Operationalizing ethics in AI : a quantitative framework for monitoring, assessing and improving ethical compliance in healthcare systems | |
| Author | Adhikari, Sonu |
| Call Number | AIT Thesis no.DSAI-25-06 |
| Subject(s) | Artificial intelligence--Moral and ethical aspects Artificial intelligence--Medical applications |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Data Science and Artificial Intelligence |
| Publisher | Asian Institute of Technology |
| Abstract | Artificial Intelligence has spread like a wildfire across the humancivilizationat this time. However, with the pervasive use of AI in almost every domains of life, there has been a significant level of concerns regarding the ethical aspects of it. Due to this reason, today several researchers have started working on how this technology can be ethically reasonable.Several frameworks and guidelines have been proposed by several researchers in this growing field. However, there is a lack of a framework or study that goes beyond the theoretical aspect and provides more real time and quantitative dimension to the ethical AI domain. This research addresses that gap by proposing a practical ethical compliance framework that introduces quantitative metrics across the AI lifecycle. Centered on four key ethical principles: Fairness, Accountability, Transparency, and Privacy, the framework consists of 39 metrics mapped across six AI lifecycle phases: data ingestion, data processing, model training, evaluation, deployment, and post-deployment. These metrics are designed to help AI Developers and Compliance Officers evaluate the degree of ethical adherence in AI systems in a measurable, repeatable manner. To validate the framework, an expert review process was conducted involving both technical and healthcare professionals. Experts rated the framework on clarity, validity, and practicality. Feedback was analyzed using descriptive statistics and thematic coding to extract key insights and improvement areas. This study offers a foundational step toward operationalizing ethical AI in healthcare through structured, lifecycle-aware evaluation. |
| Year | 2025 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Data Science and Artificial Intelligence (DSAI) |
| Chairperson(s) | Chutiporn Anutariya |
| Examination Committee(s) | Chantri Polprasert;Vatcharaporn Esichaikul |
| Scholarship Donor(s) | AIT Scholarship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2025 |