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Rise of AI performers triggers concerns about human actors_我的网站

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    The Girl Who Was FiredA virtual AI actress has gathered massive followers and stirred widespread heated debate on Chinese social media - unlike conventional celebrities, this breakout star is entirely artificially generated.
Fang Taozi, an AI-generated character who stars in the hit AI short drama series The Girl Who Was Fired, has posted lifestyle vlogs, launched social media accounts, shared her breakfasts, workouts and pets, landed brand deals and has a fanbase.
Since the drama debuted on short video platform Douyin on June 12, it has accumulated 200 million views. Fang's Douyin account has attracted more than 400,000 followers.
Fans interact with her as if she were a real celebrity, creating fan edits, discussing fictional relationships and building a community around her imagined life.
This raises a question that has become increasingly urgent for the entertainment industry: Does Fang Taozi represent the first generation of AI celebrities? The answer depends on how "celebrity" is defined, said Zhang Peng, a cultural researcher and associate professor at Nanjing Normal University, in an interview.
If celebrity status is measured by public attention, emotional connection and commercial value, Fang appears to meet many of the criteria. She has fans, a personal brand and even advertising opportunities. 
Whether AI can truly become stars depends not on the technology itself, but on their ability to forge genuine emotional connections with audiences and sustain their appeal over time, added Zhang. 
However, Shi Wenxue, a Beijing-based cultural critic, argues that AI stars have indeed emerged, but they should be viewed as part of the broader lineage of virtual idols.
From the 1958 US virtual musical group Alvin and the Chipmunks to Hatsune Miku, Luo Tianyi and the hyper-realistic digital human Liu Yexi, virtual performers have existed in various forms for decades. 
From the perspective of how she is created, Fang Taozi represents a technological advance. Her emergence is largely a product of the current economic environment of the film and television industry.
The rise of AI performers has also triggered concerns among human actors, especially those working in smaller productions.
Human performers bring personal experience, emotional interpretation and unpredictability - qualities that remain difficult to reproduce. But for industries that require large volumes of affordable content, AI characters offer obvious advantages: They do not age, can work continuously and can be customized for different audiences.
AI short dramas are cheaper, faster and free from the risks associated with human performers, raising concerns over the future of lower-level entertainment jobs in areas such as short dramas, advertising, background acting and voice work, said Zhang.
In Shi's view, beneath the debate lies a familiar tension: technological efficiency versus the threat of displacement for human workers.
The question is not whether AI will completely replace actors, but which parts of acting and entertainment can be automated, he noted.
Rather than presenting an AI figure only as a digital image, Chinese platforms appear to be building complete entertainment ecosystems around AI characters, including dramas, social accounts, fan interactions and commercial partnerships.
China's AI stars have grown out of the audience's desire for emotional companionship, while Hollywood's AI experiments have been shaped by industry battles over efficiency and costs, noted Zhang. 
According to Shi, Fang Taozi's sudden popularity is, in many ways, a reflection of audience psychology. Whether they are moviegoers, fans or casual viewers, audiences have grown weary of formulaic content, scripted fan service, predictable performances and fragile celebrity personas. An idol like Fang Taozi offers an alternative: She cannot be involved in scandals, play diva or break character, and her persona can be adjusted to meet audience demands. But the model also comes with risks, particularly the limitations of its creators and the potential for excessive commercialization.
。    第1名：威少（+30.3）          威少断档第一并不让人意外，反而很符合他的比赛特点。巅峰时期的威少是MVP级别球星，冲击力、转换和篮板能力都极其突出，可他的打法同样建立在大量持球和高风险决策之上，失误、外线投篮选择以及关键时刻的强攻，都会累计大量负面回合。

B | 进入生涯后期，随着运动能力下降，过去能够依靠身体完成的进攻越来越难，投射短板也被进一步放大，这导致威少该数据断档高居第一，也变相解释了为何今夏他迟迟找不到合适的下家。         第2名：追梦格林（+17.5）          相比之下，追梦排在第二让人有些意外。勇士王朝时期，他一直是球队防守和组织体系的重要核心，掩护、传球和防守指挥很难完全体现在普通数据里。之所以高居第二是追梦的短板太过明显，随着外线威胁下降，对手越来越敢放空他，当库里被夹击之后，追梦能不能处理好4打3，直接决定勇士进攻质量。再加上部分冒险传球，以及技术犯规和情绪问题，他确实经常制造负面效果，这也是追梦这类体系球员的通病，优势和短板都容易被放大。         3-5名：斯马特、拉塞尔、库兹马          斯马特+13.3排名第三，拉塞尔+13.2第四，库兹马+10.7第五。斯马特防守、拼抢和精神属性突出，可进攻端偶尔会承担超过自身能力的任务，导致数据不够好看，拉塞尔拥有投射和组织能力，高强度比赛下的稳定性却长期受到质疑，库兹马则是在持球和使用率增加之后，效率与决策问题更加明显。三个人风格不同，排名靠前的共同原因都是承担了过大的进攻责任，因而产生了较多失败回合。         第六名：东契奇（+9.8）          东契奇进入前六，是榜单最大的讨论点之一。

C | 如果把“失败贡献值”直接理解成拖累球队，那显然解释不通。东契奇长期承担极高球权，大量进攻都由他发起，自然也会积累更多失误、强投和失败回合。一个每场只处理几次球的角色球员，很难产生同样规模的负面数据，因此值得讨论的是，高持球打法本来就有两面性。当东契奇体能下降、比赛陷入连续单打，或者防守投入不足时，这种模式的负面影响也会被同步放大。         7-10名：大球、卢比奥、普尔、特雷-杨          大球和卢比奥同为+8.9，普尔+8.0，特雷-杨+7.2。

D | 其中普尔和特雷-杨都属于进攻创造力强、状态波动巨大的后卫，尤其特雷-杨，与东契奇类似，需要承担大量挡拆和持球任务，创造高质量机会的同时，失误和高难度出手也很难避免。

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Published on:09:39:47