AI Horizon Scanning, White Paper p3395, IEEE-SA. Part I: Areas of Attention

TL;DR

This white paper identifies key areas of attention for AI standards development, emphasizing societal impacts, safety, accountability, and infrastructure stability amidst rapid AI advancements.

Contribution

It provides an initial horizon scan highlighting critical focus areas for AI standards, including safety, regulation, and infrastructure resilience, informing future standardization efforts.

Findings

AI models pose societal risks requiring careful regulation.

Potential overdependence on cloud computing may threaten infrastructure stability.

Recent incidents illustrate the importance of safeguards for critical AI applications.

Abstract

Generative Artificial Intelligence (AI) models may carry societal transformation to an extent demanding a delicate balance between opportunity and risk. This manuscript is the first of a series of White Papers informing the development of IEEE-SA's p3995: `Standard for the Implementation of Safeguards, Controls, and Preventive Techniques for Artificial Intelligence (AI) Models', Chair: Marina Cort\^{e}s (https://standards.ieee.org/ieee/3395/11378/). In this first horizon-scanning we identify key attention areas for standards activities in AI. We examine different principles for regulatory efforts, and review notions of accountability, privacy, data rights and mis-use. As a safeguards standard we devote significant attention to the stability of global infrastructures and consider a possible overdependence on cloud computing that may result from densely coupled AI components. We review the recent cascade-failure-like Crowdstrike event in July 2024, as an illustration of potential impacts on critical infrastructures from AI-induced incidents in the (near) future. It is the first of a set of articles intended as White Papers informing the audience on the standard development. Upcoming articles will focus on regulatory initiatives, technology evolution and the role of AI in specific domains.