Mutualistic Symbiosis of Artificial Intelligence and Distributed Ledger Technologies for Social Good Applications in Human–Machine Ecosystems
About this Research Topic
Emerging and evolving intelligent infrastructures for supporting our safe and comfortable living and working environments are fostering the ubiquitous entanglement between humans and machines, forming so called Human-Machine Networks (HMN).
The two disruptive technologies at the top of their hype cycle, Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) can provide effective trustworthy HMNs for social good applications only by working together in mutualism.
In recent years, research initiatives relying on AI to deliver socially beneficial outcomes under the umbrella concept of AI for social good (AI4SG) projects have started to emerge, advocating the use of trustworthy AI principles and the United Nations’ Sustainable Development Goals (SDGs) as a benchmark for tracing the scope and spread of AI4SG solutions in our everyday lives and practices. Bockchain and other similar DLTs, characterized by several features such as immutability, and transparency, offer the possibility of creating new forms of human collaboration to foster trust between strangers.
This Research Topic aims at collecting original and high-quality papers focusing on methodologies, techniques, and tools, architectures for social good applications in Human Machine Networks. All contributions should include and explain the role of blockchain and other distributed computing technologies (such as Cloud, Fog, Dew, Edge, computing) or Internet of Things (IoT), and their mutualism with AI for enabling Trustworthy Human Machine Networks ecosystems for social good applications, specifically or in general. As most of the current research activities on smart solutions based on AI and Blockchain for social good are still fragmented between diverse communities (e.g. see Frontiers Research Topics: Blockchain for Food and Agriculture; Blockchain Uses for Social and Economic Equity in Agriculture and Food Production; Blockchain for United Nations Sustainable Development Goals (SDGs); Blockchain and Distributed Ledger Technology – enabled architectures for improving healthcare), we encourage multi-disciplinary researchers to go a step further and explore additional aspects and added value of interlacing AI and DLT, while designing smart environments for social good in newly emerging Human Machine Networks through the lens of Trustworthy AI research for achieving Sustainable Development Goals.
The Research Topic offers a venue for presenting novel research in DLT and blockchain for both application and theoretical research for social good applications with respect to the two perspectives:
(i) the augmentation of AI research with DLT properties (‘DLT for AI’ perspective) or
(ii) the utilization of AI for design of DLT systems, as well as analysis of large-scale data emerging from these DLT systems using data science methodologies based on AI algorithms (‘AI for DLT’ perspective).
Possible topics include but are not limited to the following:
- Conceptualization of interlacing AI and DLT (AI-driven DLT or DLT-driven AI) for one specific or more social good applications and for achieving one or more sustainable development goals (AI4SDG)
- Case studies of social good applications utilizing AI and DLT in mutualism.
- A unified AI driven DLT design and reference architectures for a range of social good applications and for achieving different sustainable development goals (AI4SDG).
- AI and DLT based Intelligent Infrastructures for smarter healthcare, smart farming (agriculture), smart tourism, smart grid, smart transportation or smart city in general etc.
- A unified computational and theoretical framework based on artificial intelligence (machine learning/deep learning) for facilitating the analysis and understanding of specific data arising from the blockchain ecosystem.
- Promoting cooperation between humans and machines within HMN Ecosystems using AI and DLT technologies.
- Trustworthy Blockchain Oracles for social good applications
All manuscripts must be submitted directly to the section Blockchain for Good, where they are peer-reviewed by the Associate and Review Editors of the specialty section. Article types invited for submission include Community Case Study, Correction, Data Report, Editorial, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Policy and Practice Reviews, Policy Brief, Review, Specialty Grand Challenge and Technology and Code.
Keywords: AI driven Blockchain and Blockchain driven AI for Social Good applications
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
|30 November 2021||Abstract|
|30 March 2022||Manuscript|