Hype over reality: How AI washing can dent businesses and delude users | Technology News

Hype over reality: How AI washing can dent businesses and delude users | Technology News

Soon after the release of OpenAI’s ChatGPT in 2022, there was an explosion of news and a massive surge of interest in generative AI, triggering a hype cycle that continues to peak with each new model or feature. Suddenly, it seems every tech company or startup is marketing an AI product that promises to revolutionise consumer behaviour.

According to a study by an investment fund for new tech firms, the number of startups mentioning AI in their pitches rose from 10 per cent in 2022 to more than 25 per cent in 2023. Over 50 per cent of S&P 500 companies referenced AI in their earnings calls last year, according to a report by NBC News.

But how many of these companies are walking the talk? In November last year, a survey by the US Census Bureau found that just 4.4 per cent of American businesses were using AI to produce goods and services. A 2019 survey by London-based venture capital firm MMC said that 40 per cent of European AI startups didn’t use any AI at all.

Tech companies and startups marketing themselves as using AI, but not doing so forms the basis of ‘AI washing’.

What is AI washing?

AI washing is a term derived from greenwashing, where companies exaggerate their environmental friendliness to appeal to customers. Similarly, businesses that claim to have integrated AI into their products, when they’re actually using less sophisticated technology, can be accused of AI washing.

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Advertisements that overstate the capabilities of a company’s AI tools or mislead consumers about features that are not yet operational in their AI products also constitute AI washing.

While it is unclear who coined the term AI washing, it was popularised by the US Securities and Exchange Commission (SEC) when it levied fines worth $225,000 (Rs 1.8 crore) and $175,000 (Rs 1.4 crore) against investment advisory firms Global Predictions and Delphia in March 2024. The securities regulator found that the companies had made false statements to their clients about providing ‘expert AI-driven forecasts’ and using machine learning to manage retail client portfolios.

What are some real-life examples of AI washing?

The rapid advancement and vast potential of AI have pushed many companies, including a few tech giants, to cut corners when it comes to rolling out their AI-based products. For instance, Google unveiled Gemini last year with a demonstrative video intended to show off its flagship multimodal AI chatbot, especially its ability to recognise pictures and real objects. In a portion of the video, a person draws a picture of an animal which Gemini correctly guesses as a duck.

However, it turned out that the video wasn’t shot in real time. In fact, Google confirmed to Bloomberg that the video was made by feeding text prompts to Gemini and stitching still frames together. While the YouTube description of the clip carried a disclaimer, there was no such disclosure in the video itself.

More recently, Amazon reportedly removed its cashier-less checkout systems from many grocery stores after Business Insider found that the ‘Just Walk Out’ technology, which claimed to use AI and sensors to detect what was in a customer’s shopping cart, actually relied on employees in India to review the transactions.

Not just tech companies, the AI-related claims of multinational brands such as McDonalds and Coca Cola have also come under scrutiny. McDonalds recently decided to ditch its AI technology at drive-thru restaurants in the US after customers complained that their orders had been incorrectly taken down. Meanwhile, Coca Cola attempted to jump on the AI hype train last year by introducing a limited edition, AI-generated flavour of the cold drink which ultimately failed to impress many customers.

There has also been a wave of AI apps that boast of chatbot functionalities when in reality they are just ChatGPT wrappers, meaning that the underlying technology powering the apps is not theirs but belongs to OpenAI.

In India, Ola founder Bhavesh Agarwal’s startup released a beta version of Krutim AI which was touted as being a homegrown ChatGPT rival. However, many users started questioning if Krutim AI was a ChatGPT wrapper after the chatbot purportedly confirmed to them that it was “created by OpenAI.” Responding to the speculation, the startup said that it investigated the issue and found the root cause to be a “data leakage issue originating from one of the open-source datasets used in the Large Language Model (LLM) fine-tuning process.”

Even the electronics manufacturing industry has not been spared by the AI washing effect. For instance, French company Kolibree came out with an AI-powered toothbrush in 2017 that essentially uses sensors to detect how users are brushing their teeth, after which “deep learning algorithms” analyse the data to provide personalised recommendations on how users can improve their brushing. As per reports, the annual consumer trade show CES 2024 held in Las Vegas, US, saw a proliferation of gadgets crammed with an LLM and being sold under the generative AI banner.

The rush to be branded as an AI business follows a long pattern of companies looking to capitalise on the hype surrounding new and emerging technologies. At the peak of the crypto boom back in 2017, the Long Island Iced Tea Company rebranded itself to Long Blockchain Corp only for the US SEC to revoke the beverage maker’s stock registration in 2021 as it reportedly never put its blockchain business into operation.

Why is AI washing a growing concern?

While AI washing may seem like harmless hyperbole, it could have far-reaching consequences for consumers and the tech industry itself.

Linda Yao, Lenovo’s vice president of AI solutions and services, explained to ZDNet that AI washing diverts management attention and resources away from practical AI innovation. Instead of developing meaningful AI capabilities, companies might make misguided investments in superficial enhancements, slowing real progress with the technology.

Yao also pointed out that AI washing can complicate decision making for businesses that are genuinely looking for valuable AI solutions. This can hinder their digital transformation efforts, stifle innovation, and jeopardise performance, she said. As for consumers, the Lenovo senior executive said that subpar AI technology could pose data security and privacy risks while additionally pushing consumers away from using the technology.

In order to avoid AI washing (even unintentionally), the US Federal Trade Commission (FTC) recommends businesses keep themselves in check by asking key questions such as: “Are you exaggerating what your AI product can do? Are you promising that your AI product does something better than a non-AI product? Does the product actually use AI at all?”

“Before labeling your product as AI-powered, note also that merely using an AI tool in the development process is not the same as a product having AI in it,” the FTC further said.

Meanwhile, the Securities and Exchange Board of India (SEBI) had somewhat warned against AI washing in a 2019 circular.

“As most AI / ML systems are black boxes and their behavior cannot be easily quantified, it is imperative to ensure that any advertised financial benefit owing to these technologies in investor facing financial products offered by intermediaries should not constitute to misrepresentation,” the circular read.


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