How the internet can rebuild trust - FT中文网
登录×
电子邮件/用户名
密码
记住我
请输入邮箱和密码进行绑定操作:
请输入手机号码,通过短信验证(目前仅支持中国大陆地区的手机号):
请您阅读我们的用户注册协议隐私权保护政策,点击下方按钮即视为您接受。
人工智能

How the internet can rebuild trust

Algorithms and generative AI models that decide what billions of users see should be transparent
00:00

{"text":[[{"start":null,"text":"

As AI companies fight for dominance, the temptation to embed bias — commercial, political or cultural — into training data will be immense
"}],[{"start":5.8,"text":"The writer is co-founder of Wikipedia and author of ‘The Seven Rules of Trust’"}],[{"start":11.29,"text":"When I founded Wikipedia in 2001, pioneers of the internet were excited by its promise to give the world access to truth and connection."}],[{"start":22.18,"text":"Two decades later, that optimism has curdled into cynicism. We scroll through feeds serving up news we no longer believe, interact with bots we cannot identify and brace for the next synthetic scandal created by fake images from artificial intelligence."}],[{"start":42.06,"text":"Before the web can move forward, it must remember how it earned trust in the first place."}],[{"start":48.49,"text":"The defining difference between web 1.0 and the platforms that dominate today is not technological sophistication but moral architecture. Early online communities were transparent about process and purpose. They exposed how information was created, corrected and shared. That visibility generated accountability. People could see how the system worked and participate in fixing its mistakes. Trust emerged not from perfection (there was still plenty of online trolling, flame wars and toxicity), but from openness."}],[{"start":84.49000000000001,"text":"Today’s digital landscape reverses that logic. Recommendation algorithms and generative AI models decide what billions of users see, yet their workings remain opaque. When platforms insist their systems are too complex to explain, users are asked to substitute faith for understanding."}],[{"start":105.78,"text":"AI intensifies the problem. Large language models can produce fluent paragraphs and convincing deepfakes. The tools that promised to democratise knowledge now threaten to make knowledge unrecognisable. If everything can be fabricated, the distinction between truth and illusion becomes a matter of persuasion."}],[{"start":127.36,"text":"Re-establishing trust in this environment requires more than fact-checking or content moderation. It requires structural transparency. Every platform that mediates information should make provenance visible: where data originated, how it was processed, and what uncertainty surrounds it. Think of it as nutritional labelling for information. Without it, citizens cannot make informed judgments and democracies cannot function."}],[{"start":156.64,"text":"Equally important is independence. As AI companies fight for dominance, the temptation to embed bias — commercial, political or cultural — into training data will be immense. Guardrails must ensure the entities curating public knowledge are accountable to the public, not just investors."}],[{"start":177.42999999999998,"text":"And we must revive civility too. Some of the best early online spaces relied on norms that valued reasoned argument over insult. They were imperfect but self-correcting because participants felt a duty to the collective project. Today’s social platforms monetise outrage. Restoring trust means designing systems that reward good-faith discourse — through visibility algorithms, community-based moderation, or friction that forces reflection before reposting."}],[{"start":212.55999999999997,"text":"Governments have a role to play but regulation alone cannot rebuild trust. It has to be observed in practice. Platforms should disclose not only how their algorithms work but also when they fail. AI developers should publish dataset sources and error rates."}],[{"start":232.7,"text":"The challenge of our time is not that information is scarce but that authenticity is. Important aspects of the early internet succeeded because people could trace what they read to another human being, even if the other human being was operating behind a pseudonym. The new internet must restore that chain of custody."}],[{"start":255.83999999999997,"text":"We are entering an era when machines can mimic any voice and invent any image. If we want truth to survive that onslaught, we must embed transparency, independence and empathy into the digital architecture itself. The early days of the web showed it could be done. The question is whether we still have the will to do it again."}],[{"start":284.46999999999997,"text":""}]],"url":"https://audio.ftcn.net.cn/album/a_1764835851_6780.mp3"}

版权声明:本文版权归FT中文网所有,未经允许任何单位或个人不得转载,复制或以任何其他方式使用本文全部或部分,侵权必究。

AI热潮中经济学家能否规避利益冲突?

凯恩斯:研究AI、与AI实验室合作成了经济学家的新热门,但经济学家能否保证自己的研究不被扭曲?

Lex专栏:今日运动鞋价格战,明日轮到AI巨头

恶性价格竞争或许能让消费者受益,但企业利润率可能在这一过程中崩塌。

富豪疯狂囤金之年

富豪们对黄金的信念,如同这种金属一样未曾褪色。

特朗普令冰岛加入欧盟的争论重新升温

冰岛人将于8月29日投票,决定该国是否应再次尝试加入这一集团。

为什么泰国的利率处于全球最低水平之列?

泰国尚未实现富裕便已步入老龄化,而高负债水平抑制了本可提振经济的消费支出。

侯赛因•塔伊布:帮伊朗最高领袖穆杰塔巴巩固国内控制的强硬派神职人员

一度被边缘化的塔伊布,如今获新任最高领袖提拔,负责领导革命卫队旗下权力大增的巴斯基民兵组织。
设置字号×
最小
较小
默认
较大
最大
分享×