Towards Ethical Deployment of AI for Conservation Systems
Research output: Contribution to conference › Paper › Research › peer-review
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Towards Ethical Deployment of AI for Conservation Systems. / Belongie, Serge; Kaeser-Chen, Christine; Birch, Tanya; Chou, Katherine; Gadot, Tomer; Adam, Hartwig; Robertson, Tim; Fegraus, Eric; Morris, Dan.
2019. Paper presented at Data Mining and AI for Conservation.Research output: Contribution to conference › Paper › Research › peer-review
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TY - CONF
T1 - Towards Ethical Deployment of AI for Conservation Systems
AU - Belongie, Serge
AU - Kaeser-Chen, Christine
AU - Birch, Tanya
AU - Chou, Katherine
AU - Gadot, Tomer
AU - Adam, Hartwig
AU - Robertson, Tim
AU - Fegraus, Eric
AU - Morris, Dan
PY - 2019/10
Y1 - 2019/10
N2 - The ability to collect, aggregate, and process “big data”, particularly with artificial intelligence (AI) tools, has the potential to facilitate breakthrough research in conservation. As institutions develop and deploy such systems at scale, it is critical that they be designed with ethics, fairness, and transparency best practices in mind. In this short paper, we outline potential ethical concerns around AI for conservation as a starting point for further work to advance.
AB - The ability to collect, aggregate, and process “big data”, particularly with artificial intelligence (AI) tools, has the potential to facilitate breakthrough research in conservation. As institutions develop and deploy such systems at scale, it is critical that they be designed with ethics, fairness, and transparency best practices in mind. In this short paper, we outline potential ethical concerns around AI for conservation as a starting point for further work to advance.
UR - https://www.researchgate.net/publication/336881971_Towards_Ethical_Deployment_of_AI_for_Conservation_Systems_Global_Biodiversity_Information_Facility_Conservation_International_Wildlife_Insights
M3 - Paper
T2 - Data Mining and AI for Conservation
Y2 - 1 October 2019 through 31 October 2019
ER -
ID: 304515626