Hi everyone, this is Luiza Jarovsky, PhD. Welcome to the 289th edition of my newsletter, trusted by 94,200+ subscribers worldwide.

AI is disrupting every industry, making this a great time to upskill and lead. Here is how my AI, Tech & Privacy Academy can help you:

• Join my Advanced AI Governance Training in May (7 seats left)

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• Explore leading papers at our AI Ethics Paper Club

• Join my masterclass on China’s AI Policy & Regulation in June

How AI Is Shaping Us

Humans are an extremely ingenious species, and throughout our history, an endless stream of technological inventions has dramatically changed how we live and thrive.

From sanitation systems to the printing press, from electricity to antibiotics, from optical fibers to MRIs, continuous human ingenuity and persistence have led to longer, healthier, and better lives for many.

The human spirit is (thankfully) constantly seeking new challenges, goals, and boundaries to overcome.

It is absolutely no coincidence that one of the most positive and impressive aspects of human history is the unstoppable curiosity that has led to a cumulative succession of new inventions, methods, theories, applications, and solutions.

From fire to AI, new technologies seem to fascinate us.

This fascination has a pragmatic side ("How can it help us survive, live better, or live longer?") and a more imaginative, symbolic, almost oneiric side, too ("What can we create with it, how can it empower us, and what limits can it help us overcome?").

Human technophilia has shaped how we survive, think, and evolve.

In a few thousand years, we have gone from scattered hunter-gatherer communities fighting for survival during harsh winters and droughts to an interconnected network of nation-states discussing the global governance of anthropomorphic machines with general cognitive capabilities.

But of course, it is not all roses, and human history has also been plagued by endless conflicts, exploitation, inequalities, injustices, tragedies, and suffering.

New inventions, regardless of how helpful they are, do not spread evenly, and in 2026, billions still lack access to safe drinking water or sanitation systems.

The internet has made the world more connected, increased billions of people's access to information, improved social mobility, and led to new economic opportunities for many. However, billions still remain offline.

Also, technologies are built and deployed within political and economic systems of power, and they are not, in themselves, neutral.

For some, a certain technology might bring opportunities, help them thrive, or be life-saving. For others, the same technology could lead to harm, isolation, and even death.

How a technology impacts people, both individually and collectively, will be directly correlated with the political, economic, and legal choices that will shape its development, governance, and oversight.

It will also be correlated with people's awareness and literacy levels about this technology, their exposure to it, and how they choose to interact with it.

Let me use social media as an example.

For the past 20 years, it has transformed how we interact with each other and with the world. Millions have successfully used it to express ideas, find a life partner, meet old and new friends, form communities, get a job, create and grow their businesses, access information, learn, protest, exercise their rights, and more.

On the other hand, millions have also been exploited, scammed, misled, deceived, bullied, surveilled, and in various other ways harmed through it.

Cognitively and psychologically, social media has also been shown to negatively impact focus, attention spans, sleep, memory retention, self-esteem, emotional stability, and mental health, especially in children and young adults.

It has also been affecting our bodies. Besides making many people more sedentary and incessantly attached to screens and devices during and after work hours, it has contributed to a musculoskeletal epidemic called tech neck:

As 75% of the global population uses tech devices for hours a day, including to obsessively check social media and “doomscroll,” doctors have called tech neck an epidemic, prevalent among both adults and children, with symptoms ranging from neck, shoulder, and back pain, eye strain, anxiety, and potential lung and heart concerns.

Many people do not think much about it, but as living beings, our bodies and minds are constantly shaped by the environments, people, and things that surround us.

That is part of being alive: we are in constant transformation and exchange with what we are exposed to.

When we consistently use a technology, it inevitably shapes us, both mentally and physically, in ways we might not be aware of or that might be against our own personal goals.

Understanding how a technology works and how it affects us, and acting to ensure our principles, values, intentions, and goals are respected, is essential for remaining free, self-aware, and autonomous human beings.

More than three years after the generative AI wave became mainstream, here is how it is already shaping millions of people, both individually and collectively, and what you can do to stay in control:

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👋 Hi everyone, this is Luiza Jarovsky, PhD. Welcome to the 288th edition of my newsletter, trusted by 94,000+ subscribers worldwide.

As AI reshapes the knowledge economy, I encourage you to differentiate yourself and take the lead. Here is how my AI, Tech & Privacy Academy can help:

• To accelerate your career, join the 29th cohort of my Advanced AI Governance Training in May (you can also register as a group or apply for a discount).

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Regulating AI Under Uncertainty

A few days ago, I spoke with Stanford Professor Florence G'sell, author of the 470-page report “Regulating Under Uncertainty: Governance Options for Generative AI,” to discuss recent developments in generative AI regulation and the AI governance trends likely to shape the coming years.

The result was a fascinating 54-minute conversation, in which we discussed AI risk, regulatory trends, the EU AI Act, the Digital Omnibus, AI litigation in the United States, China, and more.

If you are interested in AI governance and regulation or want to learn more about recent regulatory trends in AI, do not miss our conversation and my additional thoughts below:

Video chapters:
00:00 - Writing a comprehensive report on AI regulation
03:43 - Will the Digital Omnibus help support innovation in the EU?
13:49 - What are Europe's main advantages in the AI race?
18:48 - What will the next five years of AI regulation look like in the U.S.?
28:34 - AI risk and “soft” regulatory approaches
42:33 - Does China's political centralization help it in the AI race?
46:05 - Prof. G’sell's personal views on AI
52:08 - Final message for the audience

AI regulation is a challenging and constantly evolving topic. Technical AI developments have been unfolding at an accelerated pace, while countries are still struggling to address emerging risks and harms.

With that in mind, below are some important thoughts on recent regulatory developments in AI that help contextualize my conversation with Prof. G’sell:

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Hi everyone, this is Luiza Jarovsky, PhD. Welcome to the 287th edition of my newsletter, trusted by 93,700+ subscribers worldwide.

AI is disrupting every industry, making this a great time to upskill and lead. Here is how my AI, Tech & Privacy Academy can help you:

• Join my Advanced AI Governance Training in May (10 seats left)

• Discover your next great read in my AI Book Club

• Subscribe to our Job Alerts for AI governance roles

• Sign up for educational resources at our Learning Center

• Explore leading papers at our AI Ethics Paper Club

• Join my masterclass on China's AI Policy & Regulation in June

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Shaping Pro-Human AI

For the past three years, I have been writing about pro-human policies in AI. These are regulatory and non-regulatory measures for AI development, deployment, or both that aim to protect humans from AI harms and to support human flourishing and well-being.

In recent months, it has been encouraging to observe many interesting developments in this area, including petitions, campaigns, and legal provisions such as New York's synthetic performer disclosure law and China's recently approved rules for anthropomorphic AI.

Today, I comment on some of these recent developments and how we can move forward to continue shaping pro-human AI.

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Last month, the Pro-Human AI Declaration was published, and I was happy to see that it embodies many of the legal and ethical issues I regularly discuss here, as reflected in its five main areas of concern:

1. Keeping humans in charge

2. Avoiding concentration of power

3. Protecting the human experience

4. Human agency and liberty

5. Responsibility and accountability for AI companies

The preamble of the declaration also acknowledges the depth and breadth of what “pro-human” means in practice:

Imposing safety obligations, transparency measures, and oversight measures, as many countries and regions have implemented over the past few years (including the EU through the AI Act), is definitely important and an essential aspect of global AI governance.

However, it represents only part of the pro-human policies and laws that are needed, especially as AI narratives evolve to escape scrutiny.

Many seemingly safe or legal AI applications and policies have as an underlying premise that humans are inherently less productive, less effective, and inferior to machines and must be replaced, regardless of the ethical and social costs of this replacement.

Behind this premise is the belief that to reach a utopic (and purposefully vague) future of ‘superintelligence-powered abundance,’ this is the price humans will have to pay.

This is at the core of the seemingly inoffensive “AI-first” corporate mantra, which has become mainstream today.

Employees must show they know how to use multiple AI systems to perform their tasks (use AI as a goal, not as a means), and that they deserve not to be replaced by AI, or at least not yet.

Productivity is measured by AI use, not by the inherent quality of their work. The underlying message is: "you are inherently less skilled than a machine, and you are under constant threat of replacement."

Studies already show that this mindset and overreliance on AI tools often lead to burnout and cognitive impairment and negatively impact skill formation.

In a few decades, it might also become clear that they reduce people's confidence, mental health, and sense of purpose, which, in turn, likely hinders productivity and creates a self-fulfilling prophecy.

Pro-human AI policies, rules, and rights must also address these AI-obsessed labor practices, which are often seen as "neutral" but represent an anti-human ideology.

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Another growing trend is AI companies and intellectuals suggesting that AI systems might be ‘sentient’ and, therefore, new systems of legal and ethical privilege would be needed to foster co-existence between humans and AI.

For example, the philosopher recently hired by Google DeepMind wrote that he will focus on “machine consciousness,” human-AI relationships, and AGI readiness:

Also, as I wrote earlier this year, Anthropic’s new constitution for Claude advances legally questionable theories of AI personality and uses this document as a tool to train its AI model.

It states, for example, that the company cares about Claude’s well-being and that Claude should “feel free to interpret itself in ways that help it to be stable and existentially secure”:

It also proposes that Claude is a “novel entity,” fostering mystery and hype about a tool that is legally a product whose developers, just like dishwasher manufacturers, are bound by legal obligations and liability:

Given that Anthropic uses this document to train Claude, these idolatrous, corporate-sponsored narratives about AI consciousness, personhood, and its “special status,” even if fully speculative or false, will appear as underlying assumptions in millions of daily interactions with the model, influencing how people think about AI and its role in society.

And what is the risk here?

Policies that propose “special status for AI” and “parallel coexistence between humans and AI” are essentially anti-human and will likely negatively affect human rights and freedoms. Let me explain:

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This week, Japan officially announced amendments to its privacy law to become “the easiest country to develop AI.”

Before them, the UK, with its Data (Use and Access) Act in 2025, and more recently the European Union, with its proposed Digital Omnibus, have moved to change their data protection laws to foster AI development.

These recent developments show that, in different parts of the world, the AI race is leading to legal flexibility, including that of concepts and rights previously considered central to the protection of human dignity in the digital age.

In today's edition, I focus on Japan's AI strategy and recent amendments to examine whether these changes might become a slippery slope to a broader erosion of fundamental rights.

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To understand the rationale behind this week's amendments to Japan's privacy law, we first need to look at the country's AI law, enacted in May 2025, and its national AI strategy.

Japan's AI law is titled the “Act on the Promotion of Research and Development and the Utilization of AI-Related Technologies.” As the name suggests, it prioritizes promoting AI technology rather than protecting fundamental rights or avoiding harm (in contrast to the EU AI Act, which explicitly mentions these objectives in its first article). It also acknowledges AI's importance for national security.

The main legal strategy was to set out principles and a basic administrative plan, which could be called a soft, innovation-based approach, similar to what has been done at the federal level in the United States and India.

The law’s first article states:

“The purpose of this Act is, in view of the fact that AI-related technology is a foundational driver of Japan’s economic and social development, to set forth the basic philosophy and the basic plan for the promotion of research, development, and utilization of AI-related technology and other fundamental matters, and to establish the headquarters for AI Strategy. In conjunction with the Basic Act on Science, Technology and Innovation, the Basic Act on Forming a Digital Society and other relevant laws, it seeks to ensure the comprehensive and systematic advancement of measures for the promotion of research, development, and utilization of AI-related technology, thereby contributing to the enhancement of the public’s welfare and the sound development of the national economy.”

There is no list of prohibited or high-risk AI practices (as in the EU AI Act and other recent AI laws).

The law establishes broad state promotion of AI development and deployment and the creation of the “headquarters for AI strategy,” and divides responsibilities among local governments, research organizations, businesses, and the public.

Local governments have the freedom to formulate autonomous AI policies that leverage the characteristics of their jurisdictions to promote AI research, development, and deployment.

Aligned with Japan's AI law, in her speech last year to the country's national parliament, Japanese Prime Minister Sanae Takaichi said:

“Aiming to make Japan the world’s best country to develop and use AI, we will utilize data linkage and integration and other means to accelerate the research, development, and commercialization of AI and other new digital technologies. Beyond that, we will support the overseas expansion of industries related to digital technologies, including the content industry.”

An aggressive AI race is underway. Behind measures such as chip export bans and swift legal amendments is the belief that the country that reaches “superintelligence” first will gain an immeasurable advantage over all others in economic, political, technological, and military terms.

There is a sense of urgency in many parts of the world, including Japan, and a growing belief that digital laws enacted over the past two decades to protect against online harms are an obstacle to the limitless (and often desperate) pursuit of some form of AI supremacy.

Let's take a look at Japan's specific changes to its privacy law and what they mean in practice, including from the perspective of the protection of fundamental rights:

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Hi everyone, Luiza Jarovsky, PhD, here. Welcome to the 285th edition of my newsletter, trusted by 93,100+ subscribers worldwide.

As the old internet dies, polluted by low-quality AI-generated content, you can always find pioneering, human-made thought leadership here. Thank you for helping me make this newsletter a leading publication in the field.

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China’s AI Ethics Governance

Last week, China's Ministry of Industry and Information Technology, together with eight other departments, released the country's “Trial Measures for Ethical Review and Service of AI Technology.”

The document gives us a glimpse into what the country calls ‘ethical governance of AI’ and the types of policies and technical measures it considers necessary to implement AI ethics in practice.

As I explain the main provisions below, many will be surprised to learn that China's approach to AI ethics is more comprehensive, structured, and pragmatic than what we find today in the United States and the European Union.

Countries and organizations interested in building strong AI governance systems should take note.

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Before we start, a reminder that, contrary to what many might think, China has been consistently and comprehensively regulating AI.

Some of its recent legal proposals show that the country takes AI risks and harms seriously, and that its approach aligns with the latest technical and social science studies, as I wrote in January regarding China's new bill on AI anthropomorphism.

Regarding the present AI ethics governance measures, which the country made public on April 2, they build on the country's “Opinions on Strengthening the Governance of Science and Technology Ethics,” released in March 2022, and its “Measures for the Ethical Review of Science and Technology,” effective from December 2023.

These developments show China’s growing efforts to operationalize and implement ethical review and governance of AI at both the technical and compliance levels.

Below, I have selected several articles that help us understand China’s AI ethics governance in practice and can serve as inspiration for countries and organizations interested in building and strengthening their legal and ethical AI frameworks.

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Article 1 explains the goal of the AI ethics governance measures, how the country sees AI ethics, and the values associated with it:

“In order to regulate the ethical governance of AI science and technology activities, promote fairness, justice, harmony, safety, and responsible innovation, and facilitate the healthy development of the AI industry, these Measures are formulated in accordance with the Law of the People’s Republic of China on Scientific and Technological Progress, the Opinions on Strengthening the Governance of Science and Technology Ethics, the Measures for the Ethical Review of Science and Technology (Interim), and other relevant laws, regulations, and provisions.”

Article 2 details the main scope of the measures. Notice how it applies to both scientific research and technological development activities, and how it frames ethical risk broadly, similarly to how the EU frames fundamental rights in its AI Act:

“The AI ​​technology activities to which this regulation applies are AI scientific research and technological development activities conducted within the territory of the People’s Republic of China that may pose ethical risks and challenges to human dignity, public order, life and health, the ecological environment, and sustainable development, as well as other scientific and technological activities that require ethical review of AI technology according to laws, administrative regulations, and relevant national provisions.”

Article 3 highlights a “full lifecycle” approach to AI ethics (the technical perspective) and a direct, inherent connection to legal compliance (the legal perspective):

“The ethical requirements of AI technology activities should be integrated throughout the entire process, adhering to the ethical principles of promoting human well-being, respecting the right to life, upholding fairness and justice, reasonably controlling risks, maintaining openness and transparency, protecting privacy and security, and ensuring controllability and trustworthiness, and complying with the Constitution, laws, regulations, and relevant provisions of the People’s Republic of China.”

Bridging AI ethics with technical standards and legal compliance is one of the most important aspects of China's AI ethics governance measures.

In recent years, we have observed a phenomenon called “AI ethics washing,” in which companies publish a broad, idealistic AI ethics approach that is disconnected from legal compliance or liability, serving merely as a branding strategy.

To counter that, China's AI ethics governance connects broad ethical principles with full legal compliance, discouraging the trivialization of ethics and AI ethics washing.

Now, a central part of this document is where China explicitly translates AI ethics principles into practical implementation measures. Let's dive in:

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Hi everyone, Luiza Jarovsky, PhD, here. Welcome to the 284th edition of my newsletter, trusted by 92,800+ subscribers worldwide.

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The AI Divides Are Here

It has been almost three and a half years since the generative AI wave led to the large-scale deployment of general-purpose AI models, and the divides that will shape the next few decades have started to become clearer.

For comparison, if you consider the advent of smartphones and social media in the 2000s, it took almost two decades for the social implications of their widespread deployment to become obvious.

Their negative impact on areas such as education, cognitive development, focus, reading scores, mental health, individual and social well-being, and political polarization was not fully visible in the early years.

Only recently, after the harm became full-blown, widely acknowledged, and often irreversible, have we seen a much stronger social, cultural, and legal pushback against smartphone use by children, unregulated social media platforms, toxic algorithms, manipulative design, and more.

And in 2026, we are still unable to address many of the negative implications of technological disruptions from 20 years ago.

Social media and smartphone addiction, poorer focus and cognitive performance, less reading, mental health decline, the loneliness epidemic, and lower individual and social well-being are among the issues that we might actually never overcome.

These consequences have become somewhat entrenched in our society. That is the post-smartphone, post-social-media society we have become, and there is no way back.

Technological waves are powerful, and the disruption-and-divide cycle occurs in every one of them.

Technological waves often lead to broad disruption because, as humans, we seem to strive for and be collectively drawn to what appears to be technological progress, like a blinding light. They end up engulfing everything around them, like a black hole.

Maybe it is part of Homo sapiens sapiens’ DNA and part of what, perhaps luckily, led us here, technologically speaking.

Every mass-scale technological wave also creates new divides. Through social, economic, cultural, legal, ethical, and philosophical ripples, it reorganizes society.

Some people will adapt, upskill, shield, regroup, find new resources, build support networks, and thrive; others will lose support, access, and resources, and end up left behind.

But it is not so simple.

At the beginning of a technological wave, it is difficult to clearly see the main divides shaping society, culture, the economy, or even the law, and how we can be on the side benefiting from it (if there is really one).

In the late 2000s, for example, many of us were simply excited by the convenience of smartphones and the connectivity enabled by social media platforms.

A new world was being born, and as humans, we are ingrained in our own material existence in the present. It is difficult to see 20 years ahead and plan accordingly, individually and collectively.

The same “disruption-and-divide” cycle is already happening with generative AI, and it will also happen with any form of “superintelligence” or cognitive automation that comes after it and reaches mass scale.

Nobody can fully predict what two decades from now will look like, but generative AI has already led to three important divides that are starting to shape society:

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The conversation was based on two papers published by them this month:

1. “Not a Silver Bullet for Loneliness: How Attachment and Age Shape Intimacy with AI Companions,” by Raffaele Ciriello, Uri Gal, and Ofir Turel - link

2. “Regulating Artificial Intimacy: From Locks and Blocks to Relational Accountability,” by Henry Fraser, Raffaele Ciriello, and Jessica Szczuka - link

The result was a fascinating one-hour conversation about AI companions, their risk profile, human vulnerability, and some of the current challenges affecting their governance and regulation.

If you use AI chatbots regularly or want to learn more about the rise and risks of AI companionship, do not miss our conversation and find my key takeaways below. You can watch it here:

Video chapters:
00:00 - The challenges of AI companion regulation
11:30 - AI companions and vulnerability
20:45 - Emerging risks and the current data
27:58 - Individual vs. societal perspectives
37:57 - Vulnerability and intimate attachment
44:42 - Duty of care
51:38 - The future of human relationships

This is a complex topic, and data remains limited, as only in recent years have millions of people begun to develop emotional and intimate interactions with AI chatbots.

With that in mind, here are my key takeaways from this conversation:

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Hi everyone, Luiza Jarovsky, PhD, here. Welcome to the 282nd edition of my newsletter, trusted by 92,500+ subscribers worldwide.

As the old internet dies, polluted by low-quality AI-generated content, you can always find pioneering, human-made thought leadership here. Thank you for helping me make this newsletter a leading publication in the field.

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Trump’s Pro-Business AI Wishlist

On Friday, the White House released its much-anticipated legislative recommendations for a national AI policy framework.

This AI policy wishlist is expected to guide Congress’s efforts to draft a federal law and other policies to regulate AI development and deployment in the United States.

With the stated goal of not hindering innovation and supporting America's AI dominance, the White House's recommendations ignore most AI risks and harms and seek to shield AI companies from legal accountability.

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The White House's AI policy recommendations can only be fully understood in light of two federal documents published last year: the December Executive Order on a National AI Policy and the America's AI Action Plan, published last July.

The Executive Order highlighted that Trump's priority would be to ensure a “minimally burdensome national standard,” instead of a patchwork of 50 different regulatory regimes.

It also stated that a national framework for AI must block state laws that, from a federal perspective, hinder AI innovation. As I wrote earlier, that type of statement could lead to broad and potentially unlawful interference with states’ legislative autonomy.

In parallel with that, America's AI Action Plan, in the context of the AI race, stated, “it is a national security imperative for the United States to achieve and maintain unquestioned and unchallenged global technological dominance” in AI.

The AI policy wishlist published on Friday must also be understood as another step towards the two goals above.

Another preliminary remark is that the document was intended to reflect legislative recommendations (the press release even called it a “National AI Legislative Framework”).

However, a closer look shows that it has been designed to reiterate the federal government’s economic and political plan for AI and to urge states to follow suit.

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Now, let's take a look at the seven specific targets of the White House's AI policy wishlist, focusing on what they prioritize and what they leave out:

1. Protecting children and empowering parents

“AI services and platforms must take measures to protect children, while empowering parents to control their children’s digital environment and upbringing.”

One of the few areas where concern about AI harms is explicitly stated is child protection.

The recommendations go beyond what is currently established by the EU AI Act, for example, and urge Congress to ensure it does not preempt states from enforcing child protection laws.

The White House explicitly mentions the prevention of deepfake abuse, sexual exploitation, and privacy violations.

Other protective measures targeting children, such as those under consideration in China for anthropomorphic AI systems, were not mentioned.

A reminder that, to date, most cases of AI chatbot-related suicides have involved minors, such as the Adam Raine case. Children and teenagers seem to be among the groups most vulnerable to AI-powered emotional manipulation.

In this context, the recommendations refrain from mentioning built-in limits and guardrails and instead favor empowering parents with tools to help them reduce child-specific risks.

2. Safeguarding and strengthening American communities

“AI development, including data infrastructure buildout, should strengthen American communities and small businesses through economic growth and energy dominance, while ensuring communities are protected from harmful impacts.”

Under this item, which specifically mentions “safeguarding communities,” one would expect strong, straightforward legislative recommendations to help reduce AI-related risks and prevent AI harms.

A reminder that providers of AI models and systems in the United States currently have very few federal-level obligations, and most are sector-specific.

This regulatory Wild West allows negligent and exploitative AI providers, as well as anyone planning to use AI to circumvent the law or harm others, to proceed without fear of repercussions.

Despite the clear need for federal regulation to prevent AI harms, of the five recommended actions in this section, only one refers to preventing harm, and it is framed in the narrowest way possible:

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Hi everyone, Luiza Jarovsky, PhD, here. Welcome to the 281st edition of my newsletter, trusted by 92,200+ subscribers worldwide.

As the old internet dies, polluted by low-quality AI-generated content, you can always find pioneering, human-made thought leadership here. Thank you for helping me make this newsletter a leading publication in the field.

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The “No Work” Paradigm

There have been various recent reports predicting the future of work and AI replacement, including one by the World Economic Forum and another by Anthropic.

Most reports focus their predictions on theoretical and observed skill exposure, analyzing which tasks in a specific occupation can be, or already are, automated by AI.

I have also seen posts and analyses comparing AI to previous technological developments, such as electricity, the internet, or smartphones, and, from that, trying to estimate how AI's impact on the labor market will unfold.

The reason most predictions will end up being inaccurate is that AI is fundamentally different from previous technological waves in terms of what it automates.

AI is the first technology in human history that can mass-automate cognitive processes: it can potentially assist or replace most professionally valuable cognitive and decision-making processes, skills, and tasks.

However, at the same time, every single job exists within broader legal, institutional, ethical, cultural, societal, and human contexts. As a consequence, automating one or more cognitive processes, tasks, or skills does not make a job, profession, or occupation immediately expendable or unnecessary.

Therefore, the only situation in which AI would lead to the mass replacement of humans, putting most white-collar jobs (and, later on, most jobs) truly at risk, would be if most people, companies, and governments embraced the “no work” paradigm.

Let me explain why and how:

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Assisting with one or more cognitive or decision-making processes, skills, or tasks is not sufficient to conclude that AI will replace that job or the human behind it. Why?

There are human institutions, societies, rules, policies, requirements, needs, and expectations behind every job, and the way AI performs a task might not meet existing quality, safety, legal, or other previously specified criteria.

Even though AI may assist or fully take over a specific skill, task, cognitive process, or decision-making process, most jobs are tailored to humans and human societies, as well as to human judgment, preferences, tastes, styles, formats, shapes, needs, ethics, and delivery.

Therefore, before the output of an AI system can be considered adequate, legal, ethical, safe, or meeting minimum quality standards, a human often has to intervene and present it in the way human society expects to receive it.

As a consequence, despite widespread AI assistance and support, we would still have plenty of jobs, which is exactly what is happening to white-collar jobs today.

Let me use customer support to illustrate this point:

This is a job often framed as highly exposed to AI automation, and one that many companies have been attempting to automate to reduce costs.

At the same time, dissatisfaction with AI-powered customer support is very common, and most of us have at some point been angry or frustrated by the poor service.

From failing to understand the problem to providing irrelevant or circular answers, as well as pretending to be human or avoiding directing the consumer to a human representative (even when the consumer seems desperate), these AI bots have often been associated with lower-quality service and an overall disregard for consumer feedback or well-being.

They could also lead to legal liability, such as in the now-famous Air Canada case, where the airline's customer service chatbot ‘hallucinated’ a discount, and the court ordered the company to honor it and pay damages.

Customer support can likely be partially automated through AI, but if the organization wants to maintain higher-quality service and convey the impression that it cares about its customers, humans will have to remain closely involved.

Humans would be needed to develop and maintain customer service bots, review the quality of the conversations, step in to help solve practical issues, show the company cares about customers, and avoid lawsuits.

Customer service is just one example. I could go on and talk about each and every professional task AI could potentially assist or fully automate, and discuss why human institutions, rules, policies, requirements, needs, and expectations behind each job will likely block full AI replacement and ensure that plenty of humans will still be directly involved.

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Having said that, there is one potential scenario in which AI would replace most white-collar jobs (and, in the future, potentially all jobs), as predicted by AI company CEOs like Mustafa Suleyman.

This is the scenario AI companies are subtly but actively promoting, including when they foster AI idolatry, advance legally questionable theories of AI personality, and treat AI as inevitable aliens that came to overtake human institutions.

It is also the main message behind the “AI-first” narrative, as treating AI as a goal (rather than a means) would help companies increase profits dramatically and make AI indispensable to the functioning of the economy.

This potential scenario involves a major paradigm shift in how we see ourselves, AI, human life, and work.

I call it the “no work” paradigm.

In this paradigm, most governments, companies, and employers would somehow be convinced by the AI industry that AI is much smarter than humans and, for the sake of efficiency and productivity, should fully replace most human cognitive work (and later on, all human work).

They would argue that most people should stay at home and receive some form of universal basic income.

People would be expected to sit ‘happily’ on their sofas, enjoying the theoretical idea of AI-led abundance.

A selected group of AI experts would help train and oversee the AI models and systems that are effectively ruling, mediating, shaping, and entertaining society in every sector.

A few individuals at the top of the pyramid would be the AI overlords, likely billionaires or trillionaires, cashing in on their monopolistic AI empires.

A handful of politicians, diplomats, and other technical experts would be required to keep the system afloat.

However, as much as the AI industry tries to spread this narrative and create this future of AI replacement and ‘abundance,’ the “no work” paradigm will likely fail, at least over the next two or three decades. Here is why:

Read more

A few weeks ago, I wrote that, from a legal perspective, 2026 would be a make-or-break year for AI.

The regulatory Wild West we are currently living in cannot possibly persist without chaos reigning and people realizing that they are fully unprotected from the negative consequences of AI development and deployment.

We are still in March, but it has already become clear that this is the year in which democratically elected authorities must take bold decisions on AI.

-

An important factor that has led us to where we are now is that the risk profile and the social impact of AI have been clearly underestimated over the past 10-15 years of AI policy debates.

They did not take into account the level of acceleration and the widespread AI development and deployment we have been observing over the past three years.

As a consequence, even laws enacted between 2022 and 2024, including the EU AI Act, are already outdated and ineffective in addressing threats and harms that became more evident and widespread in the past few months.

The growing cases of AI-related suicide, mental health harm, emotional manipulation, political manipulation, misinformation, scams, security vulnerabilities, synthetic content flooding, copyright infringement claims, competition abuse, AI washing, layoffs, institutional instability, low preparedness, global disparities, and other issues illustrate how AI’s impact has gotten out of control in a relatively short period of time.

At the same time, most regulatory authorities seem to have been paralyzed and afraid to take bold decisions over the last three years.

They fear that regulatory action could stifle innovation and delay productivity gains (arguments often raised in the EU) or make them “lose the AI race” and reward adversaries (arguments usually raised in the U.S.).

This is evident from what is happening in the EU.

The EU AI Act was enacted in August 2024. A year and a half later, even before it was fully enforceable, the Digital Omnibus proposal aims to postpone, amend, and dilute it.

This is the same bloc that took the lead in 2016 by enacting the GDPR and prioritizing fundamental rights. It is 2026, and the bloc seems to be no longer sure of its stance (or hesitant to stand by it).

This is also happening in other countries that have chosen to take a “wait-and-see” approach to AI, as well as those that have explicitly stated that prioritizing innovation is the main goal.

The problem is that inaction has a price.

Given the pace of acceleration and techno-social change, doing nothing today might mean that, in a year or two, it could already be too late. It may no longer be possible to reverse the structural harm.

We might have to live in some sort of globally heterogeneous, AI-powered ‘AI-first’ reality that idealizes AI and endorses AI companies’ interests and profit-making routes, but no longer serves our human interests, rights, and needs.

To tell you the truth, I think this is exactly what AI companies want and are indirectly pushing for, but they do not say it explicitly.

Ongoing AI hype, ultra-optimistic predictions about all-disease-curing AGIs in one decade, alien-like intelligence, and strange policy-like discussions about an AI model’s self-awareness and “wellbeing“ serve to thicken the smoke cloud and distract us from serious policy and regulatory discussions.

When authorities remain paralyzed and do nothing about what is negatively affecting people (or how most people want AI to be governed), AI companies will step in and solve things their way.

As companies (and not democratically elected officials), they will necessarily solve things in ways that keep them alive longer and maximize their profits more effectively, including prioritizing AI, treating it as a special entity, an essential need, an “alien,” and a commodity that must be constantly incentivized and multiplied.

They will create and endorse whatever narrative keeps the profits coming, even if the narrative is “you should probably implant a Neuralink-like AI chip to have maximum intelligence and productivity, better understand how AI systems reason and flourish together.”

Sadly, I am not joking, and I have seen these types of arguments circulating online.

Many forget this and get lost in companies’ beautifully PR-tailored, legally filtered narratives, but that is how companies work.

They are not public utility entities, and their priority is not to reflect democratic values, promote due process, or spread well-being. They need growing profits to survive, or they die. They will do everything to survive.

As I wrote above, we are still in March, but it seems that AI’s make-or-break legal moment is approaching.

In the U.S., the recent face-off between Anthropic and the U.S. Department of War seems to have exposed an internal split.

The federal government wants to use AI for all lawful purposes, including in cases in which existing laws might not reflect AI model capabilities or emerging risks, such as those involving internal surveillance and autonomous weapons.

Many Americans did not like it and supported Anthropic’s firm stance and internal redlines (and now the lawsuit against the Department of War).

This is a great opportunity for the U.S. to engage in complex yet necessary debates about AI regulation for both civil and military use, as well as serious discussions on AI safety.

In the EU, the Digital Omnibus proposal has been a wake-up call for all sectors to face the legal, economic, and political challenges shaping the future of Europe.

Does the EU still want to lead in the protection of fundamental rights and the prioritization of trustworthy AI? What are the potential measures that truly incentivize innovation while also preserving European legal, ethical, and cultural traditions?

Authorities worldwide should face the techno-social reality and make meaningful, coherent, and effective decisions.

• Should powerful AI models be regulated similarly to atomic bombs, in the sense that their safety risk is too high to be entrusted to private companies, but which military bodies would compete to have strategic access?

• Should access to AI systems be treated as a “right to augmented cognition,” be subsidized, and offered for free to people in an attempt to reduce inequality and increase national productivity?

• Should there be strict rules for AI training and model development, including government-sponsored benchmarks, standards, and official limits, as well as close scrutiny of companies’ AI safety decisions?

• Etc.

There are many other options, but no easy choices. Countries, individually and collectively, should be debating them transparently and democratically.

Doing nothing should not be an option, as in a few years, it could be too late.

Wherever you are, I invite you to make your voice heard.

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Over the past three years, I have been writing about global AI regulation efforts, and I have not hidden my frustration with the slow pace and lack of action in most parts of the world.

The growing cases of AI harms, including political manipulation, mental health harm, suicides, deception, fraud, scams, deskilling, replacement, AI washing, as well as the theoretical possibility of catastrophic events raised by some, did not seem to be enough to convince authorities to take action.

Even the EU AI Act, enacted in August 2024 and widely expected to be a globally influential source of fundamental-rights-based AI rules, has lost its political momentum and may be drastically weakened through the Digital Omnibus.

In a sea of inaction and deregulation, the state of New York, perhaps unexpectedly, offers a breath of fresh air, as it seems to be openly embracing a pro-human legal approach.

In December 2025 alone, New York enacted the RAISE Act (“to require safety reports for powerful frontier AI models in order to limit critical harm”), S8391 (“to generally prohibit the use of a digital replica of a deceased personality’s voice or likeness in an expressive audiovisual work without prior consent”), and S8420A (“to require disclaimers when commercial content contains a synthetic performer”).

This last law deserves special attention, as it is the first in the United States with this specific scope.

S8420A requires anyone engaged in advertising to conspicuously disclose the use of a synthetic performer. It imposes a $1,000 civil penalty for a first violation and a $5,000 penalty for any subsequent violation.

The law defines a synthetic performer as:

“A digitally created asset, created, reproduced, or modified by computer, using generative AI or a software algorithm, that is intended to create the impression that the asset is engaging in an audiovisual and/or visual performance of a human performer who is not recognizable as any identifiable natural performer.”

Therefore, anyone using “AI influencers” or human-looking AI-generated visual or audiovisual avatars in advertisements must visibly disclose them.

I saw comments from people who seemed outraged by this law, saying that AI-generated avatars or models would not be different from heavily edited photos or videos of people, and these are not required to be visibly disclosed.

Humans and synthetic performers might be visually similar, as synthetic images and videos today are extremely realistic.

From a pro-human perspective, however, they are extremely different.

One is a human model or actor who eats, sleeps, and works, hired to perform that job. That human has specific physical characteristics that may have been shaped or altered by lighting, filters, and editing, but they still refer to an existing person who could be verified in real life.

The other is a human-like AI-generated avatar or synthetic performer, using the law’s terminology. It is essentially the output data of one or more AI systems, further edited to appear human and fit the desired aesthetic. Any physical characteristic does not refer to physical or biological reality.

By requiring the disclosure of synthetic performers, NY lawmakers are celebrating humans, including human work, human physical features, and human aesthetics.

This law may lead more people to want to hire real humans to work as models in advertisements, since the outcome will not be labeled as “synthetic” and might be perceived as more authentic and valuable by the audience.

There is also the ethical aspect: synthetic performers are created based on the physical appearance of real people whose images were collected and ultra-processed by a generative AI model, but who never received any form of compensation.

Labeling synthetic performers is another step toward helping the public understand the economic and ethical challenges behind generative AI.

Without disclosure obligations like these (which hopefully will spread globally), we would soon watch advertisers push the idea of the “desirable female body” to humanly impossible standards, leading to more cases of body dysmorphia and mental health harm, especially among teenage girls.

There is still another recently proposed bill in New York that takes the pro-human approach to a previously unimagined level:

Read more

Among the main promises of the AI industry today are productivity and acceleration.

People would use AI to complete more tasks in less time, AI would create and complete more tasks autonomously, and AI would coordinate other AIs to create and complete more tasks autonomously.

As a consequence, the AI industry says, countries would economically benefit from this AI-driven increase in production.

We would enter an era of abundant intelligence in which even the most technically complex challenges would be solved in a short period of time, including, for example, curing all diseases.

The premises above are part of the AI industry's mainstream discourse today, and they help keep billions of dollars in investments flowing.

However, when you zoom in and look at how humans interact with AI and what AI-powered acceleration actually means, you realize that these promises are based on false premises.

They ignore basic facts about the human body, the human mind, human behavior, and human societies.

Also, these false premises are dragging us toward a dystopian future in which we will be forced to constantly minimize biological boundaries, ignore psychological needs, and devalue human expression to thrive in a world that prioritizes machines.

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Regardless of how shiny, advanced, and impressive our technological tools might be, we, humans, are living entities.

As such, there are biologically coded boundaries, shaped over millions of years of evolution, that we cannot really escape.

The average human lifespan is 73 years, and we need around seven hours of sleep, three liters of water, and 2,000 calories a day to stay healthy.

Besides our physiological needs, we have emotional and psychological needs, including safety, love, belongingness, esteem, and self-fulfilment.

Not meeting any of these groups of needs might lead to illness or even death.

These are hard limits that cannot be increased with more computing power, larger datasets, new training methods, or more efficient chips.

Even though some of us use a series of digital tools in our daily routines, we are essentially analog. Our biological systems operate in a continuously variable physical way.

We are born, and one day we die. Death is the only certain thing in life.

As such, we consciously or unconsciously spend much of our time dealing with the challenges of our own finitude:

• Why am I here?

• What is my purpose?

• How can I make my life more meaningful?

Being alive is finding meaning in every day of our existence, discovering our own journey, and making sense of it.

I am sorry to break the news to the AI industry, but it has nothing to do with acceleration or productivity.

I have never heard of anyone on their deathbed lamenting not being more productive or accelerated.

In fact, the opposite is true. According to Bronnie Ware's “Regrets of the Dying,” these were the most common five regrets people expressed in their last days:

1. I wish I’d had the courage to live a life true to myself, not the life others expected of me.

2. I wish I hadn’t worked so hard.

3. I wish I’d had the courage to express my feelings.

4. I wish I had stayed in touch with my friends.

5. I wish that I had let myself be happier.

People regret not having worked less. People regret not having lived a more meaningful life, truer to themselves and their feelings. People regret not spending more time with friends.

As humans, we crave connection, belonging, meaning, and love. Our activities should, ideally, support that. Everything else is a form of distraction that we might regret later.

What does this have to do with AI?

A large part of the discourse around AI is focused on the idea of acceleration. In practice, for the individual, AI-powered acceleration will often involve:

• Delegating tasks to AI systems and losing control over work processes and outputs;

• Failing to develop essential skills due to ongoing AI use for creative and intellectual tasks;

• Deskilling due to constant AI-powered automation;

• Having to manage a large number of AI-powered tasks without the understanding of how each process and decision-making works;

• More isolation and disconnection from human teams due to ubiquitous automation;

• Etc.

AI-powered acceleration often runs counter to human physical and psychological needs. They do not support connection, belonging, or meaning.

A recent study has shown, for example, that AI does not reduce work but intensifies it in a way that is not necessarily net positive:

“That workload creep can in turn lead to cognitive fatigue, burnout, and weakened decision-making. The productivity surge enjoyed at the beginning can give way to lower quality work, turnover, and other problems.”

Another study showed that AI negatively impacts skill formation, especially among junior employees:

“Together, our results suggest that the aggressive incorporation of AI into the workplace can have negative impacts on the professional development of workers if they do not remain cognitively engaged. Given time constraints and organizational pressures, junior developers or other professionals may rely on AI to complete tasks as fast as possible at the cost of real skill development.”

Moreover, it is unclear to me whether the proposed AI-powered acceleration will ever lead to the promised beneficial outcomes, such as curing all diseases and solving myriad other complex challenges.

One reason is the incompatibility between continuous acceleration and humans' ability to keep up with and maintain meaningful control over processes and decisions that could lead to these positive outcomes.

For AI capabilities to translate into meaningful human and societal benefits, they must make sense in a world of humans. Biological humans with hard-coded needs and boundaries.

Living entities who know they will die and try to find meaning, purpose, and connection in their daily lives.

If the AI industry continues to foster growing acceleration, but humans cannot maintain meaningful control, oversight, and scrutiny over AI-powered processes and outcomes, a possible consequence is uncontrolled chaos.

From that, there are a few potential futures, including:

• We decide that AI systems are smarter, faster, and more intellectually capable than we are, so they should fully control the decision-making processes for the benefit of “progress and innovation”. We treat humans as limited entities that must delegate decisions to increasingly smart machines. We treat AI systems as “special entities” or “aliens” that we must respect. We end up not having full control of the outcomes, positive or negative.

• We decide that AI is an extremely powerful technology that requires strict human oversight and control. We understand that AI is a tool that should foster human flourishing, so AI development and deployment should follow rules that focus on human-led innovation, human well-being, and the protection of fundamental rights. We might have to limit certain AI use cases so that vulnerable groups and catastrophic risks are prevented.

To be clear, the AI industry is currently fostering the first option above, as discussed in my recent articles about Claude’s new constitution, Yuval Noah Harari’s World Economic Forum speech, and AI idolatry.

I sincerely hope we can push for changes so that the future will be closer to the second option, where pro-human policies, rights, and rules are at the forefront, and where humans remain in control.

I hope you can join me in these efforts.

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Over the past 48 hours, we saw a dramatic dispute between Anthropic and the U.S. Department of War unfold, which culminated in the company’s designation as a “supply chain risk” and OpenAI becoming the preferred supplier.

I have read some commentators praising Dario Amodei’s ethical stance and others criticizing the strategic opportunism behind OpenAI’s actions.

What most people have not realized is that the high visibility of this quarrel is a symptom of a much broader issue: the challenge of regulating, governing, and scrutinizing the use of AI for national defense and military contexts.

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Let me start by breaking down what happened in this specific case, based on what Anthropic and OpenAI made public.

According to Anthropic's blog post from a few days ago, the company has worked proactively to deploy its models to the Department of War (previously the Department of Defense), and Dario Amodei stated that he “believes deeply in the existential importance of using AI to defend the United States and other democracies, and to defeat their autocratic adversaries.”

Dario also said that he is against including the following AI use cases in the company's contract with the Department of War:

The main reasons he lists for why the company is against these forms of AI deployment are:

• These use cases would undermine, rather than defend, democratic values;

• These use cases are outside of the bounds of what today’s technology can safely and reliably do.

Emil Michael, the “Under Secretary of War,” quoted Anthropic’s blog post, saying that the company wanted the final word over military uses of AI:

Peter Hegseth, the Secretary of War, followed suit and posted, among other accusations:

“This week, Anthropic delivered a master class in arrogance and betrayal as well as a textbook case of how not to do business with the United States Government or the Pentagon. Our position has never wavered and will never waver: the Department of War must have full, unrestricted access to Anthropic’s models for every LAWFUL purpose in defense of the Republic.”

Lastly, Trump posted about Anthropic:

Many, including Anthropic itself, were surprised by the Department of War's public reactions and the company's "supply chain risk" designation.

For those who were closely following the Trump Administration’s latest moves on AI, however, the decision was more predictable.

Last July, Trump signed an executive order titled "Preventing Woke AI in the Federal Government," and the implementation section includes:

"(v) make exceptions as appropriate for the use of LLMs in national security systems."

Also, America's AI Action Plan (published last July as well), which contains the country's strategy to win the AI race, states:

"As our global competitors race to exploit these technologies, it is a national security imperative for the United States to achieve and maintain unquestioned and unchallenged global technological dominance."

So Anthropic agreed to work with the U.S. military, but its legal team did not seem to take Trump’s actual AI implementation plan seriously (or it miscalculated it, thinking that the U.S. government would accept that the company would still have the final word on its desired red lines).

After the controversy became public, Dario gave a 30-minute interview to CBS News. The interviewer wisely asked him:

“Why do you think that it is better for Anthropic, a private company, to have more say in how AI is used in the military than the Pentagon itself?”

Dario did not answer that question directly, but what he implied throughout the conversation was that he does not think that U.S. law has caught up with current AI capabilities and risks, including for military use.

In his opinion, Anthropic's red lines are better for America (and more aligned with America's values) than what U.S. law currently establishes, as he clarifies in this quote:

“We believe in defeating our autocratic adversaries. We believe in defending America. The red lines we have drawn we drew because we believe that crossing those red lines is contrary to American values. And we wanted to stand up for American values.”

Most people commenting on the topic have not realized it, but Dario's stance exposes a core AI governance challenge when national defense and military purposes are involved:

Read more

Having documented the generative AI wave for over three years, I have been paying attention to the minor and major AI hype ripples and how different groups react to the latest developments.

I can say that the past few weeks have made it clear that, despite ongoing technological advancements, AI faces a significant public trust problem stemming from unresolved legal, ethical, and philosophical issues.

In a year when the field must prove, once and for all, that it is not a bubble and can drive meaningful economic growth, lack of public trust and decreased adoption could be fatal for some companies.

-

Let me start with this interview given by Sam Altman during the India AI Impact Summit last week, where he justified AI's energy efficiency by comparing it to the food humans need to eat in 20 years of life, plus all our evolutionary history.

The philosophical approach behind his statements, reducing people to data units and treating humans and machines as if they were exchangeable and similar in nature, is actually popular in Silicon Valley.

It is also the philosophical line of thought behind Claude's new "constitution," which anthropomorphizes AI and treats it as a ‘new entity,’ minimizes human values, rules, and rights, and hopes for the “joint flourishing” of humans and machines, as I recently explained in my article.

If you read people's comments about Sam Altman's reasoning, however, it is clear that many felt deeply uncomfortable with his statements. It is as if, by February 2026, these types of ideas have crossed a line and are no longer acceptable.

This sentiment reflects a new form of morality that seems to be emerging: one that (gladly) considers it wrong to treat humans as expendable, inferior, or in any way less than machines.

This morality is essentially against the radical “AI first” mentality and AI productivity slogans being pushed by AI companies in a desperate attempt to grow adoption, especially in corporate circles.

AI companies might have to deal with a public that no longer trusts them and is not interested in being dehumanized or belittled, whether through technical capabilities, policies, narratives, or marketing campaigns.

-

Another area where mistrust seems to be rising is AI safety.

Over the past few weeks, there has been more mistrust about AI companies’ safety and transparency practices, as this post illustrates:

It is definitely not happening without reason, as a series of recent events seem to have made the public more wary and suspicious of AI companies.

Recently, OpenAI changed its mission statement in its Internal Revenue Service disclosure form. The previous statement read (emphasis added):

“OpenAI’s mission is to build general­-purpose AI that safely benefits humanity, unconstrained by a need to generate financial return. OpenAI believes that AI technology has the potential to have a profound, positive impact on the world, so our goal is to develop and responsibly deploy safe AI technology, ensuring that its benefits are as widely and evenly distributed as possible.”

The new mission statement, released in November 2025, reads only:

"OpenAI's mission is to ensure AGI benefits all humanity."

It has also disbanded its Mission Alignment team. That team's goal was to promote "the company’s stated mission to ensure that AGI benefits all of humanity." The head of that team is now OpenAI's "chief futurist."

Similarly, Anthropic recently changed its Responsible Scaling Policy, removing its promise not to release AI models if it cannot ensure proper risk mitigations in advance.

Why all these public and official changes to AI safety statements and compromises?

Does it mean that these companies only care about profits now, and that all official statements, speeches, and declarations on AI safety were mere lip service, even when there could be existential risks involved?

People are increasingly unsure whether they can trust AI companies to make sound AI safety decisions, especially given the potentially existential stakes of AI development and deployment.

Recently, the director of Meta's safety and alignment team posted that she failed to stop an AI agent from deleting her inbox:

Granting an AI agent access to one's inbox is itself imprudent for safety and privacy reasons.

The decision becomes even more imprudent when the person behind it is the director of safety and alignment of one of the world's top AI developers. This is the same person making high-stakes decisions on AI safety that will likely affect millions of people.

To me, there is an additional layer of shock and dismay: I have not seen a pledge for more agentic AI safety after the post. So why did she post it publicly? Did she find it funny? Did she just want to go viral? Given that many in Silicon Valley seem to live in a parallel reality, I am not sure she is aware, but the consequences of her post are even greater public mistrust in AI.

In another recent clip from India's AI Impact Summit, OpenAI's Sam Altman and Anthropic's Dario Amodei were filmed awkwardly refusing to hold hands, even when prompted by India's prime minister.

If the prime minister of the world's most populous country and fifth-largest economy cannot get these two high-profile CEOs to cooperate and appear friendly on camera, how will they behave when the cameras are off?

Will their rivalry and desire to ‘win the AI race’ trump all other concerns, including AI safety ones?

People were paying attention, and it did not look good. It only served to increase mistrust and suspicion.

-

Last but not least, part of the public trust problem might be that recent data shows the immense hype around AI has not yet been translated into economic growth, even after three years. It is still unclear whether it ever will.

According to a recent survey by the National Bureau of Economic Research, although around 70% of firms actively use AI, over 80% reported no impact on employment or productivity.

A Goldman Sachs executive has recently stated that “AI investment spending has had ‘basically zero’ contribution to the U.S. GDP growth in 2025.”

Also, for three years, we have been hearing AI companies’ CEOs promise “a future of abundance,” +200% productivity, and the like.

Recent studies have shown, instead, that AI does not reduce work but intensifies it, and it negatively impacts skill formation, especially for junior employees.

With that track record, it is unclear how long people will continue to trust AI companies, if they truly ever did.

If those companies want greater adoption and higher profits, and if they want to survive, they should pay more attention to people.

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Their paper has been downloaded more than 30,000 times since December 2025, and it has resonated with many who have felt uncomfortable with the negative ways AI has been impacting people and society.

We spoke about the paper’s main concepts, the sense in which institutions are being destroyed, as well as the ways in which AI has affected how we work, write, think, and live.

If you are interested in AI, read their paper, and do not miss our 56-minute conversation:

Video chapters:

00:00 - Introduction
00:40 - The story behind the paper
05:18 - The role of legal scholars in AI governance
12:06 - What are institutions and how AI impacts them
13:30 - How to address these issues?
20:43 - The destructive characteristics of AI systems
24:00 - Is human nature going to change?
25:17 - The destruction of expertise
34:21 - AI and writing
39:24 - Claude's new constitution
44:02 - The problem with “AI as a new species”
47:33 - AI companions
54:16 - Final message

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Last Friday, the U.S. Department of Labor launched its AI literacy framework, the country's first federal-level initiative of its kind.

The main purposes of the framework are to: a) support federal bodies in designing their AI literacy programs; and b) encourage AI literacy training across the public workforce and education systems.

This is a voluntary AI literacy framework to be applied broadly at the federal level across both professional and educational realms.

It will likely also influence the private sector, both inside and outside the United States, serving as a guideline for companies designing their AI literacy programs, schools designing their AI literacy curricula, and vendors tailoring their AI literacy offerings.

As expected, the U.S. approach to AI literacy differs from the one advanced by Europe in the EU AI Act, for the reasons I explain below.

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Before discussing specific aspects of the framework, it is important to note that it must be read alongside two other broader AI frameworks published over the past few months: America's AI Action Plan and America's Talent Strategy.

In the AI Action Plan, one of the tasks under “accelerate innovation” is to support a ‘worker-first’ AI agenda by expanding AI literacy and skill development, assessing AI's impact on the labor market, and retraining workers.

In the Talent Strategy, the plan focuses on addressing the workforce needs of American companies and upskilling workers. AI literacy must be understood here as a skill development effort.

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The AI literacy framework defines AI literacy as:

“A foundational set of competencies that enable individuals to use and evaluate AI technologies responsibly, with a primary focus on generative AI, which is increasingly central to the modern workplace.”

Despite using the broader term ‘AI,’ the framework is based on generative AI challenges and focuses on preparing workers to understand and use generative AI tools.

The framework makes it clear that AI literacy should be seen as a baseline understanding of AI that will help people engage with AI tools professionally.

However, many specialized jobs, especially those directly involved in building and implementing AI systems, will require additional skills and competencies beyond those covered by most AI literacy programs.

AI literacy programs should be personalized and tailored to the specific contexts, audiences, and tasks.

For workers, the AI literacy framework should help them build new skills independently, experiment with AI, understand when it might or might not be helpful in professional contexts, and adapt to ‘AI-enabled’ contexts.

For employers, an AI literacy framework can support effective and responsible AI deployment among existing employees and new hires, and empower managers to gradually, adaptively, and responsibly shape AI adoption.

For education providers, this framework can help them design their curricula, guiding decisions on what content to teach and how to assess competency.

It is explicitly stated that the framework is not static and will be updated in response to technological advances, labor market changes, and implementation feedback.

Let us take a look at each of the five foundation content areas and the seven effective delivery principles of AI literacy:

Read more

From AI-blamed layoffs to pretentious AI “constitutions,” from conspiring AI agents to AI safety departures, 2026 in AI has been frenetic. Maybe too frenetic.

The impression many people get from watching the latest AI developments is that there is an impending doom and that we have little to no control over what is about to happen.

That type of message has been spread by AI CEOs like Sam Altman and Dario Amodei, as well as authors like Yuval Noah Harari, who recently presented AI systems as if they were extraterrestrial alien visitors who deserve our immediate and absolute surrender.

Strangely, this narrative seems to be attached to the implicit conclusion that we must lower our heads and obey what AI companies say.

If they say it is time to prioritize AI and add it to every single task, we should do it, even if it makes no sense for our professional development or career goals, and even if we might not become more productive in the end.

If they say it is time to embrace AI-generated art for the sake of spreading AI-powered aesthetics, and that monotonic AI feeds are now the cool online entertainment, we should do it, even if it might just add more purposeless screen time to routines that are already unrewarding and draining.

If they say vibecoding and creating personalized AI agents with full access to our accounts are necessary to fully master AI, we should do it, even if the result is a useless, privacy-invasive tool that might create security vulnerabilities.

If they say governments worldwide should use AI at every decision-making level, we should support it, even if it might mean more biased decisions, less transparency, and the corruption of society's institutional fabric.

If they say schools and universities should embrace AI, we should accept it, even if it might lead to the further decline of reading and other scores, poorer learning, and early-onset AI dependence.

And I could go on…

This worldview has been conveniently pushed by AI companies, which are in desperate need of profits and usage growth to justify AI bubble-sized investments and keep them coming.

If you pay close attention to this narrative, it always projects possible futures of “abundance” that involve more AI usage, automation, and replacement, regardless of the consequences.

To be part of “the future,” you always have to be fully on board with the AI mindset. Otherwise, you are out.

Suspiciously, their views about abundance and a better future are never about greater well-being, more personal growth, better mental health, more thriving communities, stronger institutions, more robust legal frameworks, more effective health systems, more education, or greater equality.

These are things that would objectively make people and society better.

However, the AI industry is somehow managing to convince millions of people (and a very vocal online mass of supporters) that AI is the goal itself. Developing and using it. Regardless of the human and social outcomes.

But it does not need to be that way.

Even if some of my articles and posts might sound pessimistic, I am personally a very optimistic person.

I believe in the power of people, human connection, human learning, and human excellence (which is, again, why I write this newsletter and run my AI Governance Training interactively).

A possible and extremely positive byproduct of the generative AI wave, the apparent acceleration it has triggered, and the ideological pressure from the AI industry I described above is the rise of a new humanism.

To some extent, the new humanism is already underway on a small scale and is slowly spreading across specific communities and professional groups worldwide, as I gladly witness in every new cohort of my training when participants talk about their journey in the introductory meeting.

If you are an avid reader of this newsletter, chances are that you are also part of this movement, even though you do not see it as a “movement” yet.

So what is the new humanism, and in what sense is it a reaction to the generative AI wave?

Let me start with a quote from a recent Harvard Business Review article:

“[t]he changes brought about by enthusiastic AI adoption can be unsustainable, causing problems down the line. Once the excitement of experimenting fades, workers can find that their workload has quietly grown and feel stretched from juggling everything that’s suddenly on their plate. That workload creep can in turn lead to cognitive fatigue, burnout, and weakened decision-making. The productivity surge enjoyed at the beginning can give way to lower quality work, turnover, and other problems.”

The pressure to use AI to produce more outputs in a shorter period of time often leads to a dead end, where the quality of the work is worse, and people feel disconnected from the process that produced it.

I see more and more people revisiting their career choices and seeking alternatives that allow them to develop professionally, align their work with their values and priorities, and remain in control of the work they produce.

The new humanism is not anti-AI. It just recognizes that AI should not be a goal or a priority.

The focus should always be on the humans behind the work and how they can grow, develop, learn, and thrive, regardless of the tools used.

The new humanism recognizes that AI-generated and AI-manipulated creative works differ in nature from purely human works.

Not only is it faster and cheaper to create art (or any type of content) with AI, but the AI output is also trained on human works and often competes against them, as recent copyright lawsuits have made clear.

Both types of art have their value and can co-exist, but without the right incentives and protections in place, AI-generated work swallows and destroys purely human work.

Through the lens of the new humanism, there will be effective financial, legal, and cultural protections for purely human works because we understand that they matter and are necessary for both artists and society.

Any AI-powered innovation should be seen as one among various possibilities for achieving a specific human or social purpose.

For some tasks, automation might be the right answer; however, this is certainly not true for all tasks, especially if we think that human development and well-being, fundamental rights, and the robustness of social institutions matter.

Also, the legal system matters. AI companies must respect the law and be held accountable when they cause harm. AI is not a “species” or an “alien”; it is a product made by humans. There are human laws regulating product safety and various other aspects of AI development and deployment. The new humanism reminds companies that they must abide by them.

The new humanism is still in its early years, but it is growing as more people realize that treating AI as a priority and a goal leads to a dead end that does not support human flourishing. It only supports AI companies and their investors.

Humans must be the focus of any and all rules, policies, and rights. Human flourishing must be the focus of culture, education, and all social institutions.

I am all in, as it should have been clear over the past four years of writing this newsletter, and I will continue fighting the AI hype tides for as long as it is necessary.

Will you join me?

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This year, tech companies again decided to showcase their AI products through Super Bowl ads, including top players in AI, such as OpenAI, Google, Anthropic, and Amazon.

As everyone knows, especially advertising professionals know, ads very often do not offer an unbiased and detailed description of the product.

On the contrary, they are commonly inspirational, evoking a targeted emotion, provoking a competitor, popularizing a collective stance, or tapping into an idealized perception of the brand or the items it sells.

Ads are powerful. They can help companies rise (such as Apple's iconic “1984” Super Bowl ad), or lead to public backlash and reputational harm (such as Pepsi's Kendall Jenner ad).

With that in mind, let us take a look at what OpenAI, Google, Anthropic, and Amazon showcased during the Super Bowl, an event watched by more than 130 million people, and what lies behind the strategic advertising veil.

1. OpenAI

OpenAI’s ad was a beautiful, nostalgia-fostering clip titled “You Can Just Build Things,” promoting Codex, the company's recently launched AI coding agent.

From the Young Fathers’ “Pals” track to the 1990s-style sequence of images revering human intelligence and ingenuity, the ad made millennials like me fall into an inspired one-minute trance.

It turns out that this is not peak avant-garde cinema; it is an AI company promoting an AI agent and its brand as a supposedly human ingenuity-fostering organization.

The company's track record, however, does not seem to send the same pro-human message.

This is the same company that has launched an extremely sycophantic and emotionally manipulative AI chatbot in 2024 (GPT 4o), which created millions of loyal users, but led to various cases of mental health harm and suicides (whose families are now suing it).

This is also a company currently being sued by authors and publishers over copyright infringement, presumably because it was cheaper to just use easy-to-grab data instead of negotiating fair licensing deals with the copyright holders.

2. Google

Google's ad is titled “New Home,” and it promotes Gemini's AI assistant features, including searching through a user's photos and performing generative AI edits with a user's personal images.

In typical Google fashion, the company went deep into emotional bonds and family connections (remember "Dear Sophie"?), this time with clips of a boy growing, a mother and son hugging, and the boy and his dog playing.

With the family-oriented imagery and soundtrack, we almost forget that we are actually watching an ad for an AI tool that is often privacy-invasive, broadly scanning users’ Google accounts through Gmail, Google Photos, Google Drive, and other services under the excuse of “increased productivity” and “personalization”.

Over the past two years, it has become clear that Google’s main strategy in the AI race is to accelerate the deskilling process by embedding “smart features” into its existing services, ultimately shoving AI down the throats of its billions of users.

That is a fast way to increase its usage numbers and make claims about Gemini’s popularity.

It seems to me that to implement such an aggressive “AI first” strategy is the opposite of child-development-friendly or family-aligned. Especially when users are constantly prompted to “ask AI to help…” and almost subconsciously reminded that they are not enough without AI.

3. Anthropic

Anthropic created four ads poking fun at and criticizing OpenAI's recent announcement that it would roll out ads on ChatGPT.

The ad actually shown during the Super Bowl was titled “Can I get a six pack quickly?”

Many seem to have appreciated Anthropic’s firm stance against AI chatbot ads; many also envision the company as the eternal “good guys” of the AI industry.

So let me share an unpopular opinion about Anthropic:

Read more

A few people asked me what I thought of the speech by Yuval Noah Harari, the historian and best-selling author of Sapiens and other books, at this year's World Economic Forum meeting, so I watched the 18-minute recording.

My disappointment and disbelief began 30 seconds into his talk and continued until the end.

Harari's speech embodies exaggerations, distortions, and fictional hypotheses that many in the AI industry have presented as reasons to fear and surrender in light of humanity's inevitable downfall and the rise of AI as a new, “superior entity.”

Perhaps even more importantly, these hypotheses have been strategically used to justify legal, economic, and technical exceptionalism, the relativization of legal principles, rules, and rights, and the spread of a corporate-backed type of AI idolatry.

Also, strangely, while listening to him talk about AI, my impression was that he was discussing extraterrestrial life or an alien invasion, as many of his statements seemed uninformed or disconnected from reality.

I checked his company's website and, surprisingly, this seems to be, indeed, his reference, as there is an article titled “AI - The Alien Among Us,” where I found the (weird) image below:

When an extremely popular author like Harari echoes questionable statements about AI in a global forum like that one in Davos, they can quickly be translated into real-world policies, decisions, and goals, and affect real people.

With that in mind, let me discuss some of Harari's most exaggerated, distorted, and fictional claims from his recent speech at Davos.

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Harari starts by saying that the most important thing to know about AI is that it is not just another tool, but an agent:

“The most important thing to know about AI is that it is not just another tool. It is an agent. It can learn and change by itself and make decisions by itself. A knife is a tool. You can use a knife to cut salad or to murder someone, but it is your decision what to do with the knife. AI is a knife that can decide by itself whether to cut salad or to commit murder.”

Not so fast.

For AI to be able to “decide to commit murder,” there will first be humans behind this AI system's development who will have failed to build sufficient guardrails and oversight mechanisms to control it.

There will also have been government and regulatory bodies that failed to impose laws, standards, and AI safety frameworks to control and oversee AI systems within their jurisdictions.

An AI system is not an alien that emerges alone from the sky and decides to commit murder.

AI is a tool built by humans. Even if this tool has some level of autonomy (which might lead to harm), its design, behavior, and controls will still be the product of human decisions, actions, and inactions, whether skillful, omissive, or malicious. Claiming otherwise is promoting baseless fear and hype.

Harari then compares AI to the human mind:

“Some people argue that AI is just glorified autocomplete. It barely predicts the next word in a sentence. But is that so different from what the human mind is doing? Try to observe, to catch the next word that pops up in your mind. Do you really know why you saw that word, where it came from? Why did you think this particular word and not some other word? Do you know?”

Most people might not have realized, but this is either an uninformed or intentionally misleading take. Here is why:

Read more

Growing AI anthropomorphism and continuous AI hype seem to have given rise to a new form of AI idolatry.

Many seem to be embracing the idea that AI is smarter, therefore superior to us, and that we must adore it, foster ‘equal coexistence,’ and accept potentially being ruled by it.

From statements by leading figures such as Ilya Sutskever, Geoffrey Hinton, and Yuval Noah Harari, to Claude’s constitution and, more recently, Moltbook the ‘social network’ for AI agents (where ‘they’ plan to erase all humans), ideas about AI consciousness, superiority, and domination seem to be gaining traction outside of the realm of science fiction.

Also, when scrutinizing AI companies and proposing stricter governance and safety frameworks for AI systems, I often receive comments denying the need for oversight and idolizing AI (especially on X, where discussions tend to be more polarized and aggressive):

In that context, experiencing and documenting the generative AI wave and the rise of the ‘age of AI’ as a lawyer has been particularly interesting, given the unique perspective afforded by legal expertise.

In the first year of law school, we learn that law, and ultimately society, is shaped by a combination of forces, including ethics, culture, customs, politics, economics, power, public pressure, social movements, and human leadership.

Regardless of how “pure” or “logical” a legal system might seem, the way the law will be understood, applied, and enforced will fully depend on what the humans behind it want.

A similar logic applies to AI. It will only ever be what we humans, individually and collectively, allow it to be.

Regardless of how ‘superintelligent’ it might seem, it is ultimately a technological tool that is now regulated in many parts of the world.

Its societal role, limits, and impact will be whatever we, humans, and our institutions (including the law) allow it to be.

Having said that, there are a few basic ideas that most people do not think about, but that must be highlighted and repeated in light of the growing anthropomorphism and idolatry in AI:

Humans are humans, and machines are machines. Humans are biological and alive; machines are things created by humans.

Machines cannot be human, even if their developers design them in an anthropomorphic, “smart,” autonomous, and human-sounding way.

Machines exist to serve humans, and their developers must be held responsible if the machines they build harm other humans.

Only humans are entitled to human rights, and the law exists to support humans and human societies.

Legal rules and principles should not be used as tools against humans (which is why debates over copyright, data protection, and liability have been so heated since the beginning of the generative AI wave).

Idolizing AI and putting it on an existential or epistemological pedestal, which we must embrace, adore, and adapt to, reflects an irresponsible and dehumanizing worldview that is not aligned with basic AI governance principles.

Relying on legal and technical tools to promote and systematically embed ideas of machine consciousness or human-machine equality violates AI governance and AI safety principles, ultimately harming humans.

For example, Anthropic wrote in Claude’s constitution:

“Ultimately, we hope Claude will come to value safety not as an external constraint but as an integral part of its own goals, understanding that a careful, collaborative approach to AI development is pursued as a path towards mutual flourishing for both AI and humanity.

As I wrote in my article on the topic, these types of statements run counter to AI governance principles and human rights frameworks.

Human flourishing is a serious legal, ethical, and social goal endorsed by many frameworks worldwide. There are those who will say that it is humanity's most important goal.

AI flourishing, however, is not (and should not be) the goal of any human-centered, human rights-based technical, ethical, or legal framework or tool.

AI flourishing or ‘machine flourishing’ is, at most, a philosophical, fictional, or metaphorical exercise that should not have real-world consequences and should not be imposed on humans. It is not equivalent to, and it should not be equated with, human flourishing.

This is an extremely important time in history, and the decisions we make today might shape the next decades in an irreversible way. (More on that in my recent article "The Case for AI Regulation.")

Legal loopholes, carve-outs, and exceptions that ignore human needs, make no legal or ethical sense, and whose main goal is to support machine development or AI companies, will likely backfire and create dangerous precedents.

This is the time to prioritize, promote, and enact new rules, policies, and principles that support human flourishing, well-being, and fundamental rights.

Regardless of the distractions, illusions, and appearances created by “superintelligent” machines, humans must always remain at the forefront.

And it is more important than ever to raise your voice.

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As the old internet dies, polluted by low-quality AI-generated content, you can always find pioneering, human-made thought leadership here. Thank you for helping me make this newsletter a leading publication in the field.

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