The document, titled Magnifica Humanitas, is the first encyclical of the American-born pontiff and outlines a comprehensive ethical framework for the governance of artificial intelligence. Leo argued that governments, technology companies and society must ensure that AI serves humanity rather than concentrated political, military or commercial interests.

The publication had been closely anticipated since the pope declared shortly after his election that artificial intelligence represented the most significant challenge facing humanity. In the text, he warned against what he described as a “culture of power” driving the global race to develop increasingly sophisticated AI systems.

Leo directed particular criticism at the use of AI in warfare, declaring that irreversible decisions involving the use of lethal force should never be delegated to autonomous systems. He argued that accountability for military actions must remain firmly in human hands and called for greater transparency in the development and deployment of AI-enabled weapons.

The encyclical also questioned whether traditional Catholic principles governing the ethical use of force remain adequate in an era of rapidly advancing military technologies.

Leo suggested that technological transformations in warfare require renewed moral reflection and updated international safeguards.Beyond security concerns, the pope warned about the concentration of data, wealth and influence among a small number of technology companies.

He argued that ethical commitments by private firms alone were insufficient and called for robust legal frameworks, independent oversight mechanisms and stronger democratic regulation.The Vatican formally presented the document at an event that included participation from representatives of anthropic, one of the world’s leading artificial intelligence companies.

The company’s involvement reflected the Vatican’s long-running engagement with Silicon Valley on the social and ethical implications of emerging technologies.Despite hosting technology executives, Leo repeatedly emphasized that public authorities must not abdicate responsibility for regulating AI.

He urged developers and policymakers to slow the pace of deployment when necessary and to prioritize the common good over commercial gain.The pope framed the AI revolution within the broader tradition of Catholic social teaching. He linked the challenges posed by artificial intelligence to those addressed in Rerum Novarum, the historic 1891 encyclical issued by Pope Leo XIII that examined workers’ rights and the social consequences of industrialization.

Signed on the 135th anniversary of that document, Magnifica Humanitas argues that AI raises comparable questions about labor, economic power and human dignity. Leo warned that the pursuit of efficiency and profit must not come at the expense of workers whose livelihoods could be displaced by automation.

Technology experts and scholars said the encyclical is likely to become an influential reference point in debates surrounding artificial intelligence governance. Taylor Black said the rapid evolution of AI was already prompting deeper questions about the meaning of human identity, while Paolo Carozza described the document as a potentially defining contribution to discussions about the relationship between technology and society.

The manifesto also contained a historic acknowledgment of the Catholic Church’s role in legitimizing slavery during earlier centuries of European expansion. Leo issued the first papal apology specifically addressing the Holy See’s involvement in granting rulers authority to subjugate and enslave non-Christians, extending the document’s focus beyond technology to broader questions of historical responsibility and human dignity.

The encyclical marks the most comprehensive intervention by the Vatican to date on artificial intelligence and places the Catholic Church at the center of a growing global debate over how emerging technologies should be governed as they reshape economies, societies and international security.

Oxford computer scientist and artificial intelligence researcher Michael Wooldridge says the rapid expansion of artificial intelligence is being shaped less by scientific inevitability than by competitive pressures among a small group of technology companies racing to avoid falling behind rivals.

In an interview discussing his latest book, Life Lessons from Game Theory: The Art of Thinking Strategically in a Complex World, Wooldridge argued that many of the current tensions surrounding artificial intelligence can be understood through the framework of game theory, particularly scenarios in which competitors continue escalating despite recognizing collective risks.

Wooldridge, a professor at the University of Oxford and one of Britain’s most prominent public communicators on artificial intelligence, said the industry increasingly resembles a strategic trap in which companies continue investing heavily in advanced systems because they believe competitors would gain advantage if they slowed development.

“We’ve got a small number of very wealthy companies that are busy pursuing AI, while at the same time saying that they are afraid that something’s going to go horribly wrong with it,” Wooldridge said. “So why are they busy pursuing it? Because they think if we back down and we don’t pursue it, somebody else will.

”The comments come amid intensifying global competition over artificial intelligence infrastructure, computing capacity and access to data. Major technology firms including OpenAI and Google DeepMind have expanded investments in large-scale machine learning systems, while governments in the United States, Europe and China are increasingly treating AI as a strategic industry tied to economic growth and national security.

Wooldridge said many of the core technologies underpinning today’s AI systems are not recent discoveries. He noted that key neural network techniques central to modern machine learning were developed by the mid-1980s, but computing power and data limitations prevented their wider deployment at the time.

“The only obstacle standing in the way of the AI revolution in the 1980s, really, was that computers weren’t powerful enough and we didn’t have enough data,” he said.He described the emergence of GPT-3 in 2020 as a turning point driven largely by scale rather than a fundamentally new scientific breakthrough.

According to Wooldridge, many researchers initially doubted whether simply expanding computational power and training data would substantially improve performance. He said the success of that approach surprised a significant portion of the research community.

OpenAI’s development strategy demonstrated that scaling existing methods could generate major commercial results, he said, although he cautioned against interpreting those advances as evidence that artificial general intelligence, or AGI, is imminent.Executives including Sam Altman and Demis Hassabis have publicly discussed the possibility of achieving human-level general intelligence within years. Wooldridge said those forecasts remain overly optimistic.

He argued that current systems still struggle with tasks requiring physical reasoning and adaptation in unfamiliar environments. While advanced chat systems can process complex linguistic queries, he said they remain unable to reliably perform many basic real-world activities that humans execute routinely.

“You can talk to ChatGPT about quantum mechanics in Latin,” Wooldridge said, “but at the same time, we don’t have AI that could come into your house, that it had never seen before, locate the kitchen and clear the dinner table.”Wooldridge said data availability may become one of the industry’s most significant constraints.

He noted that large language models already consume enormous quantities of text and digital material, creating pressure to secure new sources of information for future training cycles.“The whole of Wikipedia made up just 3% of GPT-3’s training data,” he said. “Where do you get 10 times more data from next time around?”That search for data, he argued, could reshape relationships between governments, corporations and individuals.

Wooldridge pointed to healthcare systems, wearable devices and online content creators as examples of potentially valuable data sources for future AI development.“The NHS is sitting on a huge amount of data about human beings,” he said. “That’s the most valuable kind of data imaginable.”He warned that commercial pressure to obtain increasingly detailed behavioral information could create incentives for broader surveillance and monitoring.

Wooldridge suggested future generations of online influencers may routinely agree to extensive data collection arrangements in exchange for visibility and commercial opportunity.The professor’s latest work focuses primarily on game theory, which he defines as the study of interactions between self-interested actors.

He said many geopolitical disputes, commercial rivalries and social conflicts can be interpreted through a relatively small number of strategic models.One recurring example in his analysis is the “game of chicken,” in which opposing sides continue escalating until one party backs down or both suffer severe consequences.

Wooldridge compared the framework to current tensions involving the United States and Iran, describing unpredictability as a recognized strategic tactic within game theory.“You’ve got two sides with ever-escalating threats against each other,” he said. “Somebody’s got to back down at some point.

”Wooldridge added that highly unpredictable behavior can complicate strategic decision-making because opponents struggle to assess likely responses and risks. Under such conditions, he said, game theory often encourages actors to prepare for worst-case outcomes.He also criticized what he described as a growing “zero-sum” political mindset in parts of modern public discourse.

In game theory, he said, zero-sum situations are not merely competitions where one side wins and another loses, but systems where actors are incentivized to maximize damage to opponents.“This zero-sum mentality is very damaging,” Wooldridge said.

“One of the important lessons from game theory is that, actually, the majority of interactions that we’re in are not zero-sum.”He linked that framework to populist political narratives that portray economic or social gains by one group as direct losses for another. As an alternative, Wooldridge highlighted the “Veil of Ignorance,” a philosophical model developed by political philosopher John Rawls in 1971.

The thought experiment asks individuals to design a society without knowing which position they themselves would ultimately occupy within it.Wooldridge said the model creates incentives for fairer social systems because participants must account for the possibility of ending up disadvantaged. He noted that former U.S. presidents Bill Clinton and Barack Obama had both expressed interest in Rawls’ ideas.

Despite concerns surrounding AI development, Wooldridge said he remains optimistic about technology and scientific inquiry. Growing up in rural Herefordshire, he taught himself programming after repeatedly visiting a local electronics shop that displayed a TRS-80 computer in its storefront during the early 1980s.

He later completed a doctorate in artificial intelligence and went on to publish more than 500 scientific papers and multiple books, while also presenting public lectures on the social implications of AI.

Asked whether students should avoid fields vulnerable to automation, Wooldridge rejected the idea that education should be driven solely by labor market forecasts.

“I didn’t get into computing because I thought it was going to give me a good job,” he said. “I got into it because I was just really interested in it.”

Musk, a co-founder of OpenAI, is suing the company, Chief Executive Sam Altman, President Greg Brockman and major investor Microsoft, alleging they abandoned OpenAI’s original mission of developing artificial intelligence for the benefit of humanity and instead turned it into a commercial enterprise focused on profit.

“If we make it okay to loot a charity, the entire foundation of charitable giving in America will be destroyed,” Musk told the court on the first day of trial. “That’s my concern.”Musk is seeking $150 billion in damages from OpenAI and Microsoft, with the proceeds directed to OpenAI’s charitable arm. He is also asking the court to require OpenAI to return to nonprofit control and to remove Altman and Brockman from leadership roles, while seeking Altman’s removal from the board.

The lawsuit includes claims of breach of charitable trust and unjust enrichment and could have significant implications for OpenAI’s governance as the company explores a potential initial public offering that Reuters has previously reported could value it near $1 trillion.

OpenAI lawyer Bill Savitt told jurors during opening arguments that Musk had originally supported the idea of turning OpenAI into a for-profit structure and only sued after failing to gain control of the company and later launching his own rival artificial intelligence venture, xAI.Savitt said Musk wanted “the keys to the kingdom” and pursued litigation only after OpenAI rejected his ambitions to lead the company.

“What he cares about is Elon Musk being on top,” Savitt said. “We are here because Mr Musk didn’t get his way.”OpenAI’s legal team argued that its decision in March 2019 to establish a for-profit entity was necessary to secure the computing resources and talent needed to compete with rivals such as Google’s DeepMind artificial intelligence division.

Musk’s lawyer Steven Molo rejected that argument, saying OpenAI’s leadership shifted focus once major investors, including Microsoft, entered the picture.“It wasn’t a vehicle for people to get rich,” Molo said.Before jurors entered the courtroom, U.S. District Judge Yvonne Gonzalez Rogers warned Musk over his social media activity after OpenAI lawyers raised concerns about his posts on X, where he referred to Altman as “Scam Altman” and accused him of stealing a charity.

Rogers said she was reluctant to impose a gag order but urged Musk to avoid using social media to influence matters outside the courtroom.Musk agreed to reduce his online commentary, as did Altman. Both are expected to testify, along with Microsoft Chief Executive Satya Nadella.

The trial is expected to provide a rare public examination of OpenAI’s evolution from a nonprofit founded in 2015 in Brockman’s apartment into one of the world’s most valuable artificial intelligence companies, currently estimated to be worth more than $850 billion.

Musk testified that his concerns about artificial intelligence safety were central to OpenAI’s founding and intensified after discussions with former U.S. President Barack Obama and with Larry Page, whom he said did not take the risks of advanced AI seriously enough.“We had to have a counterpoint against Google,” Musk said.

OpenAI disputed that characterization, with Savitt telling jurors that Musk had dismissed employees focused on AI safety and that such concerns were not his primary motivation.

Musk has said he contributed about $38 million to OpenAI before leaving its board, later objecting to its restructuring and Microsoft’s multibillion-dollar investment.

Microsoft lawyer Russell Cohen said the company had acted properly throughout its partnership with OpenAI and described it as “a responsible partner every step of the way.”

The meeting, attended by senior administration officials including Scott Bessent and White House Chief of Staff Susie Wiles, comes as policymakers and industry leaders assess the implications of Anthropic’s latest AI model, Mythos, which has raised concerns about its potential to accelerate sophisticated cyberattacks.

In a statement, the White House described the talks as “productive and constructive,” saying both sides discussed collaboration frameworks and shared protocols to address risks associated with scaling advanced AI systems. It added that further engagements with other leading AI firms were planned.

Anthropic said the meeting focused on joint priorities including cybersecurity, maintaining U.S. competitiveness in artificial intelligence, and strengthening safety standards. The dialogue marks the first high-level engagement between the two sides since tensions escalated over national security concerns tied to the company’s technology.

The Mythos model, unveiled earlier this month, is being rolled out to a limited number of organizations under a controlled program known as Project Glasswing. The initiative allows selected users to test the system’s capabilities in identifying cybersecurity vulnerabilities.

Anthropic has described Mythos as its most advanced model for coding and autonomous task execution.Experts warn that such capabilities could be dual-use, enabling both defensive cybersecurity applications and the identification of exploitable weaknesses in digital infrastructure.

Financial institutions are viewed as particularly exposed due to their reliance on legacy systems integrated with modern technologies, creating complex vulnerability surfaces.Officials in the United States, Canada and Britain have held discussions with banking sector leaders to evaluate potential risks posed by advanced AI tools like Mythos, reflecting growing concern across critical sectors.

The renewed engagement follows a breakdown in relations earlier this year between the company and the Pentagon. The Defense Department imposed a supply-chain risk designation on Anthropic after the firm declined to modify safeguards preventing the use of its AI in autonomous weapons or domestic surveillance applications.

In response, the administration ordered federal agencies to halt use of Anthropic’s tools, and Donald Trump publicly criticized the company. Anthropic subsequently filed a lawsuit in March challenging the designation.

Speaking to reporters on Friday, Trump said he was unaware of the meeting, underscoring the fragmented nature of the administration’s engagement with the AI sector as it seeks to balance innovation with national security concerns.

Recent changes to Grok’s image features signal a constructive step in the global effort to balance rapid AI innovation with stronger digital responsibility and user protection frameworks.

Global regulators and technology leaders are increasingly focused on shaping responsible artificial intelligence use.

Recent updates to Grok’s image editing tools reflect this evolving alignment between innovation and accountability.

xAI has moved to restrict certain image editing functions on its Grok chatbot.

The update follows growing international concern around misuse of generative AI tools.

Regulatory bodies across Europe and the United Kingdom welcomed the changes as a positive response.

They view the move as an example of platforms adapting quickly to emerging risks.

The action highlights how dialogue between regulators and technology firms can lead to tangible outcomes.

It also demonstrates the ability of AI developers to refine systems when concerns are raised.

Digital policy experts say the episode underscores the growing maturity of AI governance discussions.

Rather than halting innovation, regulators aim to guide it toward safer applications.

The restrictions introduced by xAI focus on limiting the creation of manipulated or sexualized imagery.

Such steps are designed to protect individuals while preserving legitimate creative and commercial uses.

Observers note that generative AI tools are advancing faster than formal legislation.

Interim measures by companies can therefore play a crucial role in risk reduction.

European officials see this moment as an opportunity to test new digital oversight frameworks.

Existing laws provide mechanisms to ensure platforms act responsibly when challenges arise.

In the United Kingdom, regulators acknowledged the platform’s cooperation while continuing dialogue.

Ongoing reviews are intended to ensure safeguards remain effective over time.

Technology analysts say this development could influence broader industry standards.

Other AI providers may follow similar approaches to avoid misuse of image tools.

The debate also highlights complex questions around consent and digital representation.

Clarifying these concepts is becoming central to future AI policy discussions.

Despite the challenges, many see the recent update as a constructive milestone.

It reflects a willingness by AI firms to engage with public and regulatory expectations.

Industry leaders emphasize that responsible innovation builds long-term trust.

Clear rules and transparent safeguards can encourage wider adoption of AI technologies.

Policy specialists argue that collaboration will be essential as AI capabilities expand.

Governments and developers alike share an interest in predictable, fair digital environments.

The episode has also sparked renewed discussion on global coordination.

AI tools operate across borders, making shared standards increasingly important.

Regulators believe proactive adjustments by companies reduce the need for harsher interventions.

This approach supports innovation while addressing societal concerns early.

Market observers note that investor confidence often benefits from regulatory clarity.

Clear expectations help technology firms plan development and deployment strategies.

As AI-generated content becomes more realistic, oversight frameworks are expected to evolve.

Adaptive governance models may become the norm in fast-moving technology sectors.

Overall, the Grok update reflects a broader shift toward responsible AI deployment.

It signals that progress can be made through engagement, refinement, and shared goals.