Special Issue "Defining, Engineering, and Governing Green Artificial Intelligence"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 30 May 2022.

Special Issue Editors

Prof. Dr. Tan Yigitcanlar
E-Mail Website
Guest Editor
School of Architecture & Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
Interests: smart technologies communities, cities, and urbanism; sustainable and resilient cities; communities and urban ecosystems; knowledge-based development of cities and innovation districts
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Juan M. Corchado
E-Mail Website
Guest Editor
BISITE Research Group, Edificio Multiusos I+D+i, University of Salamanca, 37007 Salamanca, Spain
Interests: artificial Intelligence; machine learning; edge computing; distributed computing; Blockchain; consensus model; smart cities; smart grid
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Smartness is the latest trend and data-driven AI is at the heart of it. Artificial intelligence (AI) continues to amaze us with its exponential growth, manifesting itself in many disruptive technologies and smart applications that have appeared in quick succession. However, its risks and negative impacts on our lives and planet also continue to grow exponentially. Individuals, societies, and nations are struggling to deal with the challenges and issues brought by rapid AI developments. For instance, AI with its data-driven nature requires incredibly large amounts of energy and this has endangered the survivability of our planet. Solutions and tools to reduce AI energy requirements have begun to appear such as model compression, pruning, TinyML, TensorFlow Lite, etc., however, these solutions are mainly driven by technology needs rather than by the intent to reduce energy usage. The tendency is to go with bigger and bigger data and larger and larger AI models to develop the ultimate (e.g., strong, general, or super) artificial intelligence.

A fundamental shift is needed in the way the AI engineers, developers, users, and others think about and utilize AI.

The term ‘green’ for scientists and engineers typically means something that uses less energy and fewer computational resources. Environmentalists associate ‘green’ with sustainable development. Green AI has been defined as “AI research that is more environmentally friendly and inclusive”. Green AI has also been defined as an approach “that moves away from short-term efficiency solutions to focus on a long-term ethical, responsible, and sustainable AI practice that will help build sustainable urban futures for all through smart city transformation”. Many more efforts are needed to define and engineer green AI.

To this end, this Special Issue calls for defining, engineering, and governing green AI, incorporating parameters for ‘greening’ AI, including, but not limited to, equity, resilience, inclusivity, security, privacy, safety, ethics, morality, trust, legislation, regulation, compliance, AI explainability, responsibility, and sustainability (social, environmental, and economic). To elaborate, since AI is so ingrained into every aspect of our lives, there is a need to understand and infuse in AI algorithms characteristics such as equity, resilience, security, safety, and ethics so that the AI-driven systems around us make “green” decisions to sustain our societies, economies, and environment.     

The SI specifically calls for contributions from scientists and engineers that can help in developing policies, frameworks, ethics, regulations, instruments, and infrastructure for the development of green AI. The contributions can focus on hardware, software, middleware, firmware, theory, knowledge, policy, etc. Contributions from academics and practitioners in social sciences, law, and other disciplines are also welcome.

The submissions can be research papers, case reports, viewpoints, or literature reviews.

The topics include but are not limited to the following.

  • Green Smartness
  • Green Infrastructure
  • Green AI in Natural Language Processing and Generation (NLP/NLG)
  • Green AI for Smart Cities and Societies
  • Green AI for preventive and Personalized Healthcare
  • Green AI for Transportation
  • Green AI for Supply Chain Management
  • Green AI for Smart Manufacturing
  • Green AI for Precision Agriculture
  • Green AI for Tourism
  • Green AI for Robotics
  • Green AI for Collaborative Robotics
  • Big Data and Datasets for Green AI
  • Green AI for Triple Bottom Line (TBL)
  • Green AI Policies, Frameworks, Ethics, Regulations, Instruments, and Mechanisms
  • Green AI for Edge, Fog, and Cloud Computing

Prof. Dr. Rashid Mehmood
Prof. Dr. Tan Yigitcanlar
Prof. Dr. Juan M. Corchado
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • green deep learning networks
  • green NLP
  • green computer vision
  • green healthcare
  • green big data
  • green edge computing
  • green fog computing

Published Papers

This special issue is now open for submission.
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