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The Dangers of AI Washing: What It Is and How to Avoid It

July 8, 2024
AI Washing

The term AI Washing refers to the practice of some companies exaggerating or falsifying their use of artificial intelligence (AI) in their products and services to capitalize on its popularity and attract consumers and investors. According to a study by MMC Ventures, around 40% of startups claiming to use AI do not actually use this technology. This practice has become common as AI has gained notoriety and prestige in the market.

Companies use the term AI as a marketing tool without having the real technology to back up their claims. This deception can be difficult for consumers and investors to detect, as they rely on technological promises to make informed decisions.

Why is it important?

AI Washing presents multiple risks for both consumers and the market in general:

  1. Consumer distrust: When companies make false claims about their products, consumers can become skeptical and distrust genuine AI. This can slow the adoption of truly innovative and useful technologies.
  2. Incorrect investment decisions: Investors can be misled into funding companies that are not developing advanced technology, which could divert funds from companies that are genuinely driving innovation.
  3. Unfair competition: Companies practicing AI Washing can gain an unfair advantage over competitors that are truly investing in AI development and application.
  4. Environmental impact: The irresponsible implementation of AI can lead to unnecessarily high energy consumption, contributing to climate change. AI technologies require large amounts of data and processing, resulting in high energy consumption.
  5. Inflated expectations: Consumers may expect more than what the technology can currently offer, leading to frustration and disappointment.
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Additionally, the negative perception of AI due to AI Washing can lead to stricter regulation, hindering the development and deployment of genuine and useful technologies.

To protect yourself from AI Washing, it is essential to adopt a critical approach and stay well-informed about the products and services marketed as AI-driven.

Guide to Recognizing if a Service Truly Uses AI

  1. Transparency in descriptions: Companies that genuinely use AI provide clear details on how and where this technology is applied in their products.
  2. Evidence and verifiable results: Look for case studies, user testimonials, and verifiable data that demonstrate the effectiveness of AI in the product or service.
  3. Human intervention: If a service requires significant human intervention, it is likely not heavily dependent on AI.
  4. Reputation and expert opinions: Consult expert opinions and check the company’s industry reputation. Truly innovative companies often have a good reputation and receive recognition for their technological developments.
  5. Certifications and awards: Verify if the company has received certifications or awards for its AI developments. These recognitions are usually an indication that the company is effectively and authentically using AI.
  6. Transparency in data usage: Genuine companies explain how data is collected, processed, and used to train their AI models.
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To avoid falling victim to AI Washing, stay informed and critical. Ensure that technological promises are backed by concrete evidence and transparency in their applications.

Other Types of Washing


Definition: When a company exaggerates or lies about its environmental efforts to appear more eco-friendly than it really is.

Example: Volkswagen promoted its diesel vehicles as eco-friendly but manipulated emissions tests to appear less polluting than they were鈥 (Green Hive)鈥.

Pinkwashing (LGBT Washing)

Definition: The practice of using support for the LGBTQ+ community as a marketing tool without a real commitment to the rights and well-being of this community.

Example: Companies that donate to anti-LGBTQ+ politicians while using pride symbols in their campaigns鈥 (FairPlanet)鈥嬧 (2030.Builders)鈥.

Social Washing

Definition: When companies promote their image of social responsibility without meaningful actions to support their claims.

Example: Companies claiming to support racial equality while funding politicians who back discriminatory policies鈥 (Morningstar)鈥.

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