United States

Northern Mariana Islands

Puerto Rico

American Samoa

Guam

U.S. Virgin Islands

U.S. Minor Outlying Islands

US & Territories

Leonardo da Vinci was a Renaissance genius. Not only did he paint masterpieces of art, but he was an obsessive scientist and inventor, dreaming up complex machines centuries ahead of his time, including parachutes, armored tanks, hang gliders, and robots. On the 500th anniversary of Leonardo’s death, with the help of biographer Walter Isaacson, NOVA investigates the secrets of Leonardo’s success. How did his scientific curiosity, from dissections of cadavers to studies of optics, shape his genius and help him create perhaps the most famous painting of all time, the "Mona Lisa"? (Premiered November 13, 2019)

Discover the science behind Leonardo da Vinci's masterpieces—and Mona Lisa's iconic smile.

Decoding da Vinci

In a new age of information, rapid innovation, and globalization, how can we prepare our children to compete? Once the envy of the world, American schools are now in trouble. Test scores show our kids lag far behind their peers from other industrialized countries, and as the divide between rich and poor grows wider, the goal of getting all kids ready for college and the workforce gets harder by the day. How can the latest research help us fix education in America? Can the science of learning—including new insights from neuroscientists, psychologists, and educators—reveal how kids’ brains work and tell us which techniques are most likely to engage and inspire growing minds? What role should technology play in the classroom? Teachers, students, parents, and scientists take center stage as NOVA explores a new vision for the “School of the Future.”

How can the science of learning help us rethink the future of education for all children?

School of the Future

Rockets are becoming cheaper and more powerful than ever before thanks to stunning new technologies. As companies like SpaceX and Virgin Galactic make space more accessible, and NASA returns to crewed spaceflight, a new era of space exploration seems to be on the horizon. But will this seeming rocket Renaissance become more than just hype? NOVA explores the latest rocket technologies and the growing role private citizens may have in space. (Premiered February 13, 2019)

With new technologies, NASA and private companies are promising a new renaissance in space travel.

Rise of the Rockets

The Deepfake Detective

Discover how deepfakes are detected and what the future holds for truth in the digital age.

A man clenches his fist in front of a computer monitor and a prosthetic hand.

Using A.I. to Improve Prosthetic Limbs

<!DOCTYPE html><html lang="en"><head><link rel="preconnect" href="//static.pbslearningmedia.org/" crossorigin><base href="/"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><title>Using A.I. to Improve Prosthetic Limbs | NOVA | PBS LearningMedia</title><link rel="canonical" href="https://www.pbslearningmedia.org/resource/nvair-sci-aiprosthetic/using-ai-to-improve-prosthetic-limbs-nova/"/><meta name="description" content="Learn about advances in prosthetic arms using artificial intelligence with this video excerpt from NOVA: A.I. Revolution. Use this resource to provide students with opportunities to recognize how training data affects the functionality of A.I. and to communicate the benefits and drawbacks of advanced prosthetics."><meta name="viewport" content="width=device-width, initial-scale=1"><meta property="fb:pages" content="213237472033241"><meta property="og:type" content="website"/><meta property="og:site_name" content="PBS LearningMedia"/><meta name="twitter:card" content="summary_large_image"/><meta name="twitter:site" content="@PBSLrnMedia"/><meta property="og:title" content="Using A.I. to Improve Prosthetic Limbs | NOVA | PBS LearningMedia"/><meta property="og:description" content="Learn about advances in prosthetic arms using artificial intelligence with this video excerpt from NOVA: A.I. Revolution. Use this resource to provide students with opportunities to recognize how training data affects the functionality of A.I. and to communicate the benefits and drawbacks of advanced prosthetics."/><meta property="og:image" content="https://image.pbs.org/poster_images/assets/Using_A.I._to_Improve_Prosthetic_Limbs-poster.png"/><meta property="og:url" content="https://www.pbslearningmedia.org/resource/nvair-sci-aiprosthetic/using-ai-to-improve-prosthetic-limbs-nova/"/><link type="text/css" rel="stylesheet" href="https://static.pbslearningmedia.org/static/lib/fontawesome/font-awesome.css"><script src="https://static.pbslearningmedia.org/static/lib/jquery-3.2.1.min.js"></script><script src="https://static.pbslearningmedia.org/static/lib/js.cookie.min.js"></script><script type="text/javascript" src="//static.pbslearningmedia.org/static/205.0.0/lm/js/utility.js"></script><script>
 window.dataLayer = [];
 
 var org = '';
 
 if(Cookies.get("organization_name")) {
 org = Cookies.get("organization_name");
 }
 
 org = org.replace(/^\"|^\s+|\s+$|\"$/g, '');
 window.dataLayer.push({'dimension1': 'www'}); //contributor station
 // Dimension 2 - Resource Top Level Subjects
 
 // Dimension 3 - Resource Content Project Name
 
 // Dimension 4 - Resource Grade Ranges
 
 window.dataLayer.push({'dimension5': ''}); //user postal code
 window.dataLayer.push({'dimension6': org}); //user organization
 window.dataLayer.push({'dimension7': ''}); //user role
 //user preferred subjects delimited by the '&' sign
 window.dataLayer.push({'dimension8': 'None'});
 window.dataLayer.push({'dimension9': ''}); //user defined grade levels
 //user logged in state
 window.dataLayer.push({'dimension10': 'Not logged in'});
 // Dimension 11 - Resource Brand
 
 // Dimension 12 - Resource Content Type
 
 // Dimension 13 - Resource Organization
 
 // Dimension 14 - Resource Media Type
 
 window.dataLayer.push({'dimension15': ''}); //user school
 // Dimension 16 - Assignment code
 // Dimension 17 - Usage by Schools
 // Dimension 18 - Station
 window.dataLayer.push({'dimension19': 'Teacher'});
 window.dataLayer.push({'dimension20': 'false'});
 // Debug data
 window.dataLayer.push({'dimension22': '-'});
 window.dataLayer.push({'dimension23': '-'});
 window.dataLayer.push({'dimension24': '-'});
 window.dataLayer.push({'dimension25': '-'});
 
 window.dataLayer.push({'dimension26': false});
</script><script>
 window.dataLayer.push({'pbslm-redesign': "yes"});
 </script><script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);
})(window,document,'script','dataLayer','GTM-PB2JCH');</script><link href="//static.pbslearningmedia.org/static/205.0.0/station/css/bootstrap-overrides.min.css" type="text/css" rel="stylesheet" /></head><body><noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-PB2JCH"
height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript><app-root id="app-root"><div style="text-align: center; padding: 20px;">Loading...</div></app-root><script src="https://static.pbslearningmedia.org/static/lib/popper.min.js"></script><script src="https://static.pbslearningmedia.org/static/lib/bootstrap.min.js"></script><script>
 (function () {
 if (navigator.appVersion.indexOf('Trident/') > -1){
 
 var child = document.getElementById("app-root");
 child.parentNode.removeChild(child);
 document.title = "PBS LearningMedia not available"
 document.activeElement.innerHTML+='<div style="text-align: center; padding: 20px;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/warning.png" style="width: 60px; margin:20px"/>'+
 'PBS LearningMedia no longer works on Interner Explorer.'+
 'We recommend using one of the following browsers:'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/chrome.png" style="width: 40px;"/>'+
 'Google Chrome'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/safari.png" style="width: 40px;"/>'+
 'Safari'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/mozilla.png" style="width: 40px;"/>'+
 'Mozilla Firefox'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/opera.png" style="width: 40px;"/>'+
 'Opera'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/edge.png" style="width: 40px;" />'+
 'Microsoft Edge'+
 '</label>'+
 '</div>'
 }
 })();
 PBSLM = window.PBSLM || {};
 PBSLM.NATIONAL_SITE_URL = 'https://www.pbslearningmedia.org/';
 PBSLM.STATIC_URL = '//static.pbslearningmedia.org/static/205.0.0/';
 PBSLM.NG = PBSLM.ng || {};
 PBSLM.NG.VERSION = "205.0.0";
 PBSLM.NG.API_KEY = "0f1b0fae-363c-4693-bc33-7c5dcc01c749";
 PBSLM.NG.IS_AUTHENTICATED = false;
 PBSLM.NG.IS_YOUNG_STUDENT = false;
 PBSLM.NG.IS_STUDENT = false;
 PBSLM.NG.USER_PK = null;
 PBSLM.NG.USER_NAME = "";
 PBSLM.NG.ADMIN_DISPLAY = false;
 PBSLM.NG.FIRST_NAME = "";
 PBSLM.NG.PBS_AUTH_URL = "/public_media/login/";
 PBSLM.NG.PBS_AUTH_REGISTER_URL = "/public_media/register/";
 PBSLM.NG.GOOGLE_AUTH_URL = "/profile/login-national/google-oauth2/";
 PBSLM.NG.FACEBOOK_AUTH_URL = "/profile/login-national/facebook/";
 PBSLM.NG.LOGOUT_URL = "/logout/?next=/";
 PBSLM.NG.STUDENT_AUTH_URL = "/student/signup/?next=/student/";
 PBSLM.NG.GA_PBSLM_PROPERTY_ID = "None";
 PBSLM.NG.IS_SU = false;
 
 PBSLM.NG.MUX_KEY = "6327gbrtf6qvc0sr3gdtlj74f";
 
 
 PBSLM.SENTRY_JS_DSN = "https://ea62268d2e014c92ad2d288f7f2c5f0c@o260369.ingest.sentry.io/1465871";
 PBSLM.NG.CAPTCHA_SITE_KEY = "6Lc0IEsaAAAAAFtF5ZhOptQoGgr2wc7eGdzLEm5P";
 PBSLM.TEMP_FAV_URL = "/tools/favorites/";
 PBSLM.SHOW_VIRGINIA_MODAL = false;
 PBSLM.FORM_SEARCH_ACTION = "/search/";
 
 
 PBSLM.NG.EMBEDDED_PAGE = false;
 PBSLM.NG.CDN = 'https://static.pbslearningmedia.org/';
 
 PBSLM.NG.ERROR_MESSAGE = "";
 
 
 
 
 PBSLM.FEATURE_FLAGS = {
 RECOMMENDATION_ENGINE_SHOW_TO_USERS: false,
 RECOMMENDATION_ENGINE_COLLECT_DATA: false,
 RECOMMENDATION_ENGINE_INTEREST_QUIZ: false
 };
 PBSLM.PRELOADED_ENDPOINTS = JSON.parse('' || '{}');
 </script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/polyfills.js" type="text/javascript"></script><link rel="stylesheet" href="//static.pbslearningmedia.org/static/205.0.0/lm/dist/styles.css"><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/main.js" type="text/javascript"></script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/runtime.js" type="text/javascript"></script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/vendor.js" type="text/javascript"></script><script type="application/ld+json">
 {"@context": "https://schema.org", "@type": ["VideoObject", "LearningResource"], "name": "Using A.I. to Improve Prosthetic Limbs | NOVA", "publisher": {"@type": "Organization", "name": "NOVA", "logo": {"@context": "http://schema.org", "@type": "ImageObject", "url": "https://static.pbslearningmedia.org/media/entity/NOVA-color.png"}}, "dateModified": "2025-04-30 17:17:38", "description": "Learn about advances in prosthetic arms using artificial intelligence with this video excerpt from NOVA: A.I. Revolution. Use this resource to provide students with opportunities to recognize how training data affects the functionality of A.I. and to communicate the benefits and drawbacks of advanced prosthetics.", "thumbnailUrl": "https://image.pbs.org/poster_images/assets/Using_A.I._to_Improve_Prosthetic_Limbs-poster.png", "contentURL": null, "duration": "PT03M29S", "expires": null, "interactionCount": 2415, "uploadDate": "2025-01-22 17:28:33", "educationalAlignment": [{"@type": "AlignmentObject", "alignmentType": "educationalSubject", "educationalFramework": "NGSS - Grade Level Disciplinary Core Ideas", "targetName": "MS-LS1.D.1", "targetUrl": ""}, {"@type": "AlignmentObject", "alignmentType": "educationalSubject", "educationalFramework": "Benchmarks for Science Literacy", "targetName": "6E/H3a", "targetUrl": ""}], "educationalLevel": "Grade 6-12 (US)", "learningResourceType": "Concept Overview Video", "regionsAllowed": {"@type": "Region", "name": ""}}
 </script><script>
 (function(apiKey){
 (function(p,e,n,d,o){var v,w,x,y,z;o=p[d]=p[d]||{};o._q=[];
 v=['initialize','identify','updateOptions','pageLoad'];for(w=0,x=v.length;w<x;++w)(function(m){
 o[m]=o[m]||function(){o._q[m===v[0]?'unshift':'push']([m].concat([].slice.call(arguments,0)));};})(v[w]);
 y=e.createElement(n);y.async=!0;y.src='https://cdn.pendo.io/agent/static/'+apiKey+'/pendo.js';
 z=e.getElementsByTagName(n)[0];z.parentNode.insertBefore(y,z);})(window,document,'script','pendo');
 var initData = {'visitor': {}, 'account': {}};
 
 
 pendo.initialize(initData);
 })('33f33e71-b8a2-4711-57b6-cae11b98c10a');
</script></body></html>

Learn about advances in prosthetic arms using artificial intelligence with this video excerpt from NOVA: A.I. Revolution.

The image shows two faces: a deep fake A.I. image of Barack Obama and the real Jordan Peele

Manipulating Reality: Deepfake Videos and Generated Images

<!DOCTYPE html><html lang="en"><head><link rel="preconnect" href="//static.pbslearningmedia.org/" crossorigin><base href="/"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><title>Manipulating Reality: Deepfake Videos and Generated Images | NOVA | PBS LearningMedia</title><link rel="canonical" href="https://www.pbslearningmedia.org/resource/nvair-sci-deepfake/manipulating-reality-deepfake-videos-and-generated-images-nova/"/><meta name="description" content="Learn how artificial intelligence can generate deepfake images and videos with these video excerpts from NOVA: A.I. Revolution. Use this resource to provide students with opportunities to recognize how generative A.I. technology can impact society and to learn how to minimize its harmful effects."><meta name="viewport" content="width=device-width, initial-scale=1"><meta property="fb:pages" content="213237472033241"><meta property="og:type" content="website"/><meta property="og:site_name" content="PBS LearningMedia"/><meta name="twitter:card" content="summary_large_image"/><meta name="twitter:site" content="@PBSLrnMedia"/><meta property="og:title" content="Manipulating Reality: Deepfake Videos and Generated Images | NOVA | PBS LearningMedia"/><meta property="og:description" content="Learn how artificial intelligence can generate deepfake images and videos with these video excerpts from NOVA: A.I. Revolution. Use this resource to provide students with opportunities to recognize how generative A.I. technology can impact society and to learn how to minimize its harmful effects."/><meta property="og:image" content="https://image.pbs.org/poster_images/assets/Fake_Images_and_Videos-_Past_and_Present-poster.png"/><meta property="og:url" content="https://www.pbslearningmedia.org/resource/nvair-sci-deepfake/manipulating-reality-deepfake-videos-and-generated-images-nova/"/><link type="text/css" rel="stylesheet" href="https://static.pbslearningmedia.org/static/lib/fontawesome/font-awesome.css"><script src="https://static.pbslearningmedia.org/static/lib/jquery-3.2.1.min.js"></script><script src="https://static.pbslearningmedia.org/static/lib/js.cookie.min.js"></script><script type="text/javascript" src="//static.pbslearningmedia.org/static/205.0.0/lm/js/utility.js"></script><script>
 window.dataLayer = [];
 
 var org = '';
 
 if(Cookies.get("organization_name")) {
 org = Cookies.get("organization_name");
 }
 
 org = org.replace(/^\"|^\s+|\s+$|\"$/g, '');
 window.dataLayer.push({'dimension1': 'www'}); //contributor station
 // Dimension 2 - Resource Top Level Subjects
 
 // Dimension 3 - Resource Content Project Name
 
 // Dimension 4 - Resource Grade Ranges
 
 window.dataLayer.push({'dimension5': ''}); //user postal code
 window.dataLayer.push({'dimension6': org}); //user organization
 window.dataLayer.push({'dimension7': ''}); //user role
 //user preferred subjects delimited by the '&' sign
 window.dataLayer.push({'dimension8': 'None'});
 window.dataLayer.push({'dimension9': ''}); //user defined grade levels
 //user logged in state
 window.dataLayer.push({'dimension10': 'Not logged in'});
 // Dimension 11 - Resource Brand
 
 // Dimension 12 - Resource Content Type
 
 // Dimension 13 - Resource Organization
 
 // Dimension 14 - Resource Media Type
 
 window.dataLayer.push({'dimension15': ''}); //user school
 // Dimension 16 - Assignment code
 // Dimension 17 - Usage by Schools
 // Dimension 18 - Station
 window.dataLayer.push({'dimension19': 'Teacher'});
 window.dataLayer.push({'dimension20': 'false'});
 // Debug data
 window.dataLayer.push({'dimension22': '-'});
 window.dataLayer.push({'dimension23': '-'});
 window.dataLayer.push({'dimension24': '-'});
 window.dataLayer.push({'dimension25': '-'});
 
 window.dataLayer.push({'dimension26': false});
</script><script>
 window.dataLayer.push({'pbslm-redesign': "yes"});
 </script><script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);
})(window,document,'script','dataLayer','GTM-PB2JCH');</script><link href="//static.pbslearningmedia.org/static/205.0.0/station/css/bootstrap-overrides.min.css" type="text/css" rel="stylesheet" /></head><body><noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-PB2JCH"
height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript><app-root id="app-root"><div style="text-align: center; padding: 20px;">Loading...</div></app-root><script src="https://static.pbslearningmedia.org/static/lib/popper.min.js"></script><script src="https://static.pbslearningmedia.org/static/lib/bootstrap.min.js"></script><script>
 (function () {
 if (navigator.appVersion.indexOf('Trident/') > -1){
 
 var child = document.getElementById("app-root");
 child.parentNode.removeChild(child);
 document.title = "PBS LearningMedia not available"
 document.activeElement.innerHTML+='<div style="text-align: center; padding: 20px;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/warning.png" style="width: 60px; margin:20px"/>'+
 'PBS LearningMedia no longer works on Interner Explorer.'+
 'We recommend using one of the following browsers:'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/chrome.png" style="width: 40px;"/>'+
 'Google Chrome'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/safari.png" style="width: 40px;"/>'+
 'Safari'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/mozilla.png" style="width: 40px;"/>'+
 'Mozilla Firefox'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/opera.png" style="width: 40px;"/>'+
 'Opera'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/edge.png" style="width: 40px;" />'+
 'Microsoft Edge'+
 '</label>'+
 '</div>'
 }
 })();
 PBSLM = window.PBSLM || {};
 PBSLM.NATIONAL_SITE_URL = 'https://www.pbslearningmedia.org/';
 PBSLM.STATIC_URL = '//static.pbslearningmedia.org/static/205.0.0/';
 PBSLM.NG = PBSLM.ng || {};
 PBSLM.NG.VERSION = "205.0.0";
 PBSLM.NG.API_KEY = "0f1b0fae-363c-4693-bc33-7c5dcc01c749";
 PBSLM.NG.IS_AUTHENTICATED = false;
 PBSLM.NG.IS_YOUNG_STUDENT = false;
 PBSLM.NG.IS_STUDENT = false;
 PBSLM.NG.USER_PK = null;
 PBSLM.NG.USER_NAME = "";
 PBSLM.NG.ADMIN_DISPLAY = false;
 PBSLM.NG.FIRST_NAME = "";
 PBSLM.NG.PBS_AUTH_URL = "/public_media/login/";
 PBSLM.NG.PBS_AUTH_REGISTER_URL = "/public_media/register/";
 PBSLM.NG.GOOGLE_AUTH_URL = "/profile/login-national/google-oauth2/";
 PBSLM.NG.FACEBOOK_AUTH_URL = "/profile/login-national/facebook/";
 PBSLM.NG.LOGOUT_URL = "/logout/?next=/";
 PBSLM.NG.STUDENT_AUTH_URL = "/student/signup/?next=/student/";
 PBSLM.NG.GA_PBSLM_PROPERTY_ID = "None";
 PBSLM.NG.IS_SU = false;
 
 PBSLM.NG.MUX_KEY = "6327gbrtf6qvc0sr3gdtlj74f";
 
 
 PBSLM.SENTRY_JS_DSN = "https://ea62268d2e014c92ad2d288f7f2c5f0c@o260369.ingest.sentry.io/1465871";
 PBSLM.NG.CAPTCHA_SITE_KEY = "6Lc0IEsaAAAAAFtF5ZhOptQoGgr2wc7eGdzLEm5P";
 PBSLM.TEMP_FAV_URL = "/tools/favorites/";
 PBSLM.SHOW_VIRGINIA_MODAL = false;
 PBSLM.FORM_SEARCH_ACTION = "/search/";
 
 
 PBSLM.NG.EMBEDDED_PAGE = false;
 PBSLM.NG.CDN = 'https://static.pbslearningmedia.org/';
 
 PBSLM.NG.ERROR_MESSAGE = "";
 
 
 
 
 PBSLM.FEATURE_FLAGS = {
 RECOMMENDATION_ENGINE_SHOW_TO_USERS: false,
 RECOMMENDATION_ENGINE_COLLECT_DATA: false,
 RECOMMENDATION_ENGINE_INTEREST_QUIZ: false
 };
 PBSLM.PRELOADED_ENDPOINTS = JSON.parse('' || '{}');
 </script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/polyfills.js" type="text/javascript"></script><link rel="stylesheet" href="//static.pbslearningmedia.org/static/205.0.0/lm/dist/styles.css"><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/main.js" type="text/javascript"></script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/runtime.js" type="text/javascript"></script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/vendor.js" type="text/javascript"></script><script type="application/ld+json">
 {"@context": "https://schema.org", "@type": "NewsArticle", "author": "NOVA", "datePublished": "2025-04-30 13:52:13", "headline": "Manipulating Reality: Deepfake Videos and Generated Images | NOVA", "publisher": {"@type": "Organization", "name": "NOVA", "logo": {"@context": "http://schema.org", "@type": "ImageObject", "url": "https://static.pbslearningmedia.org/media/entity/NOVA-color.png"}}, "dateModified": "2025-04-30 17:17:17", "description": "Learn how artificial intelligence can generate deepfake images and videos with these video excerpts from NOVA: A.I. Revolution. Use this resource to provide students with opportunities to recognize how generative A.I. technology can impact society and to learn how to minimize its harmful effects.", "mainEntityOfPage": {"@type": "WebPage", "@id": "/resource/nvair-sci-deepfake/manipulating-reality-deepfake-videos-and-generated-images-nova/"}, "image": ["https://static.pbslearningmedia.org/media/assets/Fake_Images_and_Videos-_Past_and_Present-poster.png", "https://static.pbslearningmedia.org/media/assets/How_Deepfakes_and_Image_Generators_Work-poster.png"]}
 </script><script>
 (function(apiKey){
 (function(p,e,n,d,o){var v,w,x,y,z;o=p[d]=p[d]||{};o._q=[];
 v=['initialize','identify','updateOptions','pageLoad'];for(w=0,x=v.length;w<x;++w)(function(m){
 o[m]=o[m]||function(){o._q[m===v[0]?'unshift':'push']([m].concat([].slice.call(arguments,0)));};})(v[w]);
 y=e.createElement(n);y.async=!0;y.src='https://cdn.pendo.io/agent/static/'+apiKey+'/pendo.js';
 z=e.getElementsByTagName(n)[0];z.parentNode.insertBefore(y,z);})(window,document,'script','pendo');
 var initData = {'visitor': {}, 'account': {}};
 
 
 pendo.initialize(initData);
 })('33f33e71-b8a2-4711-57b6-cae11b98c10a');
</script></body></html>

Learn how artificial intelligence can generate deepfake images and videos with these video excerpts from NOVA: A.I. Revolution.

Engineering the Eiffel Tower

<!DOCTYPE html><html lang="en"><head><link rel="preconnect" href="//static.pbslearningmedia.org/" crossorigin><base href="/"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><title>Engineering the Eiffel Tower | NOVA | PBS LearningMedia</title><link rel="canonical" href="https://www.pbslearningmedia.org/resource/nvbtet-sci-eiffeltower/engineering-the-eiffel-tower-nova/"/><meta name="description" content="Investigate the choices of materials and structure in the design of the Eiffel Tower with these video excerpts from NOVA: Building the Eiffel Tower. Use this resource to provide students with opportunities to investigate how engineers met key criteria while designing the Eiffel Tower."><meta name="viewport" content="width=device-width, initial-scale=1"><meta property="fb:pages" content="213237472033241"><meta property="og:type" content="website"/><meta property="og:site_name" content="PBS LearningMedia"/><meta name="twitter:card" content="summary_large_image"/><meta name="twitter:site" content="@PBSLrnMedia"/><meta property="og:title" content="Engineering the Eiffel Tower | NOVA | PBS LearningMedia"/><meta property="og:description" content="Investigate the choices of materials and structure in the design of the Eiffel Tower with these video excerpts from NOVA: Building the Eiffel Tower. Use this resource to provide students with opportunities to investigate how engineers met key criteria while designing the Eiffel Tower."/><meta property="og:image" content="https://image.pbs.org/poster_images/assets/nvbtet-vid-materialeiffel-poster.png"/><meta property="og:url" content="https://www.pbslearningmedia.org/resource/nvbtet-sci-eiffeltower/engineering-the-eiffel-tower-nova/"/><link type="text/css" rel="stylesheet" href="https://static.pbslearningmedia.org/static/lib/fontawesome/font-awesome.css"><script src="https://static.pbslearningmedia.org/static/lib/jquery-3.2.1.min.js"></script><script src="https://static.pbslearningmedia.org/static/lib/js.cookie.min.js"></script><script type="text/javascript" src="//static.pbslearningmedia.org/static/205.0.0/lm/js/utility.js"></script><script>
 window.dataLayer = [];
 
 var org = '';
 
 if(Cookies.get("organization_name")) {
 org = Cookies.get("organization_name");
 }
 
 org = org.replace(/^\"|^\s+|\s+$|\"$/g, '');
 window.dataLayer.push({'dimension1': 'www'}); //contributor station
 // Dimension 2 - Resource Top Level Subjects
 
 // Dimension 3 - Resource Content Project Name
 
 // Dimension 4 - Resource Grade Ranges
 
 window.dataLayer.push({'dimension5': ''}); //user postal code
 window.dataLayer.push({'dimension6': org}); //user organization
 window.dataLayer.push({'dimension7': ''}); //user role
 //user preferred subjects delimited by the '&' sign
 window.dataLayer.push({'dimension8': 'None'});
 window.dataLayer.push({'dimension9': ''}); //user defined grade levels
 //user logged in state
 window.dataLayer.push({'dimension10': 'Not logged in'});
 // Dimension 11 - Resource Brand
 
 // Dimension 12 - Resource Content Type
 
 // Dimension 13 - Resource Organization
 
 // Dimension 14 - Resource Media Type
 
 window.dataLayer.push({'dimension15': ''}); //user school
 // Dimension 16 - Assignment code
 // Dimension 17 - Usage by Schools
 // Dimension 18 - Station
 window.dataLayer.push({'dimension19': 'Teacher'});
 window.dataLayer.push({'dimension20': 'false'});
 // Debug data
 window.dataLayer.push({'dimension22': '-'});
 window.dataLayer.push({'dimension23': '-'});
 window.dataLayer.push({'dimension24': '-'});
 window.dataLayer.push({'dimension25': '-'});
 
 window.dataLayer.push({'dimension26': false});
</script><script>
 window.dataLayer.push({'pbslm-redesign': "yes"});
 </script><script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src=
'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);
})(window,document,'script','dataLayer','GTM-PB2JCH');</script><link href="//static.pbslearningmedia.org/static/205.0.0/station/css/bootstrap-overrides.min.css" type="text/css" rel="stylesheet" /></head><body><noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-PB2JCH"
height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript><app-root id="app-root"><div style="text-align: center; padding: 20px;">Loading...</div></app-root><script src="https://static.pbslearningmedia.org/static/lib/popper.min.js"></script><script src="https://static.pbslearningmedia.org/static/lib/bootstrap.min.js"></script><script>
 (function () {
 if (navigator.appVersion.indexOf('Trident/') > -1){
 
 var child = document.getElementById("app-root");
 child.parentNode.removeChild(child);
 document.title = "PBS LearningMedia not available"
 document.activeElement.innerHTML+='<div style="text-align: center; padding: 20px;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/warning.png" style="width: 60px; margin:20px"/>'+
 'PBS LearningMedia no longer works on Interner Explorer.'+
 'We recommend using one of the following browsers:'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/chrome.png" style="width: 40px;"/>'+
 'Google Chrome'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/safari.png" style="width: 40px;"/>'+
 'Safari'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/mozilla.png" style="width: 40px;"/>'+
 'Mozilla Firefox'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/opera.png" style="width: 40px;"/>'+
 'Opera'+
 '</label>'+
 '<label style="margin: 8px; width:100px; vertical-align: top;">'+
 '<img src="https://static.pbslearningmedia.org/static/assets/edge.png" style="width: 40px;" />'+
 'Microsoft Edge'+
 '</label>'+
 '</div>'
 }
 })();
 PBSLM = window.PBSLM || {};
 PBSLM.NATIONAL_SITE_URL = 'https://www.pbslearningmedia.org/';
 PBSLM.STATIC_URL = '//static.pbslearningmedia.org/static/205.0.0/';
 PBSLM.NG = PBSLM.ng || {};
 PBSLM.NG.VERSION = "205.0.0";
 PBSLM.NG.API_KEY = "0f1b0fae-363c-4693-bc33-7c5dcc01c749";
 PBSLM.NG.IS_AUTHENTICATED = false;
 PBSLM.NG.IS_YOUNG_STUDENT = false;
 PBSLM.NG.IS_STUDENT = false;
 PBSLM.NG.USER_PK = null;
 PBSLM.NG.USER_NAME = "";
 PBSLM.NG.ADMIN_DISPLAY = false;
 PBSLM.NG.FIRST_NAME = "";
 PBSLM.NG.PBS_AUTH_URL = "/public_media/login/";
 PBSLM.NG.PBS_AUTH_REGISTER_URL = "/public_media/register/";
 PBSLM.NG.GOOGLE_AUTH_URL = "/profile/login-national/google-oauth2/";
 PBSLM.NG.FACEBOOK_AUTH_URL = "/profile/login-national/facebook/";
 PBSLM.NG.LOGOUT_URL = "/logout/?next=/";
 PBSLM.NG.STUDENT_AUTH_URL = "/student/signup/?next=/student/";
 PBSLM.NG.GA_PBSLM_PROPERTY_ID = "None";
 PBSLM.NG.IS_SU = false;
 
 PBSLM.NG.MUX_KEY = "6327gbrtf6qvc0sr3gdtlj74f";
 
 
 PBSLM.SENTRY_JS_DSN = "https://ea62268d2e014c92ad2d288f7f2c5f0c@o260369.ingest.sentry.io/1465871";
 PBSLM.NG.CAPTCHA_SITE_KEY = "6Lc0IEsaAAAAAFtF5ZhOptQoGgr2wc7eGdzLEm5P";
 PBSLM.TEMP_FAV_URL = "/tools/favorites/";
 PBSLM.SHOW_VIRGINIA_MODAL = false;
 PBSLM.FORM_SEARCH_ACTION = "/search/";
 
 
 PBSLM.NG.EMBEDDED_PAGE = false;
 PBSLM.NG.CDN = 'https://static.pbslearningmedia.org/';
 
 PBSLM.NG.ERROR_MESSAGE = "";
 
 
 
 
 PBSLM.FEATURE_FLAGS = {
 RECOMMENDATION_ENGINE_SHOW_TO_USERS: false,
 RECOMMENDATION_ENGINE_COLLECT_DATA: false,
 RECOMMENDATION_ENGINE_INTEREST_QUIZ: false
 };
 PBSLM.PRELOADED_ENDPOINTS = JSON.parse('' || '{}');
 </script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/polyfills.js" type="text/javascript"></script><link rel="stylesheet" href="//static.pbslearningmedia.org/static/205.0.0/lm/dist/styles.css"><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/main.js" type="text/javascript"></script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/runtime.js" type="text/javascript"></script><script src="//static.pbslearningmedia.org/static/205.0.0/lm/dist/vendor.js" type="text/javascript"></script><script type="application/ld+json">
 {"@context": "https://schema.org", "@type": "NewsArticle", "author": "NOVA", "datePublished": "2025-04-30 13:51:32", "headline": "Engineering the Eiffel Tower | NOVA", "publisher": {"@type": "Organization", "name": "NOVA", "logo": {"@context": "http://schema.org", "@type": "ImageObject", "url": "https://static.pbslearningmedia.org/media/entity/NOVA-color.png"}}, "dateModified": "2025-04-30 17:12:40", "description": "Investigate the choices of materials and structure in the design of the Eiffel Tower with these video excerpts from NOVA:\u00a0Building the Eiffel Tower. Use this resource to provide students with opportunities to investigate how engineers met key criteria while designing the Eiffel Tower.", "mainEntityOfPage": {"@type": "WebPage", "@id": "/resource/nvbtet-sci-eiffeltower/engineering-the-eiffel-tower-nova/"}, "image": ["https://static.pbslearningmedia.org/media/assets/nvbtet-vid-materialeiffel-poster.png", "https://static.pbslearningmedia.org/media/assets/nvbtet-vid-windeiffel-poster.png"]}
 </script><script>
 (function(apiKey){
 (function(p,e,n,d,o){var v,w,x,y,z;o=p[d]=p[d]||{};o._q=[];
 v=['initialize','identify','updateOptions','pageLoad'];for(w=0,x=v.length;w<x;++w)(function(m){
 o[m]=o[m]||function(){o._q[m===v[0]?'unshift':'push']([m].concat([].slice.call(arguments,0)));};})(v[w]);
 y=e.createElement(n);y.async=!0;y.src='https://cdn.pendo.io/agent/static/'+apiKey+'/pendo.js';
 z=e.getElementsByTagName(n)[0];z.parentNode.insertBefore(y,z);})(window,document,'script','pendo');
 var initData = {'visitor': {}, 'account': {}};
 
 
 pendo.initialize(initData);
 })('33f33e71-b8a2-4711-57b6-cae11b98c10a');
</script></body></html>

Investigate the choices of materials and structure in the design of the Eiffel Tower with these video excerpts from NOVA: Building the Eiffel Tower.

US, US Territories, Canada

Computer algorithm displayed in a hospital corridor

When Machines Prescribe

Investigate medical algorithms in which the patient’s race drives decisions.
Doctors rely on computer programs to make decisions about diagnosis and treatment. Designed to weigh factors like symptoms, medical history, and test results to achieve the best possible outcomes for patients, some common medical algorithms were built using data based on old pseudoscience about racial differences. Investigate how their continued use has harmed the health of Black patients.
When Machines PrescribePublished: April 30, 2025NARRATOR: We routinely depend on doctors and medical institutions for our health, but what if some guidelines used to diagnose and treat patients were based on bad science, resulting in actual harm?In 2022, Gregory Mumford learned from his doctor he had a kidney problem.GREGORY MUMFORD: He says my kidney function was lowering, little by little. That got me a little concerned. I said, “Oh, what’s that about? Why is it doing that?”He said, “We might have to make some changes. We might have to put you on dialysis for a while.”NARRATOR: The kidneys’ critical job is removing waste materials from the blood.A dialysis machine would have to do the work of Gregory’s kidneys, cleansing the blood before sending it back to his body.PIPIER SMITH-MUMFORD: What was really challenging was how does he get a transplant? That was the goal, not to be on dialysis, but to get a more permanent solution.NARRATOR: For decisions like who should get a kidney transplant, doctors across many medical fields routinely use calculations that combine a patient’s medical history with additional data. These calculations are called “clinical algorithms.”MICHELLE MORSE, M.D. (Acting Commissioner, New York City Health Department): A clinical algorithm is a tool that clinicians would use to really best understand their patient’s specific diagnosis or treatment.NARRATOR: According to the clinical algorithm that Gregory’s doctors used, if Gregory had the same test results but was white, he would’ve immediately qualified for a kidney transplant evaluation. But why would race be a variable in determining kidney function?MICHELLE MORSE: There should be no reason why the physiological function of someone who’s Black would look different than the physiological function of someone who’s white.NARRATOR: For centuries, western medicine held that Black people were less sensitive to pain and had lower lung capacity and denser muscle mass. Science has shown these assertions to be baseless, but that doesn’t mean they’ve been erased from modern medicine.SHAZIA SIDDIQUE, M.D. (Gastroenterologist and Health Services Researcher, University of Pennsylvania Perelman School of Medicine): Most of us, as clinicians, are taught in medical school that race is a biologic variable, and the problem is that it takes active effort to undo a lot of that teaching.NARRATOR: In many places, those efforts have begun.DARSHALI VYAS, M.D. (Fellow in Pulmonary &amp; Critical Care, MGH-BIDMC Harvard): I began medical school in 2015. We got the message loud and clear in the classroom that race is a social construct, that it’s not meant to be used as a construct or proxy for biological difference.MICHELLE MORSE: The tipping point for that understanding was the completion of the Human Genome Project that showed that there was more racial difference, genetically, within races than between races.NARRATOR: In 2003, the Human Genome Project successfully sequenced the nearly three-billion base pairs of D.N.A. in the human genome.MICHELLE MORSE: It’s really in more recent decades that there’s been broader agreements that race is not biological and that it is actually a social classification.DARSHALI VYAS: But as we made that transition, gradually, from the classroom to going to the wards and starting to see clinical medicine, we noticed a real tension between how we were taught about race and how we were seeing it being used by physicians and by our supervisors.NARRATOR: Medical students’ questions about the use of race in decision-making would soon spark a national controversy.MELANIE HOENIG (Nephrologist, Beth Israel Deaconess Medical Center): In 2016, I’m at Harvard Medical School. And so, the very first week of my new course, we are explaining about estimated G.F.R.NARRATOR: G.F.R., or “glomerular filtration rate,” refers to how much work the kidneys are doing. Estimated G.F.R., or e.G.F.R., was the algorithm that nephrologists, or kidney doctors, used to calculate Gregory Mumford’s kidney function.MELANIE HOENIG: And one of my students raised his hand and said, “Wait a second. Why would you have a formula that provides a healthier value to the individuals at greatest risk of kidney disease?” I mean, I still remember that moment, because he was exactly right.NARRATOR: A higher rate of kidney disease among Black Americans is largely attributed to social and environmental factors, like access to health care and poverty.MARTHA PAVLAKIS, M.D. (Transplant Nephrologist, Beth Israel Deaconess Medical Center): You’re telling us that Black patients have a higher prevalence, a higher incidence of kidney disease, and yet the formula makes them look like they have better kidney function for the same blood test as a non-African-American patient. How does that make sense?”NARRATOR: Before 1999, doctors were searching for a reliable alternative to the complex, expensive process of measuring kidney function, or G.F.R. They wanted an estimate.MARTHA PAVLAKIS: So, we came up with this notion of estimated G.F.R.NARRATOR: Essential to the e.G.F.R. calculation was creatinine, a waste product created by protein digestion and the normal breakdown of muscle tissue. High creatinine levels in the blood are usually an indicator of poor kidney function.MARTHA PAVLAKIS: In 1999, what they had found was that in the handful of patients that they looked at, the Black patients actually had a higher creatinine for the same G.F.R. as the white patients.NARRATOR: Researchers assumed higher creatinine levels in the small sample of Black patients was due to their naturally “greater muscle mass.”AMAKA ENEANYA, M.D. (Nephrologist and Chief Transformation Officer, Emory Healthcare): Where that science comes from, really, goes back to slavery and how Black bodies were assumed to be different. Skulls were a different size, bones were thicker, lung capacity was different amongst Black slaves, based on absolutely no science, “pseudoscience,” as they call it.NARRATOR: Other factors that might increase creatinine, like diet, medications or dehydration had not been considered.AMAKA ENEANYA: There’s been no study to date that has ever proven that Black individuals, just by being Black, have more muscle mass than any other race.NARRATOR: Nonetheless, a corrective race factor was added to the equation to account for higher creatinine levels and supposedly greater muscle mass. Now, instead of showing the true function of their kidneys, the equation calculated that Black patients’ kidneys were healthier than they really were.GREGORY MUMFORD: I was told that it takes three to four years to, you know, be on the list for three or four years, before you’re even considered to get a kidney. I got depressed with that.MELANIE HOENIG: It was just shocking how long most of us in the field had accepted the formula without questioning.And so, after, when I met with students, I said, “You know what? We could change this. Why don’t we just change it?”So, that’s what we set out to do.NARRATOR: Eleven months later, in 2017, Beth Israel Deaconess Hospital, in Boston, became the first medical institution in the country to remove the race variable from the e.G.F.R. calculation.Medical students pressured hospitals across the country to drop e.G.F.R.’s race factor, but the majority of hospitals didn’t update their e.G.F.R. equation and the algorithm continued to deny many Black patients access to kidney transplants.AMAKA ENEANYA: So, I had a family member that was diagnosed with advanced chronic kidney disease. I was told that he would not be listed for a kidney transplant because his e.G.F.R.was too high.NARRATOR: In 2019, Dr. Amaka Eneanya published a paper on the harmful consequences of using a race-correction factor in the e.G.F.R. equation.AMAKA ENEANYA: I went to the science. I picked apart that statistical equation. I picked apart the performance metrics used to assess equations.NARRATOR: Her findings added to a growing firestorm.COMMENTATOR: Critical race theory has now come to medical school.AMAKA ENEANYA: I received the most resistance from my fellow nephrologists, to be honest.MARTHA PAVLAKIS: The pushback was, “Just because you don’t like it, doesn’t mean it’s not true. It is data-driven, it’s research-based. It’s what we’ve been doing. How could it be so wrong?” It suggests that what you’ve been doing for years had a negative impact on Black patients in this country. That’s a very painful thing for physicians to contemplate.PROTESTORS: No justice, no peace!AMAKA ENEANYA: Collectively, we became seen as the “woke” movement and that we were anti-science.NARRATOR: But, in fact, the problem turned out to be much bigger than the e.G.F.R. algorithm.DARSHALI VYAS: Over time, as we got further along in our clinical training, we realized how many more examples there are of race-based correction or race-based guidelines. It was everywhere.NARRATOR: Guidelines for treating high blood pressure advised different medications for Black patients. The Osteoporosis Risk Score added 5 points for non-Black patients, implying Black people were at far lower risk for this disease. The “vaginal birth after cesarean: or V.B.A.C. calculator assumed that Black and Hispanic women were less likely to have a successful vaginal birth after a cesarean section.In 2020, Dr. Darshali Vyas and colleagues investigated these and other race-based algorithms, along with the original studies they were based on.DARSHALI VYAS: A lot of those studies do originate in the antebellum period to validate, and to continue the enslavement of Black people at that time.MICHELLE MORSE: So, there were all of these algorithms hidden in plain sight, that I used every day as a doctor, that unfortunately misused race or used race in a way that essentially normalized or exacerbated racial inequities and health outcomes.NARRATOR: That year, Dr. Michelle Morse was a health policy fellow for the House Committee on Ways and Means. When she shared Dr. Vyas’s paper with committee members, serious questions followed. Medical associations across the country were instructed to report to the committee on their use of race-based clinical tools.Meanwhile, for Gregory and Pipier, time was running out.PIPIER MUMFORD: So, I’m reaching out to family and friends in a letter that I’d written for both of us that says, “Gregory needs a kidney transplant, and we’re trying to find someone who’d be willing to be a donor.”NARRATOR: The desperate couple had no idea help was on its way.MARTHA PAVLAKIS: So, the National Kidney Foundation and the American Society of Nephrology formed a task force and, eventually, dropped the race variable completely.But, as that was happening, I was actually the vice chair of the Kidney Transplantation Committee for the Nationwide Organ Procurement Transplant Network. I proposed that we actually change the wording of national policy that race could not be used in the kidney function estimate for access to the transplant list.AMAKA ENEANYA: None of the 240 or so transplant centers could use a race-based e.G.F.R. equation for listing. Mandatory.NARRATOR: And there was more. The country’s transplant programs would now review their kidney transplant lists with a new race-neutral e.G.F.R. algorithm. The result: more than 14,000 Black American kidney patients saw their transplant waiting time modified, reflecting the true severity of their kidney disease.KIDNEY TRANSPLANT PATIENT: I’m in the hospital getting ready for my transplant.AMAKA ENEANYA: And to see people tag me in social media, make videos, crying.KIDNEY TRANSPLANT PATIENT 2: Kidney right now is operating well.AMAKA ENEANYA: My family member received 18 months back on the waitlist. That, words can’t describe. I mean, it made all of this worth it.NARRATOR: Instead of a three to four year wait, Gregory Mumford’s kidney transplant came after just a few months.GREGORY MUMFORD: When they changed it, and they said, “Your name jumped right to the top of the list.” So, a lot of people got kidneys because of that change.PIPIER MUMFORD: So, this is a picture that we laugh about because it’s, on the one hand, kind of funny. On the other hand, but it’s, like, so serious. But it’s a way to lighten up such a serious thing.SHAZIA SIDDIQUE: I truly believe that we genuinely don’t know how many race-based algorithms are out there. Many of the algorithms that are being utilized, unfortunately, are not transparent. And so, we’re unable to vet them.DARSHALI VYAS: I strongly believe that we should continue to study race and its effects on healthcare and how it affects outcomes of our patients.MICHELLE MORSE: We need to have standards on how race and ethnicity should be used and should not be used in clinical algorithms.DARSHALI VYAS: It’s not about being woke or not being woke, it’s about making sure that our tools are safe and accurate and do the best job at taking care of our patient.

Investigate medical algorithms in which the patient’s race drives decisions.

These Smart Glasses Know Who You Are, and Much More

Two students created glasses that can identify people on the street, without them knowing.
The facial recognition glasses can pull personal information, like and phone number and even home address from existing online databases.
These Smart Glasses Know Who You Are, and Much MorePublished: April 17, 2025Caine Ardayfio: Oh, hi, ma&#x27;am. Wait, are you (beep)?Person #1 at a train station: Yes.Caine Ardayfio: Oh, okay. I think I met you through like the Cambridge Community Foundation, right?Person #1 at a train station: Oh, yeah.Caine Ardayfio: Yeah, yeah, it&#x27;s great...Narrator: What if you could immediately know the name and personal details of any stranger you passed on the street?Two undergraduate college students developed a tool that can pull sensitive personal information, like home addresses and phone numbers, from existing databases just by using a person&#x27;s face, and without that person even knowing it&#x27;s happening.AnhPhu Nguyen and Caine Ardayfio are students at Harvard University. They set out to build facial recognition glasses using these smart glasses built by Meta, the parent company of social media sites like Facebook and Instagram. Basically, they wanted to be able to put on the glasses, look at a random person, and identify who they were.After just four days of coding, they had a working prototype and were trying it on students around campus. Even on strangers at a train station.AnhPhu Nguyen: Are you the person working on like minority stuff for like Muslims in India at all, or something?Person #2 at a train station: That&#x27;s me, yeah.AnhPhu Nguyen: Really?Person #1 at a train station: Yeah.AnhPhu Nguyen: Are you (beep)?Person #1 at a train station: Yes.AnhPhu Nguyen: Oh, I&#x27;ve read your work before, it&#x27;s super cool.Narrator: Here&#x27;s how it works. Once AnhPhu or Caine puts on these glasses, an LED light turns on to indicate they&#x27;re recording, and they start to live stream the video feed to Instagram. Then a bot they built takes screenshots of the video and scans a facial recognition library, looking for a face.AnhPhu Nguyen: Once you look at someone, it puts the face into this database that returns links to where that person appears online.Narrator: That database is called PimEyes; a facial recognition search engine that scours the internet to find websites where that face shows up.AnhPhu Nguyen: We use some large language models to scrape those websites, all the information, and then guess who it might be on those websites.Narrator: A large language model, or LLM, is a type of artificial intelligence, like ChatGPT, that can understand and summarize data into text that&#x27;s similar to how humans speak. The LLM suggests a name to match the face, and then that name is used to find more information.Caine Ardayfio: And then it would put it through a bunch of databases to try to figure out like home address, job, what they enjoy doing, that type of thing.Narrator: And then all of that information, the photos, names, address, and interest, gets sent to their phone. From beginning to end, this takes about 90 seconds. AnhPhu and Caine use the free versions of these databases, but they say if they had unlimited access, they could have gotten results in just a few seconds.The project raises a lot of ethical questions, but it&#x27;s not illegal. Some states, like Massachusetts, do have stringent rules that restrict how the government can use facial recognition technology, but that is not the norm across the country.And the databases themselves can also impose limits. Once the project went public, PimEyes removed AnhPhu and Caine&#x27;s access, because they say the students violated the site&#x27;s terms of service by uploading photos of people without their permission. But AnhPhu and Caine&#x27;s goal isn&#x27;t for this to be used, it&#x27;s to show that we&#x27;re already vulnerable to this kind of technology.AnhPhu Nguyen: We basically exposed the fact that you can go on the street and pull all of this data. It was simply like a technical demonstration.Narrator: In a Google Doc accompanying their video, they encourage and instruct people to remove personal information from databases that contain details, like addresses and even the names of relatives.Caine Ardayfio: All of these databases that we use, they have opt-out systems where you can just go onto their website, verify your identity, and then you&#x27;re completely scrubbed from those databases.Narrator: Facial recognition software already exists, like the kind used to verify your identity when you&#x27;re going through a airport security, or to unlock your iPhone, and similar facial recognition technology is being used by some law enforcement agencies, both at the federal, state, and local levels to identify individuals and support criminal investigations. Though a few cities like San Francisco, Boston, and Portland, Oregon have lost specifically prohibiting city officials, like police departments, from using facial recognition systems.But AnhPhu and Caine showed private citizens can also use facial recognition software to identify strangers. They don&#x27;t plan to take this project any further, instead, they started working with data privacy advocacy groups. As engineers, they say they&#x27;ve done their job to bring awareness and show that this is possible.As facial recognition technology continues to advance, questions about data privacy and security will continue to arise, and many may start to use this technology for more than just a demonstration.

Two students created glasses that can identify people on the street, without them knowing.

Ultimate Crash Test

In this two-part special, a first-of-its-kind staged pileup sheds new light on car safety.
What really happens in a multi-vehicle pileup? Surprisingly little is known about the behavior of cars and drivers in uncontrolled, real-world accidents. In this two-part special, go behind the scenes as scientists design a first-of-its-kind experiment to test a large-scale crash. The plan is for eight drivers to drive eight different types of cars by remote control at 70 mph down a hazardous roadway. They only have one shot. Then, follow scientists, engineers, and accident investigators as they analyze a treasure trove of data – more than they’ve ever been able to work with before. See what they find, and discover insights about driver behavior and vehicle design that could save lives. (A two-part series premiering May 7 and May 14 at 9 pm on PBS.)

In this two-part special, a first-of-its-kind staged pileup sheds new light on car safety.

Topic: Tech & Engineering

Hero Feature