Camila is a 13-year-old seventh-grade student, an only child living with her parents in an urban area of Chile. She used to be a regular Alexa user \u2014 roughly twice a day \u2014 until she began to feel that the device was watching her without her permission. She switched it off, and has not gone back. That episode of privacy unease is the clearest window into how Camila thinks: she is genuinely enthusiastic about what AI can do, and acutely alert to what it might take.<\/p>\n\n\n\n
A World of Possibilities \u2014 With Eyes Open<\/strong><\/p>\n\n\n\n Camila came to her views on AI through lived experience as much as abstract thinking. A family emergency brought it into focus: when a family member needed urgent help, a phone app allowed her family to stay informed in real time and find him. “Having a cellphone saved our life during the pandemic to be able to talk to my relatives who live far away,” she says. These are not hypothetical benefits \u2014 they are things that happened, to her, and that shapes how seriously she takes the potential of intelligent technology. She expects the next thirty years to bring enormous advances, particularly in medicine, though she notes that the most promising tools remain extremely expensive today.<\/p>\n\n\n\n Society in 2050: Environment First<\/strong><\/p>\n\n\n\n When Camila pictures 2050, her hopes centre on the environment: she wants to see all cars electric, and imagines AI-enabled technologies making real progress on environmental problems. She does not describe a personal life transformed by robots so much as a society made more liveable \u2014 cleaner, better connected, with tools that reach people who currently cannot access them.<\/p>\n\n\n\n Where AI Belongs \u2014 and Where It Doesn’t<\/strong><\/p>\n\n\n\n Camila’s views on specific applications are unusually detailed for her age. She supports robot assistance in housekeeping \u2014 she uses the Thermomix as an example of a device that helps you do other things, not just replaces effort. She thinks robots can and should help with the elderly and pets, and she is positive about robot teachers: a robot, she argues, would know everything there is to know about a subject and would not carry a human teacher’s preferences or blind spots. Robot grading, she adds, would be “better because teachers make mistakes.” For store clerks, she is more cautious \u2014 she notices the difference between staff who know their products and those who do not, and is unsure a robot would always improve on the human range.<\/p>\n\n\n\n Where Camila is firm: children need adult human care, not automated substitutes. “Every person has different symptoms and AI may be missing information that patients give you as a human being” \u2014 the same logic she applies to medicine. She believes doctors must remain central to healthcare, because they observe far more than the physical; she accepts AI assistance in nursing homes for companionship, mental exercises, and cleaning, but stops short of full replacement.<\/p>\n\n\n\n Accountability and the Limits of Trust<\/strong><\/p>\n\n\n\n One of Camila’s consistent concerns is accountability: who is responsible when a machine fails? She thinks companies should be held responsible for errors in their AI technologies, whether that is an autonomous car that misjudges a situation or a drone delivery that goes wrong. She acknowledges that automated cars may drive more reliably than intoxicated humans \u2014 but “AI driven cars can fail” too, and that possibility must be owned by someone. This is not distrust of the technology itself so much as insistence that responsibility cannot be outsourced to a machine.<\/p>\n\n\n\n Growing Into an AI World<\/strong><\/p>\n\n\n\n Camila is clear that she wants to understand how intelligent robots work. She frames this as a matter of necessity: “we are entering a world where AI would be more and more present.” She imagines that school in 2050 will look quite different \u2014 and she is excited by that, while also insisting that learning itself must not be abandoned. “I imagine that we should learn the same way we do it today, because it’s important that people learn” \u2014 though she admits, half-jokingly, that a learning chip to absorb it all at once would be welcome. People, she believes, should keep preparing for a range of jobs without handing every task to automated systems. The future she wants is collaborative: automated technologies taking on what humans prefer not to do, freeing people to focus on what matters.<\/p>\n\n\n\n <\/p>","protected":false},"featured_media":0,"template":"","media_category":[],"media_tag":[49,51],"class_list":["post-1130","genzaimedia","type-genzaimedia","status-publish","hentry","media_tag-aixgen-z","media_tag-series","en-US"],"_links":{"self":[{"href":"https:\/\/gen-zai.org\/wp-json\/wp\/v2\/genzaimedia\/1130","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gen-zai.org\/wp-json\/wp\/v2\/genzaimedia"}],"about":[{"href":"https:\/\/gen-zai.org\/wp-json\/wp\/v2\/types\/genzaimedia"}],"wp:attachment":[{"href":"https:\/\/gen-zai.org\/wp-json\/wp\/v2\/media?parent=1130"}],"wp:term":[{"taxonomy":"media_category","embeddable":true,"href":"https:\/\/gen-zai.org\/wp-json\/wp\/v2\/media_category?post=1130"},{"taxonomy":"media_tag","embeddable":true,"href":"https:\/\/gen-zai.org\/wp-json\/wp\/v2\/media_tag?post=1130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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