Technology advances neither enhances nor detracts from cognitive human bias since its existence over thousands of years. However, skewness in conventional artificial intelligence mechanisms leads to algorithmic mishaps. Understanding the interconnection between human and machine, that algorithms are subject to bias through interactions, and the output of algorithmic bias forms a source of inspiration to the U.S. Intelligence Community (IC). As a result of emerging technologies such as artificial intelligence (AI) and its subset of machine learning, complex cybercrimes raises security concerns and highlights pertinent considerations for national security; infectious diseases can be a national security concern and facilitate bioterrorism and the production of biological weapons; and automation systems in the form of unmanned aerial systems (UAS) can have national security implications as an attractive tool for criminals and nefarious actors. This article uses grounded theory to analyse congressional hearing reports and related official documents. Increasing our understanding of the process leads to output attainment since AI operates at the speed of light and more data than we can humanly manage accessible. The present research intends to contribute to international relations, international studies, security and strategic studies, and science and technology studies.

技术进步既没有增强也没有削弱人类认知偏见，因为它已经存在了数千年。然而，传统人工智能机制的偏度会导致算法失误。理解人机互联，算法在交互过程中会产生偏差，算法偏差的输出形成了美国情报界（IC）的灵感来源。由于人工智能 (AI) 及其机器学习子集等新兴技术的出现，复杂的网络犯罪引发了安全问题，并突出了对国家安全的相关考虑；传染病可能成为国家安全问题，并促进生物恐怖主义和生物武器的生产；无人机系统 (UAS) 形式的自动化和自动化系统可能对国家安全产生影响，成为对犯罪分子和邪恶行为者有吸引力的工具。本文使用扎根理论来分析国会听证会报告和相关官方文件。增加我们对过程的理解会导致输出实现，因为人工智能以光速运行，并且比我们可以管理的数据更多。本研究旨在为国际关系、国际研究、安全和战略研究以及科学和技术研究做出贡献。增加我们对过程的理解会导致产出的实现，因为人工智能以光速运行，而且数据比我们人工管理的可访问的数据多。本研究旨在为国际关系、国际研究、安全和战略研究以及科学和技术研究做出贡献。增加我们对过程的理解会导致产出的实现，因为人工智能以光速运行，而且数据比我们人工管理的可访问的数据多。本研究旨在为国际关系、国际研究、安全和战略研究以及科学和技术研究做出贡献。