- 62% of the public wants tighter AI regulations, highlighting a significant confidence gap.
- International standards like ISO/IEC 42001 can help harmonize AI best practices and support legislation.
- The quality sector can provide a consistent, global framework for AI regulation, addressing privacy, security, and ethical concerns.
The rapid development of artificial intelligence (AI) has generated excitement and concern, particularly regarding the need for effective regulation. A BSI poll of 10,000 people across nine countries revealed that 62% desire global guidelines for AI development, reflecting a significant confidence gap in the technology. This concern spans various aspects, including the potential displacement of jobs, ethical implications in military applications, and privacy and security risks.
The survey also highlighted that nearly 40% of respondents use AI daily, with 62% expecting their industry to adopt AI by 2030. Despite its transformative potential, AI poses risks if not correctly implemented. BSI emphasizes the importance of having guardrails in place to ensure responsible use. AI technologies driven by data and machine learning can introduce new threats if not protected by proper cybersecurity controls. Additionally, there is fear that AI could become so advanced that it might pose an existential threat to humanity, a concern echoed by tech leaders like Bill Gates and Warren Buffett.
Amid varying global legislative efforts, the quality sector offers a solution through international standards such as ISO/IEC 42001. Developed with input from 38 countries, this standard aims to harmonize best practices and support legislation globally. BSI provides various AI tools and services, including training courses and algorithm-testing services, to help organizations build trust with clients and the public. By adopting these standards, the quality sector can act swiftly and internationally, providing a consistent approach to AI regulation and addressing the confidence gap while awaiting comprehensive legislative frameworks.
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