Developing Ecological Safety of Artificial Intelligence in Human Society

Aleksejs Zorins, Peteris Grabusts

Abstract


The paper presents cyber systems especially based on artificial intelligence (AI) from a perspective of ecological safety for humanity. The study provides a definition of ecological safety of AI and discusses its relevance to a modern science and society, as well as reviews risks of smart AI systems.

Keywords:
Artificial intelligence; cybersecurity; risks of artificial intelligence; safe artificial intelligence

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References


S. Schliebs, N. Kasabov, “Evolving spiking neural networks: A Survey”, 2013. [Online] Available: https://www.zora.uzh.ch/id/eprint/75356/1/Schliebs_Kasabov_Evolving_spiking_neural_networks.pdf [Accessed: May. 9, 2020].

A. T. Sherman, et al. “Cybersecurity: Exploring core concepts through six scenarios,” Cryptologia, July 2018, vol. 42, no. 4, pp. 337–377. https://doi.org/10.1080/01611194.2017.1362063

N. Bostrom, Global Catastrophic Risks. Oxford: Oxford University Press, 2007.

N. Bostrom, The ethics of artificial intelligence. Cambridge Handbook of Artificial Intelligence, 2011. [Online]. Available: https://nickbostrom.com/ethics/artificial-intelligence.pdf [Accessed: Feb 22, 2020].

S. Hawking, Science in the next millennium, 1998. [Online]. Available: https://www.learnoutloud.com/Catalog/Science/Physics/Science-in-the-Next-Millennium/45223 [Accessed: Feb 19, 2020].

M. Kiss, and C. Muha, “The cybersecurity capability aspects of smart government and industry 4.0 programmes,” Interdisciplinary Description of Complex Systems, vol. 16, no. 3-A, pp. 313–319, 2018. https://doi.org/10.7906/indecs.16.3.2

N. Sales, “Privatizing Cybersecurity,” UCLA Law Review, April 2018, vol. 65, no. 3, pp. 620–688, 2018.

E. Yudkowsky, The AI-Box experiment. [Online]. Available: http://yudkowsky.net/singularity/aibox/ [Accessed: Feb. 9, 2020].

R. Yampolskiy, “Leakproofing the Singularity Artificial Intelligence Confinement Problem,” Journal of Consciousness Studies, vol. 19, pp. 1–2, 2012.

R. V. Yampolskiy, Artificial Superintelligence: A Futuristic Approach. Chapman and Hall/CRC, 2015. https://doi.org/10.1201/b18612

M. Scala, and A. Reilly, Risk and the Five Hard Problems of Cybersecurity. Risk Analysis: An Official Publication of The Society for Risk Analysis, March 2019, pp. 32–37, 2019.

A. Tavanaei, et al. Deep Learning in Spiking Neural Networks, 2019. [Online] Available: https://arxiv.org/pdf/1804.08150.pdf [Accessed: May. 9, 2020].

B. Lampson, A Note on the Confinement Problem, 1973. [Online]. Available: https://www.cs.utexas.edu/~shmat/courses/cs380s_fall09/lampson73.pdf [Accessed: Feb. 19, 2020]

Open AI project. [Online]. Available: https://openai.com/ [Accessed: Feb. 11, 2020].

S. Legg, and M. Hutter, “Universal Intelligence: A definition of machine intelligence,” Minds & Machines, vol. 17, pp. 391–444, 2007. https://doi.org/10.1007/s11023-007-9079-x

S. J. Russell, “Should We Fear Supersmart Robots?” Scientific American, vol. 314, no. 6, pp. 58–59, 2016. https://doi.org/10.1038/scientificamerican0616-58

T. Everitt, Towards Safe Artificial General Intelligence. PhD thesis, Australian National University, 2018.

D. Gunning, Explainable Artificial Intelligence, DARPA project, 2018. [Online]. Available: https://www.darpa.mil/program/explainable-artificial-intelligence [Accessed: February 23, 2020].

A. Holzinger, “From Machine Learning to Explainable AI,” World Symposium on Digital Intelligence for Systems and Machines, August 2018. https://doi.org/10.1109/DISA.2018.8490530

W. Samek, T. Wegang, and K. Muller, Explainable artificial intelligence: understanding, Visualizing and interpreting deep learning models, 2017. [Online]. Available: https://arxiv.org/abs/1708.08296 [Accessed: Feb. 7, 2020].

B. Cheatham, K. Javanmardian, and H. Samandari, “Confronting the risks of artificial intelligence,” McKinsey Quarterly, 2019. [Online]. Available: https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/Confronting-the-risks-of-artificial-intelligence [Accessed: Sept 22, 2020].

L. Benjamin, C. A. Curtis, E. W. Wright, and D. K. Pearl, “Time of Conscious Intention to Act in Relation to Onset of Cerebral Activity (Readiness-Potential) - The Unconscious Initiation of a Freely Voluntary Act,” Brain, vol. 106, no. 3, pp. 623–642, 1983. https://doi.org/10.1093/brain/106.3.623

E. F. Loftus, and J. E. Pickrell, “The formation of false memories,” Psychiatric Annals, vol. 25, no. 12, pp. 720–725, 1995. https://doi.org/10.3928/0048-5713-19951201-07

W. Schwarting, J. Alonso-Mora, and D. Rus, “Planning and decision-making for autonomous vehicles,” Annual Rev., vol. 1, pp. 187–210, 2018. https://doi.org/10.1146/annurev-control-060117-105157

A. Way, “Quality Expectations of Machine Translation,” in Translation Quality Assessment. Machine Translation: Technologies and Applications, Moorkens J., Castilho S., Gaspari F., Doherty S. (eds), vol. 1. Springer, Cham. 2018. https://doi.org/10.1007/978-3-319-91241-7_8

A. Zorins, and P. Grabusts, “Safety of Artificial Superintelligence,” Environment. Technology. Resources, Proceedings 12th International Scientific and Practical Conference, Rezekne, Latvia, 2019. https://doi.org/10.17770/etr2019vol2.4042




DOI: 10.7250/itms-2020-0009

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