{"id":1421,"date":"2023-06-06T21:26:23","date_gmt":"2023-06-06T21:26:23","guid":{"rendered":"https:\/\/dailyai.com\/?p=1421"},"modified":"2023-06-06T23:02:27","modified_gmt":"2023-06-06T23:02:27","slug":"the-ai-industry-should-learn-from-nuclear-safety-argue-researchers","status":"publish","type":"post","link":"https:\/\/dailyai.com\/es\/2023\/06\/the-ai-industry-should-learn-from-nuclear-safety-argue-researchers\/","title":{"rendered":"La industria de la IA deber\u00eda aprender de la seguridad nuclear, seg\u00fan los expertos"},"content":{"rendered":"

El desarrollo de la IA ha sido r\u00e1pido, lo que significa que la regulaci\u00f3n tiene que ponerse al d\u00eda, y la gobernanza es en cierto modo una idea tard\u00eda. <\/b><\/p>\n

Existen pocos procesos formales para garantizar la seguridad de la IA, y los investigadores afirman que corresponde a la industria cambiar esta situaci\u00f3n.<\/p>\n

Muchos l\u00edderes y figuras del sector han comparado la IA con la energ\u00eda nuclear. Hay muchas similitudes - <\/span>La IA crece r\u00e1pidamente, plantea un riesgo potencialmente existencial y se complica por los asuntos exteriores, esta vez entre las superpotencias emergentes de la IA, Estados Unidos y China.<\/p>\n

Pasaron d\u00e9cadas antes de que los ingenieros nucleares convencieran a la comunidad cient\u00edfica en general de la seguridad de los reactores nucleares. Los primeros reactores se construyeron a finales de los a\u00f1os 40 y principios de los 50, y no fue hasta la Ley de Energ\u00eda At\u00f3mica estadounidense de 1954 cuando surgi\u00f3 cierto nivel de regulaci\u00f3n.\u00a0<\/span><\/p>\n

El gobierno estadounidense era consciente de los riesgos de la energ\u00eda nuclear, pero la URSS puso en marcha su primer reactor civil a mediados de 1954, por lo que no perdi\u00f3 tiempo en construir el suyo. En 1955, el comisario Willard F. Libby dijo: \"Nuestro gran peligro es que este gran beneficio para la humanidad muera abortado por una regulaci\u00f3n innecesaria\".<\/span><\/p>\n

\u00bfLe suena algo? Fue s\u00f3lo el mes pasado que el CEO de OpenAI Sam Altman inst\u00f3 a la creaci\u00f3n de un organismo internacional<\/a> para la seguridad de la IA como el Organismo Internacional de la Energ\u00eda At\u00f3mica (OIEA), fundado en 1957. Al igual que la energ\u00eda nuclear, la g<\/span>os gobiernos de todo el mundo est\u00e1n estudiando la forma de preservar las ventajas de la inteligencia artificial y, al mismo tiempo, regular sus riesgos.\u00a0<\/span><\/p>\n

El OIEA era un componente aut\u00f3nomo de la ONU y actualmente cuenta con 174 Estados miembros. Despu\u00e9s de 1957, hubo relativamente pocas cat\u00e1strofes nucleares hasta Chernobil.<\/span><\/p>\n

La IA debe aprender de la historia de la seguridad nuclear<\/span><\/h2>\n

Heidy Khlaaf, director de ingenier\u00eda de la consultora de ciberseguridad Rastro de bits<\/a>utilizado para evaluar y verificar la seguridad de las centrales nucleares. <\/span>Recientemente declar\u00f3 al MIT<\/span><\/a> que las centrales nucleares requieren miles de documentos que certifiquen su seguridad, profundizando en los m\u00e1s peque\u00f1os matices de cada componente individual.\u00a0<\/span><\/p>\n

Tras Chern\u00f3bil, la normativa nuclear se hizo extremadamente estricta. Planificar, autorizar y construir un reactor nuclear puede llevar 10 a\u00f1os o m\u00e1s, en parte porque el proceso se controla rigurosamente en cada momento. Khlaaf se\u00f1ala que esto no tiene nada que ver con los beneficios: la seguridad nuclear nace de un aut\u00e9ntico riesgo existencial.\u00a0<\/span><\/p>\n

En cambio, las empresas de IA informan de sus modelos mediante simples \"fichas\" que esencialmente enumeran funciones.\u00a0<\/span><\/p>\n

Adem\u00e1s, el funcionamiento interno del modelo suele ser una \"caja negra\", lo que significa que los procesos de toma de decisiones est\u00e1n en gran medida cerrados a los observadores externos.\u00a0<\/span><\/p>\n

Incluso ChatGPT, al contrario que el hom\u00f3nimo de OpenAI, es una caja negra, y las empresas de IA ya se han labrado la reputaci\u00f3n de ser <\/span>cautelosos sobre sus modelos y datos de entrenamiento.<\/span><\/a>\u00a0<\/span><\/p>\n

\u00bfImagina que los reactores nucleares fueran una \"caja negra\" y que sus promotores no dijeran al p\u00fablico c\u00f3mo funcionan?\u00a0<\/span><\/p>\n

El an\u00e1lisis de los riesgos de la IA debe ser sistem\u00e1tico\u00a0<\/span><\/h2>\n

Para mitigar los riesgos que l\u00edderes en IA como Altman admiten de buen grado, las empresas deben profundizar en sus estrategias de trazabilidad. Esto implica una supervisi\u00f3n rigurosa desde el principio del proceso de desarrollo de la IA.\u00a0<\/span><\/p>\n

Khlaaf afirma: \"Hay que tener una forma sistem\u00e1tica de analizar los riesgos. No se trata de un escenario en el que simplemente dices: 'Oh, esto podr\u00eda pasar. D\u00e9jame escribirlo'\".\u00a0<\/span><\/p>\n

En la actualidad, no existe un proceso establecido para la evaluaci\u00f3n de riesgos de la IA, pero ha habido algunos intentos de crearlo.\u00a0<\/span><\/p>\n

Por ejemplo, <\/span>DeepMind ha publicado recientemente un blog t\u00e9cnico<\/span><\/a> en colaboraci\u00f3n con varias universidades, especificando que los modelos deben ser evaluados para detectar \"riesgos extremos\" antes del entrenamiento. El documento propone dos estrategias:<\/span><\/p>\n

    \n
  1. Evaluar el alcance de las \"capacidades peligrosas\" de un modelo que podr\u00edan utilizarse para amenazar la seguridad, ejercer influencia o eludir la supervisi\u00f3n humana.<\/span><\/li>\n
  2. Evaluar el grado de probabilidad de que un modelo cause da\u00f1os, por ejemplo, si corre el riesgo de no comportarse seg\u00fan lo previsto.\u00a0<\/span><\/li>\n<\/ol>\n

    Toby Shevlane, uno de los investigadores del proyecto, declar\u00f3: \"Las empresas l\u00edderes en IA que est\u00e1n impulsando la frontera tienen la responsabilidad de estar atentas a los problemas emergentes y detectarlos a tiempo para poder abordarlos cuanto antes.\"<\/span><\/p>\n

    Si la IA debe aprender de la seguridad nuclear, la regulaci\u00f3n temprana es fundamental, pero la complacencia a largo plazo es letal. Nadie sabe c\u00f3mo ser\u00eda una versi\u00f3n de Chern\u00f3bil o Fukushima basada en la IA, y nadie quiere averiguarlo. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    El desarrollo de la IA ha sido r\u00e1pido, lo que significa que la normativa tiene que ponerse al d\u00eda, y la gobernanza es algo secundario. Existen pocos procesos formales que garanticen la seguridad de la IA, y los investigadores afirman que corresponde al sector cambiar esta situaci\u00f3n. Muchos l\u00edderes y figuras del sector han comparado la IA con la energ\u00eda nuclear. Hay muchas similitudes: la IA crece r\u00e1pidamente, plantea un riesgo potencialmente existencial y se complica por los asuntos exteriores, esta vez entre las superpotencias emergentes de la IA, Estados Unidos y China. Pasaron d\u00e9cadas antes de que los ingenieros nucleares convencieran a la comunidad cient\u00edfica en general de la seguridad de los reactores nucleares.<\/p>","protected":false},"author":2,"featured_media":1422,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[93,91,92],"class_list":["post-1421","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-openai","tag-policy","tag-regulation"],"yoast_head":"\nThe AI industry should learn from nuclear safety, argue experts | DailyAI<\/title>\n<meta name=\"description\" content=\"There are many parallels between AI and nuclear technology. 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