{"id":1014747,"date":"2024-04-02T08:58:55","date_gmt":"2024-04-02T15:58:55","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/?post_type=msr-project&p=1014747"},"modified":"2024-09-19T09:50:54","modified_gmt":"2024-09-19T16:50:54","slug":"fundamental-rights-ai-for-good","status":"publish","type":"msr-project","link":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/project\/fundamental-rights-ai-for-good\/","title":{"rendered":"Fundamental Rights – AI for Good"},"content":{"rendered":"
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Fundamental rights<\/h1>\n\n\n\n

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AI-driven solutions<\/h2>\n\n\n\n

In today’s evolving landscape, safeguarding fundamental rights is crucial, especially in addressing the aftermath of natural disasters, which disproportionately impact vulnerable communities. Climate change puts millions in danger and causes significant economic losses. With help from AI, governments and emergency responders can better anticipate crises, and deploy targeted interventions that save lives and minimize damage. Simultaneously, advancing individuals’ rights to accessible digital technology is vital. Without it, access to education, healthcare, jobs, and essential services is limited, hindering the ability to fully participate and thrive in society.<\/p>\n\n\n\n

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A world seen in full is a better world<\/a><\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n
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Empower communities to take anticipatory action with early warnings<\/h2>\n\n\n\n
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Identifying at-risk communities<\/h4>\n\n\n\n

Traditional population mapping often overlooks communities amidst unplanned growth and migration. Microsoft’s AI for Good Lab, partnering with Planet (opens in new tab)<\/span><\/a> and the Institute for Health Metrics and Evaluation (IHME) (opens in new tab)<\/span><\/a>, employs satellite imagery and AI to produce high-resolution population maps for better climate-event resilience.<\/p>\n\n\n\n

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Advanced forecasting for hunger<\/h4>\n\n\n\n

With 690 million people facing hunger in 2020, worsened by climate disasters, urgent assistance is vital. A study by Microsoft AI for Good Lab and Catholic Relief Services used machine learning to predict food insecurity in southern Malawi with 83% accuracy up to 4 months ahead, aiding informed decisions for proactive interventions.<\/p>\n\n\n\n

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Targeted early warnings with risk maps<\/h4>\n\n\n\n

Extreme heat poses a significant global threat, especially in densely populated areas where soaring indoor temperatures endanger vulnerable populations. SEEDS (opens in new tab)<\/span><\/a>, in collaboration with Microsoft AI for Good Lab, developed AI models that provide targeted early warnings, resource allocation, and actionable insights.<\/p>\n\n\n\n

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“A very important component to measuring health and being able to provide services is knowing where people live in the world.\u201d<\/p>\n\u2013 Dr. Emmanuela Gakidou, The Institute for Health Metrics and Evaluation<\/cite><\/blockquote>\n\n\n\n

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Protect communities with accurate and rapid response to climate events<\/h2>\n\n\n\n
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Reliable data is vital to relief efforts<\/h4>\n\n\n\n

After earthquakes in Afghanistan and Turkey-Syria region, aid organizations faced obstacles due to limited data. With over 56,400 lives lost and millions impacted, Microsoft AI for Good Lab collaborated with Planet Labs to deploy AI models for rapid building identification and damage assessment, highlighting the importance of technology in improving disaster relief efforts.<\/p>\n\n\n\n

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Rapid response means saving lives<\/h4>\n\n\n\n

Over 100 lives were lost in the Lahaina fire, and 2,810 buildings were extensively damaged, causing displacement and over $6 billion in damage. AI-powered damage assessments completed within four hours with 97% accuracy facilitated swift provision of actionable maps to the American Red Cross and emergency groups.
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Geospatial fundamentals<\/h4>\n\n\n\n

Learn basic skills on AI and Disaster Management through a specialized course on Coursera with our partner Deeplearning.ai (opens in new tab)<\/span><\/a>, exploring mitigation, preparation, response, and recovery. Or solve a machine learning problem end to end in Let’s Map Africa (opens in new tab)<\/span><\/a>. Our materials are here to support your learning journey.
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\u201cOur preliminary damage assessment process is days ahead of our typical timeframe, thanks to a donation of time, expertise and technology from Microsoft\u2019s AI for Good Research Lab that is using AI models and satellite imagery to analyze the extent of the damage\u201d<\/p>\n\u2013 Brad Kieserman, American Red Cross<\/cite><\/blockquote>\n\n\n\n

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Increasing equity, accessibility and cultural preservation<\/h2>\n\n\n\n
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Close the connectivity gap<\/h4>\n\n\n\n

Approximately 2.7 billion people globally lack internet access. Our commitment with partners aims to provide internet access to 250 million people in underserved communities worldwide enabling participation in education, work, telehealth, and beyond.<\/p>\n\n\n\n

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Promote accessibility and inclusion<\/h4>\n\n\n\n

We are committed to accessible technology and advocating for policies that recognize accessibility as a fundamental right. With over 285 million worldwide experiencing vision impairment, Seeing AI helps blind and low-vision people navigate their daily lives with AI.<\/p>\n\n\n\n

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Preserve our cultural heritage<\/h4>\n\n\n\n

Harnessing the power of AI, we honor the past and connect to the future with the “Thread of Memory.” This immersive digital experience takes you on a captivating journey through the pivotal events of D-Day, bringing history to life and preserving it for future generations.<\/p>\n\n\n\n

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Microsoft is committed to strengthening communities and empowering the organizations that help them thrive. We have a responsibility to protect people\u2019s fundamental rights, and help all communities succeed.<\/p>\n","protected":false},"featured_media":1033209,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556],"msr-locale":[268875],"msr-impact-theme":[261670],"msr-pillar":[],"class_list":["post-1014747","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[1020171,920430,936363,949443,957576,957582,959733,1007853,1007859,900249,1024761,1090491,1097580,1115781,1115796,1115802,1115814,617997,899397,899205,899082,885015,837169,821485,809140,808807,802924,760624,745216,706030,696790,637458],"related-downloads":[],"related-videos":[],"related-groups":[696544],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[],"msr_research_lab":[],"msr_impact_theme":["Resilience"],"_links":{"self":[{"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1014747","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":70,"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1014747\/revisions"}],"predecessor-version":[{"id":1085700,"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1014747\/revisions\/1085700"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/media\/1033209"}],"wp:attachment":[{"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1014747"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1014747"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1014747"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1014747"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=1014747"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}