Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67601
Volume:
10 |
9 |
Sep 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Information Technology and Computer Science
D.G. Ruparel College of Arts, Science and Commerce
Department of Information Technology and Computer Science
D.G. Ruparel College of Arts, Science and Commerce
Department of Information Technology and Computer Science
D.G. Ruparel College of Arts, Science and Commerce
The shift from conversational chatbots to autonomous AI agents changes the role of AI from providing answers to planning and carrying out tasks. This paper examines GPT-6 Astra as a case study to analyze how increasing autonomy relates to usefulness, perceived risk, trust, and human oversight. The study combines an analysis of Astra’s agentic capabilities and existing safety approaches with a questionnaire-based study of 50 respondents. The findings show that respondents generally recognize the benefits of greater autonomy but become more cautious as AI gains access to more tools, data, and consequential actions. Privacy and personal-data misuse emerged as the main concern, while privacy protection, clear explanations, and reliability were key factors influencing trust. The responses also showed a preference for greater human involvement in higher-impact actions rather than uniform supervision of every task. Based on these findings, the paper presents a risk-based oversight approach in which the level of human control is matched to the potential consequences of an AI action. The study highlights that the challenge is not simply how much autonomy AI should have, but how that autonomy can remain useful while keeping human control meaningful.
KEYWORDS
This paper examines the shift from traditional chatbots to autonomous AI agents by analyzing GPT-6 Astra’s capabilities, associated risks, and the role of human oversight. It highlights how greater autonomy allows AI systems to perform more complex and multi-step tasks, while also increasing concerns related to privacy, security, unintended actions, and loss of control. The questionnaire-based study further shows that users recognize the benefits of autonomous AI but remain cautious when the system is given greater access or is involved in higher-impact actions. Privacy and personal-data misuse emerged as the most prominent concern, while privacy protection, clear explanations, and reliability were important factors in building trust. The study also indicates that users do not expect the same level of control for every task, with stronger human approval preferred for significant actions. Based on these observations, the paper presents a risk-based approach to human oversight, where the level of control is matched to the potential impact of an action. This approach aims to retain the usefulness of autonomous AI while keeping human involvement meaningful.
1. OpenAI, “GPT-6 Astra: The Next Generation in Intelligence for Work,” 2026. [Online]. Available: https://openai.com/index/gpt-6-astra-next-generation-work/ 2. OpenAI, “GPT-6 Astra System Card,” OpenAI Deployment Safety Hub, 2026. [Online]. Available: https://deploymentsafety.openai.com /gpt-6-astra 3. NIST, Artificial Intelligence Risk Management Framework (AI RMF 1.0), National Institute of Standards and Technology, 2023. 4. Anthropic, “Our framework for developing safe and trustworthy agents,” Aug. 2025. 5. Anthropic, “Trustworthy agents.”.2026 6. OpenAI, “GPT-6 Astra: A new generation of intelligence,” Sept. 2026. 7. OpenAI, “Safety overview: GPT-6 Astra,” Sept. 2026. 8. Passi, S., Dhanorkar, S., Vorvoreanu, M.: Appropriate Reliance on Generative AI: Research Synthesis. Microsoft Technical Report MSR-TR-2024-7. Microsoft Corporation (2024) 9. Siebert, L.C., Lupetti, M.L., Aizenberg, E., Beckers, N., Zgonnikov, A., Veluwenkamp, H., Abbink, D., Giaccardi, E., Houben, G.-J., Jonker, C.M., van den Hoven, J., Forster, D., Lagendijk, R.L.: Meaningful Human Control: Actionable Properties for AI System Development. AI Ethics 3 (2023) 241–255 10. Zhu, L., Lu, Q., Ding, M., Lee, S.U., Wang, C.: Designing Meaningful Human Oversight in AI. AI Ethics 6 (2026) 286
Publication Date
9/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
1
Total views since publication
PDF Downloads
4
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...