develop AI in-house, check if their team has the necessary skills to create and tune AI models.
- Seek case studies and testimonials: Review any published case studies or customer testimonials that explain how the vendor’s AI has solved specific problems.
Asking the Right Questions
When speaking with a vendor representative, consider these questions to determine if they might be AI washing:
- Define AI: Ask them to define what they mean by AI. The explanation should be clear and understandable.
- Core functionality: Inquire about the AI technology their product/service relies on for its core functionality. Remember, using AI tools in development does not make an offering “AI-powered.”
- Data and model handling: Ask about the data used to train their AI models and how they handle bias and model drift. A clear, knowledgeable response is essential.
The Consequences of AI Washing
AI washing, like any deceitful marketing tactic, can backfire. When consumers find that a product doesn’t deliver the AI capabilities advertised, they are likely to stop using it and seek alternatives that truly meet their needs. Negative reviews and social media posts can damage the company’s reputation, leading to a loss of trust and more negative publicity. This cycle can ultimately turn AI into just another tech buzzword.
Moreover, the negative impact of AI washing can harm the perception of AI as a whole, making it harder for legitimate AI projects to gain trust and funding.
Impact on Technology and Innovation
The hype around AI, even when positive, creates noise that makes it difficult for truly innovative companies to stand out. AI washing exacerbates this issue by diverting funds and attention from genuine AI advancements to those with superior marketing strategies.
This creates a vicious cycle:
- Skepticism about AI’s value.
- Difficulty attracting investors and customers.
- Slowed AI advancements.
Real-Life Examples of AI Washing
In the United States, the Securities and Exchange Commission (SEC) charged two investment advisory firms, Delphia Inc. and Global Predictions Inc., with AI washing. Delphia claimed it “put[s] collective data to work to make our artificial intelligence smarter so it can predict which companies and trends are about to make it big and invest in them before everyone else.” Meanwhile, Global Predictions touted itself as the “first regulated AI financial advisor” offering “[e]xpert AI-driven forecasts.”
Investigations revealed that both companies misrepresented their AI capabilities. They agreed to settle the SEC’s charges and pay a total of $400,000 in civil penalties. Gurbir S. Grewal, Director of the SEC’s Division of Enforcement, stated, “As more and more investors consider using AI tools in making their investment decisions or deciding to invest in companies claiming to harness its transformational power, we are committed to protecting them against those engaged in AI washing.”
The Regulatory Landscape of AI Washing
When a company claims to offer AI-powered solutions but fails to explain how AI is used or exaggerates its role, it’s misleading at best and fraudulent at worst. The intent and extent of misrepresentation play crucial roles in determining legal consequences.
Currently, no comprehensive law specifically addresses AI washing. However, regulations around AI transparency, ethics, and accountability indirectly impact AI washing. The European Union Artificial Intelligence Act (EU AI Act), for example, is expected to define AI legally and mandate transparency requirements, potentially deterring AI washing by requiring companies to substantiate their claims.
The Bottom Line
While it might be tempting for marketers to label anything developed with AI tools as “AI-powered,” true AI integration means the technology must be a core component of the product or service, enhancing performance, efficiency, or user experience beyond what traditional computing methods can achieve. Only then can companies legitimately claim their offerings are “Powered by AI.”
