The release of OpenAI’s ChatGPT in 2022 sparked an explosion of news and interest in generative AI.

Background for Artificial Intelligence Washing 

• Many tech companies and startups are now marketing AI products, claiming they will revolutionise consumer behaviour.
  • Rise in pitch by Startups: Startups mentioning AI in their pitches increased from 10% in 2022 to over 25% in 2023.
  • AI and earnings: According to a report by NBC News: Over 50% of S&P 500 companies referenced AI in their earnings calls last year.

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Concept of AI Washing

• About: AI washing is a deceptive marketing tactic companies employ to exaggerate the amount of Artificial Intelligence (AI) technology they use in their products. 
• Goal of AI Washing: The goal of AI washing is to make a company’s offerings seem more advanced than they are and capitalise on the growing interest in AI technology.
• Derived from: AI washing is a term derived from greenwashing, where companies exaggerate their environmental friendliness to appeal to customers. 
• Some Components of AI Washing: 
  • False Claims of AI Integration: Businesses claiming to have integrated AI into their products while using less sophisticated technology.
  • Misleading Advertisements: 
    • Advertisements that overstate the capabilities of a company’s AI tools.
    • Misleading consumers about features that are not yet operational in their AI products.
• Coined by: It is unclear who coined the term AI washing, it was popularised by the US Securities and Exchange Commission (SEC) when it levied fines 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.

Reasons for AI Washing

• Pressure to Advance Quickly: 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.
• Capitalise the AI rush: 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.
• Raising Funds: AI washing often stems from the desire to raise funds by exaggerating AI capabilities to attract investors who view AI as a promising sector. 

Reality of AI adoption

• Discrepancy Between Claims and Practice:
  • AI adoption often reveals a significant gap between what companies claim and what they actually implement. 
  • Many businesses tout AI integration in their operations but struggle to fully implement or utilise AI technologies effectively.
  • A US Census Bureau survey in November last year found only 4.4% of American businesses were actually using AI to produce goods and services.

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AI washing a Concern

• AI washing has multidimensional repercussions as it not only erodes trust and transparency in technological claims but also distorts market perceptions.
• Diversion of Resources: AI washing redirects management attention and resources away from genuine AI innovation.
• Misguided Investments: Companies may prioritise superficial AI enhancements over developing meaningful capabilities.
• Slowed Progress: The focus on superficial AI could hinder real technological advancements.
• Impact on Consumers: Misleading AI claims can lead to disillusionment and distrust among consumers.
• Industry Implications: AI washing undermines the credibility and progress of the broader tech industry in AI development.
  • Subpar AI technology could pose data security and privacy risk
• Complicate decision making for businesses: 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.

Guidelines to Avoid AI Washing

• There are several guidelines issued to avoid AI Washing. Some of them by the Federal Trade Commission (FTC) and Securities and Exchange Board of India (SEBI) are as follows:
• Federal Trade Commission (FTC) Recommendations: 
  • Assessment: 
    • Businesses should assess if they are exaggerating their AI product’s capabilities.
    • They should avoid claiming superiority over non-AI products unless substantiated.
    • Verification is essential to confirm if the product genuinely utilises AI technology.
  • Clarification on AI Labelling: Merely using AI tools in development does not qualify a product as AI-powered.
• Securities and Exchange Board of India (SEBI) Circular: 
  • Issued Caution: SEBI’s 2019 circular cautions companies about the risks associated with AI washing.
  • Transparency requirements: Companies are advised to ensure transparency and accuracy in their AI-related claims.
  • Financial gains from AI in financial products should be accurately represented: Artificial Intelligence( AI)/Machine Learning (ML) systems are often opaque, making it hard to understand their behaviour. 
    • Financial gains from AI in financial products should be accurately represented to avoid misleading investors.
    • Intermediaries must be clear about what AI can and cannot do in their financial offerings to maintain trust and clarity.

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