OpenAI boss says world ‘right to be afraid’ but ‘should trust’ AI firms
AI Leaders Debate Whether Industry Can Police Itself
Constantvpn.com – Growing concern over the speed of artificial intelligence development has put renewed focus on who should decide when powerful new systems are safe enough for public release. At a technology conference in San Francisco on Tuesday, OpenAI chief executive Sam Altman argued that AI companies must earn public confidence while also acknowledging that fears about the technology are understandable.
Altman said people should believe that major AI developers recognise the seriousness of the choices before them. He described the responsibility as more than a business question, saying companies working on advanced AI understand the scale of possible consequences.
“The world should trust that we are going to do the right thing because it's the right thing and we feel the magnitude of this.”
At the same time, Altman did not dismiss public anxiety. He said the fast rise in AI capability has made harmful scenarios easier to picture than they were in the past.
“It doesn't take as much imagination as it used to for [us] to imagine how this could go wrong.”
“I think the world is right to be afraid of this.”
Pressure grows after warnings from inside the sector
The discussion intensified after a former Anthropic researcher published a widely shared warning last week, claiming unchecked AI could lead to human extinction before the end of the decade. Several executives and specialists in the field said they shared the concern, although they did not set out a detailed explanation of how such an outcome might occur.
The warning prompted fresh scrutiny of the companies creating frontier AI models. Anthropic chief executive Dario Amodei called for slower overall development and urged governments to establish rules for the sector. His intervention received public support from Altman, Google DeepMind co-founder Demis Hassabis and Elon Musk, who owns X and is connected to the Grok AI assistant.
Yet the San Francisco conference also exposed a competing view: that companies should retain broad discretion over how they test, improve and release their systems. Altman said he was confident that developers could manage the risks themselves, provided safety work remains ahead of the push for more capable products.
“We will get it right, I'm very confident in our company's and industry's ability to do this safely.”
He said AI firms would keep “alignment and safety way ahead of capabilities,” and would slow development or halt it if that balance could not be maintained. Alignment refers to efforts to ensure an AI system behaves in ways intended by its creators and does not produce damaging or unwanted outcomes.
Executives argue safety incentives already exist
Meta chief executive Mark Zuckerberg made a similar case on X, writing that each AI laboratory can take action to build models with safety in mind. He argued that companies that ignore alignment will lose ground to competitors and face substantial legal exposure if their products cause harm.
Nvidia chief executive Jensen Huang also spoke at the Salesforce gathering, saying decisions on releasing new AI systems should be made by the companies that build them rather than imposed by outside authorities. Nvidia has become the world’s most highly valued company as demand has surged for the computing chips used to train and operate AI systems.
“We don't need new laws or regulations.”
Huang rejected the idea that society must choose between rapid innovation and safer products. In his view, safety can be addressed through engineering, testing and responsible release decisions.
“Safety is paramount. However, safety is an engineering problem.”
He added that leaders should stop a launch if they are not confident in the product or in their organisation’s ability to manage it.
“Run as fast as you can, but if at any time you feel the institution is not in control, take a pause.”
Why self-regulation remains controversial
The central disagreement is not whether AI safety matters, but whether voluntary commitments are enough. Companies have strong reasons to avoid flawed products, including reputational damage, legal liability and the possibility of losing customers. Supporters of self-regulation say those pressures, combined with internal testing and technical safeguards, can encourage responsible conduct without slowing useful innovation through rigid rules.
Critics respond that commercial incentives can also push companies to release systems quickly, particularly when rivals are moving fast. They argue that risks affecting workers, businesses, public trust and cybersecurity may extend beyond the interests of any single company. For them, independent oversight is needed precisely because the consequences of a serious failure could be shared widely.
Jack Clark, an Anthropic executive and co-founder, said leaving AI as a completely unregulated field would mean taking enormous risks. His view reflects concern that voluntary promises may not provide enough accountability when companies are racing to build increasingly advanced models.
Patrick Hillman, chief operating officer of Logical Intelligence, also highlighted the public’s limited trust in technology companies acting solely for the wider good. Logical Intelligence is chaired by Yann LeCun, a prominent figure in AI research.
Risks go beyond extinction scenarios
Debate about AI often focuses on dramatic warnings about humanity’s future, but more immediate issues are already shaping business decisions. Altman told the conference audience that companies should use AI to improve their work while also preparing for cyber threats that may be strengthened by the same technology.
AI tools can help organisations analyse information, automate routine work and support customer services. But they can also lower the barrier for more convincing scams, automated phishing efforts and other cyber attacks. That makes safety a practical concern for businesses now, rather than only a question about distant future systems.
The argument over regulation is therefore likely to remain central as AI becomes more capable and more widely used. Public confidence will depend not just on assurances from leading companies, but on visible evidence that safety testing, accountability and restraint are applied when they are needed most.
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