@Irenemate En Francia es dificilísimo encontrar un pediatra de primaria. Solo se consiguen médicos de atención primaria que han hecho un semestre de formación en urgencias pediátricas.
El niño sano y el acompañamiento a la infancia no lo conocen adecuadamente y seguimiento de patologías 😓
@verona5ber@juanisolano Yo hay una cosa que no entiendo, pero yo coso poco. Siempre he entendido que si coses más tenso de lo que toca o pones más o menos puntos de lo que toca lo que tienes son problemas, no un mejor resultado. Nunca he entendido muy bien cómo se iba a hacer técnicamente hablando
@nachorosell La única manera de que eso sea imposible que te pase es no usar el coche para desplazamientos rutinarios. Te pasarán otras cosas, pero esa no.
@RBlancoMFyC@ajfs_99@oscarnephro El MIR no es obligatorio porque hay muchas cosas para las cuales no hace falta tener experiencia clínica para ejercer.
@AmargoToronjo Mi percepción es que es algo bastante frecuente en la generación de abuelos « boomers » tardíos, que son los mismos que colocaron a sus hijos todo lo posible con sus propios padres.
@verona5ber Suelen ser diagnósticos complejos que requieren colaboración pluridisciplinar (tuiteros, youtubers, tertulianos, vecinos, el del bar, …). No es tan fácil como pensamos los mortales
@veganibalecter La mayoría de franceses que van a consultar a Suiza sobre eutanasia no quieren continuar con el proceso. Solo les da paz saber que si un día no quieren continuar, pueden ser atendidos allí.
Every time I discuss the economic and social disruptions caused by the worldwide decline in fertility, I hear the same response: artificial intelligence (AI) and robots will make this issue irrelevant.
I find the answer deeply paradoxical because, despite being an economist, I am compelled to point out that the argument suffers from the mistake of “economism”: thinking that all social interactions in life are solely about productivity.
Most of the problems caused by declining fertility are largely unrelated to productivity: the depopulation of rural areas, the collapse of public services, and inverted family structures in which one child supports four grandparents. Reducing all of this to purely economic terms is an extremely narrow view of society and life. A robot cannot visit your grandmother in a nursing home in a depopulated town in Korea.
But there is an even more fundamental question: how do you know that societies will permit the deployment of artificial intelligence on a large enough scale? If we have learned anything from economic history, it is that societies repeatedly create barriers to wealth and hinder the adoption of new technologies.
The Roman Empire had a working steam device, the aeolipile, and never developed it beyond a toy. The Ming dynasty burned Zheng He’s fleet and turned inward. Spain expelled its Jewish and Moorish populations at the height of its imperial power, gutting its merchant and artisan classes. The Ottoman Empire resisted the printing press for nearly three centuries after Gutenberg. Tokugawa Japan had firearms in the 1500s but chose to abandon them. The Qing restricted all foreign trade to a single port in Canton for over a century. Argentina was one of the ten richest countries in the world in 1910 and spent a century in relative decline through self-inflicted policy choices. The Soviet Union had world-class mathematicians and physicists but could not produce a decent pair of shoes because the institutional framework would not allow it. India’s License Raj strangled industrial development for four decades after independence. Closer to our own time, much of Europe spent decades resisting genetically modified crops despite the technology being available. Right now, the EU is drafting some of the strictest AI regulations in the world.
And these problems will hit hardest where people least expect them. The conversation about aging and AI tends to focus on rich countries like the U.S. or Japan, but the most acute disruptions will come in emerging economies. Latin America and the Middle East have experienced some of the deepest and fastest declines in fertility on the planet. Colombia’s TFR is 1.06, Jamaica’s 1.20, Turkey’s 1.48, and Mexico’s 1.60. These countries are getting old before they get rich. On top of that, they face a double blow: not only are fewer children being born, but their most skilled and ambitious young workers are leaving. The doctors, engineers, and entrepreneurs who might drive AI adoption are moving to the US, Canada, or Europe.
And let’s be honest: these are not exactly countries known for getting out of the way of innovation. The political economies of Latin America and the Middle East are riddled with extractive institutions, captured regulators, powerful incumbents who block competition, and states that struggle to deliver basic public services, let alone manage an AI transition. If Argentina could not reform its economy in a hundred years of trying (perhaps it is doing it now, but the jury is still out on whether this reform will be sustainable), if Mexico cannot keep its own engineers from leaving, if Egypt cannot fix its educational system, I am not sure why we should expect them to seamlessly deploy the most disruptive technology in human history. The countries that most need technological dynamism to offset demographic decline are precisely the ones least equipped to make it happen.
There is nothing inevitable about adopting new technologies. It requires political will, institutional flexibility, and social acceptance. Aging, fiscally strained democracies dominated by elderly voters are not obviously the best candidates for any of those three.
So when someone tells me “don’t worry, AI will fix it,” I hear an argument that assumes the best possible technological outcome, assumes societies will actually adopt it, assumes it will be deployed fast enough, and assumes the only thing that matters is productivity. That is four enormous assumptions stacked on top of each other. And I am sorry, but since I teach global economic history for a living, I have learned that optimistic assumptions are rarely validated by the crooked timber of humanity.
@cupra_amarillo@mir64_ Yo hace más de una década, sin existencia de la IA, no necesité academia para sacar el número que quería para mi especialidad. Estáis obsesionados con las academias y parece que fuera condición necesaria para un examen público.
A Yazidi man cries as he meets his sister for the first time in 9 years after ISIS kidnapped her as a young girl.
Yazidis didn't have the resources to influence liberals, universities, or media, so they are not considered important!
What ISIS did to Yazidis is not forgivable.
@Cordobesdel72@JulianTapia64 En muy pocos aviones medicalizados metes a alguien en hdfvvc, que es lo que decían algunas noticias que quería la familia. Y si los metes, desde luego no es para hacer del sudeste asiático a Europa.
@princessdr19@YH1M En francés usan « personnel soignant ». Me parece muy apropiada, soigner se traduce como cuidar o atender, y guérir como curar.
En general, a los médicos hay mucha gente que los diferencia del resto de soignants