The SMART+ Framework for AI Systems
Laxmiraju Kandikatla, Branislav Radeljic

TL;DR
The paper introduces the SMART+ Framework, a comprehensive model for evaluating and governing AI systems across industries, emphasizing safety, accountability, transparency, and privacy to ensure responsible AI deployment.
Contribution
It presents the SMART+ Framework, integrating safety, monitoring, accountability, and privacy considerations into a structured approach for AI governance across sectors.
Findings
Demonstrates how SMART+ enhances AI safety and trustworthiness.
Shows alignment of SMART+ with regulatory standards.
Provides a practical guide for AI risk mitigation and compliance.
Abstract
Artificial Intelligence (AI) systems are now an integral part of multiple industries. In clinical research, AI supports automated adverse event detection in clinical trials, patient eligibility screening for protocol enrollment, and data quality validation. Beyond healthcare, AI is transforming finance through real-time fraud detection, automated loan risk assessment, and algorithmic decision-making. Similarly, in manufacturing, AI enables predictive maintenance to reduce equipment downtime, enhances quality control through computer-vision inspection, and optimizes production workflows using real-time operational data. While these technologies enhance operational efficiency, they introduce new challenges regarding safety, accountability, and regulatory compliance. To address these concerns, we introduce the SMART+ Framework - a structured model built on the pillars of Safety,…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI · Adversarial Robustness in Machine Learning
