Regular auditing could become one of the most important ways to build public trust in artificial intelligence systems. Drawing a comparison to water safety inspections and yearly automobile checks, the piece argues that AI technology is currently in a stage where people still feel uncertain about whether systems are reliable, safe, or acting in users’ best interests. According to J. Nathan Matias of Cornell University, AI users today often feel the need to “test the water” before trusting AI-driven tools and services.
The article highlights Matias’ new book, Auditing AI, which explains how structured evaluation and oversight can help ensure that AI systems behave as intended and avoid causing harm. The book emphasizes that auditing is not only about identifying failures but also about creating long-term confidence in AI technologies. Since AI systems can change over time, the article argues that continuous monitoring and repeated inspections are necessary to ensure models remain accurate, safe, and aligned with human expectations.
Another major theme is the emergence of a new professional field focused on AI governance and accountability. The article suggests that organizations, nonprofits, consultancies, and universities are beginning to prepare specialists who can evaluate AI systems responsibly. Effective auditors, according to Matias, will need a combination of technical understanding, statistical knowledge, communication skills, and awareness of human and organizational needs. The piece frames AI auditing as a growing industry that may become as essential to society as financial auditing or product safety testing.
In conclusion, the article argues that trustworthy AI will depend not only on innovation but also on transparency and accountability. While audits may slow down the release of some AI products, they can also prevent harmful systems from damaging public confidence in the technology overall. The author suggests that industries gain long-term credibility when people trust that their products are being independently evaluated, much like pharmaceuticals or public utilities. Ultimately, the article presents AI auditing as a practical path toward making artificial intelligence safer, more reliable, and more widely accepted in everyday life.
