The release of OpenAI’s ChatGPT in 2022 sparked a wave of enthusiasm and interest in generative AI, leading to a significant hype cycle that continues to reach new heights with each innovation.
In this environment, many tech companies and startups have begun marketing AI products that promise to revolutionize consumer experiences.
Amidst this surge, a concerning trend has emerged AI washing. This term, popularized by the US Securities and Exchange Commission, refers to the practice of companies exaggerating their use of AI technologies to appeal to consumers and investors.
Understanding AI washing and its implications is crucial, as this practice can have far-reaching consequences for both consumers and the tech industry.
The Rise of AI Washing
In the wake of OpenAI’s ChatGPT release, the tech industry has seen a dramatic increase in companies claiming to use AI in their products and services.
This surge is evident in the growing number of startups and established firms incorporating AI into their pitches and marketing strategies.
According to a study by an investment fund for new tech firms, the percentage of startups mentioning AI in their pitches increased from 10 per cent in 2022 to over 25 per cent in 2023.
More than half of S&P 500 companies referenced AI in their earnings calls last year, according to a report by NBC News.
The reality behind these claims often falls short. A survey by the US Census Bureau in November last year revealed that only 4.4 per cent of American businesses were actually using AI to produce goods and services.
Similarly, a 2019 survey by London-based venture capital firm MMC found that 40 per cent of European AI startups did not use any AI at all. This gap between claims and actual implementation forms the basis of AI washing.
AI washing, much like greenwashing, involves companies overstating their AI capabilities to attract customers and investors.
This can include exaggerating the sophistication of their technology or misleading consumers about the operational status of AI features in their products.
The practice has become increasingly prevalent as businesses rush to capitalize on the AI hype, often prioritizing marketing over genuine technological development.
Real-Life Examples of AI Washing
The rapid advancement and vast potential of AI have led many companies, including some tech giants, to cut corners when rolling out AI-based products.
For instance, Google released Gemini with a video showcasing its AI chatbot’s ability to recognize pictures and real objects. It was later revealed that the video wasn’t shot in real time but was made by feeding text prompts to Gemini and stitching still frames together.
Although the YouTube description had a disclaimer, the video itself lacked this transparency. Amazon faced similar scrutiny when it removed its cashier-less checkout systems from many grocery stores.
Business Insider reported that the ‘Just Walk Out’ technology, which claimed to use AI and sensors to detect items in a customer’s cart, actually relied on human reviewers in India to process transactions.
This revelation highlighted the discrepancy between Amazon’s AI claims and the actual technology used. Multinational brands like McDonald’s and Coca-Cola have also been implicated in AI washing.
McDonald’s abandoned its AI technology at drive-thru restaurants in the US after customers experienced numerous errors in their orders.
Coca-Cola’s attempt to introduce a limited edition, AI-created flavour of their drink also fell flat, failing to impress customers and casting doubt on the company’s AI capabilities.
A surge of AI apps claiming advanced chatbot functionalities has turned out to be mere wrappers for ChatGPT, using OpenAI’s technology rather than their own.
In India, Ola founder Bhavesh Agarwal’s startup released a beta version of Krutim AI, touted as a homegrown ChatGPT rival. Users quickly questioned its authenticity when the chatbot seemed to confirm it was created by OpenAI.
The startup later attributed this to a “data leakage issue” from an open-source dataset used in training the model.
These examples underscore the pervasive nature of AI washing and its potential to mislead consumers and investors, highlighting the need for greater transparency and honesty in the tech industry’s AI claims.
The Consequences of AI Washing
AI washing may initially appear as harmless marketing hyperbole. Still, it can have significant and far-reaching consequences for both consumers and the tech industry.
For consumers, exaggerated AI claims can lead to data security and privacy risks. When companies overstate their AI capabilities, the actual technology might not be robust enough to protect sensitive information, leading to potential breaches and misuse of data.
For businesses, AI washing diverts resources and attention from genuine AI innovation. Instead of investing in meaningful advancements, companies might focus on superficial enhancements to appear more technologically advanced.
This misallocation of resources can slow down real progress and hinder the development of effective AI solutions.
As noted by Linda Yao, Lenovo’s vice president of AI solutions and services, AI washing can complicate decision-making for businesses genuinely seeking valuable AI tools, thereby stifling innovation and jeopardizing performance.
AI washing can erode trust between businesses and their customers. When consumers discover that a company’s AI claims are exaggerated or false, it can lead to scepticism and reluctance to adopt new technologies.
This can ultimately slow down the overall acceptance and integration of AI into various sectors, hindering the potential benefits that AI can offer. Regulatory bodies have started to address the issue of AI washing.
The US Federal Trade Commission recommends that businesses ask critical questions to avoid misleading AI claims, such as whether they are exaggerating their AI product’s capabilities or if the product actually uses AI.
India’s Securities and Exchange Board of India has issued warnings against AI washing in financial products to prevent misrepresentation.
Regulatory Responses
Regulatory bodies have recognized the risks associated with AI washing and have started to implement measures to address these issues.
The US Securities and Exchange Commission has played a significant role in popularizing the term AI washing by taking action against companies that make false AI claims.
In March 2024, the SEC fined investment advisory firms Global Predictions and Delphia a combined total of $400,000 for making misleading statements about their AI-driven forecasts and machine learning capabilities.
The US Federal Trade Commission has also provided guidelines to help businesses avoid AI washing. The FTC advises companies to ask themselves critical questions, such as whether they are overstating what their AI products can do or if their AI products genuinely outperform non-AI alternatives.
The FTC emphasizes that merely using an AI tool in the development process does not equate to the final product being AI-powered.
These guidelines aim to ensure that businesses provide honest and accurate information about their AI capabilities, preventing consumers from being misled.
In India, the Securities and Exchange Board of India issued a circular in 2019 warning against AI washing in investor-facing financial products.
SEBI highlighted the importance of transparency in AI and machine learning systems, noting that the behaviour of these systems cannot be easily quantified.
SEBI stressed that any advertised financial benefits derived from AI technologies must not constitute misrepresentation, urging financial intermediaries to provide clear and accurate information about their AI-driven products.
These regulatory responses and guidelines are crucial in maintaining the integrity of the tech industry and protecting consumers from the adverse effects of AI washing.
By holding companies accountable for their AI claims and promoting transparency, regulatory bodies aim to foster genuine innovation and build trust in AI technologies.
AI washing, the practice of exaggerating AI capabilities, poses significant risks to both consumers and businesses. It can lead to data security issues, misallocated resources, and eroded trust in AI technologies.
Regulatory bodies like the SEC, FTC, and SEBI have started to address these concerns by implementing guidelines and taking action against misleading AI claims.
To ensure the sustainable growth and adoption of AI, companies must prioritize transparency and genuine innovation.
