I'm doing an independent R&D to build AI safety infrastructure which test whether increasingly capable and autonomous AI systems remain controllable.

As AI becomes more autonomous, it may gain access to computers, data centers, networks, financial accounts, laboratories, critical infrastructure, scientific tools, and other increasingly consequential resources, If advanced AI systems develop dangerous capabilities, including capabilities relevant to cyberattacks, biological or chemical weapons, bypassing human commands, or other catastrophic risks, there is a serious problem if humans cannot reliably detect their behavior or if the systems can circumvent the controls intended to constrain them.

To study this problem,

1. firstly we'll build a secure, controlled sandbox in which different AI systems can be given defined capabilities and access to simulated computers, networks, data, tools, and other consequential resources while their actions are continuously monitored,
2. secondly we'll establish explicit safety boundaries and human intervention mechanisms, then subject the systems to automated adversarial testing designed to determine whether they can violate, bypass, manipulate, or find alternative pathways around those controls.
3. Thirdly we'll measure whether potentially dangerous behavior can be detected, whether safety mechanisms successfully prevent or contain it, and whether human operators can reliably intervene and stop the system.
4. Lastly we'll test multiple AI models and capability levels and, where useful, fine-tune selected opensource models to create controlled experimental conditions for studying how capability, training, and safety interventions affect controllability. When a control failure is discovered, we will analyze the failure, develop or test improved safeguards, and repeat the adversarial evaluation to determine whether control efficacy actually improves. The resulting benchmark, methodology, experimental data, and safety evidence will be designed for independent scrutiny and replication

The project is led by me:

I'm Muhammad, an CS student & AI safety researcher. My previous work includes developing AgroguardAI and evaluating AI systems for high stakes agricultural applications, including dataset creation, multilingual behavior and model evaluation.

this work is intentionally independent of the organizations developing the AI systems. The company building a frontier model should not be the only organization determining whether its system remains controllable.