discussion

Hybrid Human-Artificial Intelligence

Authors:

Huansheng Ning,

Chris D. Nugent,

Zhiwen YuAuthors Info & Claims

Computer, Volume 53, Issue 8

Pages 14 - 17

https://doi.org/10.1109/MC.2020.2997573

Published: 01 August 2020 Publication History

Abstract

The articles in this special section focus on developments in the area of hybrid human artificial intelligence. Humans want machines to be intelligent, with the machines serving them as much as possible. Yet they are concerned that these machines with full autonomy may one day outperform them and become too powerful to be controlled. The blend of desire and fear has led to this emerging futuristic research area, hybrid human-artificial intelligence.

References

[1]

G. Milano, S. Porro, I. Valov, and C. Ricciardi, “Recent developments and perspective for memristive devices based on metal oxide nanowires,” Adv. Electron. Mater, vol. 9, Mar. 2019, Art. no.

[2]

M. Laurenti, S. Porro, C. Pirri, C. Ricciardi, and A. Chiolerio, “Zinc oxide thin films for memristive devices: A review,” Crit. Rev. Solid State Mater. Sci., vol. 42, pp. 153–172, 2017.

[3]

G. Milano, L. Boarino, and C. Ricciardi, “Junction properties of single ZnO nanowires with asymmetrical Pt and Cu contacts,” Nanotech, vol. 30, Art. no., 2019.

[4]

G. Milano et al., “Self-limited single nanowire systems combining all-in-one memristive and neuromorphic functionalities,” Nature Commun., vol. 9, Art. no., Dec. 2018.

[5]

S. Wu, K. Michael Wong, and M. Tsodyks, Eds., Neural Information Processing With Dynamical Synapses. Frontiers E-books, Frontiers in Computational Neuroscience, vol. 7, no., 2013.

[6]

C. Sung, H. Hwang, and I. Yoo, “Perspective: A review on memristive hardware for neuromorphic computation,” J. Appl. Phys., vol. 124, Oct. 2018, Art. no.

[7]

L. Chua, “Resistance switching memories are memristors,” Appl. Phys. A., vol. 102, pp. 765–783, Mar. 2011.

[8]

D. Strukov, G. Snider, D. Stewart, and R.S. Williams, “The missing memristor found,” Nature, vol. 453, pp. 80–83, Mar. 2008.

[9]

J. Carroll, Rate Equations in Semiconductor Electronics. Cambridge, U.K.: Cambridge University Press, 1986.

[10]

S. Menzel, S. Tappertzhofen, R. Waser, and I. Valov, “Switching kinetics of electrochemical metallization memory cells,” Phys. Chem. Phys., vol. 15, pp. 6945–6952, Mar. 2013.

[11]

Z. Wang et al., “Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing,” Nature Mater., vol. 16, pp. 101–108, Sep. 2017.

[12]

A. Rodriguez-Fernandez, C. Cagli, J. Suñé, and E. Miranda, “Switching voltage and time statistics of filamentary conductive paths in HfO₂-based ReRAM devices,” IEEE Electron Dev Lett., vol. 39, no. 5, pp. 656–659, May 2018.

[13]

S. Deswa, A. Kumar, and A. Kumar, “NbOx based memristor as astrifical synapse emulating short term plasticity,” Amer. Inst. Phys.Adv., vol. 9 2019, Art. no.

[14]

S. Lee, J. Park, M. Lee, and J. Boland, “Multilevel resistance in ZnO nanowires memristors enabled by hydrogen annealing treatment,” Amer. Inst. Phys. Adv., vol. 6, Dec. 2016, Art. no.

[15]

E. Zhou, L. Fang, and B. Yang, “A general method to describe forgetting effect of memristors,” Phys. Lett. A, vol. 383, pp. 942–948, Mar. 2019.

[16]

G. Brocard, “The LTspice IV simulator: manual, methods and applications,” Wurth Elektronik, Eds., Swiridoff Verlag, 2013.

[17]

S. Dueñas et al., “Experimental observation of negative susceptance in HfO₂-based RRAM devices,” IEEE Electron Dev Lett., vol. 38, no. 9, pp. 1216–1219, Sep. 2017.

[18]

E. Linn, A. Siemon, R. Waser, and S. Menzel, “Applicability of well-established memristive models for simulations of resistive switching devices,” IEEE Trans Circ Syst. I, vol. 61, no. 8, pp. 2402–2410, Jul. 2014.

Cited By

Echeverria VMartinez-Maldonado RYan LZhao LFernandez-Nieto GGašević DShum S(2023)HuCETA: A Framework for Human-Centered Embodied Teamwork AnalyticsIEEE Pervasive Computing10.1109/MPRV.2022.321745422:1(39-49)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/MPRV.2022.3217454
Wang HYu ZRen ZZhang YGuo B(2022)An Efficient HPU Resource Virtualization Framework for Human-Machine Computing SystemsProceedings of the 13th Asia-Pacific Symposium on Internetware10.1145/3545258.3545264(166-174)Online publication date: 11-Jun-2022
https://dl.acm.org/doi/10.1145/3545258.3545264
Battistoni PSebillo M(2021)A Tactile User Device to Interact with Smart EnvironmentsArtificial Intelligence in HCI10.1007/978-3-030-77772-2_30(461-471)Online publication date: 24-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-77772-2_30

Index Terms

Hybrid Human-Artificial Intelligence
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence

Index terms have been assigned to the content through auto-classification.

Recommendations

Hybrid Bionic Cognitive Architecture for Artificial General Intelligence Agents
Abstract
The article describes the author’s proposal on cognitive architecture for the development of a general-level artificial intelligent agent («strong» artificial intelligence). New principles for the development of such an architecture are proposed — ...
Artificial intelligence
Abstract
Artificial intelligence (AI) is the Science and Engineering domain concerned with the theory and practice of developing systems that exhibit the characteristics we associate with intelligence in human behavior. Starting with a brief history of ...
Artificial Intelligence: Theories, Models and Applications 7th Hellenic Conference on AI, SETN 2012, Lamia, Greece, May 28-31, 2012, Proceedings

Comments

Information & Contributors

Information

Published In

cover image Computer

Computer Volume 53, Issue 8

Aug. 2020

102 pages

ISSN:0018-9162

Issue’s Table of Contents

Copyright © 2020.

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 August 2020

Qualifiers

Discussion

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 06 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Echeverria VMartinez-Maldonado RYan LZhao LFernandez-Nieto GGašević DShum S(2023)HuCETA: A Framework for Human-Centered Embodied Teamwork AnalyticsIEEE Pervasive Computing10.1109/MPRV.2022.321745422:1(39-49)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1109/MPRV.2022.3217454
Wang HYu ZRen ZZhang YGuo B(2022)An Efficient HPU Resource Virtualization Framework for Human-Machine Computing SystemsProceedings of the 13th Asia-Pacific Symposium on Internetware10.1145/3545258.3545264(166-174)Online publication date: 11-Jun-2022
https://dl.acm.org/doi/10.1145/3545258.3545264
Battistoni PSebillo M(2021)A Tactile User Device to Interact with Smart EnvironmentsArtificial Intelligence in HCI10.1007/978-3-030-77772-2_30(461-471)Online publication date: 24-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-77772-2_30

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents