Integration of Artificial Intelligence into the US Intelligence System: An Analysis of Ethical Dilemma

Artificial intelligence has been a controversial contradiction since its birth, and the huge technological prospect is in stark contrast to a series of social and ethical issues that follow. For the intelligence community, the "human-machine relationship" between intelligence personnel and artificial intelligence is an unavoidable problem, and data security and data traps are also aspects that must be paid attention to at all times. How to understand the current development dilemma of artificial intelligence is the premise of whether it can be effectively dealt with in the future.

1. Humanistic Ethical Issues

The U.S. intelligence community has two distinct views on the use of artificial intelligence. One side believes that artificial intelligence systems lack abstract thinking, so there is a greater risk in handing over the power of analysis and judgment to algorithms that rely entirely on patterned decision-making. The other side believes that the computing power of artificial intelligence far exceeds that of the human brain, so as long as the model is properly built, it can undertake most of the analysis work. In fact, this is the long-standing dispute between the "rationalism" that emphasizes the symbolization of thinking and the "people-oriented" concept that serves human beings.

On the one hand, whether the use of artificial intelligence will harm the dignity of intelligence personnel is indeed a question to be explored. The introduction of artificial intelligence into intelligence work will not only touch the interests of human intelligence employees, but also weaken the confidence of intelligence personnel in the long run. The two views of the intelligence community are reflected in the actual promotion level as the dispute between "artificial intelligence" (AI) and "intelligence augmentation" (IA). The essence is still entangled in the use of technology to replace humans or enhance humans as a tool. Granted, AI will never be at its best when it comes to the nuances of language, complex problem solving, and certain tasks of emotional and social intelligence. Machines and algorithms always lack sufficient human value. When faced with intelligence problems that are difficult to quantify and describe, analysts can often make quick judgments based on work experience and knowledge accumulation, which is undoubtedly a test for machines.

On the other hand, the purpose of using artificial intelligence systems in the intelligence community is to collect and screen as much intelligence information as possible. Especially for open source intelligence and signal intelligence, artificial intelligence will inevitably pose a threat to citizens' right to privacy in the process of data collection. AI-based systems such as big data analytics, persistent ISR, facial recognition, and cyber capabilities could enable dictators to spy on their populations, target dissidents, censor content, or otherwise violate basic human rights. The rights and responsibilities of personal privacy data itself have legal implications. Once leaked, it will cause serious social consequences. Intelligence agencies not only need to bear corresponding responsibilities, but also have a great negative impact on their own image. The case of former CIA employee Edward Snowden exposing the secret surveillance program of the U.S. intelligence community is a typical example.

2. Crisis of confidence

For or against the development of lethal autonomous weapons systems (LAWS) is an important ethical question facing the field of artificial intelligence and robotics. The intelligence community faces the same problem. Autonomous systems can collect, analyze and output intelligence with almost no human intervention, but complex algorithms also prevent people from simply interpreting and understanding the analysis process and conclusions of artificial intelligence. This makes the accuracy, degree of autonomy, and authority definition of autonomous systems face considerable difficulties.

On the one hand, artificial intelligence can quickly analyze large amounts of data and provide short-term judgments for making decisions, but intelligence analysis is a continuous and complex mental confrontation between the enemy and us. Although the analysis process requires objectivity based on the data level, accurate judgment conclusions are often the result of the analyst's perception of the current situation and the logic of thinking. This essentially subjective judgment is beyond the reach of model artificial intelligence algorithms. .

On the other hand, after the introduction of artificial intelligence and robots into the U.S. intelligence system, although it has undertaken a lot of transactional work for intelligence personnel, it has inevitably replaced part of the mental work. And assuming the additional responsibility that comes from machine decision-making is undoubtedly something that any intelligence officer would do his best to avoid. In fact, artificial intelligence does not have the traditional elements of "cognition" and "consciousness" to determine the attribution of responsibility. In other words, under the premise that the algorithm cannot guarantee that its choice is completely correct, even if artificial intelligence can analyze and judge the situation through complex calculations, and take corresponding measures or make decisions, they still lack ethical decision-making capabilities. Therefore, responsibility for actions or decisions that humans entrust to them remains with the human agents who develop and use the technology. However, at the current level of technology, neither developers nor users of software systems can have absolute trust in artificial intelligence, and naturally they are unwilling to take corresponding responsibilities for it. This instinctive lack of trust cannot be avoided by any technology.

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