Tools & Platforms

Nation boosts global AI governance

Published

2 months ago

July 27, 2025

杨怡

Visitors play mahjong on Saturday with a PsiBot humanoid robot at the opening of the 2025 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance in Shanghai. Ying Tang / Getty Images

As artificial intelligence technologies immensely reshape people’s lifestyles and profoundly influence the global economic and technological development landscape, China, as one of the leading countries in the AI sector, has continuously contributed its wisdom to global AI governance to make AI technologies more secure, reliable, controllable and equitable.

Following President Xi Jinping’s proposal of the Global AI Governance Initiative in 2023, the Chinese government has proposed the creation of a global AI cooperation organization, and it is tentatively considering establishing the organization’s headquarters in Shanghai.

Premier Li Qiang announced the initiative about the organization on Saturday in Shanghai when addressing the opening ceremony of the 2025 World AI Conference and High-Level Meeting on Global AI Governance, a three-day event themed “Global Solidarity in the AI Era”.

Vice-Foreign Minister Ma Zhaoxu said that the initiative is an important move that China has made to practice multilateralism and promote a style of global governance that features extensive consultation and joint contribution for shared benefits.

It is also a concrete action taken by China in response to the call of Global South nations to bridge the digital and intelligence divide, and to promote the inclusive development of AI and the use of AI for good, Ma added.

China expects that the organization will serve as a platform for countries to deepen cooperation on innovation, promote pragmatic cooperation to fully unleash the unlimited potential of AI, and achieve common development and prosperity, Ma said, adding that China is ready to discuss relevant arrangements with countries that are willing to join the organization.

Addressing the conference on Saturday, Premier Li said that the risks and challenges brought by AI development, such as machine hallucination, deep fakes and AI proliferation, have received widespread attention.

There is an urgent need to further consolidate a societal consensus on how to achieve a balance between development and security in the AI sector, he said.

Li highlighted that greater emphasis should be placed on collective governance to ensure that AI ultimately benefits humanity.

Given that global AI governance appears fragmented, it is essential to enhance coordination and alignment among countries around the world to establish a framework and rules for global AI governance with a broad consensus, the premier added.

Noting that China places great importance on global AI governance and actively participates in promoting multilateral and bilateral cooperation in this regard, Li said the nation is willing to offer more Chinese solutions to the international community and contribute more Chinese wisdom to global AI governance.

China actively promotes open source development and is willing to collaborate with countries around the world to promote progress in software and hardware technologies, intensify open source initiatives, and collectively propel AI development to higher levels, he said.

Also on Saturday, the conference adopted the Global AI Governance Action Plan, which calls on all parties to work in solidarity to advance AI development and governance.

In recent years, various Chinese “AI+” technological products and solutions have broken new ground globally.

For example, in Brazil, the Bright Power Large Model developed by State Grid Corp of China has enabled the South American country’s state grid to achieve smart operation and maintenance.

When Sagaing, Myanmar, was struck by a 7.9 magnitude earthquake in March, the DeepSeek-based Chinese-Myanmar-English translation system joined international quake rescue efforts, demonstrating the value of AI language models in emergency rescue situations.

In late 2022, the Passenger Rail Agency of South Africa began deploying Huawei’s AI-powered optical-visual linkage platform to fortify the security of the African country’s century-old railway network. Thanks to the AI knowledge intelligence project jointly developed by Huawei and PRASA, a smart app powered by DeepSeek has helped the country’s railway system to enhance its efficiency in operations and maintenance.

Meanwhile, in a landmark announcement at the 2025 World AI Conference on Saturday, the China Meteorological Administration unveiled “MAZU”, a comprehensive national early warning solution poised to reshape global disaster preparedness.

Named after a revered sea goddess and protector against natural disasters in Chinese coastal culture, MAZU stands for “multihazard, alert, zero-gap and universal”. It is a proactive, AI-driven initiative designed to share China’s advanced meteorological technology and experience with the world, particularly focusing on developing countries that face the brunt of climate change impacts.

Anne Bouverot, the special envoy of French President Emmanuel Macron for AI, spoke positively of China’s role in global AI governance, highlighting the importance of international cooperation in AI development.

“There is an urgency for global action toward openness, accessibility and inclusiveness. For this to happen, a strong, inclusive global governance framework for AI must be established,” she said.

During a “Fireside Chat” on Saturday at the opening ceremony of the World AI Conference, Harry Shum, former executive vice-president of Microsoft, and Eric Schmidt, former CEO of Google, underlined the need for transnational cooperation to set rules for global competition and collaboration in AI.

While explaining his view on Sino-US cooperation on AI, Schmidt quoted former US secretary of state Henry Kissinger, saying that “as long as both sides have common goals, they can reach an agreement”.

He pointed out that some key issues must be discussed. “We should sit down and clarify them, such as whether AI can control weapons, replicate itself and learn automatically.”

Schmidt added: “I’m a genuine optimist. China and the United States can build trust from the bottom, step by step. It’s been done before, and it can be done again.”

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Tools & Platforms

The rise of AI tools forces schools to reconsider what counts as cheating

Published

1 hour ago

September 14, 2025

The Editors

By JOCELYN GECKER
Associated Press

The book report is now a thing of the past. Take-home tests and essays are becoming obsolete.

Student use of artificial intelligence has become so prevalent, high school and college educators say, that to assign writing outside of the classroom is like asking students to cheat.

“The cheating is off the charts. It’s the worst I’ve seen in my entire career,” says Casey Cuny, who has taught English for 23 years. Educators are no longer wondering if students will outsource schoolwork to AI chatbots. “Anything you send home, you have to assume is being AI’ed.”

The question now is how schools can adapt, because many of the teaching and assessment tools that have been used for generations are no longer effective. As AI technology rapidly improves and becomes more entwined with daily life, it is transforming how students learn and study and how teachers teach, and it’s creating new confusion over what constitutes academic dishonesty.

“We have to ask ourselves, what is cheating?” says Cuny, a 2024 recipient of California’s Teacher of the Year award. “Because I think the lines are getting blurred.”

Cuny’s students at Valencia High School in southern California now do most writing in class. He monitors student laptop screens from his desktop, using software that lets him “lock down” their screens or block access to certain sites. He’s also integrating AI into his lessons and teaching students how to use AI as a study aid “to get kids learning with AI instead of cheating with AI.”

In rural Oregon, high school teacher Kelly Gibson has made a similar shift to in-class writing. She is also incorporating more verbal assessments to have students talk through their understanding of assigned reading.

“I used to give a writing prompt and say, ‘In two weeks, I want a five-paragraph essay,’” says Gibson. “These days, I can’t do that. That’s almost begging teenagers to cheat.”

Take, for example, a once typical high school English assignment: Write an essay that explains the relevance of social class in “The Great Gatsby.” Many students say their first instinct is now to ask ChatGPT for help “brainstorming.” Within seconds, ChatGPT yields a list of essay ideas, plus examples and quotes to back them up. The chatbot ends by asking if it can do more: “Would you like help writing any part of the essay? I can help you draft an introduction or outline a paragraph!”

Students are uncertain when AI usage is out of bounds

Students say they often turn to AI with good intentions for things like research, editing or help reading difficult texts. But AI offers unprecedented temptation, and it’s sometimes hard to know where to draw the line.

College sophomore Lily Brown, a psychology major at an East Coast liberal arts school, relies on ChatGPT to help outline essays because she struggles putting the pieces together herself. ChatGPT also helped her through a freshman philosophy class, where assigned reading “felt like a different language” until she read AI summaries of the texts.

“Sometimes I feel bad using ChatGPT to summarize reading, because I wonder, is this cheating? Is helping me form outlines cheating? If I write an essay in my own words and ask how to improve it, or when it starts to edit my essay, is that cheating?”

Her class syllabi say things like: “Don’t use AI to write essays and to form thoughts,” she says, but that leaves a lot of grey area. Students say they often shy away from asking teachers for clarity because admitting to any AI use could flag them as a cheater.

Schools tend to leave AI policies to teachers, which often means that rules vary widely within the same school. Some educators, for example, welcome the use of Grammarly.com, an AI-powered writing assistant, to check grammar. Others forbid it, noting the tool also offers to rewrite sentences.

“Whether you can use AI or not depends on each classroom. That can get confusing,” says Valencia 11th grader Jolie Lahey. She credits Cuny with teaching her sophomore English class a variety of AI skills like how to upload study guides to ChatGPT and have the chatbot quiz them, and then explain problems they got wrong.

But this year, her teachers have strict “No AI” policies. “It’s such a helpful tool. And if we’re not allowed to use it that just doesn’t make sense,” Lahey says. “It feels outdated.”

Schools are introducing guidelines, gradually

Many schools initially banned use of AI after ChatGPT launched in late 2022. But views on the role of artificial intelligence in education have shifted dramatically. The term “AI literacy” has become a buzzword of the back-to-school season, with a focus on how to balance the strengths of AI with its risks and challenges.

Over the summer, several colleges and universities convened their AI task forces to draft more detailed guidelines or provide faculty with new instructions.

The University of California, Berkeley emailed all faculty new AI guidance that instructs them to “include a clear statement on their syllabus about course expectations” around AI use. The guidance offered language for three sample syllabus statements — for courses that require AI, ban AI in and out of class, or allow some AI use.

“In the absence of such a statement, students may be more likely to use these technologies inappropriately,” the email said, stressing that AI is “creating new confusion about what might constitute legitimate methods for completing student work.”

Carnegie Mellon University has seen a huge uptick in academic responsibility violations due to AI, but often students aren’t aware they’ve done anything wrong, says Rebekah Fitzsimmons, chair of the AI faculty advising committee at the university’s Heinz College of Information Systems and Public Policy.

For example, one student who is learning English wrote an assignment in his native language and used DeepL, an AI-powered translation tool, to translate his work to English. But he didn’t realize the platform also altered his language, which was flagged by an AI detector.

Enforcing academic integrity policies has become more complicated, since use of AI is hard to spot and even harder to prove, Fitzsimmons said. Faculty are allowed flexibility when they believe a student has unintentionally crossed a line, but are now more hesitant to point out violations because they don’t want to accuse students unfairly. Students worry that if they are falsely accused, there is no way to prove their innocence.

Over the summer, Fitzsimmons helped draft detailed new guidelines for students and faculty that strive to create more clarity. Faculty have been told a blanket ban on AI “is not a viable policy” unless instructors make changes to the way they teach and assess students. A lot of faculty are doing away with take-home exams. Some have returned to pen and paper tests in class, she said, and others have moved to “flipped classrooms,” where homework is done in class.

Emily DeJeu, who teaches communication courses at Carnegie Mellon’s business school, has eliminated writing assignments as homework and replaced them with in-class quizzes done on laptops in “a lockdown browser” that blocks students from leaving the quiz screen.

“To expect an 18-year-old to exercise great discipline is unreasonable,” DeJeu said. “That’s why it’s up to instructors to put up guardrails.”

___

The Associated Press’ education coverage receives financial support from multiple private foundations. AP is solely responsible for all content. Find AP’s standards for working with philanthropies, a list of supporters and funded coverage areas at AP.org.

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Tools & Platforms

Vibe coding has turned senior devs into ‘AI babysitters,’ but they say it’s worth it

Published

2 hours ago

September 14, 2025

Dominic-Madori Davis

Carla Rover once spent 30 minutes sobbing after having to restart a project she vibe coded.

Rover has been in the industry for 15 years, mainly working as a web developer. She’s now building a startup, alongside her son, that creates custom machine learning models for marketplaces.

She called vibe coding a beautiful, endless cocktail napkin on which one can perpetually sketch ideas. But dealing with AI-generated code that one hopes to use in production can be “worse than babysitting,” she said, as these AI models can mess up work in ways that are hard to predict.

She had turned to AI coding in a need for speed with her startup, as is the promise of AI tools.

“Because I needed to be quick and impressive, I took a shortcut and did not scan those files after the automated review,” she said. “When I did do it manually, I found so much wrong. When I used a third-party tool, I found more. And I learned my lesson.”

She and her son wound up restarting their whole project — hence the tears. “I handed it off like the copilot was an employee,” she said. “It isn’t.”

Rover is like many experienced programmers turning to AI for coding help. But such programmers are also finding themselves acting like AI babysitters — rewriting and fact-checking the code the AI spits out.

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A recent report by content delivery platform company Fastly found that at least 95% of the nearly 800 developers it surveyed said they spend extra time fixing AI-generated code, with the load of such verification falling most heavily on the shoulders of senior developers.

These experienced coders have discovered issues with AI-generated code ranging from hallucinating package names to deleting important information and security risks. Left unchecked, AI code can leave a product far more buggy than what humans would produce.

Working with AI-generated code has become such a problem that it’s given rise to a new corporate coding job known as “vibe code cleanup specialist.”

TechCrunch spoke to experienced coders about their time using AI-generated code about what they see as the future of vibe coding. Thoughts varied, but one thing remained certain: The technology still has a long way to go.

“Using a coding co-pilot is kind of like giving a coffee pot to a smart six-year-old and saying, ‘Please take this into the dining room and pour coffee for the family,’” Rover said.

Can they do it? Possibly. Could they fail? Definitely. And most likely, if they do fail, they aren’t going to tell you. “It doesn’t make the kid less clever,” she continued. “It just means you can’t delegate [a task] like that completely.”

“You’re absolutely right!”

Feridoon Malekzadeh also compared vibe coding to a child.

He’s worked in the industry for more than 20 years, holding various roles in product development, software, and design. He’s building his own startup and heavily using vibe-coding platform Lovable, he said. For fun, he also vibe codes apps like one that generates Gen Alpha slang for Boomers.

He likes that he’s able to work alone on projects, saving time and money, but agrees that vibe coding is not like hiring an intern or a junior coder. Instead, vibe coding is akin to “hiring your stubborn, insolent teenager to help you do something,” he told TechCrunch.

“You have to ask them 15 times to do something,” he said. “In the end, they do some of what you asked, some stuff you didn’t ask for, and they break a bunch of things along the way.”

Malekzadeh estimates he spends around 50% of his time writing requirements, 10% to 20% of his time on vibe coding, and 30% to 40% of his time on vibe fixing — remedying the bugs and “unnecessary script” created by AI-written code.

He also doesn’t think vibe coding is the best at systems thinking — the process of seeing how a complex problem could impact an overall result. AI-generated code, he said, tries to solve more surface-level problems.

“If you’re creating a feature that should be broadly available in your product, a good engineer would create that once and make it available everywhere that it’s needed,” Malekzadeh said. “Vibe coding will create something five different times, five different ways, if it’s needed in five different places. It leads to a lot of confusion, not only for the user, but for the model.”

Meanwhile, Rover finds that AI “runs into a wall” when data conflicts with what it was hard-coded to do. “It can offer misleading advice, leave out key elements that are vital, or insert itself into a thought pathway you’re developing,” she said.

She also found that rather than admit to making errors, it will manufacture results.

She shared another example with TechCrunch, where she questioned the results an AI model initially gave her. The model started to give a detailed explanation pretending it used the data she uploaded. Only when she called it out did the AI model confess.

“It freaked me out because it sounded like a toxic co-worker,” she said.

On top of this, there are the security concerns.

Austin Spires is the senior director of developer enablement at Fastly and has been coding since the early 2000s.

He’s found through his own experience — along with chatting with customers — that vibe code likes to build what is quick rather than what is “right.” This may introduce vulnerabilities to the code of the kind that very new programmers tend to make, he said.

“What often happens is the engineer needs to review the code, correct the agent, and tell the agent that they made a mistake,” Spires told TechCrunch. “This pattern is why we’ve seen the trope of ‘you’re absolutely right’ appear over social media.”

He’s referring to how AI models, like Anthropic Claude, tend to respond “you’re absolutely right” when called out on their mistakes.

Mike Arrowsmith, the chief technology officer at the IT management software company NinjaOne, has been in software engineering and security for around 20 years. He said that vibe coding is creating a new generation of IT and security blind spots to which young startups in particular are susceptible.

“Vibe coding often bypasses the rigorous review processes that are foundational to traditional coding and crucial to catching vulnerabilities,” he told TechCrunch.

NinjaOne, he said, counters this by encouraging “safe vibe coding,” where approved AI tools have access controls, along with mandatory peer review and, of course, security scanning.

The new normal

While nearly everyone we spoke to agrees that AI-generated code and vibe-coding platforms are useful in many situations — like mocking up ideas — they all agree that human review is essential before building a business on it.

“That cocktail napkin is not a business model,” Rover said. “You have to balance the ease with insight.”

But for all the lamenting on its errors, vibe coding has changed the present and the future of the job.

Rover said vibe coding helped her tremendously in crafting a better user interface. Malekzadeh simply said that, despite the time he spends fixing code, he still gets more done with AI coders than without them.

“‘Every technology carries its own negativity, which is invented at the same time as technical progress,” Malekzadeh said, quoting the French theorist Paul Virilio, who spoke about inventing the shipwreck along with the ship.

The pros far outweigh the cons.

The Fastly survey found that senior developers were twice as likely to put AI-generated code into production compared to junior developers, saying that the technology helped them work faster.

Vibe coding is also part of Spires’ coding routine. He uses AI coding agents on several platforms for both front-end and back-end personal projects. He called the technology a mixed experience but said it’s good in helping with prototyping, building out boilerplate, or scaffolding out a test; it removes menial tasks so that engineers can focus on building, shipping, and scaling products.

It seems the extra hours spent combing through the vibe weeds will simply become a tolerated tax on using the innovation.

Elvis Kimara, a young engineer, is learning that now. He just graduated with a master’s in AI and is building an AI-powered marketplace.

Like many coders, he said vibe coding has made his job harder and has often found vibe coding a joyless experience.

“There’s no more dopamine from solving a problem by myself. The AI just figures it out,” he said. At one of his last jobs, he said senior developers didn’t look to help young coders as much — some not understanding new vibe-coding models, while others delegated mentorship tasks to said AI models.

But, he said, “the pros far outweigh the cons,” and he’s prepared to pay the innovation tax.

“We won’t just be writing code; we’ll be guiding AI systems, taking accountability when things break, and acting more like consultants to machines,” Kimara said of the new normal for which he’s preparing.

“Even as I grow into a senior role, I’ll keep using it,” he continued. “It’s been a real accelerator for me. I make sure I review every line of AI-generated code so I learn even faster from it.”

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