Authors :
Dr. T. Amalraj Victorie; M. Vasuki; Sakthi Ganapathy S
Volume/Issue :
Volume 9 - 2024, Issue 4 - April
Google Scholar :
https://tinyurl.com/pa7z2tpb
Scribd :
https://tinyurl.com/42rjty29
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24APR2477
Abstract :
This paper explores how the combination of
artificial intelligence (AI) can enhance governance in
cryptocurrency communities and Decentralized
Autonomous Organizations (DAOs). Using insights from
blockchain, machine studying, and social computing, we
examine moral concerns and dangers While addressing
them, we discuss the potential of AI to improve
efficiency, transparency and inclusion in phrases of
governance shape. Through case studies, we demonstrate
sensible packages of AI, consisting of social media
sentiment analysis, algorithmic trading, and
decentralized forecasting markets. We explore the
impact of AI on governance token systems, selection-
making processes and community-pushed governance
models. Challenges along with algorithmic bias, records
privacy, and the need for human oversight are discussed
in conjunction with suggested studies suggestions and
great practices for implementing responsible AI. This
paper explores how the integration of synthetic
intelligence (AI) can enhance governance in
cryptocurrency communities and decentralized c
Decentralized Autonomous Organizations (DAOs). Using
insights from blockchain, gadget learning, and social
computing, we examine moral worries and dangers
While addressing them, we talk the potential of AI to
enhance performance, transparency and inclusion in
terms of governance structure. Through case research,
we display realistic programs of AI, which include social
media sentiment evaluation, algorithmic trading, and
decentralized forecasting markets. We discover the effect
of AI on governance token systems, decision-making
methods and network-pushed governance models.
Challenges including algorithmic bias, records
privateness, and the need for human oversight are
mentioned in conjunction with suggested research tips
and exceptional practices for the responsible use of AI By
clarifying the ability of AI in cryptocurrency governance,
we help bridge the space among AI and decentralized
selection-making.
Keywords :
Cryptocurrency, Governance, Artificial Intelligence (AI), Machine Learning, Decentralized Autonomous Organizations (DAOs), Sentiment Analysis, Decision-Making, Community Dynamics, Blockchain, Transparency.
References :
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- Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8), 1735-1780.
- Karras, T., et al. (2019). StyleGAN: A Style-Based Generator Architecture for Generative Adversarial Networks. CVPR.
- LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.
- OpenAI. (2021). GPT-3: Language Models are Few-Shot Learners.
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- Babbar, H.; Rani, S.; Singh, A.; Abd-Elnaby, M.; Choi, B.J. Cloud Based Smart City Services for Industrial Internet of Things in Software-Defined Networking. Sustainability 2021, 13, 8910.
- Khattak, H.A.; Tehreem, K.; Almogren, A.; Ameer, Z.; Din, I.U.; Adnan, M. Dynamic pricing in industrial internet of things: Blockchain application for energy management in smart cities. J. Inf. Secur. Appl. 2020, 55, 102615.
- Ashena, E. Evaluating a Blockchain-based Method for Industrial IoT Data Confidentiality: Proof of Concept. In Proceedings of the 2021 7th International Conference on Web Research (ICWR), Teheran, Iran, 19–20 May 2021; IEEE: Manhattan, NY, USA, 2021; pp. 260–266.
- Perez Dominguez, L.A.; Contreas-Masse, R.; Ochoa-Zezzatti, A.; Garcia, V.; Elizondo-Cortes, M. Implementing a novel use of multicriteria decision analysis to select IIoT platforms for smart manufacturing. Symmetry 2020, 12, 368.
- Umair, M.; Cheema, M.; Cheema, O.; Li, H.; Lu, H. Impact of COVID-19 on IoT Adoption in Healthcare, Smart Homes, Smart Buildings, Smart Cities, Transportation and Industrial IoT. Sensors 2021, 21, 3838.
- Ammi, M.; Alarabi, S.; Benkhelifa, E. Customized blockchain-based architecture for secure smart home for lightweight IoT. Inf. Process. Manag. 2021, 58, 102482.
- Yang, Q.; Wang, H. Privacy-Preserving Transactive Energy Management for IoT-aided Smart Homes via Blockchain. IEEE Internet Things J. 2021, 8, 11463–11475.
- Rajashree, S.; Sukumar, R. CBC (Cipher Block Chaining)-Based Authenticated Encryption for Securing Sensor Data in Smart Home. In Smart IoT for Research and Industry; Springer: Cham, Switzerland, 2022; pp. 189–204.
This paper explores how the combination of
artificial intelligence (AI) can enhance governance in
cryptocurrency communities and Decentralized
Autonomous Organizations (DAOs). Using insights from
blockchain, machine studying, and social computing, we
examine moral concerns and dangers While addressing
them, we discuss the potential of AI to improve
efficiency, transparency and inclusion in phrases of
governance shape. Through case studies, we demonstrate
sensible packages of AI, consisting of social media
sentiment analysis, algorithmic trading, and
decentralized forecasting markets. We explore the
impact of AI on governance token systems, selection-
making processes and community-pushed governance
models. Challenges along with algorithmic bias, records
privacy, and the need for human oversight are discussed
in conjunction with suggested studies suggestions and
great practices for implementing responsible AI. This
paper explores how the integration of synthetic
intelligence (AI) can enhance governance in
cryptocurrency communities and decentralized c
Decentralized Autonomous Organizations (DAOs). Using
insights from blockchain, gadget learning, and social
computing, we examine moral worries and dangers
While addressing them, we talk the potential of AI to
enhance performance, transparency and inclusion in
terms of governance structure. Through case research,
we display realistic programs of AI, which include social
media sentiment evaluation, algorithmic trading, and
decentralized forecasting markets. We discover the effect
of AI on governance token systems, decision-making
methods and network-pushed governance models.
Challenges including algorithmic bias, records
privateness, and the need for human oversight are
mentioned in conjunction with suggested research tips
and exceptional practices for the responsible use of AI By
clarifying the ability of AI in cryptocurrency governance,
we help bridge the space among AI and decentralized
selection-making.
Keywords :
Cryptocurrency, Governance, Artificial Intelligence (AI), Machine Learning, Decentralized Autonomous Organizations (DAOs), Sentiment Analysis, Decision-Making, Community Dynamics, Blockchain, Transparency.