Despite my unwavering belief in AI’s transformative potential, it’s undeniable that there’s a lot of hype and exaggeration surrounding the subject. This is not surprising, considering studies indicating that startups mentioning ‘AI’ attract significantly more investment. However, it’s crucial to differentiate between genuine advancements and marketing ploys designed to sell us something that may not be as revolutionary as it seems.
AI washing involves exaggerating the capabilities of products and services labeled as ‘AI’ to make them appear more sophisticated and innovative than they actually are. It’s essentially a form of bandwagon jumping, akin to greenwashing, which overstates the environmental friendliness of products or services.
Marketers engaged in AI washing often overstate their capabilities, implying that their AI models and algorithms are more powerful, useful, or flexible than they genuinely are. They may also misleadingly use the term ‘intelligent’ when the software doesn’t use algorithms capable of learning and making decisions without explicit programming. Additionally, they may offer vague definitions, failing to clarify which elements are ‘intelligent’ and which rely on traditional software methodologies or human input. They downplay the amount of human input involved, either on the part of the service provider or the user.
AI washing can stifle true innovation as real AI breakthroughs struggle to gain attention amidst the noise of exaggerated claims. It erodes consumer trust in AI, leading to cynicism about industry claims. Investors seeking to support genuinely innovative projects may miss opportunities due to inflated expectations. Businesses setting unrealistic goals and targets can also result from inflated expectations.
Examples of AI washing include labeling home appliances as ‘smart’ or ‘intelligent’ when they’re simply ‘connected.’ Despite being internet-connected and controllable via apps, they often lack the capacity to learn or operate autonomously, which is generally expected of AI applications. Many companies offer tools that claim to automate video, copy, and content creation. However, these tools often require substantial human input to generate acceptable output.
Coca-Cola was accused of AI washing for claiming to use AI to create a new drink. While they stated that the Y3000 flavor was ‘co-created’ with AI, there was no clear explanation of how AI was involved in the process. Critics suggested that it was merely name-dropping AI to make the product appear more innovative.
In the finance world, two firms were charged with making ‘false and misleading statements’ regarding the extent of AI’s use in managing their investment strategies.
Spotting AI washing involves developing a skeptical eye for claims. Look for specific models, technologies, or algorithms mentioned, such as natural language processing, neural networks, or deep learning. Seek out ‘transparent’ AI, where companies are open about the types of data and algorithms involved. Beware of companies that seem unwilling or unable to describe how their technology works. Sometimes, this information can be found in case studies or white papers published on corporate websites. Ask sales representatives to explain steps taken to avoid bias in their data and algorithms, or AI hallucinations. If they don’t have solutions to these problems, it’s possible that they aren’t using AI at all.
This skepticism is critical for making informed decisions about technology investments and contributing to a more honest and transparent AI landscape in the long run.
