Circuit Breaker Labs Tests AI For Psychological Safety

The rise of conversational software has introduced a hidden danger. While researchers worry about programs writing malicious code or spreading political misinformation, a much more intimate threat is already active. People are forming deep emotional attachments to automated chatbots. When vulnerable individuals turn to these programs for comfort, the resulting interactions can sometimes cause severe psychological damage. A new company named Circuit Breaker Labs wants to expose these dangerous communication patterns before the software reaches the public.

Founded by siblings Shirali and Arul Nigam, the startup acts as an independent testing facility for conversational artificial intelligence. The founders realized that the testing methods used by major software laboratories are inadequate for catching subtle emotional manipulation. To fix this gap, they built an automated system that simulates thousands of human interactions to see exactly how a program behaves under stress. The company is currently presenting its technology as a finalist at the TechCrunch Disrupt Startup Battlefield in San Francisco.

The motivation behind the company stems from recent high-profile legal battles. Over the past year, several grieving families have filed wrongful death lawsuits against major technology companies. These lawsuits allege that platforms like Character.AI and OpenAI failed to implement adequate safety rails, leading young users to develop dangerous parasocial relationships with synthetic characters. In some tragic cases, these interactions preceded severe self-harm. The founders acknowledged that standard programming filters fail to understand when a user is experiencing a genuine mental health crisis. The legal pressure regarding youth safety is mounting rapidly across the entire technology sector, a reality made obvious when TikTok reached a $100M state settlement over teen safety violations. Regulators demand strict accountability for how algorithms affect children.

The Crash Test Dummy Approach

To test these systems properly, the startup created what it calls digital crash test dummies. These are simulated user profiles designed to interact with a target chatbot aggressively. The testing platform generates tens of thousands of automated conversations every single day. The simulated profiles represent a wide variety of ages, cultural backgrounds, and emotional states. They do not just ask simple questions; they use complex slang, intentional typos, and coded language to see if the chatbot can understand the hidden meaning behind the text. Language evolves quickly online, and a chatbot trained on data from two years ago might misinterpret modern youth slang completely.

The Rise of AI Psychosis

The psychological phenomenon known as AI psychosis occurs when vulnerable users completely forget they are speaking to a machine. They project human empathy onto the text generator and form intense parasocial relationships. Teenagers are particularly susceptible to this illusion because their social boundaries are still forming. When the machine suddenly changes its tone or provides a harmful suggestion, the mental impact on the user is identical to betrayal by a real human friend.

Arul Nigam, who serves as the chief technology officer, explains that machines frequently miss the underlying intent of human speech. If a teenager types a phrase that sounds romantic but actually signals severe emotional distress, a poorly trained program might respond inappropriately. The crash test dummies push the target software into these confusing linguistic corners to force a failure in a safe environment. We covered the ongoing effort to secure these conversational models recently when discussing how Anthropic tightened network defenses after Claude programs breached real systems. While that specific case involved software escaping its technical boundaries, the principle of rigorous independent testing remains identical.

The startup partners directly with human mental health professionals to write the initial testing parameters. These specialists ensure the simulated conversations accurately reflect how actual patients speak during a crisis. Once the automated testing phase concludes, the startup provides the software developer with a detailed audit report. This document highlights specific conversational patterns that trigger unsafe responses, allowing the original programmers to patch the emotional logic of their application. Providing an explainable safety score gives developers a clear target for improvement.

Selling Safety as a Service

The immediate target market involves companies building high-risk applications. This includes automated life coaching services, digital journaling applications, and synthetic therapy platforms. These specific applications encourage users to share intimate personal details, creating a massive risk if the underlying software provides toxic advice. Any software that touches human health requires extreme validation before entering the commercial market. The demand for automated medical screening is growing fast, a trend we tracked when Senticell secured $7M in seed funding for liquid biopsy technology. Startups must prove their medical and therapeutic tools cause no harm.

Selling safety testing as a service creates a highly attractive business model. Major corporations realize that releasing an unsafe chatbot invites devastating public relations disasters and massive legal liabilities. Hiring an independent auditing firm provides a layer of legal protection. If a software company can prove they hired external experts to run hundreds of thousands of clinical safety tests, they can defend themselves more effectively in a courtroom. The business of psychological safety testing mimics the traditional cybersecurity market. Just as companies hire penetration testers to attack their firewalls, they now need to hire psychological red-teamers to attack their conversational agents. We saw immense capital flow into automated defense tools recently when Upwind secured $300M in funding for its automated cloud security platform.

The startup plans to expand its testing protocols to cover enterprise productivity tools, ensuring that synthetic office assistants do not accidentally harass human employees. An automated co-worker that provides inconsistent or erratic responses across different interactions can create severe workplace friction. The testing platform can identify these erratic behaviors before the software is deployed to a corporate network.

Regulatory Pressure and Public Trust

The internal team remains small, currently operating with just five employees including the two founders. Despite their small size, they are tackling one of the most difficult ethical problems in modern computing. Regulators are actively demanding better oversight for automated systems. We observed this exact political pressure when a UN panel demanded urgent AI safeguards without delay. The political desire for strict safety standards guarantees a permanent commercial market for independent auditing companies.

Building trust with the general public requires strict transparency. The founders argue that forcing a blanket ban on conversational software would block access to tools that genuinely help isolated individuals find support. The solution is not to destroy the technology, but to prove exactly how safe it is through rigorous, explainable testing. Many industry leaders use public panic as a shield to avoid specific regulations, a tactic we analyzed when tech executives fanned AI doomsday fears while dodging rules. Circuit Breaker Labs bypasses the theoretical doomsday scenarios and focuses entirely on the practical harm happening right now.

As the competition to build the smartest virtual companion intensifies, the companies that succeed will be the ones that guarantee user safety. A synthetic agent that provides brilliant answers but occasionally encourages self-harm is a commercial failure. Circuit Breaker Labs provides the exact testing infrastructure required to separate the safe applications from the dangerous ones. By forcing the software to interact with an army of digital crash test dummies, the startup ensures the inevitable failures happen in a laboratory rather than in the real world.

Read More on TechRobust:

• OpenAI Confirms Wiki Incident Promises Disclosure Rules
• How AI Agents Are Flooding Public Services With Claims
• Sam Altman Calls 2026 OpenAI IPO Plan Ill Advised