Secure AI Adoption: Governance Models for Copilot in Healthcare and Non-Profit Enterprises
DOI:
https://doi.org/10.15680/IJCTECE.2024.0704015Keywords:
Artificial Intelligence (AI), Copilot Governance, Healthcare Informatics, Non-Profit Enterprises, Data Security, Ethical AI, Regulatory ComplianceAbstract
The decision support, documentation, communication and services delivery in the different sectors is changing with the introduction of the artificial intelligence (AI) copilots in the organization processes. But, there are dire governance issues to be brought forward when Copilot technologies are adopted in the healthcare and non-profit organizations that can be associated with privacy, accountability, transparency, ethical implementation, regulatory compliance, and data security. The research article discusses how AI can be safely used in the governance systems that are unique to these two industries because of their unique nature of operation. The keys to reliable implementation are the sensitive clinical data and patient secretiveness of healthcare copilot systems, regulatory compliance and human control. The application of AI to the non-profits has to consider the trade-off between resource constraint and innovation, reliability of the sponsors, safety of beneficiaries, and mission fidelity. The essay proposes a comparative, risk categorization, the access control, the data custodianship, the algorithmic responsibility, the role-based monitoring, the auditing as well as the ongoing monitoring regulatory design. It believes that technical protection is not the only way of safe adoption; but that it also relies on institutional policies, ethical review measures, stakeholder training and maturity of governance of the sector. Drawing a comparison of priorities in governance, in both non-profits and healthcare organizations, the article uncovers the shared common values and the context itself, which defines the responsible Copilot adoption. These findings can be utilized in designing adaptive governance systems that can potentially enable security, trust and efficiency in operations with the least unintended harm. The work can be connected to the continuously expanding literature on the topic of responsible AI considering it offers a realistic and politically-minded foundation to businesses planning on incorporating Copilot systems into high-stakes and socially-sensitive fields.
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