AI Horizon Scanning -- White Paper p3395, IEEE-SA. Part III: Technology Watch: a selection of key developments, emerging technologies, and industry trends in Artificial Intelligence
- URL: http://arxiv.org/abs/2411.03449v1
- Date: Tue, 05 Nov 2024 19:04:42 GMT
- Title: AI Horizon Scanning -- White Paper p3395, IEEE-SA. Part III: Technology Watch: a selection of key developments, emerging technologies, and industry trends in Artificial Intelligence
- Authors: George Tambouratzis, Marina Cortês, Andrew R. Liddle,
- Abstract summary: Generative Artificial Intelligence (AI) technologies are in a phase of unprecedented rapid development following the landmark release of Chat-GPT.
As the deployment of AI products rises geometrically, considerable attention is being given to the threats and opportunities that AI technologies offer.
This manuscript is the third of a series of White Papers informing the development of IEEE-SA's p3995 it Standard for the Implementation of Safeguards, Controls, and Preventive Techniques for Artificial Intelligence Models'
- Score: 0.3277163122167434
- License:
- Abstract: Generative Artificial Intelligence (AI) technologies are in a phase of unprecedented rapid development following the landmark release of Chat-GPT, which brought the phenomenon to wide public attention. As the deployment of AI products rises geometrically, considerable attention is being given to the threats and opportunities that AI technologies offer, and to the need for regulatory and standards initiatives to ensure that use of the technology aligns with societal needs and generates broad benefits while mitigating risks and threats. This manuscript is the third of a series of White Papers informing the development of IEEE-SA's p3995 {\it `Standard for the Implementation of Safeguards, Controls, and Preventive Techniques for Artificial Intelligence Models'} \cite{P3395}, Chair Marina Cort\^{e}s. This part focuses on assessing calmly and objectively, as far as is possible, the current state of Artificial Intelligence (AI) technology development and identifying predominant trends, prospects, and ensuing risks. It necessarily forms a snapshot of the current instant of a rapidly-evolving landscape, with new products and innovations emerging continuously. While our main focus is on software and hardware developments and their corporate context, we also briefly review progress on robotics within the AI context and describe some implications of the substantial and growing AI energy demand.
Related papers
- On the role of Artificial Intelligence methods in modern force-controlled manufacturing robotic tasks [0.0]
AI's role in enhancing robotic manipulators is rapidly leading to significant innovations in smart manufacturing.
This article is to frame these innovations in practical force-controlled applications, highlighting their necessity for maintaining high-quality production standards.
The analysis concludes with a perspective on future research directions, emphasizing the need for common performance metrics to validate AI techniques.
arXiv Detail & Related papers (2024-09-25T11:29:26Z) - AI Horizon Scanning, White Paper p3395, IEEE-SA. Part I: Areas of Attention [0.22470290096767004]
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'
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.
arXiv Detail & Related papers (2024-09-13T18:00:01Z) - Trustworthy, Responsible, and Safe AI: A Comprehensive Architectural Framework for AI Safety with Challenges and Mitigations [14.150792596344674]
AI Safety is an emerging area of critical importance to the safe adoption and deployment of AI systems.
Our goal is to promote advancement in AI safety research, and ultimately enhance people's trust in digital transformation.
arXiv Detail & Related papers (2024-08-23T09:33:48Z) - Security Risks Concerns of Generative AI in the IoT [9.35121449708677]
In an era where the Internet of Things (IoT) intersects increasingly with generative Artificial Intelligence (AI), this article scrutinizes the emergent security risks inherent in this integration.
We explore how generative AI drives innovation in IoT and we analyze the potential for data breaches when using generative AI and the misuse of generative AI technologies in IoT ecosystems.
arXiv Detail & Related papers (2024-03-29T20:28:30Z) - From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the
Generative Artificial Intelligence (AI) Research Landscape [5.852005817069381]
The study critically examined the current state and future trajectory of generative Artificial Intelligence (AI)
It explored how innovations like Google's Gemini and the anticipated OpenAI Q* project are reshaping research priorities and applications across various domains.
The study highlighted the importance of incorporating ethical and human-centric methods in AI development, ensuring alignment with societal norms and welfare.
arXiv Detail & Related papers (2023-12-18T01:11:39Z) - Managing extreme AI risks amid rapid progress [171.05448842016125]
We describe risks that include large-scale social harms, malicious uses, and irreversible loss of human control over autonomous AI systems.
There is a lack of consensus about how exactly such risks arise, and how to manage them.
Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness, and barely address autonomous systems.
arXiv Detail & Related papers (2023-10-26T17:59:06Z) - AI Maintenance: A Robustness Perspective [91.28724422822003]
We introduce highlighted robustness challenges in the AI lifecycle and motivate AI maintenance by making analogies to car maintenance.
We propose an AI model inspection framework to detect and mitigate robustness risks.
Our proposal for AI maintenance facilitates robustness assessment, status tracking, risk scanning, model hardening, and regulation throughout the AI lifecycle.
arXiv Detail & Related papers (2023-01-08T15:02:38Z) - Selected Trends in Artificial Intelligence for Space Applications [69.3474006357492]
This chapter focuses on differentiable intelligence and on-board machine learning.
We discuss a few selected projects originating from the European Space Agency's (ESA) Advanced Concepts Team (ACT)
arXiv Detail & Related papers (2022-12-10T07:49:50Z) - Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society.
A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests.
This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
arXiv Detail & Related papers (2021-06-25T22:31:55Z) - An interdisciplinary conceptual study of Artificial Intelligence (AI)
for helping benefit-risk assessment practices: Towards a comprehensive
qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence.
The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
arXiv Detail & Related papers (2021-05-07T12:01:31Z) - Empowering Things with Intelligence: A Survey of the Progress,
Challenges, and Opportunities in Artificial Intelligence of Things [98.10037444792444]
We show how AI can empower the IoT to make it faster, smarter, greener, and safer.
First, we present progress in AI research for IoT from four perspectives: perceiving, learning, reasoning, and behaving.
Finally, we summarize some promising applications of AIoT that are likely to profoundly reshape our world.
arXiv Detail & Related papers (2020-11-17T13:14:28Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.