Journals / İnsan ve Sosyal Bilimler Dergisi / 2022 / Cilt: 5 Sayı: 2

A review on Risk Reduction Potentials of Artificial Intelligence in Humanitarian Aid Sector

Ahmet Efe(INTERNATIONAL FEDERATION OF RED CROSS AND RED CRESCENT (IFRC))0000-0002-2691-7517
Pages
184–205
Publication Date
2022-10-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In this study, the applicability of AI to humanitarian aid is evaluated in terms of technical capability under the Emergency Social Safety Net (ESSN) program operated by IRFC Türkiye.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Many humanitarian system bottlenecks can be overcome with the help of artificial intelligence (AI) and other complementary emerging innovative technologies.
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Key Findings & Data:Research and investment in the development of AI tools tailored to resource-poor settings will accelerate the realization of the full potential of AI to improve global well-being.
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Conclusion & Impact:In this study, the applicability of AI to humanitarian aid is evaluated in terms of technical capability under the Emergency Social Safety Net (ESSN) program operated by IRFC Türkiye.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:İnsani yardım · yapay zeka · akıllı sistemler

Abstract

Many humanitarian system bottlenecks can be overcome with the help of artificial intelligence (AI) and other complementary emerging innovative technologies. Research and investment in the development of AI tools tailored to resource-poor settings will accelerate the realization of the full potential of AI to improve global well-being. It is argued that AI algorithms and machine learning techniques have become necessary in humanitarian aid operations due to their impact on efficiency and effectiveness. The study further argues that AI has the potential to support humanitarian INGOs like the IFRC and recommends that current risks, including those related to ethical issues and privacy concerns, should be addressed so that they are not deployed at the expense of humanity. Various analyzes and evaluations are made in this direction, claiming that critical issues such as need assessment, estimation, method determination, field monitoring, auditing, and reporting in humanitarian aid are to be realized through innovative technology with relatively less resources allocated. That is why the practical and efficient use of humanitarian aid funds spent by relevant institutions has become a critical issue. In this study, the applicability of AI to humanitarian aid is evaluated in terms of technical capability under the Emergency Social Safety Net (ESSN) program operated by IRFC Türkiye.

Özet

Yapay zeka (YZ) ve diğer tamamlayıcı yeni ortaya çıkan yenilikçi teknolojilerin yardımıyla birçok insani sistem darboğazlarını aşılabilir. Kaynakların yetersiz olduğu ortamlara göre uyarlanmış YZ araçlarının geliştirilmesine yönelik araştırma ve yatırım, küresel refahı iyileştirmek için YZ’nin tüm potansiyelinin gerçekleştirilmesini hızlandıracaktır. YZ algoritmalarının ve makine öğrenimi tekniklerinin, verimlilik ve etkililik üzerindeki etkileri nedeniyle insani yardım operasyonlarında gerekli hale geldiği tartışılmaktadır. Makale ayrıca, AI'nın IFRC gibi insani yardım aktörlerini destekleme potansiyeline sahip olduğunu iddia ediyor ve etik konular ve mahremiyet endişeleriyle ilgili olanlar da dahil olmak üzere mevcut risklerin, insanlığın pahasına konuşlandırılmaması için ele alınması gerektiğini tavsiye ediyor. İnsani yardım süreçlerinde ihtiyaç belirleme, tahmin, yöntem belirleme, saha izleme, denetleme, raporlama gibi kritik konuların yenilikçi teknoloji ile nispeten daha az kaynak ayrılarak gerçekleştirileceği iddiasıyla bu doğrultuda çeşitli analizler ve değerlendirmeler yapılmaktadır. Bu nedenle ilgili kurumlar tarafından harcanan insani yardım fonlarının pratik ve verimli kullanımı kritik bir konu haline gelmiştir. Bu çalışmada, AI'nın insani yardıma uygulanabilirliği, IRFC Türkiye tarafından yürütülen Acil Sosyal Güvenlik Ağı (SUY) programı kapsamında teknik yeterlilik açısından değerlendirilmektedir.

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Cite This Article

Efe, A. (2022). A review on Risk Reduction Potentials of Artificial Intelligence in Humanitarian Aid Sector. İnsan ve Sosyal Bilimler Dergisi, Cilt: 5 Sayı: 2, 184–205. https://doi.org/10.53048/johass.1189814

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References (56)

  1. Adıgüzel, S. (2022). Afet durumlarinda yapay zeka teknolojisi ile lojistik yönetimi örnekleri. Bitlis Eren Üniversitesi İktisadi ve İdari Bilimler Fakültesi Akademik İzdüşüm Dergisi, 7 (1), 47-70. Aiken, E., Bellue, S., Karlan, D. et al. (2022). Machine learning and phone data can improve targeting of humanitarian aid. Nature, https://doi.org/10.1038/s41586-022-04484-9
  2. Ali, M. (2021). Artificial intelligence could stop millions from going hungry by 2030, Euronews Eco-Innovation, https://www.euronews.com/green/2021/06/30/could-artificial-intelligence-stop-840-million-people-from-going-hungry-by-2030
  3. Aoukar, Y. (2019). Can AI help save our children from online sexual abuse?, https://www.centreforpublicimpact.org/insights/can-ai-help-save-our-children-from-online-sexual-abuse#nav-1 Apps, P. (2019). Commentary: Are China, Russia winning the AI arms race? Reuters, https://www.reuters.com/article/us-apps-ai-commentary/commentary-are-china-russia-winning-the-ai-arms-race-idUSKCN1P91NM
  4. Arkin, R., (2015). Communications of the ACM, Viewpoints, DOI:10.1145/2835965, https://www.cc.gatech.edu/ai/robot-lab/online-publications/308_V5812_VP_PCPREVArkinREV.pdf
  5. Axe, D. (2019). This video might be the future of russia's army: armed ground robots. The National Interest, https://nationalinterest.org/blog/buzz/video-might-be-future-russias-army-armed-ground-robots-48022
  6. Bakır, Z. Z. (2016). Küresel insani yardım sistemi ve değişim ihtiyacı, INSAMER, https://insamer.com/tr/kuresel-insani-yardim-sistemi-ve-degisim-ihtiyaci_373.html
  7. Bennet, C. (2016). Humanitarian Policy Group, "Time to Let Go: A Three-Point Proposal to Change The Humanitarian System," April.
  8. Çapan, F. (2021). Olanı engelleyemiyoruz (şimdilik) ama ya sonuçlara etki edebilirsek?, https://ayayderliderlikokulu.org/2021/06/06/olani-engelleyemiyoruz-simdilik-ama-ya-sonuclara-etki-edebilirsek/
  9. Cassidy, M. (2020). Oakland police have 1,200 untested rape kits, second most in California, audit finds. San Fransisco Cronicle, https://www.sfchronicle.com/crime/article/ Audit-finds-Oakland-police-have-1-200-untested-15271265.php
  10. Coppi, G., Moreno Jimenez, R. & Kyriazi, S. (2021). Explicability of humanitarian AI: a matter of principles. Int J Humanitarian Action 6, 19 https://doi.org/10.1186/s41018-021-00096-6
  11. Cox, M. (2019). Army looking at ai-controlled weapons to counter enemy fire. Military, https://bit.ly/2zg9q2w
  12. Cunningham, O. (2012). The humanitarian adi regime in the republic of NGOs.
  13. Dindarik N. & Fidan Y. (2020). Türkiye’de mültecilerin yaşadıkları bölgelere yönelik insani yardım lojistiği: Kızılay örneği. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi Manisa Celal Bayar University Journal of Social Sciences; 18 (2), 135-154.
  14. DLR, (2021). Humanitarian aid with uncrewed aircraft and artificial intelligence, https://www.dlr.de/content/en/articles/news/2021/01/20210208_launch-of-the-drones4good-project.html
  15. DuBois, M. et al. (2015). The Ebola Response in West Africa: Exposing the Politics and Culture of International aid. https://odi.org/en/publications/the-ebola-response-in-west-africa-exposing-the-politics-and-culture-of-international-aid/
  16. Duffield, M. (2007). Development, Security and unending war: governing the world of peoples, Cambridge: Polity Press.
  17. Hornyak, T. (2017). Mapping dengue fever hazard with machine learning. Eos. https://eos.org/articles/mapping-dengue-fever-hazard-with-machine-learning (updated 14 June 2017). 10.1029/2017EO076019
  18. Huang, K. (2019). China's Sky Hawk stealth drone has the capability to 'talk' to fighter pilots, developer says, SCMP, https://www.scmp.com/news/china/military/article/2181731/chinas-sky-hawk-stealth-drone-has-capability-talk-fighter-pilots
  19. Imran, M., Ofli, F., Alam, F., & Qazi, U. (2020). Using Artificial Intelligence and Social Media Multimodal Data for Humanitarian Aid.
  20. Intell (2020). Türkiye’nin yardım politikası uluslararası rolüne işaret ediyor, https://www.intell4.com/kamu-diplomasisi-nedir-turkiyenin-yardim-politikasi-turkiyenin-yardim-ettigi-ulkeler-tika-ne-is-yapar-haber-185390
  21. Joshi, N. (2018). 4 ways global defense forces use ai. Forbes, https://www.forbes.com/sites/cognitiveworld/2018/08/26/4-ways-the-global-defense-forces-are-using-ai/#7e9d8703503e
  22. Kalkan, E. (2009). "Here is the Reality of Darfur", http://www.hurriyet.com.tr/iste-darfur-gercegi-13122856
  23. Kissos L, Goldner L, Butman M, Eliyahu N, Lev-Wiesel R. (2020). Can artificial intelligence achieve human-level performance? A pilot study of childhood sexual abuse detection in self-figure drawings. Child Abuse Negl. 2020 Nov; 109:104755. doi: 10.1016/j.chiabu.2020.104755. Epub Oct 16. PMID: 33075702.
  24. Köksoy, F. (2017). Uluslararası Kızılhaç komitesi’nin faaliyetleri ekseninde insani diplomasi. Batman University Journal of Life Sciences, 7(1).
  25. Lee, E., (2018). Yapay zeka açlık sorununu çözer mi?, amerikanın sesi, https://www.amerikaninsesi.com/a/yapay-zeka-aclik-sorununu-cozer-mi-/4627595.html
  26. Li, L. ve Tang, S. (2021). An artificial emergencylogistics-planning system for severe disasters. Intelligent Transportation System. 86-88. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4580551.
  27. Malewar, A. (2019). US Army's next rifle could have facial-recognition technology, Techexplorist, https://www.techexplorist.com/u-s-armys-next-rifle-facial-recognition-technology/23782/
  28. Meinetten J. (2017). AI is a game-changer in the fight against hunger and poverty. Here's Why. HU Media Analysis 2017/2018, https://hucmdmediaanalysis1718b.wordpress.com/2017/12/02/ai-is-a-game-changer-in-the-fight-against-hunger-and-poverty-heres-why/
  29. MFA (2016). Turkish humanitarian Aids. http://www.mfa.gov.tr/turkiye_nin_-insani-yardimlari.tr.mfa
  30. Microsoft (2022). AI for humanitarian action projects, https://www.microsoft.com/en-us/ai/ai-for-humanitarian-action-projects?activetab=pivot1:primaryr6
  31. Misthi, A. (2021). Artificial intelligence could stop millions from going hungry by 2030, https://www.euronews.com/green/2021/06/30/could-artificial-intelligence-stop-840-million-people-from-going-hungry-by-2030
  32. Mohamedou, M. (2014). "ISIS and the deceptive rebooting of al qaeda", GCSP Policy Paper, http://gcsp.ch.
  33. Naval (2019). USMC gets final RQ-21A Blackjack unmanned aircraft system, https://www.naval-technology.com/news/usmc-gets-final-rq-21a-blackjack-unmanned-aircraft-system/
  34. Oriel, A. (2020). Top 8 AI technologies to mitigate child abuse and child trafficking, https://www.analyticsinsight.net/top-8-ai-technologies-mitigate-child-abuse-child-trafficking/
  35. Oroz, M. L. (2020). From big data to humanitarian-in-the-loop algorithms, UNCHR Innvation Service, https://www.unhcr.org/innovation/big-data-humanitarian-loop-algorithms/
  36. Özen, F. (2017). Afetlerde robotların kullanımı. TMMOB Journal, https://www.emo.org.tr/ekler/09c7bd3514f9da1_ek.pdf?dergi=1106
  37. Pandya, J. (2019). The Weaponization of artificial intelligence. Forbes, https://www.forbes.com/sites/cognitiveworld/2019/01/14/the-weaponization-of-artificial-intelligence/#4a35170b3686
  38. Peck M., (2019). Forget stealth fighters or aircraft carriers: China will beat America with this. The National Interest, https://nationalinterest.org/blog/buzz/forget-stealth-fighters-or-aircraft-carriers-china-will-beat-america-62987
  39. Reis MA, Ortega NR, Silveira PS. (2004). Fuzzy expert system in the prediction of neonatal resuscitation. Braz J Med Biol Res, 37, 755–64. 10.1590/S0100-879X2004000500018
  40. Roth, M. (2019). Artificial Intelligence at the Top 5 US Defense Contractors, https://emerj.com/ai-sector-overviews/artificial-intelligence-at-the-top-5-us-defense-contractors/
  41. Şen, G. & Esmer, S. (2017). Afet lojistiği bir literatür taraması. International New Issues in Socials Sciences International Scientific Refereed Journal https://www.academia.edu/36749745/AFET_LOJ%C4%B0ST%C4%B0%C4%9E%C4%B0_B%C4%B0R_L%C4%B0TERAT%C3%9CR_TARAMASI?auto=download&email_work_card=download-paper.
  42. Staff, T. (2018). IDF using autonomous drone system to try to intercept Gaza kites, balloons. The Time of Israel, https://www.timesofisrael.com/idf-using-autonomous-drone-system-to-intercept-gaza-kites-balloons/
  43. Swasdee, A., Anshari, M., & Hamdan, M. (2020, November). Artificial ıntelligence as decision aid in humanitarian response. International Conference on Decision Aid Sciences and Application (DASA) (pp. 773-777). IEEE.
  44. Swetlitz, I. (2016). Watson goes to Asia as hospitals use supercomputer for cancer treatment: PBS NewsHour. http://www.pbs.org/newshour/rundown/hospitals-use-supercomputer-cancer-treatment/2017
  45. ThinkTech (2020). Yapay zekâ savaşları başlıyor mu?, https://thinktech.stm.com.tr/tr/yapay-zeka-savaslari-basliyor-mu
  46. Toplic, L. (2020). AI in the humanitarian sector, nethope report, https://reliefweb.int/report/world/ai-humanitarian-sector
  47. Tzavella, K., Fekete, A., & Fiedrich, F. (2018). Natural hazardd opportunities provided by geographic ınformation systems and volunteered geographic ınformation for a timely emergency response during flood events in cologne, Germany. Natural Hazards, 91(1), 2957.
  48. UNWOMEN (2019). Using AI in accessing justice for survivors of violence, https://www.unwomen.org/en/news/stories/2019/5/feature-using-ai-in-accessing-justice-for-survivors-of-violence
  49. Wahl, B., Cossy-Gantner, A., Germann, S., & Schwalbe, N. R. (2018). Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings?. BMJ Global Health, 3(4), e000798. https://doi.org/10.1136/bmjgh-2018-000798
  50. WHO, (2017). Dengue and severe dengue. http://www.who.int/mediacentre/factsheets/fs117/en/2017
  51. Wieland ML, Wu ST, Kaggal VC, et al. (2013). Tracking health disparities through natural-language processing. Am J Public Health; 103:448–9. 10.2105/AJPH.2012.300943
  52. Zhang, P., Guo, Z., Ullah, S., Melagraki, G., Afantitis, A. & Iseult, L. (2021). Nanotechnology and artificial intelligence enable sustainable and precision agriculture. Nature Plants, DOI: 10.1038/s41477-021-00946-6
  53. Zhongming, Z., Linong, L., Xiaona, Y., Wangqiang, Z., & Wei, L. (2021). Humanitarian aid with uncrewed aircraft and artificial intelligence.
  54. Zhu, X., Zhang, G., ve Sun, B. (2019). A comprehensive literature review of the demand forecasting methods of emergency resources from the perspective of artificial ıntelligence. Natural Hazards, 97(1), 65-82.
  55. Adıgüzel, S. (2022). Afet durumlarinda yapay zeka teknolojisi ile lojistik yönetimi örnekleri. Bitlis Eren Üniversitesi İktisadi ve İdari Bilimler Fakültesi Akademik İzdüşüm Dergisi, 7 (1), 47-70.
  56. Swetlitz, I. (2016). Watson goes to Asia as hospitals use supercomputer for cancer treatment: PBS NewsHour. http://www.pbs.org/newshour/rundown/hospitals-use-supercomputer-cancer-treatment/2017