TIM-6074

Awashreh, R., & Ramachandran, B. (2024). Can artificial intelligence dominate and control human beings? Int. Res. J. Multidiscip. Scope, 5(4), 427–438. https://www.irjms.com/wp-content/uploads/2024/10/Manuscript_IRJMS_01569_WS.pdf 
This article explores the potential for AI to dominate and control humans, analyzing it through multidisciplinary perspectives and emphasizing the need for ethical considerations and regulatory measures to protect human autonomy and values.

Azoulay, P., Krieger, J. L., & Nagaraj, A. (2024). Old moats for new models: Openness, control, and competition in generative ai. National Bureau of Economic Research. https://www.nber.org/papers/w32474 
This working paper uses innovation economics concepts to analyze the likely competitive environment in generative AI, arguing that incumbent firms' control over complementary assets may lead to a concentrated market structure and stifle innovation despite the transformative potential of generative AI models. 

Brusilovsky, P. (2024). AI in education, learner control, and human-AI collaboration. International Journal of Artificial Intelligence in Education, 34(1), 122–135. https://doi.org/10.1007/s40593-023-00356-z 
This paper discusses user control and human-AI collaboration in AI systems, focusing specifically on the context of AI in education and comparing it to research in recommender systems, advocating for more research on empowering learners to control and collaborate with AI technologies.

Gallatin, E. R. (2024). Balancing national security and individual privacy rights & the role of accountability and transparency in signals intelligence (SIGINT) activities. Security and Intelligence, 9(1). https://gsis.scholasticahq.com/article/94588.pdf 
This article reviews the literature on balancing national security interests and individual privacy rights in intelligence operations, highlighting the importance of robust oversight, public participation, transparency, accountability, and mitigating biases to navigate the complex interplay between these competing concerns. 

Kuźmicz, M. M. (2025). Equilibrating the scales: balancing and power relations in the age of AI. AI & Society. Advance online publication. https://doi.org/10.1007/s00146-025-02300-2  
This paper explores the equilibrium model of balancing as a legal safeguard against AI-driven power imbalances and domination, identifying sources of AI power (control over resources and events) and discussing potential legal tools like regulations, information obligations, rights, and prohibitions to counterbalance AI power and preserve human autonomy and dignity. 

Nagy, N. (2023). “Humanity’s new frontier”: Human rights implications of artificial intelligence and new technologies. https://doi.org/10.1556/2052.2023.00481 
This article provides a comprehensive overview of the human rights implications of AI, examining how AI systems can affect a wide range of civil, political, economic, social, and cultural rights, including privacy, non-discrimination, freedom of expression, and fair trial rights, and calls for a precautionary approach to AI regulation that embeds human rights into its design and deployment. 

Rahaman, M., Lin, C.-Y., Pappachan, P., Gupta, B. B., & Hsu, C.-H. (2024). Privacy-centric AI and IoT solutions for smart rural farm monitoring and control. Sensors, 24 (13), 4157. https://www.mdpi.com/1424-8220/24/13/4157 
This paper addresses privacy and security concerns in AI and IoT solutions for smart farming by proposing a comprehensive framework and secure communication protocol designed to protect data exchange between users, IoT sensors, and central servers through rigorous cryptographic techniques, aiming to ensure the safe and effective application of these technologies in agriculture.