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《纽时》砸2000万美元告OpenAI、微软!AI时代新闻版权与记者未来会如何?

2026-10-27 17:34:02 网络 阅读(75)

人工智慧(AI)快速渗透新闻产业之际,《纽约时报》与OpenAI、微软(MSFT-US) 的著作权诉讼,也逐渐从单一法律案件,演变成科技公司如何取得新闻内容、媒体如何维持商业模式的产业战争。

《纽时》砸2000万美元告OpenAI、微软!AI时代新闻版权与记者未来会如何?

截至2026年7月底,《纽约时报》已为诉讼投入超过2000万美元费用,但案件仍未完成证据开示程序。若持续诉讼,总成本可能攀升至4000万美元。

对多数新闻机构而言,这笔金额足以支撑一家编辑部运作多年,但《纽约时报》并没有停战的打算。

《纽约时报》发行人苏兹伯格(A.G. Sulzberger)认为,这场诉讼争论的并不只是《纽约时报》能否获得赔偿,而是科技公司是否可以先取得新闻机构多年投入大量人力与资源制作的内容,再以「技术创新」为由决定是否付费,以及应该支付多少。

他强调,《纽约时报》并非反对AI,而是反对一种正在形成的商业模式:科技公司愿意为人才、晶片、资料中心与电力支付高昂成本,却把新闻、书籍、音乐与电影等内容统称为可以免费取得的「资料」。

从谈判破裂到对簿公堂

这场法律冲突最初并非始于法院。

2023年4月,《纽约时报》开始与OpenAI及微软协商,希望针对新闻内容的使用方式达成协议。当时ChatGPT问世不到半年,出版业已逐渐意识到,生成式AI不只可能改变内容制作方式,也可能成为新闻网站的替代入口。

然而,双方最终未能达成协议。

2023年12月27日,《纽约时报》向美国纽约南区联邦地区法院正式起诉OpenAI与微软,指控两家公司未经授权复制数百万篇《纽约时报》文章,用于训练GPT系列大型语言模型,成为大型新闻机构首次同时将OpenAI与微软告上法庭的案件。

《纽约时报》的指控主要集中在三个层面。

首先是模型训练阶段。该报认为,OpenAI在搜集、整理并输入训练资料时复制其文章,而部分内容之后被模型「记住」,同样可能构成未经授权的复制。

其次是模型输出阶段。《纽约时报》在诉状中列举包括纽约计程车牌照产业普立兹奖调查,以及《Snow Fall: The Avalanche at Tunnel Creek》(《雪崩:隧道溪事件》)等报导,主张ChatGPT能产生与原文高度相似、甚至接近逐字重现的内容。

微软旗下Browse with Bing也遭到指控。该服务被指直接整理《纽约时报》旗下消费产品评测网站Wirecutter的推荐内容,保留推荐结果,却未保留原文连结及可为Wirecutter带来佣金收入的购物连结。

第三则是替代效应。

过去读者通常透过搜寻引擎找到新闻,再点进《纽约时报》网站;如今ChatGPT与微软Copilot可以直接提供答案,使用者可能不再造访原始文章,使媒体面临流量、订阅、广告及内容授权收入受到影响的风险。

《纽约时报》同时认为,AI生成错误资讯也可能被使用者误认为来自该报,进而伤害新闻机构多年建立的品牌与公信力。

至于微软,《纽约时报》并非因其投资OpenAI而将其一并列为被告。该公司向OpenAI提供资金与运算资源,并将相关模型整合至Bing搜寻、Copilot及Azure等产品。《纽约时报》因此认为,微软既参与相关技术体系的建构,也利用模型推出商业服务,因此应承担相应责任。

《纽约时报》并未提出具体索赔金额,但主张OpenAI与微软可能须承担数十亿美元的法定赔偿及实际损失,并要求销毁包含其受著作权保护作品的训练资料及相关模型。

若法院最终支持这项要求,影响将不只是赔偿金额,更可能牵动整个AI产业取得训练资料的方式。

《纽时》不是反AI 而是要求内容先取得授权

面对诉讼,OpenAI将《纽约时报》的行动形容为阻碍新技术发展。

OpenAI在2024年2月提交的文件中指控,《纽约时报》为取得诉状中的模型重现结果,曾对ChatGPT进行数万次尝试,并透过文章片段与特殊提示词诱导模型输出。OpenAI认为,这并非一般使用者正常使用产品的方式。

微软则将《纽约时报》对AI冲击新闻业的描述形容为「末日式推演」,并以电影业过去反对录影机的案例进行比喻,主张新技术虽然会改变内容消费方式,但不应因此直接被认定为侵权。

两家公司抗辩的核心都是「合理使用」。

OpenAI与微软认为,大型语言模型是在学习语言规律,而不是建立一个让使用者搜寻原文的资料库;模型偶尔重现文章,是技术上需要解决的问题,并不代表整个训练行为违法。

但《纽约时报》并没有选择全面拒绝AI。苏兹伯格表示,新闻机构没有必要急着成为新技术的第一批使用者,更稳妥的方式是先观察、学习与试验,同时确保记者、编辑及新闻机构仍对最终内容负责。

《纽约时报》内部目前也将AI更多用于辅助采访,而非直接取代记者完成写作、编辑与发布。

例如,在一项针对加萨走廊弹坑的调查中,AI协助记者从数百万张图片中筛选出数千张可能具有价值的影像,但最终辨识、验证与判断仍由记者完成。参与报导的记者将AI形容为「过滤器」,可以缩小搜寻范围,却无法取代人类承担新闻责任。

这也是苏兹伯格对AI的核心立场:无论采用什么工具,《纽约时报》发布的内容最终都必须由人负责。AI可以协助记者找到线索,但不应自行决定什么是真相、什么内容可以发布。

一边打官司、一边授权 《纽时》划出合作红线

《纽约时报》也并非拒绝与科技公司合作。

2025年5月,该报与亚马逊(AMZN-US) 达成首份生成式AI内容授权协议。亚马逊可以在Alexa等产品中展示《纽约时报》、NYT Cooking及《The Athletic》的内容摘要,也可以利用相关内容训练自身基础模型。

双方没有正式公布交易金额,但《华尔街日报》后续报导称,亚马逊每年支付的授权费约2000万至2500万美元。

这也形成一个值得注意的对比:《纽约时报》一方面已花费超过2000万美元与OpenAI、微软打官司,另一方面则透过授权协议,每年从亚马逊取得大致相当规模的收入。

分析指出,两者真正的差异并不在于是否使用AI,而在于是否事先取得授权,以及是否承认新闻内容具有价格。

2025年12月,《纽约时报》又对AI搜寻公司Perplexity提起诉讼,指控对方未经授权复制并展示包括付费文章在内的内容。

从这些行动可以看出,《纽约时报》正试图为与矽谷的关系划出界线:愿意付费并接受授权条件的公司,可以成为合作伙伴;先使用内容、之后才协商的公司,则可能成为被告。

官司仍未定案 双方争夺证据成战场

2025年4月4日,负责审理本案的美国联邦地区Sidney H. Stein做出首项重要裁定。法院允许《纽约时报》的主要著作权诉求继续推进,未接受OpenAI关于部分早期训练行为已超过诉讼时效的主张,也没有驳回与模型输出及使用者复制相关的主要指控。

然而,这并不代表《纽约时报》已经胜诉。法院同时撤销普通法不正当竞争及部分《数位千年著作权法》(DMCA)相关诉求。更重要的是,法官当时并未判定OpenAI训练模型是否属于合理使用,只认定《纽约时报》提出的核心事实足以进入证据开示阶段。

此后,双方开始围绕证据展开攻防。2025年5月,法官一度要求OpenAI保存原本可能被删除的ChatGPT输出纪录,包括使用者主动删除的对话。OpenAI则认为,这可能违反其对使用者的隐私承诺。相关全面保存义务后来于2025年9月26日结束。

法院随后要求OpenAI提供2022年12月至2024年11月期间随机抽取的2000万份ChatGPT对话,以判断使用者是否曾透过ChatGPT复制《纽约时报》文章或绕过付费墙。

OpenAI已对这些对话进行去识别化,并将存取权限限制在特定律师及技术顾问范围,但仍认为大部分对话与案件无关,《纽约时报》的要求可能侵犯一般使用者隐私。

到了2026年7月9日,双方冲突再度升高。《纽约时报》、纽约《每日新闻》等媒体要求法院制裁OpenAI,指控OpenAI曾表示无法从训练资料及ChatGPT输出纪录中搜寻新闻机构的著作权内容,但OpenAI员工后来作证称,公司过去曾进行类似搜寻。

原告进一步指控OpenAI删除数十亿笔相关对话,或让这些纪录无法继续搜寻,并要求法院命令OpenAI负担律师费,同时对其作出不利的证据推定。

不过,这些目前仍属原告提出的指控,并非法院已认定的事实。

OpenAI在8月14日提交反对意见,认为新闻机构将大型诉讼中的正常证据处理程序描述为蓄意阻挠,并扭曲相关事件。法院尚未就制裁动议作出裁决,《纽约时报》等原告须在9月10日前提交回复。

另一方面,法院8月6日也撤销新闻机构基于「终端使用者直接侵权」提出的部分帮助侵权主张,并拒绝《纽约时报》在诉讼后期针对微软新增的帮助侵权理论;商标淡化诉求也遭撤销。

不过,未经授权训练模型、模型输出是否构成新闻内容复制,以及相关行为是否属于合理使用,仍是整起案件的核心争议。

截至2026年8月底,法院仍未作出实体判决,任何一方都尚未赢得这场诉讼。

AI不一定消灭记者 但可能先改变新闻工作的样貌

比著作权归属更早发生的变化,是AI已经进入新闻编辑部,逐步重新分配记者与机器的工作。

早在2014年,《美联社》就开始利用自动化系统撰写美国上市公司季度财报快讯。导入自动化工具前,《美联社》记者每季约能完成300篇财报新闻;系统上线后,每季自动生成的稿件超过3000篇,数量增加10倍。

当时《美联社》的说法并不是以机器取代记者,而是让记者不必再花时间重复输入营收、获利及年增率等资讯,转而投入财报电话会议、企业异常变化、产业趋势及消息来源建立。

也就是说,机器接手的是格式化生产,而记者负责解读数字背后的意义。

进入生成式AI时代后,机器处理的工作进一步扩大。除了结构化资料,AI如今也可以阅读会议纪录、整理采访笔记、摘要文件,甚至产出新闻初稿。

美国俄亥俄州《克利夫兰老实人报》已设立「AI改写台」。记者提交采访笔记、会议资料或录音后,由AI生成短篇新闻初稿,再交由编辑审核。

支持这种做法的人认为,AI可以让记者减少机械式写作,把更多时间投入找线索、采访及建立消息来源,也有助地方媒体在经营压力下维持工作机会。

但另一种风险也随之出现。若AI可以直接根据采访笔记生成稿件,媒体对初阶记者与文字编辑的需求可能下降。过去,年轻记者往往透过会议新闻、财报快讯及短消息累积基本功,这条进入新闻业的职涯路径也可能因此受到影响。

因此,AI未必会一次性消灭「记者」这个职业,却可能让同样规模的内容生产只需要更少的人力。

根据牛津大学路透新闻研究所《2025年新闻、媒体与科技趋势及预测》报告,调查51个国家及地区、共326名媒体管理者后发现,87%的受访者认为生成式AI正在「完全或一定程度上」改变编辑部,60%则将后台自动化视为非常重要的发展方向。

媒体准备探索的AI应用已涵盖内容生产各个环节,包括将文字报导转成音讯、在文章前加入AI摘要、翻译新闻,以及提供AI聊天与搜寻服务。

换言之,AI改变的不只是「谁来写稿」,而是从资料搜集、录音整理、翻译、写作、编辑,到标题、音讯、搜寻及内容分发的完整流程。

受众仍更信任「有人负责」的新闻

不过,读者并没有准备把新闻完全交给机器。牛津大学路透新闻研究所研究员Felix Simon、哥本哈根大学教授Rasmus Kleis Nielsen及研究主任Richard Fletcher 2025年的一项六国调查显示,仅12%的受访者能接受完全由AI制作的新闻。

当新闻由记者主导、AI仅提供辅助时,可接受比例提高至43%;完全由人类制作的新闻,接受度则达62%。

受众最能接受AI执行的工作包括拼字检查、文法修改与翻译;最难接受的则是AI记者、AI主持人,以及完全由机器独立制作新闻。

这显示大众并非完全排斥AI,而是不愿放弃新闻背后那个可以被追问、被查证,也必须承担责任的人。

这也成为苏兹伯格坚持《纽约时报》可以使用AI、却不能把最终责任交给AI的原因。

分析指出,《纽约时报》所担心的并非AI本身,而是新闻机构仍需承担记者薪资、海外采访、调查报导及法律风险等成本,AI公司却可以凭借技术与使用者入口,把这些新闻转化为自己的答案,同时取得内容分发与主要利润。

如果这种模式最终成形,记者这个职业或许不会立即消失,但愿意持续投入资源进行原创报导的新闻机构可能逐渐减少。

届时,世界看似拥有更多、更快的资讯,AI也能更迅速回答问题;但真正愿意走进现场、挖掘机器尚不知道的事实的人,却可能变得越来越少。

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          "id": 71,
          "pid": 10,
          "name": "经纪商 ",
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      "pid": 0,
      "name": "外汇平台",
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      "target": "0",
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      "pid": 0,
      "name": "外汇开户",
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      "pid": 0,
      "name": "外汇策略",
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      "name": "外汇入门",
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      "pid": 0,
      "name": "实时",
      "pinyin": "hour",
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      "orderBy": 0,
      "target": "0",
      "status": "0",
      "listView": "list.html",
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      "type": "0",
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      "pid": 0,
      "name": "广告招商",
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      "target": "0",
      "status": "1",
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      "type": "0",
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      "id": 65,
      "pid": 0,
      "name": "外汇经纪商",
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      "path": "/whjjs",
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      "target": "0",
      "status": "0",
      "listView": "list.html",
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      "type": "0",
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          "pid": 65,
          "name": "XM外汇",
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          "id": 67,
          "pid": 65,
          "name": "Exness外汇",
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          "orderBy": 0,
          "target": "0",
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        {
          "id": 68,
          "pid": 65,
          "name": "TMGM外汇",
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          "orderBy": 0,
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          "status": "0",
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          "id": 69,
          "pid": 65,
          "name": "Doo Prime德璞资本",
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          "path": "/whjjs/doo",
          "orderBy": 0,
          "target": "0",
          "status": "0",
          "listView": "list.html",
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          "type": "0",
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        {
          "id": 70,
          "pid": 65,
          "name": "FXTM富拓",
          "pinyin": "fxtm",
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          "orderBy": 0,
          "target": "0",
          "status": "0",
          "listView": "list.html",
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          "seoTitle": "",
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          "type": "0",
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        {
          "id": 72,
          "pid": 65,
          "name": "EC外汇",
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    "title": "《纽时》砸2000万美元告OpenAI、微软!AI时代新闻版权与记者未来会如何?",
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    "description": "《纽约时报》与OpenAI、微软的AI著作权诉讼持续延烧,已投入逾2000万美元。从训练资料、内容授权到AI取代新闻工作,这场官司可能重塑新闻产业与AI公司的内容规则。",
    "img": "https://cimg.cnyes.cool/prod/news/6592344/l/789e77ee241e1b4178fa28f334b13dc3.jpg",
    "content": "<p>人工智慧(AI)快速渗透新闻产业之际,《纽约时报》与OpenAI、微软(<a data-symbol-template=\"USS:MSFT:STOCK:COMMON\" href=\"#\">MSFT-US</a>) 的著作权诉讼,也逐渐从单一法律案件,演变成科技公司如何取得新闻内容、媒体如何维持商业模式的产业战争。</p>\n<p style=\"text-align:center;\"><img src=\"https://cimg.cnyes.cool/prod/news/6592344/l/789e77ee241e1b4178fa28f334b13dc3.jpg\" alt=\"《纽时》砸2000万美元告OpenAI、微软!AI时代新闻版权与记者未来会如何?\" style=\"width:50%;height:auto;border-radius:6px;margin:15px auto;display:block;\"></p>\n\n\n<p>截至2026年7月底,《纽约时报》已为诉讼投入超过2000万美元费用,但案件仍未完成证据开示程序。若持续诉讼,总成本可能攀升至4000万美元。</p>\n\n<p>对多数新闻机构而言,这笔金额足以支撑一家编辑部运作多年,但《纽约时报》并没有停战的打算。</p>\n\n<p>《纽约时报》发行人苏兹伯格(A.G. Sulzberger)认为,这场诉讼争论的并不只是《纽约时报》能否获得赔偿,而是科技公司是否可以先取得新闻机构多年投入大量人力与资源制作的内容,再以「技术创新」为由决定是否付费,以及应该支付多少。</p>\n\n<p>他强调,《纽约时报》并非反对AI,而是反对一种正在形成的商业模式:科技公司愿意为人才、晶片、资料中心与电力支付高昂成本,却把新闻、书籍、音乐与电影等内容统称为可以免费取得的「资料」。</p>\n\n<h6>从谈判破裂到对簿公堂</h6>\n\n<p>这场法律冲突最初并非始于法院。</p>\n\n<p>2023年4月,《纽约时报》开始与OpenAI及微软协商,希望针对新闻内容的使用方式达成协议。当时ChatGPT问世不到半年,出版业已逐渐意识到,生成式AI不只可能改变内容制作方式,也可能成为新闻网站的替代入口。</p>\n\n<p>然而,双方最终未能达成协议。</p>\n\n<p>2023年12月27日,《纽约时报》向美国纽约南区联邦地区法院正式起诉OpenAI与微软,指控两家公司未经授权复制数百万篇《纽约时报》文章,用于训练GPT系列大型语言模型,成为大型新闻机构首次同时将OpenAI与微软告上法庭的案件。</p>\n\n<p>《纽约时报》的指控主要集中在三个层面。</p>\n\n<p>首先是模型训练阶段。该报认为,OpenAI在搜集、整理并输入训练资料时复制其文章,而部分内容之后被模型「记住」,同样可能构成未经授权的复制。</p>\n\n<p>其次是模型输出阶段。《纽约时报》在诉状中列举包括纽约计程车牌照产业普立兹奖调查,以及《Snow Fall: The Avalanche at Tunnel Creek》(《雪崩:隧道溪事件》)等报导,主张ChatGPT能产生与原文高度相似、甚至接近逐字重现的内容。</p>\n\n<p>微软旗下Browse with Bing也遭到指控。该服务被指直接整理《纽约时报》旗下消费产品评测网站Wirecutter的推荐内容,保留推荐结果,却未保留原文连结及可为Wirecutter带来佣金收入的购物连结。</p>\n\n<p>第三则是替代效应。</p>\n\n<p>过去读者通常透过搜寻引擎找到新闻,再点进《纽约时报》网站;如今ChatGPT与微软Copilot可以直接提供答案,使用者可能不再造访原始文章,使媒体面临流量、订阅、广告及内容授权收入受到影响的风险。</p>\n\n<p>《纽约时报》同时认为,AI生成错误资讯也可能被使用者误认为来自该报,进而伤害新闻机构多年建立的品牌与公信力。</p>\n\n<p>至于微软,《纽约时报》并非因其投资OpenAI而将其一并列为被告。该公司向OpenAI提供资金与运算资源,并将相关模型整合至Bing搜寻、Copilot及Azure等产品。《纽约时报》因此认为,微软既参与相关技术体系的建构,也利用模型推出商业服务,因此应承担相应责任。</p>\n\n<p>《纽约时报》并未提出具体索赔金额,但主张OpenAI与微软可能须承担数十亿美元的法定赔偿及实际损失,并要求销毁包含其受著作权保护作品的训练资料及相关模型。</p>\n\n<p>若法院最终支持这项要求,影响将不只是赔偿金额,更可能牵动整个AI产业取得训练资料的方式。</p>\n\n<h6>《纽时》不是反AI 而是要求内容先取得授权</h6>\n\n<p>面对诉讼,OpenAI将《纽约时报》的行动形容为阻碍新技术发展。</p>\n\n<p>OpenAI在2024年2月提交的文件中指控,《纽约时报》为取得诉状中的模型重现结果,曾对ChatGPT进行数万次尝试,并透过文章片段与特殊提示词诱导模型输出。OpenAI认为,这并非一般使用者正常使用产品的方式。</p>\n\n<p>微软则将《纽约时报》对AI冲击新闻业的描述形容为「末日式推演」,并以电影业过去反对录影机的案例进行比喻,主张新技术虽然会改变内容消费方式,但不应因此直接被认定为侵权。</p>\n\n<p>两家公司抗辩的核心都是「合理使用」。</p>\n\n<p>OpenAI与微软认为,大型语言模型是在学习语言规律,而不是建立一个让使用者搜寻原文的资料库;模型偶尔重现文章,是技术上需要解决的问题,并不代表整个训练行为违法。</p>\n\n<p>但《纽约时报》并没有选择全面拒绝AI。苏兹伯格表示,新闻机构没有必要急着成为新技术的第一批使用者,更稳妥的方式是先观察、学习与试验,同时确保记者、编辑及新闻机构仍对最终内容负责。</p>\n\n<p>《纽约时报》内部目前也将AI更多用于辅助采访,而非直接取代记者完成写作、编辑与发布。</p>\n\n<p>例如,在一项针对加萨走廊弹坑的调查中,AI协助记者从数百万张图片中筛选出数千张可能具有价值的影像,但最终辨识、验证与判断仍由记者完成。参与报导的记者将AI形容为「过滤器」,可以缩小搜寻范围,却无法取代人类承担新闻责任。</p>\n\n<p>这也是苏兹伯格对AI的核心立场:无论采用什么工具,《纽约时报》发布的内容最终都必须由人负责。AI可以协助记者找到线索,但不应自行决定什么是真相、什么内容可以发布。</p>\n\n<h6>一边打官司、一边授权 《纽时》划出合作红线</h6>\n\n<p>《纽约时报》也并非拒绝与科技公司合作。</p>\n\n<p>2025年5月,该报与亚马逊(<a data-symbol-template=\"USS:AMZN:STOCK:COMMON\" href=\"#\">AMZN-US</a>) 达成首份生成式AI内容授权协议。亚马逊可以在Alexa等产品中展示《纽约时报》、NYT Cooking及《The Athletic》的内容摘要,也可以利用相关内容训练自身基础模型。</p>\n\n<p>双方没有正式公布交易金额,但《华尔街日报》后续报导称,亚马逊每年支付的授权费约2000万至2500万美元。</p>\n\n<p>这也形成一个值得注意的对比:《纽约时报》一方面已花费超过2000万美元与OpenAI、微软打官司,另一方面则透过授权协议,每年从亚马逊取得大致相当规模的收入。</p>\n\n<p>分析指出,两者真正的差异并不在于是否使用AI,而在于是否事先取得授权,以及是否承认新闻内容具有价格。</p>\n\n<p>2025年12月,《纽约时报》又对AI搜寻公司Perplexity提起诉讼,指控对方未经授权复制并展示包括付费文章在内的内容。</p>\n\n<p>从这些行动可以看出,《纽约时报》正试图为与矽谷的关系划出界线:愿意付费并接受授权条件的公司,可以成为合作伙伴;先使用内容、之后才协商的公司,则可能成为被告。</p>\n\n<h6>官司仍未定案 双方争夺证据成战场</h6>\n\n<p>2025年4月4日,负责审理本案的美国联邦地区Sidney H. Stein做出首项重要裁定。法院允许《纽约时报》的主要著作权诉求继续推进,未接受OpenAI关于部分早期训练行为已超过诉讼时效的主张,也没有驳回与模型输出及使用者复制相关的主要指控。</p>\n\n<p>然而,这并不代表《纽约时报》已经胜诉。法院同时撤销普通法不正当竞争及部分《数位千年著作权法》(DMCA)相关诉求。更重要的是,法官当时并未判定OpenAI训练模型是否属于合理使用,只认定《纽约时报》提出的核心事实足以进入证据开示阶段。</p>\n\n<p>此后,双方开始围绕证据展开攻防。2025年5月,法官一度要求OpenAI保存原本可能被删除的ChatGPT输出纪录,包括使用者主动删除的对话。OpenAI则认为,这可能违反其对使用者的隐私承诺。相关全面保存义务后来于2025年9月26日结束。</p>\n\n<p>法院随后要求OpenAI提供2022年12月至2024年11月期间随机抽取的2000万份ChatGPT对话,以判断使用者是否曾透过ChatGPT复制《纽约时报》文章或绕过付费墙。</p>\n\n<p>OpenAI已对这些对话进行去识别化,并将存取权限限制在特定律师及技术顾问范围,但仍认为大部分对话与案件无关,《纽约时报》的要求可能侵犯一般使用者隐私。</p>\n\n<p>到了2026年7月9日,双方冲突再度升高。《纽约时报》、纽约《每日新闻》等媒体要求法院制裁OpenAI,指控OpenAI曾表示无法从训练资料及ChatGPT输出纪录中搜寻新闻机构的著作权内容,但OpenAI员工后来作证称,公司过去曾进行类似搜寻。</p>\n\n<p>原告进一步指控OpenAI删除数十亿笔相关对话,或让这些纪录无法继续搜寻,并要求法院命令OpenAI负担律师费,同时对其作出不利的证据推定。</p>\n\n<p>不过,这些目前仍属原告提出的指控,并非法院已认定的事实。</p>\n\n<p>OpenAI在8月14日提交反对意见,认为新闻机构将大型诉讼中的正常证据处理程序描述为蓄意阻挠,并扭曲相关事件。法院尚未就制裁动议作出裁决,《纽约时报》等原告须在9月10日前提交回复。</p>\n\n<p>另一方面,法院8月6日也撤销新闻机构基于「终端使用者直接侵权」提出的部分帮助侵权主张,并拒绝《纽约时报》在诉讼后期针对微软新增的帮助侵权理论;商标淡化诉求也遭撤销。</p>\n\n<p>不过,未经授权训练模型、模型输出是否构成新闻内容复制,以及相关行为是否属于合理使用,仍是整起案件的核心争议。</p>\n\n<p>截至2026年8月底,法院仍未作出实体判决,任何一方都尚未赢得这场诉讼。</p>\n\n<h6>AI不一定消灭记者 但可能先改变新闻工作的样貌</h6>\n\n<p>比著作权归属更早发生的变化,是AI已经进入新闻编辑部,逐步重新分配记者与机器的工作。</p>\n\n<p>早在2014年,《美联社》就开始利用自动化系统撰写美国上市公司季度财报快讯。导入自动化工具前,《美联社》记者每季约能完成300篇财报新闻;系统上线后,每季自动生成的稿件超过3000篇,数量增加10倍。</p>\n\n<p>当时《美联社》的说法并不是以机器取代记者,而是让记者不必再花时间重复输入营收、获利及年增率等资讯,转而投入财报电话会议、企业异常变化、产业趋势及消息来源建立。</p>\n\n<p>也就是说,机器接手的是格式化生产,而记者负责解读数字背后的意义。</p>\n\n<p>进入生成式AI时代后,机器处理的工作进一步扩大。除了结构化资料,AI如今也可以阅读会议纪录、整理采访笔记、摘要文件,甚至产出新闻初稿。</p>\n\n<p>美国俄亥俄州《克利夫兰老实人报》已设立「AI改写台」。记者提交采访笔记、会议资料或录音后,由AI生成短篇新闻初稿,再交由编辑审核。</p>\n\n<p>支持这种做法的人认为,AI可以让记者减少机械式写作,把更多时间投入找线索、采访及建立消息来源,也有助地方媒体在经营压力下维持工作机会。</p>\n\n<p>但另一种风险也随之出现。若AI可以直接根据采访笔记生成稿件,媒体对初阶记者与文字编辑的需求可能下降。过去,年轻记者往往透过会议新闻、财报快讯及短消息累积基本功,这条进入新闻业的职涯路径也可能因此受到影响。</p>\n\n<p>因此,AI未必会一次性消灭「记者」这个职业,却可能让同样规模的内容生产只需要更少的人力。</p>\n\n<p>根据牛津大学路透新闻研究所《2025年新闻、媒体与科技趋势及预测》报告,调查51个国家及地区、共326名媒体管理者后发现,87%的受访者认为生成式AI正在「完全或一定程度上」改变编辑部,60%则将后台自动化视为非常重要的发展方向。</p>\n\n<p>媒体准备探索的AI应用已涵盖内容生产各个环节,包括将文字报导转成音讯、在文章前加入AI摘要、翻译新闻,以及提供AI聊天与搜寻服务。</p>\n\n<p>换言之,AI改变的不只是「谁来写稿」,而是从资料搜集、录音整理、翻译、写作、编辑,到标题、音讯、搜寻及内容分发的完整流程。</p>\n\n<h6>受众仍更信任「有人负责」的新闻</h6>\n\n<p>不过,读者并没有准备把新闻完全交给机器。牛津大学路透新闻研究所研究员Felix Simon、哥本哈根大学教授Rasmus Kleis Nielsen及研究主任Richard Fletcher 2025年的一项六国调查显示,仅12%的受访者能接受完全由AI制作的新闻。</p>\n\n<p>当新闻由记者主导、AI仅提供辅助时,可接受比例提高至43%;完全由人类制作的新闻,接受度则达62%。</p>\n\n<p>受众最能接受AI执行的工作包括拼字检查、文法修改与翻译;最难接受的则是AI记者、AI主持人,以及完全由机器独立制作新闻。</p>\n\n<p>这显示大众并非完全排斥AI,而是不愿放弃新闻背后那个可以被追问、被查证,也必须承担责任的人。</p>\n\n<p>这也成为苏兹伯格坚持《纽约时报》可以使用AI、却不能把最终责任交给AI的原因。</p>\n\n<p>分析指出,《纽约时报》所担心的并非AI本身,而是新闻机构仍需承担记者薪资、海外采访、调查报导及法律风险等成本,AI公司却可以凭借技术与使用者入口,把这些新闻转化为自己的答案,同时取得内容分发与主要利润。</p>\n\n<p>如果这种模式最终成形,记者这个职业或许不会立即消失,但愿意持续投入资源进行原创报导的新闻机构可能逐渐减少。</p>\n\n<p>届时,世界看似拥有更多、更快的资讯,AI也能更迅速回答问题;但真正愿意走进现场、挖掘机器尚不知道的事实的人,却可能变得越来越少。</p>\n<div class=\"related-articles seo-links\">\n  <h4>相关阅读</h4>\n  <ul>\n    <li><a href=\"/new/AI/article-10367.html\" title=\"伊朗战事曝弹药断层!华邮:五角大厦勒令国防承包商21天内交出增产计划\">伊朗战事曝弹药断层!华邮:五角大厦勒令国防承包商21天内交出增产计划</a></li>\n    <li><a href=\"/new/AI/article-3931.html\" title=\"DRAM龙头之争!三星市占38%重返王座 HBM仍是SK海力士天下\">DRAM龙头之争!三星市占38%重返王座 HBM仍是SK海力士天下</a></li>\n    <li><a href=\"/new/AI/article-380.html\" title=\"手机最高降价台币9,000元?大陆网友:让子弹再飞一会儿\">手机最高降价台币9,000元?大陆网友:让子弹再飞一会儿</a></li>\n    <li><a href=\"/new/AI/article-4213.html\" title=\"韩启动三大超级项目!李在明:将加快AI基设建设 三星、SK海力士砸逾800兆韩元扩产\">韩启动三大超级项目!李在明:将加快AI基设建设 三星、SK海力士砸逾800兆韩元扩产</a></li>\n    <li><a href=\"/new/AI/article-21271.html\" title=\"结合12吋混合键合技术 长鑫存储加速高阶记忆体与3D DRAM布局\">结合12吋混合键合技术 长鑫存储加速高阶记忆体与3D DRAM布局</a></li>\n    <li><a href=\"/new/AI/article-5786.html\" title=\"Waymo再攻4座美国城市 扩张脚步领先特斯拉与Zoox\">Waymo再攻4座美国城市 扩张脚步领先特斯拉与Zoox</a></li>\n  </ul>\n</div>",
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    "createdAt": "2026-08-31T08:40:03.000Z",
    "updatedAt": "2026-10-27T09:34:02.000Z"
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