Moral consideration for AI systems by 2030-Reference-Cited by-同舟云学术

Moral consideration for AI systems by 2030

Published:2023-12-11 Issue: Volume: Page:
ISSN:2730-5953
Container-title:AI and Ethics
language:en
Short-container-title:AI Ethics

Author:

Sebo Jeff^ORCID,Long Robert

Abstract

AbstractThis paper makes a simple case for extending moral consideration to some AI systems by 2030. It involves a normative premise and a descriptive premise. The normative premise is that humans have a duty to extend moral consideration to beings that have a non-negligible chance, given the evidence, of being conscious. The descriptive premise is that some AI systems do in fact have a non-negligible chance, given the evidence, of being conscious by 2030. The upshot is that humans have a duty to extend moral consideration to some AI systems by 2030. And if we have a duty to do that, then we plausibly also have a duty to start preparing now, so that we can be ready to treat AI systems with respect and compassion when the time comes.

Funder

The Centre for Effective Altruism

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s43681-023-00379-1.pdf

Reference105 articles.

1. Zhang, C., Zhang, C., Zheng, S., Qiao, Y., Li, C., Zhang, M., Dam, S. K., Thwal, C. M., Tun, Y. L., Huy, L. L., Kim, D., Bae, S. H., Lee, L. H., Yang, Y., Shen, H. T., Kweon, I. S., Hong, C. S.: A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need? (arXiv:2303.11717). arXiv (2023). http://arxiv.org/abs/2303.11717. Accessed 15 June 2023

2. Meta Bakhtin, A., Brown, N., Dinan, E., Farina, G., Flaherty, C., Fried, D., Goff, A., Gray, J., Hu, H., Jacob, A.P., Komeili, M., Konath, K., Kwon, M., Lerer, A., Lewis, M., Miller, A.H., Mitts, S., Renduchintala, A., Roller, S., Zijlstra, M., Meta Fundamental AI Research Diplomacy Team (FAIR)†: Human-level play in the game of diplomacy by combining language models with strategic reasoning. Science. 378(6624), 1067–1074 (2022)

3. Padalkar, A., Pooley, A., Jain, A., Bewley, A., Herzog, A., Irpan, A., Khazatsky, A., Rai, A., Singh, A., Brohan, A., Raffin, A., Wahid, A., Burgess-Limerick, B., Kim, B., Schölkopf, B., Ichter, B., Lu, C., Xu, C., Finn, C., Cui, Z. J.: Open X-Embodiment: Robotic Learning Datasets and RT-X Models (arXiv:2310.08864). arXiv (2023). Accessed 15 June 2023

4. Villalobos, P.: "Scaling Laws Literature Review," Published online at epochai.org (2023). Retrieved from: 'https://epochai.org/blog/scaling-laws-literature-review'. Accessed 15 June 2023

5. Bowman, S.: Eight things to know about large language models (arXiv:2304.00612). arXiv (2023). https://doi.org/10.48550/arXiv.2304.00612. Accessed 15 June 2023