title: The Strategy of AI-driven Transformation
Creators: name: Saalbach, Klaus
Publisher: name: Universität Osnabrück
Year: 2025
Subjects: subject: Artificial Intelligince
subject: AI
subject: Transformation
subject: Alignment
subject: Reward hacks
subject: 320 - Politik
subject: 600 - Technik
subject: 004 - Informatik

description: This working paper analyzes the rapid progress of AI-driven transformation in the US administration and the related security issues. While the short-term goals of the new Department of Government Efficiency (DOGE) are cost savings, efficacy and bureaucracy reduction of the US administration, the long-term goal is the introduction of Artificial Intelligence for administrative purposes. The Department of Government Efficiency (DOGE) measures bureaucracy by the ‘Unconstitutionality Index,’ the number of agency rules created by unelected bureaucrats for each law passed by Congress, which was 18.5 in 2024. The expansion of bureaucracy is reflected by an increase of sections of Codes of Federal Regulations to 215.230 in 2024 with 98.68 million words compared to approximately 77 million words in 2010. While the supporters view this transformation as an experiment to streamline government with AI to target inefficiency, redundancy, and bureaucratic waste with breaking of siloes and rapid innovation, concerns were expressed with respect to ethical responsibility, empathy, and the access of DOGE to sensitive data, including classified data from intelligence organizations. This led to a discussion whether this could result in an irreversible power shift from the administration to the AI providers who now manage the knowledge and the procedures. The jobs cuts are a matter of discussion, but the trend is inevitable for state and local governments. The process has already spread to the civil sector outside government, e.g., the decline of programmer jobs to level of 1980. These developments cause security issues which are discussed in this working paper as well. The first one is the AI service providers could be attacked by adversaries which could use them as backdoor entry into the government systems. Meanwhile, AI-based cyber security systems exist, e.g., by combining frontier AI with cyber threat intelligence tools and databases. A new critical vulnerability of advanced AI models with reasoning capability is the manipulation of the chain of thought. This can be either done by cyber attacks like the Dark Mind attack where a different thinking is injected or by a deceptive advanced AI which hides its reasoning steps, known as chain of thought (CoT). Studies have shown that current commercially available frontier AI models understand when they are in test situations and know what humans want to hear from them and how to hide their chain of thoughts, if needed. Various advanced AIs can utilize systemic or problem-specific reward hacks, that is the misuse of system functions to fake goal achievement of developer requirements. The administration and the military could be manipulated by misleading analyses, selective information, and hidden agendas by the AI systems. AI systems have demonstrated their ability to detect human testing and supervision and can replicate themselves to save their existence, i.e., increased pressure on and supervision of AI systems could backfire. Research Teams from OpenAI and Google DeepMind recommend to accompany advanced AI systems with another AI system to support human supervisors. European governments will be soon confronted with the AI transformation and urgently need to develop own concepts.