The rise of “AI washing” is causing companies to overstate their AI capabilities, potentially eroding trust and making it harder for investors to identify truly innovative firms.
Key Takeaways:
- AI washing refers to companies making over-inflated claims about their use of AI, such as using less sophisticated computing while claiming to use AI or overstating the effectiveness of their AI solutions.
- The phenomenon is driven by competition for funding and the desire to appear cutting-edge, with the percentage of tech start-ups mentioning AI in their pitches rising from 10% in 2022 to an expected 35% in 2024.
- The lack of a single agreed-upon definition of AI contributes to the ambiguity that allows AI washing to emerge.
Potential Impacts:
AI washing can have concerning consequences for various stakeholders:
- Businesses may overpay for technology and services or fail to meet operational objectives that the AI was expected to help achieve.
- Investors may find it more difficult to identify genuinely innovative companies.
- Consumers may experience unmet expectations from products claiming to offer advanced AI-driven solutions, eroding trust in start-ups doing groundbreaking work.
Regulatory Response:
Regulators, particularly in the US, are beginning to address AI washing:
- The US Securities and Exchange Commission (SEC) has charged two investment advisory firms with making false and misleading statements about their use of AI, signaling a lack of leeway for AI washing violations.
- In the UK, existing rules and laws, such as the Advertising Standards Authority’s (ASA) code of conduct, already cover AI washing, with the ASA investigating several cases of exaggerated AI claims in advertisements.
Critical Analysis:
While AI has the potential to be beneficial in specific tasks and sectors, it is essential to approach its implementation thoughtfully:
- The environmental impact of AI is often overlooked, with the technology already contributing more to climate change than aviation.
- As AI becomes ubiquitous, simply being “AI-powered” may cease to be a differentiator for companies, potentially leading to a natural reduction in AI washing over time.
What is 'AI washing' and why is it a problem?