Campbell Brown's recent Wall Street Journal op-ed argues that artificial intelligence needs rigorous public quality testing before widespread deployment. The piece draws on journalist Jonathan Rauch's concept of the 'checking' function - the essential role that independent reviewers play in maintaining truth and accountability across democratic institutions.

Brown emphasizes that honest checkers have always been necessary because of human imperfection and ambition. From constitutional checks and balances to regulatory agencies, these verification mechanisms prevent abuse of power and ensure reliability. The application to AI represents the latest adaptation of this fundamental principle - machines require the same oversight that humans have always needed.

However, the op-ed highlights a concerning trend: declining public trust in traditional checking institutions. Universities, government bodies, the press, credit agencies, and legal institutions all face increased suspicion due to politicization and mission drift. This erosion of confidence complicates efforts to establish credible AI oversight frameworks.

Without trusted institutions to validate AI systems, businesses risk deploying unreliable technology while consumers lose faith in digital solutions. The market needs clear standards and credible oversight bodies to function effectively, making institutional trust a prerequisite for AI's commercial success.