Measurement of Compliance Distance in Business Processes

The underuse of AI in the health sector: Opportunity costs, success stories, risks and recommendations

Purpose

This contribution explores the underuse of artificial intelligence (AI) in the health sector, what this means for practice, and how much the underuse can cost. Attention is drawn to the relevance of an issue that the European Parliament has outlined as a "major threat" in 2020. At its heart is the risk that research and development on trusted AI systems for medicine and digital health will pile up in lab centers without generating further practical relevance. Our analysis highlights why researchers, practitioners and especially policymakers, should pay attention to this phenomenon.

Methods

The paper examines the ways in which governments and public agencies are addressing the underuse of AI. As governments and international organizations often acknowledge the limitations of their own initiatives, the contribution explores the causes of the current issues and suggests ways to improve initiatives for digital health.

Results

Recommendations address the development of standards, models of regulatory governance, assessment of the opportunity costs of underuse of technology, and the urgency of the problem.

Conclusions

The exponential pace of AI advances and innovations makes the risks of underuse of AI increasingly threatening.

Graphical Abstract

USING PATTERNS FOR THE ANALYSIS AND RESOLUTION OF COMPLIANCE VIOLATIONS

Today's enterprises demand a high degree of compliance of business processes to meet laws and regulations, such as Sarbanes-Oxley and Basel II. Compliance should be enforced during all phases of business process lifecycle, from the phases of analysis and design to deployment, monitoring and evaluation. In this paper, a taxonomy of compliance constraints for business processes is introduced based on the notion of compliance patterns. Patterns facilitate the formal specification of compliance constraints that enable their verification and analysis against business process models. This taxonomy serves as the backbone of the root-cause analysis, which is conducted to reason about and eventually to resolve design-time compliance violations, by providing appropriate guidelines as remedies to alleviate design-time compliance deviations. We have developed and integrated a set of tools to observe and evaluate the applicability of our approach, and experiment with it in case studies.