Tu\u1ea7n tr\u01b0\u1edbc, t\u00f4i tham d\u1ef1 m\u1ed9t cu\u1ed9c h\u1ed9i ngh\u1ecb c\u00f4ng ngh\u1ec7 t\u1ea1i Detroit, c\u1ef1u “th\u1ee7 \u0111\u00f4 \u00f4 t\u00f4 c\u1ee7a th\u1ebf gi\u1edbi.” Qua m\u1ed9t tr\u0103m n\u0103m, Henry Ford x\u00e2y d\u1ef1ng \u0111\u1ebf ch\u1ebf \u00f4 t\u00f4 c\u1ee7a m\u00ecnh \u1edf \u0111\u00e2y v\u1edbi kh\u00e1i ni\u1ec7m v\u1ec1 d\u00e2y chuy\u1ec1n l\u1eafp r\u00e1p v\u00e0 s\u1ea3n xu\u1ea5t s\u1ed1 l\u1edbn. Trong “th\u1eddi \u0111\u1ea1i v\u00e0ng” n\u00e0y c\u1ee7a c\u00e1ch m\u1ea1ng c\u00f4ng nghi\u1ec7p, nhi\u1ec1u c\u00f4ng ti \u00f4 t\u00f4 v\u00e0 c\u01a1 x\u01b0\u1edfng \u0111\u00e3 \u0111\u01b0\u1ee3c t\u1ea1o ra, \u0111i\u1ec1u \u0111\u01b0a t\u1edbi nhu c\u1ea7u cao v\u1ec1 c\u00f4ng nh\u00e2n lao \u0111\u1ed9ng. Nhi\u1ec1u n\u00f4ng d\u00e2n b\u1ecf n\u00f4ng tr\u1ea1i, chuy\u1ec3n t\u1edbi c\u00e1c th\u00e0nh ph\u1ed1 \u0111\u1ec3 t\u00ecm vi\u1ec7c l\u00e0m t\u1ed1t h\u01a1n. Nhu c\u1ea7u v\u1ec1 c\u00f4ng nh\u00e2n lao \u0111\u1ed9ng ti\u1ebfp t\u1ee5c d\u00e2ng l\u00ean, v\u00e0 nhi\u1ec1u c\u00f4ng ti ph\u1ea3i “nh\u1eadp kh\u1ea9u” c\u00f4ng nh\u00e2n lao \u0111\u1ed9ng t\u1eeb ch\u00e2u \u00c2u. Gi\u1eefa n\u0103m 1900 v\u00e0 1930, s\u1ed1 c\u00f4ng nh\u00e2n \u0111\u00e3 t\u0103ng v\u1ecdt t\u1eeb 300,00 l\u00ean tr\u00ean 1.8 tri\u1ec7u. Vi\u1ec7c d\u00e2ng l\u00ean c\u1ee7a \u00f4 t\u00f4 y\u00eau c\u1ea7u nhi\u1ec1u x\u00e2y d\u1ef1ng h\u01a1n \u0111\u1ec3 c\u00f3 v\u1eadn t\u1ea3i t\u1ed1t h\u01a1n \u1edf M\u0129, \u0111i\u1ec1u d\u1eabn t\u1edbi vi\u1ec7c thi\u1ebfu h\u1ee5t lao \u0111\u1ed9ng kh\u00e1c v\u1ec1 c\u00f4ng nh\u00e2n x\u00e2y \u0111\u01b0\u1eddng, xa l\u1ed9, \u0111\u01b0\u1eddng cao t\u1ed1c v\u00e0 c\u00e1c k\u1ebft c\u1ea5u n\u1ec1n kh\u00e1c. Khi c\u00f4ng nh\u00e2n lao \u0111\u1ed9ng ch\u00e2u \u00c2u di c\u01b0 sang M\u0129 v\u00ec vi\u1ec7c l\u00e0m t\u1ed1t h\u01a1n, cu\u1ed9c s\u1ed1ng t\u1ed1t h\u01a1n, n\u1ec1n kinh t\u1ebf b\u00f9ng ph\u00e1t v\u1edbi nhi\u1ec1u vi\u1ec7c l\u00e0m h\u01a1n v\u00e0 th\u1ecbnh v\u01b0\u1ee3ng.<\/p>\n
Trong b\u1ed1n m\u01b0\u01a1i n\u0103m, m\u1ecdi th\u1ee9 \u0111\u00e3 thay \u0111\u1ed5i. Xe h\u01a1i c\u1ee7a \u0110\u1ee9c v\u00e0 Nh\u1eadt b\u1eaft \u0111\u1ea7u c\u1ea1nh tranh th\u00e0nh c\u00f4ng v\u1edbi xe h\u01a1i c\u1ee7a M\u0129. \u0110\u1ec3 v\u1eabn c\u00f2n t\u00ednh c\u1ea1nh tranh, nhi\u1ec1u c\u00f4ng ti ph\u1ea3i gi\u1ea3m chi ph\u00ed x\u00e2y d\u1ef1ng xe h\u01a1i b\u1eb1ng vi\u1ec7c chuy\u1ec3n c\u01a1 x\u01b0\u1edfng sang c\u00e1c n\u01b0\u1edbc c\u00f3 chi ph\u00ed th\u1ea5p h\u01a1n nh\u01b0 Trung Qu\u1ed1c, \u1ea4n \u0110\u1ed9 hay Th\u00e1i Lan, v.v. C\u00f4ng nh\u00e2n c\u00f3 vi\u1ec7c l\u00e0m trong c\u01a1 x\u01b0\u1edfng \u00f4 t\u00f4 \u0111\u1ed9t nhi\u00ean bi\u1ebft r\u1eb1ng h\u1ecd kh\u00f4ng c\u00f2n c\u00f3 vi\u1ec7c l\u00e0m n\u1eefa. Tuy nhi\u00ean, c\u1ea1nh tranh trong th\u1ecb tr\u01b0\u1eddng \u00f4 t\u00f4 l\u00e0 d\u1eef d\u1ed9i, nhi\u1ec1u c\u00f4ng ti ch\u1eadm thay \u0111\u1ed5i v\u00e0 kh\u00f4ng th\u1ec3 c\u1ea1nh tranh \u0111\u01b0\u1ee3c \u0111\u00e3 ph\u1ea3i n\u1ed9p \u0111\u01a1n xin ph\u00e1 s\u1ea3n. T\u1eeb tr\u00ean hai m\u01b0\u01a1i c\u00f4ng ti \u00f4 t\u00f4 trong qu\u00e1 kh\u1ee9, gi\u1edd Detroit ch\u1ec9 c\u00f3 ba c\u00f4ng ti c\u00f2n s\u1ed1ng s\u00f3t – GM, Ford, v\u00e0 Chrysler. Th\u00e0nh ph\u1ed1 ph\u00e1t \u0111\u1ea1t \u0111\u1ed9t nhi\u00ean r\u01a1i v\u00e0o s\u00fat gi\u1ea3m. C\u00f4ng nh\u00e2n c\u01a1 x\u01b0\u1edfng b\u1ecb cho\u00e1ng v\u00ec chu\u1ea9n s\u1ed1ng c\u1ee7a h\u1ecd bi\u1ebfn m\u1ea5t c\u00f9ng vi\u1ec7c l\u00e0m c\u1ee7a h\u1ecd. H\u00e0ng tr\u0103m ngh\u00ecn c\u00f4ng nh\u00e2n c\u01a1 x\u01b0\u1edfng m\u1ea5t vi\u1ec7c l\u00e0m c\u1ee7a h\u1ecd ch\u1ec9 trong v\u00e0i n\u0103m ng\u1eafn ng\u1ee7i.<\/p>\n
Tu\u1ea7n tr\u01b0\u1edbc, khi t\u00f4i l\u00e1i xe qua th\u00e0nh ph\u1ed1 n\u00e0y, t\u00f4i th\u1ea5y nhi\u1ec1u to\u00e0 nh\u00e0 tr\u1ed1ng r\u1ed7ng kh\u00f4ng c\u00f3 ng\u01b0\u1eddi \u1edf v\u00e0 nhi\u1ec1u nh\u00e0 rao b\u00e1n m\u00e0 kh\u00f4ng c\u00f3 ng\u01b0\u1eddi mua. B\u1ea1n t\u00f4i ng\u01b0\u1eddi \u0111i c\u00f9ng v\u1edbi t\u00f4i than: “N\u00f3 l\u00e0 th\u00e0nh ph\u1ed1 bu\u1ed3n, ngo\u1ea1i tr\u1eeb khu trung t\u00e2m, m\u1ecdi n\u01a1i \u0111\u1ec1u c\u00f3 v\u1ebb gi\u1ed1ng nh\u01b0 ch\u1ed7 b\u1ecf hoang.” T\u00f4i b\u1ea3o anh \u1ea5y: “\u0110i\u1ec1u \u0111\u00e3 x\u1ea3y ra \u1edf \u0111\u00e2y ch\u1ec9 l\u00e0 b\u1eaft \u0111\u1ea7u, ch\u00fang ta s\u1ebd th\u1ea5y c\u00f9ng \u0111i\u1ec1u n\u00e0y x\u1ea3y ra \u1edf c\u00e1c n\u01b0\u1edbc kh\u00e1c khi t\u1ef1 \u0111\u1ed9ng v\u00e0 robot \u0111ang l\u1ea5y \u0111i nhi\u1ec1u vi\u1ec7c l\u00e0m c\u1ee7a m\u1ecdi ng\u01b0\u1eddi.”<\/p>\n
Trong cu\u1ed9c h\u1ed9i ngh\u1ecb v\u1ec1 c\u00f4ng ngh\u1ec7 th\u00f4ng tin, nhi\u1ec1u nh\u00e0 khoa h\u1ecdc chia s\u1ebb nghi\u00ean c\u1ee9u c\u1ee7a h\u1ecd v\u1ec1 nh\u1eefng c\u00f4ng ngh\u1ec7 m\u1edbi nh\u01b0 “H\u1ecdc s\u00e2u;” “Big Data;” “Internet m\u1ecdi v\u1eadt;” “Th\u1ef1c t\u1ea1i \u1ea3o v\u00e0 th\u1ef1c t\u1ea1i gia t\u0103ng,” v.v. Nh\u01b0ng t\u00f4i quan t\u00e2m t\u00f3i c\u00e1c b\u00e0i tr\u00ecnh b\u00e0y v\u1ec1 vi\u1ec7c l\u00e0m m\u00e0 c\u00f3 th\u1ec3 b\u1ecb \u1ea3nh h\u01b0\u1edfng b\u1edfi c\u00f4ng ngh\u1ec7.\u00a0 Di\u1ec5n gi\u1ea3 ch\u00ednh, m\u1ed9t nh\u00e0 kinh t\u1ebf n\u1ed5i ti\u1ebfng, n\u00f3i v\u1edbi th\u00ednh gi\u1ea3 r\u1eb1ng \u00f4ng \u1ea5y tin robot v\u00e0 t\u1ef1 \u0111\u1ed9ng c\u00f3 th\u1ec3 thay th\u1ebf qu\u00e3ng 47% vi\u1ec7c l\u00e0m c\u1ee7a M\u0129 trong m\u01b0\u1eddi n\u0103m, nh\u01b0ng 82% vi\u1ec7c l\u00e0m \u1edf c\u00e1c n\u01b0\u1edbc kh\u00e1c, ch\u1ee7 y\u1ebfu l\u00e0 vi\u1ec7c l\u00e0m lao \u0111\u1ed9ng, s\u1ebd c\u00f3 nguy c\u01a1 cao h\u01a1n v\u00e0 c\u00f3 th\u1ec3 m\u1ea5t \u0111i trong n\u0103m n\u0103m n\u1eefa. \u00d4ng \u1ea5y h\u1ecfi: “V\u00ec ch\u1ed7 l\u00e0m vi\u1ec7c c\u1ee7a t\u01b0\u01a1ng lai g\u1ea7n s\u1ebd kh\u00e1c xa v\u1edbi t\u00ecnh tr\u1ea1ng hi\u1ec7n t\u1ea1i. Bao nhi\u00eau ng\u01b0\u1eddi \u0111ang l\u00e0m c\u00e1c b\u01b0\u1edbc chu\u1ea9n b\u1ecb cho thay \u0111\u1ed5i kh\u00f4ng tr\u00e1nh kh\u1ecfi n\u00e0y? Bao nhi\u00eau ng\u01b0\u1eddi bi\u1ebft v\u1ec1 cu\u1ed9c kh\u1ee7ng ho\u1ea3ng “s\u1eafp x\u1ea3y ra” n\u00e0y? Bao nhi\u00eau ng\u01b0\u1eddi l\u00e3nh \u0111\u1ea1o \u0111ang chu\u1ea9n b\u1ecb cho th\u1ea3m ho\u1ea1 n\u00e0y \u1edf n\u01b0\u1edbc h\u1ecd?”<\/p>\n
Trong nhi\u1ec1u n\u0103m, t\u00f4i \u0111\u00e3 vi\u1ebft v\u1ec1 to\u00e0n c\u1ea7u ho\u00e1, kho\u00e1n ngo\u00e0i, c\u00f4ng ngh\u1ec7 m\u1edbi n\u1ed5i l\u00ean, v\u00e0 c\u00e1ch nh\u1eefng y\u1ebfu t\u1ed1 n\u00e0y c\u00f3 th\u1ec3 t\u00e1c \u0111\u1ed9ng l\u00ean m\u1ecdi ng\u00e0nh c\u00f4ng nghi\u1ec7p v\u00e0 c\u00e1c n\u01b0\u1edbc. Vi\u1ec7c l\u00e0m truy\u1ec1n th\u1ed1ng n\u01a1i c\u00f4ng nh\u00e2n c\u00f3 th\u1ec3 l\u00e0m vi\u1ec7c trong c\u1ea3 \u0111\u1eddi h\u1ecdc gi\u1edd m\u1ea5t r\u1ed3i. M\u1ecdi c\u00f4ng nh\u00e2n \u0111\u1ec1u ph\u1ea3i h\u1ecdc c\u00e1ch th\u00edch nghi v\u1edbi n\u1ec1n kinh t\u1ebf to\u00e0n c\u1ea7u \u0111ang ti\u1ebfn ho\u00e1 v\u00ec n\u00f3 s\u1ebd x\u1ea3y ra r\u1ea5t ch\u00f3ng. \u0110i\u1ec1u quan tr\u1ecdng l\u00e0 m\u1ecdi ng\u01b0\u1eddi ph\u1ea3i li\u00ean t\u1ee5c h\u1ecdc k\u0129 n\u0103ng m\u1edbi \u0111\u1ec3 \u0111\u1ea3m b\u1ea3o an ninh cho ngh\u1ec1 nghi\u1ec7p c\u1ee7a h\u1ecd v\u00ec kh\u00f4ng c\u00f3 vi\u1ec7c l\u00e0m an ninh n\u1eefa.<\/p>\n
Sau khi quay l\u1ea1i Carnegie Mellon, t\u00f4i k\u1ec3 cho sinh vi\u00ean c\u1ee7a t\u00f4i v\u1ec1 tr\u1ea3i nghi\u1ec7m c\u1ee7a t\u00f4i \u1edf Detroit v\u00e0 cu\u1ed9c h\u1ed9i ngh\u1ecb: “Trong khi v\u00e0o \u0111\u1ea1i h\u1ecdc v\u00e0 ki\u1ebfm m\u1ea3nh b\u1eb1ng l\u00e0 quan tr\u1ecdng, nh\u01b0ng s\u1ef1 ki\u1ec7n l\u00e0 ph\u1ea7n l\u1edbn vi\u1ec7c h\u1ecdc c\u1ee7a c\u00e1c em s\u1ebd x\u1ea3y ra trong khi c\u00e1c em \u0111ang l\u00e0m vi\u1ec7c tr\u00ean m\u1ed9t vi\u1ec7c l\u00e0m. L\u00e0 sinh vi\u00ean, c\u00e1c em ph\u1ea3i h\u1ecdc “C\u00e1ch h\u1ecdc nhanh” v\u00e0 ph\u00e1t tri\u1ec3n th\u00f3i quen “H\u1ecdc c\u1ea3 \u0111\u1eddi” n\u1ebfu c\u00e1c em mu\u1ed1n gi\u1eef \u0111\u01b0\u1ee3c vi\u1ec7c l\u00e0m c\u1ee7a c\u00e1c em. Cho d\u00f9 c\u00f3 vi\u1ec7c l\u00e0m t\u1ed1t, c\u00e1c em s\u1ebd c\u1ea7n li\u00ean t\u1ee5c h\u1ecdc k\u0129 n\u0103ng m\u1edbi b\u1eb1ng vi\u1ec7c ghi danh v\u00e0o C\u00e1c m\u00f4n h\u1ecdc tr\u1ef1c tuy\u1ebfn m\u1edf cho \u0111\u1ea1i ch\u00fang Massive Open Online Courses (MOOCs). Ph\u1ea7n l\u1edbn c\u00e1c em \u0111\u1ec1u l\u00e0 sinh vi\u00ean k\u0129 thu\u1eadt nh\u01b0ng \u0111\u1eebng gi\u1edbi h\u1ea1n b\u1ea3n th\u00e2n c\u00e1c em v\u00e0 l\u0129nh v\u1ef1c n\u00e0y. C\u00e1c em c\u1ea7n m\u1edf v\u1edbi nh\u1eefng \u00fd t\u01b0\u1edfng m\u1edbi v\u00e0 tham gia v\u00e0o c\u00e1c d\u1ef1 \u00e1n \u0111a d\u1ea1ng, t\u00ecm ra c\u01a1 h\u1ed9i \u0111\u1ec3 h\u1ecdc c\u00e1i g\u00ec \u0111\u00f3 m\u1edbi. Ng\u01b0\u1eddi th\u00e0nh c\u00f4ng bao gi\u1edd c\u0169ng c\u1ed1 g\u1eafng g\u1eb7p g\u1ee1 v\u00e0 l\u00e0m b\u1ea1n v\u1edbi ng\u01b0\u1eddi kh\u00e1c gi\u1ecfi h\u01a1n v\u00e0 th\u00f4ng minh h\u01a1n \u0111\u1ec3 h\u1ecdc nh\u1eefng k\u0129 n\u0103ng m\u1edbi, x\u00e2y d\u1ef1ng tri th\u1ee9c, v\u00e0 t\u00ecm c\u01a1 h\u1ed9i m\u1edbi. V\u1ea5n \u0111\u1ec1 tu\u1ef3 \u1edf c\u00e1c em ti\u1ebfp t\u1ee5c ph\u00e1t tri\u1ec3n chuy\u00ean nghi\u1ec7p c\u1ee7a c\u00e1c em v\u00e0 chu\u1ea9n b\u1ecb cho b\u1ea3n th\u00e2n c\u00e1c em v\u1ec1 ch\u1ed7 l\u00e0m vi\u1ec7c c\u1ee7a ng\u00e0y mai. Kh\u00f4ng th\u00e0nh v\u1ea5n \u0111\u1ec1 li\u1ec7u vi\u1ec7c l\u00e0m c\u1ee7a c\u00e1c em c\u00f3 th\u1ec3 \u0111\u01b0\u1ee3c t\u1ef1 \u0111\u1ed9ng ho\u00e1 ho\u00e0n to\u00e0n hay kh\u00f4ng, ch\u1ed7 l\u00e0m vi\u1ec7c bao gi\u1edd c\u0169ng thay \u0111\u1ed5i, v\u00e0 g\u1ea7n nh\u01b0 m\u1ecdi vi\u1ec7c l\u00e0m \u1edf m\u1ecdi ng\u00e0nh c\u00f4ng nghi\u1ec7p s\u1ebd b\u1ecb \u1ea3nh h\u01b0\u1edfng. M\u1ecdi k\u0129 n\u0103ng m\u00e0 c\u00e1c em c\u00f3 s\u1ebd s\u1edbm tr\u1edf th\u00e0nh l\u1ed7i th\u1eddi, cho n\u00ean c\u00e1c em c\u1ea7n ph\u00e1t tri\u1ec3n nh\u1eefng k\u0129 n\u0103ng m\u1edbi m\u00e0 s\u1ebd \u0111\u1ec3 cho c\u00e1c em th\u0103ng ti\u1ebfn v\u00e0 \u0111\u1ea1t t\u1edbi m\u1ee5c \u0111\u00edch c\u1ee7a c\u00e1c em.”<\/p>\n
<\/p>\n
—English version—<\/p>\n
<\/p>\n
The Changing world<\/p>\n
Last week, I attended a technology conference in Detroit, the former “Automobile Capital of the world.” Over a hundred years ago, Henry Ford built his automobile empire here with the concept of the assembly line and mass production. In this “golden age” of the industrial revolution, many automobile companies and factories were created that led to high demands for labor workers. Many farmers abandoned their farms, moved to the cities for better jobs. The demand for labor workers continued to rise, and many companies had to “Import” labor workers from Europe. Between 1900 and 1930, the workers’ population soared from 300,00 to over 1.8 million. The rise of the automobile required more constructions for better transportation in the U.S. which led to another labor shortage of workers to build roads, highways, freeways and other infrastructures. As European labor workers immigrated to the U.S. for better jobs, better lives, the economy exploded with more jobs and prosperity.<\/p>\n
Forty years ago, everything changed. German and Japanese cars began to compete successfully with American cars. To remain competitive, many companies had to reduce their cost of building cars by moving factories to lower-cost countries such as China, India or Thailand, etc. Workers who had jobs in automobile factory suddenly learned that they no longer have jobs. However, competition in the automobile market was fierce, many companies that were slow to change and could not compete had to file for bankruptcy. From over twenty automobile companies in the past, now Detroit has only three that survive – GM, Ford, and Chrysler. The thriving city suddenly fell into decline. Factory workers were in shock as their standard of living disappeared with their jobs. Hundred thousands of factory workers lost their job in just a few short years.<\/p>\n
Last week, as I drove through the city, I saw many empty buildings with no occupation and many houses for sale with no buyers. My friends who traveled with me lamented: “It is a sad city, except downtown, everywhere look like an abandoned places.” I told him: “What happened here is only the beginning, we will see the same thing happen in other countries when automation and robots are taking more jobs from people.”<\/p>\n
In the Information Technology conference, many scientists share their research on new technologies such as “Deep learning;” “Big Data;” “The Internet of Things;” “Virtual Reality and Augmented Reality,” etc. But I was interested in the presentations about jobs that could be impacted by technology.\u00a0 The main speaker, a well-known economist, told the audiences that he believed robots and automation could replace about 47% of U.S. jobs\u00a0in ten years, but 82% of jobs in other countries, mostly labor jobs, will be at higher risk and could be gone in another five years. He asked: “Since the workplace of the near future will be far different from its current state. How many people are taking steps to prepare for the inevitable change? How many people know about this “soon to happen” crisis? How many leaders are preparing for this disaster in their country?”<\/p>\n
For many years, I have written about globalization, outsourcing, emerging technologies, and how these factors can impact all industries and countries. The traditional job where workers can work for their entire life is gone. All workers must learn how to adapt to the evolving global economy because it will happen very fast. It is important that people must continue to learn new skills to secure their career because there is no secure job anymore.<\/p>\n
After came back to Carnegie Mellon, I told my students about my experience in Detroit and the conference: “While going to college and earning a degree is important, but the fact is most of your learning will happen while you are working on a job. As students, you must learn “How to learn fast” and develop a “Lifelong learning” habit if you want to keep your job. Even having a good job, you will need to continue to learn new skills by enrolling in Massive Open Online Courses (MOOCs). Most of you are technical students but do not limit yourselves to this field. You need to be open to new ideas and participate in various projects, to find an opportunity to learn something new. Successful people always try to meet and befriend with other better and smarter people to learn new skills, building knowledge, and finding new opportunities. It is up to you to continue your professional development and prepare yourself for the workplace of\u00a0tomorrow. It does not matter whether or not your job can be completely automated, the working place is always changing, and almost every job in every industry will be affected. Every skill that you have will soon become obsolete, so you need to develop new skills that will let you advance and achieve your goals.”<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
Tu\u1ea7n tr\u01b0\u1edbc, t\u00f4i tham d\u1ef1 m\u1ed9t cu\u1ed9c h\u1ed9i ngh\u1ecb c\u00f4ng ngh\u1ec7 t\u1ea1i Detroit, c\u1ef1u “th\u1ee7 \u0111\u00f4 \u00f4 t\u00f4 c\u1ee7a th\u1ebf gi\u1edbi.” Qua m\u1ed9t tr\u0103m n\u0103m, … <\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18,1],"tags":[],"class_list":["post-5293","post","type-post","status-publish","format-standard","hentry","category-loi-khuyen-cho-sinh-vien","category-xu-huong-toan-cau"],"_links":{"self":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/5293","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5293"}],"version-history":[{"count":1,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/5293\/revisions"}],"predecessor-version":[{"id":5294,"href":"https:\/\/science-technology.vn\/index.php?rest_route=\/wp\/v2\/posts\/5293\/revisions\/5294"}],"wp:attachment":[{"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5293"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5293"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/science-technology.vn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5293"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}