ORCID Profile
0000-0002-1954-0045
Current Organisation
University of North Texas
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Publisher: American Chemical Society (ACS)
Date: 24-11-2020
Publisher: Springer Science and Business Media LLC
Date: 26-07-2023
DOI: 10.1057/S42984-023-00063-Y
Abstract: Artificial intelligences (AI) will increasingly participate digitally and physically in conflicts yet there is a lack of trusted communications with humans for humanitarian purposes. For ex le, in disasters and conflicts messaging and social media are used to share information, however, international humanitarian relief organisations treat this information as unverifiable and untrustworthy. Furthermore, current AI implementations can be brittle, with a narrow scope of application and wide scope of ethical risks. Meanwhile, human error can cause significant civilian harms even by combatants committed to compliance with international humanitarian law. AI offers an opportunity to help reduce the tragedy of war and better deliver humanitarian aid to those who need it. However, to be successful, these systems must be trusted by humans and their information systems, overcoming flawed information flows in conflict and disaster zones that continue to be marked by intermittent communications, poor situation awareness, mistrust and human errors. In this paper, we consider the integration of a communications protocol (the ‘Whiteflag protocol’), distributed ledger ‘blockchain’ technology, and information fusion with artificial intelligence (AI), to improve conflict communications called “Protected Assurance Understanding Situation & Entities” (PAUSE). Such a trusted human-AI communication network could provide accountable information exchange regarding protected entities, critical infrastructure, humanitarian signals and status updates for humans and machines in conflicts. Trust-based information fusion provides resource-efficient use of erse data sources to increase the reliability of reports. AI can catch human mistakes and complement human decision making, while human judgment can direct and override AI recommendations. We examine several realistic potential case studies for the integration of these technologies into a trusted human-AI network for humanitarian benefit including mapping a conflict zone with civilians and combatants in real time, preparation to avoid incidents and using the network to manage misinformation. We finish with a real-world ex le of a PAUSE-like network, the Human Security Information System (HSIS), being developed by USAID, that uses blockchain technology to provide a secure means to better understand the civilian environment.
Publisher: Springer Science and Business Media LLC
Date: 19-05-2021
DOI: 10.1038/S41467-021-22392-W
Abstract: The climate-carbon cycle feedback is one of the most important climate- lifying feedbacks of the Earth system, and is quantified as a function of carbon-concentration feedback parameter ( β ) and carbon-climate feedback parameter ( γ ). However, the global climate- lifying effect from this feedback loop (determined by the gain factor, g ) has not been quantified from observations. Here we apply a Fourier analysis-based carbon cycle feedback framework to the reconstructed records from 1850 to 2017 and 1000 to 1850 to estimate β and γ . We show that the β -feedback varies by less than 10% with an average of 3.22 ± 0.32 GtC ppm −1 for 1880–2017, whereas the γ -feedback increases from −33 ± 14 GtC K −1 on a decadal scale to −122 ± 60 GtC K −1 on a centennial scale for 1000–1850. Feedback analysis further reveals that the current lification effect from the carbon cycle feedback is small ( g is 0.01 ± 0.05), which is much lower than the estimates by the advanced Earth system models ( g is 0.09 ± 0.04 for the historical period and is 0.15 ± 0.08 for the RCP8.5 scenario), implying that the future allowable CO 2 emissions could be 9 ± 7% more. Therefore, our findings provide new insights about the strength of climate-carbon cycle feedback and about observational constraints on models for projecting future climate.
Publisher: American Chemical Society (ACS)
Date: 15-02-2021
Location: United States of America
No related grants have been discovered for Sundeep Mukherjee.