Open access · Peer reviewed · No APCs
Machine LearningJournal of Scientometric ResearchVol. 8 | Issue 2s | 2019 | pp. s2–s6Open access
On the Implications of Artificial Intelligence and its Responsible Growth
- 1,
- 2,
- 3*
- 1 University of Michigan Ann Arbor.
- 2 Astroinformatics Research Group, IEEE Computer Society Bangalore Chapter and Center for Mathematical Modeling and Simulation (CAMMS)..
- 3 Department of Computer Science and Engineering, The University of Texas at Arlington.
Published in Journal of Scientometric Research
Correspondence: Suryoday Basak
Department of Computer Science and Engineering, The University of Texas at Arlington.
Email: suryodaybasak@gmail.com
Copyright: © 2019 Manuscript Technomedia. This is an open access article.
- Published:
- Nov 1, 2019
- Received:
- Feb 15, 2019
- Accepted:
- Sep 16, 2019
How to cite
Devaraj, H., Makhija, S., & Basak, S. (2019). On the Implications of Artificial Intelligence and its Responsible Growth. Journal of Scientometric Research, 8(2s), s2–s6. https://doi.org/10.5530/jscires.8.2.21
Abstract
As a set of technologies, Artificial Intelligence (AI) has received growing interest from a variety of fields. However, many fundamental questions about AI are still mysteries to the everyday person. This paper seeks to address the history of AI, the current state of the field, important distinctions between related fields, misconceptions birthed by popular media, and irresponsible applications of AI. The authors believe this basic understanding of AI and its shortcomings is vital, and the advancement of the field should be matched by the advancement in public understanding of AI.
Keywords
Subject
Article metadata
| Title | On the Implications of Artificial Intelligence and its Responsible Growth |
|---|---|
| Authors | Harsha Devaraj; Simran Makhija; Suryoday Basak |
| Affiliations | University of Michigan Ann Arbor.; Astroinformatics Research Group, IEEE Computer Society Bangalore Chapter and Center for Mathematical Modeling and Simulation (CAMMS)..; Department of Computer Science and Engineering, The University of Texas at Arlington. |
| Corresponding author | suryodaybasak@gmail.com |
| Journal | Journal of Scientometric Research |
| Volume / Issue | Vol. 8, Issue 2s (2019) |
Also in this issue
- Special Issue on Machine Learning in Scientometricspp. s1
- Analyzing the Common Wisdom of Binarization Doctrine in Internationality Classification of Journals: A Machine Learning Approachpp. s7–s38
- Relevance of Innovations in Machine Learning to Scientometricspp. s39–s43
- SES-RREF: The Machine Learning Approach to Credible Metrics of Scholastic Evidence via Recursive Referencingpp. s44–s73
- Treatment Repurposing using Literature-related Discoverypp. s74–s84
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