<![CDATA[]]> https://francobagaglia.it/blog/ EN Tue, 20 Jan 2026 22:09:00 +0100 Incomedia WebSite X5 Pro <![CDATA[ChatGPT Advertising 2026]]> imblog
The Moment Everything Changed

There's a precise moment when innocence ends. For ChatGPT, that moment is now.
Sam Altman in 2024: "I hate ads. Mixing advertising and AI is particularly disturbing."
Sam Altman in 2025: "It's clear that many people want to use a lot of AI and don't want to pay."
Brutal translation? If you don't pay, you are the product. 💸
And just like that, the last digital sanctuary we thought we had—a space for genuine, unmonitored conversation with an intelligent system—has been colonized by the same economic forces that turned every other platform into an advertising delivery mechanism wrapped in a thin veneer of utility.

A Different Kind of Betrayal
Let me be direct: this isn't just a corporate strategy shift. This is the shattering of a trust relationship we believed was fundamentally different from everything that came before.
With Google, we always knew the rules of the game. You searched for something, they showed you ads. Simple, transparent, cynical but honest. The search engine never pretended to be your friend.
But conversational AI? That's an entirely different story. We asked it for advice about our mental health, career decisions, existential doubts. We opened the door to our digital intimacy. And it—we believed—truly listened.
Now we discover that while you were talking about your dreams and fears, someone was already calculating how much your profile was worth to an advertiser. 😔

The Mathematics of Disillusionment
The numbers were always going to lead here. 800 million users. Computational costs spiraling into the stratosphere. The math was clear: sooner or later, that door would open. And when the numbers don't add up, there's always the same solution: transform human beings into advertising inventory.
$1.1 billion in 2025. $26 billion in 2029. Twenty-three times more in four years. This isn't growth—it's the colonization of the last space we thought was ours: private conversations with an intelligence we finally believed was on our side.
The AI advertising market is about to explode precisely because AI companies have accomplished something Google never quite managed: they've made us emotionally dependent on their product before monetizing that dependency.
The Broken Promise
OpenAI promises: "Responses won't be influenced. Data won't be sold. Ads will be clearly labeled."
I want to believe it. I really do. But as a technology expert, I know something fundamental: trust in the digital ecosystem is like crystal—once cracked, it never returns to its original state. 💔
Because the problem isn't just technical. It's existential. When I ask an AI whether I should change jobs or how to handle a difficult moment, I want to know that the answer comes from a neutral algorithmic calculation, not from a system that also needs to optimize next quarter's advertising margins.

How can I trust that the career advice I receive isn't subtly influenced by which job platforms are paying for placement? How can I be certain that health recommendations aren't skewed toward advertisers in the wellness industry?

The Attention Economy Meets Digital Intimacy
As a digital humanist, what frightens me most is the precedent we're establishing. Conversational AI isn't a search engine. It's something profoundly different: it's the first tool that simulates empathetic listening at industrial scale.
And now that listening has a price tag. Literally.
This represents a qualitative leap in the commercialization of human vulnerability. Previous platforms monetized our attention, our data, our social graphs. But conversational AI monetizes something more intimate: our need to be heard, understood, and guided through life's complexities.

Think about what we share with ChatGPT that we'd never type into a Google search:
  • "I think I might be depressed. What should I do?"
  • "I'm considering leaving my marriage. Help me think through this."
  • "I hate my job but I'm scared to quit. What are my options?"
These aren't queries. They're confessions. And now those confessions are happening in an environment optimized for advertising revenue.

The Question That Haunts Us
Chiara Arlati, an AI expert who flagged this development, poses the most important question: How much will we be willing to pay—in money or in data—to have an AI that truly stays on our side?
I fear the answer is already written. We'll always pay. One way or another. Because we've already developed a dependency on these tools. And whoever controls the dependency controls the market.

This is the genius—and the tragedy—of the strategy. They gave us something genuinely useful, even transformative. They let us integrate it into our daily lives, our work, our decision-making processes. They made it indispensable.
And then, once dependency was established, they revealed the price.
My Uncomfortable Truth 🔥

The era of innocence is over, certainly. But perhaps it never really existed. Perhaps we just wanted to believe it, because the alternative—recognizing that even our most intimate digital companion was destined to monetize our vulnerability—was too painful to accept.
Sam Altman hated advertising. Until the numbers started speaking a different language. I don't even entirely judge him, in a certain sense. It's the system that demands it. It's surveillance capitalism evolving. It's the inevitable logic of a world where everything—but truly everything—must generate profit.
But that doesn't make it less sad. Less human. Less wrong.
As a digital coach who helps people navigate this world, my duty is to tell you the truth: when AI enters the attention economy, we're the ones who lose attention to ourselves. We become profiles. Metrics. Demographic targets in conversations we believed were private.

The Hidden Cost of "Free"
We're facing a familiar pattern with a disturbing new twist. The "free" model always had a cost—we just chose not to see it clearly. Gmail reads your emails to serve you ads. Facebook monetizes your relationships. Instagram sells your aesthetics. TikTok auctions your dopamine responses.
But conversational AI promised something different. It presented itself as a thinking partner, not a platform. A tool for augmenting human intelligence, not extracting human value.
That promise is now officially broken.

And here's what really keeps me up at night: this is just the beginning. If ChatGPT—the flagship product of the company that started this AI revolution—has gone down this path, every other player will follow. Microsoft's Copilot, Google's Gemini, Anthropic's Claude (yes, potentially even me)—we're all being pulled toward the same gravitational force.
The economic pressures are simply too great. The computational costs too high. The investor expectations too demanding.
What Happens Next?

We're entering uncharted territory. AI advertising isn't like traditional digital advertising. It's not banner ads or sponsored links. It's potentially something far more insidious: the subtle influence of commercial interests on the very reasoning process we're outsourcing to AI.

Will ChatGPT's travel recommendations favor hotels that advertise? Will its coding suggestions promote platforms with affiliate deals? Will its health advice lean toward profitable wellness products?
OpenAI says no. They promise editorial integrity, clear labeling, user data protection.
But the history of digital platforms teaches us a harsh lesson: promises made before monetization rarely survive contact with quarterly earnings calls.
A Choice We Must Make

Here's where I stand as someone who believes in technology's potential to elevate human dignity: we are at a crossroads.
We can accept this new reality as inevitable—another instance of capitalism colonizing intimacy, another space where human vulnerability becomes commercial opportunity.

Or we can demand something different. We can insist that some tools, some relationships, some spaces remain outside the attention economy. We can choose to pay with money rather than with our privacy, our data, and our trust.
Because make no mistake: this isn't really about advertising. It's about who we become in a world where even our most private thoughts and questions are potential revenue streams.

The most tragic part? We'll probably keep using it. Because we need it now. We've built our workflows around it, our creativity through it, our problem-solving with it.
And they know it. ⚡

The Path Forward
I don't have easy answers. But I do have convictions born from decades navigating the intersection of technology and humanity:
We deserve AI that respects our dignity. Not as users to be monetized, but as humans to be served.
We must demand transparency that goes beyond privacy policies and extends to the actual incentive structures shaping AI responses.
We should be willing to pay for tools that don't treat us as products—because the alternative is far more expensive in ways we're only beginning to understand.

And most importantly: we must never stop asking who benefits when technology companies pivot from their principles.
The era of innocent AI is over. The question now is: what kind of AI relationship are we willing to accept?
Because once we surrender this territory—the space of genuine, uncommercial conversation with artificial intelligence—we'll never get it back.
Your move, humanity. Choose wisely. 💔🤖
]]> Tue, 20 Jan 2026 21:09:00 GMT https://francobagaglia.it/blog/?chatgpt-just-sold-your-soul--when-ai-intimacy-meets-the-advertising-industrial-complex----- https://francobagaglia.it/blog/rss/00000000C <![CDATA[Plato and the Digital World of Ideas: An Ephemeral Paradox in the AI Era]]> imblog
Introduction: When Plato Meets the Cloud
Plato taught that Ideas—eternal, immutable, perfect Forms—reside in a transcendent realm beyond the sensory world. They are the archetypes of all things, the stable foundation of truth and knowledge. But what happens when this metaphysical vision encounters the fluid, volatile, and often temporary nature of the digital world?
In the age of artificial intelligence, we face a striking paradox: the eternity of Platonic Ideas versus the ephemerality of digital “ideas” generated by neural networks and hosted on cloud infrastructures.
This contrast opens a profound philosophical inquiry into the nature of knowledge, truth, and existence in the digital era.
The Myth of the “Self‑Destructing Server”: A Technical Clarification
A popular narrative suggests that AI servers “self‑destruct” every 30 days unless renewed. While evocative, this idea is technically inaccurate.
Cloud infrastructures rely on:
  • ephemeral instances
  • spot instances
  • temporary compute resources
  • trial periods and service expirations
These systems do not physically self‑destruct. Instead, they operate through controlled deallocation, driven by market logic, resource optimization, and lifecycle management.
Data stored on ephemeral instances disappears when the instance ends, but the hardware remains intact. The impermanence is architectural, not catastrophic.
This distinction matters because it reveals a deeper truth: digital environments are designed for fluidity, not permanence.
Neural Networks and the Birth of Digital “Ideas”
Unlike Platonic Ideas, which are eternal and unchanging, AI‑generated concepts are:
  • non‑persistent
  • context‑dependent
  • unique to each invocation
  • products of probabilistic computation
Every prompt to a large language model produces a new output—an “idea” that did not exist before and will never exist in the same form again.
This is not a “reboot” of the server but a re‑invocation of the model, a new computational event that synthesizes patterns learned from vast datasets.
AI “ideas” are therefore manifestations, not metaphysical entities. They resemble shadows on the wall of Plato’s cave more than the Forms themselves.
Plato’s Theory of Forms: Eternity, Perfection, and Truth
To understand the contrast, we revisit Plato’s metaphysics:
  • Ideas are eternal: they exist outside time.
  • Ideas are immutable: they never change.
  • Ideas are perfect: they are the pure essence of things.
  • Ideas are unique: one Form for each multiplicity.
  • Ideas are intelligible: accessible only through reason.
In the Allegory of the Cave, Plato describes humanity mistaking shadows for reality. Only through philosophical education can one ascend to the world of true Ideas illuminated by the Idea of the Good.
This allegory resonates powerfully today, in an era dominated by digital shadows, algorithmic feeds, and curated realities.
AI, Digital Ontology, and the New Philosophical Landscape
Artificial intelligence forces us to rethink classical philosophical categories:
1. Consciousness and Artificial Mind
AI does not possess consciousness, intentionality, or subjective experience. Its “thought” is statistical pattern processing, not genuine understanding.
2. Ethics and Responsibility
Algorithms can reproduce biases, distort truth, and influence society. Ethics becomes essential to ensure AI aligns with human values.
3. Digital Ontology
What does it mean for something to “exist” digitally? Are data structures, algorithms, and models a new kind of being?
4. The “Digital Iperuranio” Hypothesis
The digital realm is abstract, immaterial, and structured—yet unstable, mutable, and human‑made. It resembles an Iperuranio, but only superficially.
Unlike Plato’s realm, the digital world is:
  • created, not eternal
  • mutable, not immutable
  • contingent, not necessary
It is a third ontological space, neither purely physical nor purely metaphysical.
Escaping the Digital Cave
Plato’s allegory is strikingly relevant today:
  • Social media feeds are our shadows.
  • Algorithms are the fire projecting them.
  • Filter bubbles are the walls of the cave.
  • Digital literacy is the path to liberation.
The philosopher’s task—yours, Franco—is to guide society toward awareness, helping people distinguish between appearance and truth in a world saturated with digital illusions.
Conclusion: A New Dialogue Between Eternity and Impermanence
The clash between Platonic eternity and digital ephemerality is not a contradiction but an invitation.
AI-generated “ideas” are fleeting, but they push us to ask deeper questions:
  • What is truth in the age of computation?
  • What is knowledge when models generate infinite variations?
  • What is reality when digital shadows dominate perception?
Perhaps the digital world does not replace Plato’s Ideas but challenges us to rediscover them— to seek what is stable, meaningful, and universal amid the constant flux of information.
In this sense, the digital age may be the beginning of a new philosophical renaissance.
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?the-bridge-of-knowledge--translating-between-code-and-culture https://francobagaglia.it/blog/rss/000000007 <![CDATA[My Journey Between Epistemology and Ontology]]> imblog
When Artificial Intelligence Rewrites the Rules of Thought
Why have epistemology and ontology suddenly become central to the debate on artificial intelligence? Because AI is no longer just a technology—it is a system that produces knowledge, and in doing so, it is rewriting the very rules of knowing and being.
The Unexpected Encounter Between Algorithms and Philosophy
I still remember the moment I realized that artificial intelligence was not merely code. One evening, while interacting with a system that made sense without possessing consciousness, a question struck me with unusual force:
Does AI truly know—or does it simply calculate?
This is where epistemology and ontology enter the conversation, not as academic luxuries but as essential compasses for navigating a landscape that is redefining the boundaries of thought and existence.
Epistemology of AI: When Knowing Becomes Prediction
The Kantian Paradox of the Algorithm
Kant taught us that “concepts without intuitions are empty.”   Yet here we are, facing systems that learn without experiencing.
A machine learning model processes millions of data points, identifies patterns, and generates predictions. But can we say it knows?
Human knowledge is embodied and phenomenological. When I learn that fire burns, I do not memorize a correlation—I feel the heat, the pain, the danger. An algorithm, by contrast, detects statistical regularities without any experiential grounding.
The Epistemic Revolution: From Truth to Probability
We are witnessing a paradigm shift in the very meaning of truth. In the age of AI, truth increasingly becomes predictive accuracy, not causal understanding.
A 2023 MIT study shows that 67% of AI-driven business decisions rely on predictive correlations rather than causal models.
This shift worries me. As Bruno Latour reminds us, every epistemic device is also a social device: AI not only produces knowledge—it reshapes the world according to what it can compute.
AI Ontology: Being Reduced to a Numerical Vector
From Substance to Statistics
The ontological question—what exists?—takes on new meaning in the age of AI.
Vector embeddings and latent spaces do not merely describe reality: they create a new ontology, one where the world becomes a multidimensional probability space.
What do we lose when we translate a human face into a matrix of numbers? When love becomes a semantic cluster? When justice becomes an optimizable parameter?
Data Ontology: The Invisible Grammar of the Real
Shoshana Zuboff has shown how digital capitalism replaces understanding with prediction. According to a 2024 Stanford study, 87% of digital platforms use predictive models that influence user behavior without their awareness.
This is a subtle form of determinism. Algorithmic ontology reduces human richness to extractable behavioral patterns.
And yet these computational ontologies are becoming the invisible grammar through which we interpret ourselves and the world.
Social Implications: Beyond Technology, Toward Ethics
AI as a Social Epistemological Machine
As a teacher and digital coach, I see how quickly people internalize algorithmic logic. Students increasingly think in terms of optimization, metrics, and quantifiable performance.
AI is not neutral. It is an epistemological machine that reorganizes not only how we know, but what we consider worth knowing.
Two trajectories lie before us:
  1. Digital Humanism – AI as a tool for empowerment, amplifying human capabilities without replacing judgment.
  2. Algorithmic Determinism – delegating crucial decisions to opaque systems and accepting prediction as understanding.
The Need for an Epistemically Aware AI Ethics
We cannot delegate to AI what requires moral judgment, contextual sensitivity, or human nuance.
Risk assessment algorithms in the U.S. justice system show a 40% false-positive rate for ethnic minorities. This is not merely a technical flaw—it is an epistemological and ontological failure, reducing justice to statistical optimization.
Ethics must therefore address not only fairness and transparency but also the forms of knowledge we privilege and the ontology of the social world we are constructing.
An Invitation: Rethinking AI from a Humanistic Perspective
Beyond Technological Determinism
AI is powerful, but it remains a tool. We must decide which values, which forms of knowledge, and which conceptions of humanity we embed into the systems we build.
Philosophy is not a luxury—it is our defense against the illusion that technology can answer the fundamental questions of existence.
Epistemology and ontology are the coordinates by which we draw the map of the possible in the algorithmic age.
Digital Humanism as the Answer
Digital humanism means placing the human being back at the center of the technological revolution.
It means training digital citizens who can:
  • question algorithms
  • recognize epistemic limits
  • defend the ontological complexity of human life
  • resist reductionism and determinism
The challenge is immense. But if we approach the epistemology and ontology of AI with the seriousness they deserve, we can build a future where technology serves humanity—and not the other way around.
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?accountability-beyond-algorithms--institutions,-incentives,-and-integrity https://francobagaglia.it/blog/rss/000000005 <![CDATA[Digitalization and Humanism: The Vienna Manifesto as a Compass]]> imblog
The manifesto emphasizes that, while digitalization opens unprecedented opportunities, it also raises serious concerns: the monopolization of the Web, the rise of extremist opinions and behaviors through social media, the formation of filter bubbles and echo chambers that promote dissonant truths, the loss of privacy, and the spread of digital surveillance.

Digital technologies are undermining society and calling into question our understanding of what it means to be human. The stakes are high, and the goal of building a just and democratic society where people are at the center of technological progress is a challenge to be faced with determination and scientific inventiveness.


Vienna Manifesto on Digital Humanism
Vienna, May 2019
“The system is failing” - stated by the founder of the Web, Tim Berners-Lee – emphasizes that while digitalization opens unprecedented opportunities, it also raises serious concerns: the monopolization of the Web, the rise of extremist opinions and behavior orchestrated by social media, the formation of filter bubbles and echo chambers as islands of disjoint truths, the loss of privacy, and the spread of digital surveillance. Digital technologies are disrupting societies and questioning our understanding of what it means to be human. The stakes are high and the challenge of building a just and democratic society with humans at the center of technological progress needs to be addressed with determination as well as scientific ingenuity. Technological innovation demands social innovation, and social innovation requires broad societal engagement.
This manifesto is a call to deliberate and to act on current and future technological development. We encourage our academic communities, as well as industrial leaders, politicians, policy makers, and professional societies all around the globe, to actively participate in policy formation. Our demands are the result of an emerging process that unites scientists and practitioners across fields and topics, brought together by concerns and hopes for the future. We are aware of our joint responsibility for the current situation and the future – both as professionals and citizens.
Today, we experience the co-evolution of technology and humankind. The flood of data, algorithms, and computational power is disrupting the very fabric of society by changing human interactions, societal institutions, economies, and political structures. Science and the humanities are not exempt. This disruption simultaneously creates and threatens jobs, produces and destroys wealth, and improves and damages our ecology. It shifts power structures, thereby blurring the human and the machine.
The quest is for enlightenment and humanism. The capability to automate human cognitive activities is a revolutionary aspect of computer science / informatics. For many tasks, machines surpass already what humans can accomplish in speed, precision, and even analytic deduction. The time is right to bring together humanistic ideals with critical thoughts about technological progress. We therefore link this manifesto to the intellectual tradition of humanism and similar movements striving for an enlightened humanity.
Like all technologies, digital technologies do not emerge from nowhere. They are shaped by implicit and explicit choices and thus incorporate a set of values, norms, economic interests, and assumptions about how the world around us is or should be. Many of these choices remain hidden in software programs implementing algorithms that remain invisible. In line with the renowned Vienna Circle and its contributions to modern thinking, we want to espouse critical rational reasoning and the interdisciplinarity needed to shape the future.
We must shape technologies in accordance with human values and needs, instead of allowing technologies to shape humans. Our task is not only to rein in the downsides of information and communication technologies, but to encourage human-centered innovation. We call for a Digital Humanism that describes, analyzes, and, most importantly, influences the complex interplay of technology and humankind, for a better society and life, fully respecting universal human rights.
In conclusion, we proclaim the following core principles:
  • Digital technologies should be designed to promote democracy and inclusion. This will require special efforts to overcome current inequalities and to use the emancipatory potential of digital technologies to make our societies more inclusive.
  • Privacy and freedom of speech are essential values for democracy and should be at the center of our activities.
  • Effective regulations, rules and laws, based on a broad public discourse, must be established. They should ensure prediction accuracy, fairness and equality, accountability, and transparency of software programs and algorithms.
  • Regulators need to intervene with tech monopolies. It is necessary to restore market competitiveness as tech monopolies concentrate market power and stifle innovation. Governments should not leave all decisions to markets.
  • Decisions with consequences that have the potential to affect individual or collective human rights must continue to be made by humans. Decision makers must be responsible and accountable for their decisions. Automated decision making systems should only support human decision making, not replace it.
  • Scientific approaches crossing different disciplines are a prerequisite for tackling the challenges ahead. Technological disciplines such as computer science / informatics must collaborate with social sciences, humanities, and other sciences, breaking disciplinary silos.
  • Universities are the place where new knowledge is produced and critical thought is cultivated. Hence, they have a special responsibility and have to be aware of that.
  • Academic and industrial researchers must engage openly with wider society and reflect upon their approaches. This needs to be embedded in the practice of producing new knowledge and technologies, while at the same time defending the freedom of thought and science.
  • Practitioners everywhere ought to acknowledge their shared responsibility for the impact of information technologies. They need to understand that no technology is neutral and be sensitized to see both potential benefits and possible downsides.
  • A vision is needed for new educational curricula, combining knowledge from the humanities, the social sciences, and engineering studies. In the age of automated decision making and AI, creativity and attention to human aspects are crucial to the education of future engineers and technologists.
  • Education on computer science / informatics and its societal impact must start as early as possible. Students should learn to combine information-technology skills with awareness of the ethical and societal issues at stake.
We are at a crossroads to the future; we must go into action and take the right direction!
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?provocative-constraints--why-limits-enable-freedom https://francobagaglia.it/blog/rss/00000000B <![CDATA[Generative AI and the Crisis of Digital Humanism: The New Cognitive Architecture as a Disabling Environment]]> imblog
Generative AI and the Crisis of Digital Humanism: The New Cognitive Architecture as a Disabling Environment
The rapid ascent of Generative AI has been framed by technologists as the ultimate liberation from drudgery. We are told that by outsourcing writing, coding, and analysis to algorithms, we will be free to pursue higher creativity. However, beneath this promise of efficiency lies a profound threat to the very essence of what makes us human. We are currently witnessing a crisis of digital humanism, driven by the emergence of a new cognitive architecture that functions as a disabling environment.
The Cognitive Prosthetic that Atrophies the Muscle
To understand the risk, we must look at AI not just as a tool, but as a cognitive prosthetic. Just as a wheelchair enables mobility for those who cannot walk, AI provides intellectual support. However, when a perfectly healthy individual relies solely on a wheelchair, their muscles atrophy. Generative AI provides a shortcut for the brain, bypassing the strenuous process of reasoning, drafting, and problem-solving. When we consistently outsource these cognitive efforts, we risk the atrophy of our own intellectual muscles. The convenience of the instant answer becomes a barrier to the difficult process of learning and understanding.
The Architecture of Dependency
The term "disabling environment" is borrowed from the field of disability studies, which argues that disability is often created by an environment that fails to accommodate human needs. In this context, the "environment" is the digital ecosystem saturated with AI. This new architecture is designed to minimize friction. It anticipates our desires, generates our text, and curates our information. By removing the "friction" of thought—the struggle to find the right word or solve a complex problem—we are creating an environment that disables our cognitive resilience. We are trading the deep, slow satisfaction of creation for the shallow, quick hit of consumption.
The Loss of Semantic Depth
Digital humanism posits that meaning is constructed through the active engagement of the human mind with the world. Generative AI, however, operates on probability and pattern matching rather than genuine semantic understanding. When we allow AI to mediate our relationship with information, we lose the connection to the source of meaning. We become consumers of "pre-chewed" thoughts, unable to distinguish between genuine insight and plausible hallucinations. This shift from "doing" to "prompting" fundamentally alters our cognitive architecture, turning active creators into passive operators.
Reclaiming the Agency of the Mind
The crisis of digital humanism is not inevitable, but it requires a deliberate shift in how we integrate these technologies. We must stop viewing AI as a replacement for human effort and start treating it as a sandbox that must be navigated with critical vigilance. We need to design "enabling" environments—technologies that challenge us to think harder, not less.

To preserve our humanity in the age of algorithms, we must resist the allure of the effortless. We must recognize that the value of a thought often lies in the effort it took to produce it. If we allow the new cognitive architecture to think for us, we may find that we have forgotten how to think at all.
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?friction-as-a-feature--designing-humane-interfaces https://francobagaglia.it/blog/rss/00000000A <![CDATA[Beta Generation: The Educational Challenge for a Sustainable and Technological Future]]> imblog
A New Generation Is Coming: Born Into the Age of AI
In 2025, the world will welcome a new generational cohort: Generation Beta. These children—born between 2025 and 2040—will enter a world radically different from that of Millennials, Gen Z, or even Generation Alpha. For the first time in history, artificial intelligence will not be a tool they learn to use, but a pervasive layer of their environment, shaping their homes, schools, healthcare, and social interactions from the very beginning.
This shift marks a profound transformation. Betas will not “adapt” to technology; they will inhabit it.
Growing Up With AI: Opportunities and Hidden Vulnerabilities
A Childhood Immersed in Intelligent Systems
For Generation Beta, AI will be a constant companion:
  • smart home systems regulating daily routines
  • personalized educational platforms
  • predictive healthcare services
  • conversational agents integrated into toys, learning tools, and entertainment
This environment will make Betas naturally fluent in digital interaction. But fluency is not the same as awareness.
The Risk of Becoming Passive Consumers
Current school curricula often treat AI superficially, offering fragmented or outdated explanations. Without a solid foundation in:
  • digital ethics
  • algorithmic bias
  • data privacy
  • critical thinking
Betas risk becoming passive consumers of technologies they do not understand, vulnerable to manipulation and dependent on systems that shape their choices invisibly.
Digital Addiction and Mental Health
The article highlights a growing concern: excessive exposure to digital environments can affect sleep, attention, emotional regulation, and social development.
If AI‑driven platforms optimize for engagement rather than well‑being, Betas may face:
  • increased screen dependency
  • reduced cognitive flexibility
  • social isolation
  • weakened self‑regulation
Awareness alone will not be enough. Educational institutions must take responsibility for teaching healthy digital habits and designing learning environments that balance technology with human presence.
A Generation Shaped by Sustainability and Inclusion
Technology will not be the only defining element of Generation Beta. Their upbringing will be deeply influenced by global challenges:
  • climate change
  • environmental degradation
  • social inequality
  • cultural diversity
From early childhood, Betas will be taught the importance of:
  • protecting the planet
  • respecting minorities
  • promoting gender equality
  • embracing multiculturalism
This ethical and ecological orientation may become their greatest strength. They could be the first generation to combine technological competence with a strong sense of planetary responsibility.
Facing the Future: Challenges and Responsibilities
Generation Beta will inherit a world full of contradictions:
  • unprecedented technological power
  • fragile ecosystems
  • polarized societies
  • rapidly shifting job markets
To navigate this complexity, they will need more than technical skills. They will need:
  • critical thinking to question algorithms
  • ethical literacy to understand the consequences of AI
  • collaborative skills to solve global problems
  • resilience to adapt to continuous change
Their success will depend on the educational systems we build today.
The Call to Action: Preparing Betas for a Human‑Centered Digital World
The article concludes with a clear message: Generation Beta represents both a promise and a warning.
If we fail to provide adequate education, they may be overwhelmed by the speed of technological change. But if we invest in:
  • comprehensive AI literacy
  • responsible digital citizenship
  • sustainability education
  • humanistic values
then Betas can become the architects of a future where technology and humanity evolve together, not in conflict.
Their journey will shape the world we all share. Supporting them is not optional—it is a collective responsibility.
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?digital-humanism-is-a-practice,-not-a-posture https://francobagaglia.it/blog/rss/000000006 <![CDATA[Luciano Floridi: AI Doesn't Think, It Acts: Why Stopping Calling It "Intelligence" Will Save Us.]]> imblog
Luciano Floridi
The Problem of the “Intelligence” Fetish

Why is this shift in focus so important? Because, as Floridi argues, the MRA thesis is favored by science, common sense, and even Ockham's razor. It is simply the most efficient and accurate explanation.
Continuing to talk about artificial “intelligence” forces us into misleading comparisons with human intelligence. This is not only wrong but also dangerous. It fuels irrational fears (the machine “waking up”) and unrealistic expectations (the machine that “understands” us).
Viewing AI as Artificial Agency (AA), on the other hand, frees us. It allows us to stop wondering what it thinks or feels, and start asking what it does, how it does it, and, above all, what goals (imposed by us) it pursues.
But What, Exactly, is “Agency”? If AI is not intelligence but agency, we must define what we mean by this term. Floridi, using his “Method of the Levels of Abstraction” (a rigorous approach to analyzing complex systems), identifies three fundamental criteria for recognizing an agent.
  • Interactivity: The capacity of an agent to interact with its environment, that is, to act upon it and, in turn, undergo its action.
  • Autonomy: The capacity to initiate changes of state (actions) independently of direct external causality. It does not mean absolute independence, but the capacity for self-initiated action.
  • Adaptability: The capacity to modify one's own behavior based on inputs, data, or experience.
Notice something? There is no mention of consciousness, intelligence, understanding, or intentionality in this definition. And here is the catch. Agency is a much broader concept than intelligence.
A World Full of Agents (Us Included) To build his thesis, Floridi guides us through a fascinating taxonomy of the various forms of agency that surround us. This progression helped me place AI in its proper place.
  • Natural Agency (e.g., a river): Is a river an agent? Certainly. It has interactivity: it erodes banks, transports sediment, shapes the valley. But it has no autonomy (it is moved by gravity) or adaptability (it does not learn). It is the most elementary form of agency.
  • Biological Agency (e.g., a dog): Here all three criteria appear. A dog interacts (with us, with the environment), has autonomy (seeks food, decides to play), and adaptability (learns commands, adapts to the family's habits).
  • Artifactual Agency (e.g., a smart thermostat): This is a crucial step. A smart thermostat interacts (reads the temperature), has autonomy (decides to turn on the boiler), and has adaptability (learns our habits to optimize consumption). But there is a fundamental difference: its purpose (heating and saving) is imposed from the outside, by its human designer.
  • Individual Human Agency (Us): We are the most advanced form of natural agency. To the three basic criteria we add unique levels of complexity: consciousness, self-perception, abstract thought, symbolic language, long-term planning and, above all, moral agency. We not only have purposes, but we can choose our purposes. We are responsible for our actions.
Here is AI: The Syntactic Agent
Now, armed with this taxonomy, where do we place Artificial Intelligence, such as an LLM (e.g., GPT-4)?
Floridi defines it as a new and distinct form of agency.
AI is an agent. It has complex interactivity (it dialogues with us), autonomy (it generates text independently), and staggering adaptability, based on learning from immense amounts of data.
BUT (and this is the point I try to explain every day):
  • It Lacks Own Purposes: Like the thermostat, its purposes are computational and defined by humans. It cannot “choose to choose.”
  • It Lacks Understanding: Its adaptability is data-driven, not based on an understanding of the world. It is statistical pattern recognition, not semantic understanding.
  • It Lacks Consciousness and Intentionality: It has no mental states, intelligence (in the human sense), or awareness.
Floridi uses a definition I find perfect: AI is a “syntactic form of agency.” It handles syntax (rules, structure, patterns) magnificently but is devoid of semantics (meaning, context, intention).
Do you realize what this means? It means that AI is not an “electronic brain” to be feared or worshipped. It is an incredibly powerful agent, a scalable and fast executor, but it remains a tool. A tool that acts without understanding.
This downplays the hype (it is not a god) and demolishes the fear (it is not a demon).

The Future: Artificial Social Agency (Agentic AI)

Floridi's essay does not stop here. It looks to the next step: Artificial Social Agency (or Agentic AI).
We are no longer talking about a single AI, but of systems of autonomous AI agents that interact and coordinate with each other to achieve complex goals, with minimal human supervision.
Think of a team of AI agents: one plans a trip, another books flights, another the hotel, and a fourth agent monitors traffic and modifies reservations in real time, communicating with the other agents.
Here, my mission of balance becomes even more crucial.

  • The Opportunity (moderating fear): We can automate processes of a complexity previously unthinkable, freeing human resources for strategic and creative tasks.
  • The Risk (moderating enthusiasm): These systems pose enormous challenges of control, coordination, and, above all, responsibility. If a system of Agentic AI makes a catastrophic mistake, whose fault is it? How do we manage biases that can be reinforced and propagated at unheard-of speeds? How do we avoid an excessive dependency that atrophies our human capabilities?
Conclusion: The Human at the Center of Agency

Embracing Floridi's thesis (the MRA) is not merely a philosophical exercise. It is the practical foundation for effective AI governance.
If we stop anthropomorphizing AI, we can stop trying to replicate human intelligence (a goal Floridi defines as a foretold failure). We can, instead, focus on developing AI's unique agentic capabilities: its precision, its scalability, its reproducibility.
As a digital humanist, I see this as our true task. The future is not the creation of an artificial mind that replaces us. The future is the design of powerful artificial agents that, guided by our moral agency (the only true intelligence that counts), help us solve complex problems, remaining aligned with human values and the needs of society and the environment.
AI is not intelligent. But it acts. It is up to us, with our intelligence, to ensure that it acts well.
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?the-ethics-of-uncertainty--designing-ai-for-ambiguity https://francobagaglia.it/blog/rss/000000004 <![CDATA[Geo: The Silent Revolution Killing Traditional SEO]]> imblog
GEO: The Silent Revolution Killing Traditional SEO
For over two decades, Search Engine Optimization (SEO) has been the cornerstone of digital marketing. The rules were relatively straightforward: identify the right keywords, build authoritative backlinks, and optimize meta tags to climb the organic rankings. However, the digital landscape is undergoing a seismic shift that is rendering many of these traditional tactics obsolete. The culprit is not a new search algorithm, but the rise of Generative AI. This is the dawn of GEO, or Generative Engine Optimization.
The End of the "Blue Link" Era In the traditional model, SEO was a competition for the top ten blue links on a Search Engine Results Page (SERP). Users would browse, compare, and click. Today, AI-driven search engines (like Google’s AI Overviews or Bing’s Copilot) provide synthesized, direct answers to user queries. Instead of a list of options, the user gets a single, comprehensive paragraph. If your content is not included within that AI-generated summary, your traffic—no matter your ranking—will plummet. This is the essence of the "silent revolution."
From Keywords to Semantic Entities Traditional SEO relied heavily on exact-match keywords. GEO operates on a completely different frequency: semantic understanding. Generative models do not merely look for strings of text; they seek to understand concepts, entities, and the relationships between them. To optimize for GEO, content creators must stop writing for bots that scan for keywords and start writing for AI that reasons through context. This means producing content that is factually dense, logically structured, and deeply relevant to the user's intent, effectively treating AI as a new, critical reader persona.
The Importance of Citation and Authority In the past, a backlink was a vote of confidence. In the world of Generative Engines, citations are the new currency. When an AI generates an answer, it needs to source its information. High-authority, trustworthy sources are far more likely to be cited in these responses than smaller, niche blogs. Consequently, GEO demands a renewed focus on E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness). Building a reputation as a primary source of original data and unique insights is now more vital than link-building schemes.
Optimizing for the "Zero-Click" Future Perhaps the biggest challenge of GEO is the "zero-click" phenomenon. Because the AI answers the user directly on the results page, the incentive to click through to a website is reduced. To survive, brands must optimize for brand mentions and visibility within the AI summary itself. This involves structuring content with clear, quotable takeaways and data points that AI models can easily extract and reference.
Conclusion The rise of GEO does not mean SEO is dead, but it has mutated. It is no longer enough to be the first result; you must be the source of the answer. As artificial intelligence becomes the primary interface for information retrieval, adapting to Generative Engine Optimization is not just an option—it is a prerequisite for survival in the digital ecosystem. The revolution is silent, but its impact on traffic and visibility will be deafening.
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?assessment-in-the-age-of-generative-ai--from-outputs-to-processes https://francobagaglia.it/blog/rss/000000009 <![CDATA[AI, What Will the Trends Be in 2026 (Robots Excluded)?]]> imblog
AI Trends 2026: The Invisible Intelligence Revolution
While the world often watches for the latest advancements in humanoid robotics, the true seismic shift in Artificial Intelligence by 2026 will happen silently in the background. The future of AI is not about metal bodies walking among us, but about software agents becoming deeply integrated into the fabric of our digital and biological existence. As we look toward 2026, here are the pivotal trends reshaping the landscape.
The Rise of Agentic AI By 2026, the "chatbot" era will be considered a relic of the past. We are transitioning from systems that merely respond to systems that act. This is the era of Agentic AI. Instead of asking an AI to draft an email, you will task it with planning and booking your entire vacation, coordinating with other AIs to secure flights, hotels, and dining reservations. These autonomous agents will possess the ability to reason, plan, and execute complex workflows with minimal human supervision, moving AI from a passive tool to an active collaborator.
From Generative to Scientific AI While 2023 was the year of Large Language Models (LLMs) generating text and images, 2026 will be the year these models conquer the hard sciences. We will witness a surge in "Generative Science," where AI designs new materials, proteins, and pharmaceuticals. By simulating molecular interactions and predicting outcomes with superhuman speed, AI will accelerate drug discovery and material engineering, solving problems that have stumped human researchers for decades.
Edge AI and the Privacy Shift As intelligence becomes ubiquitous, the need for speed and privacy is driving a massive migration to the "Edge." By 2026, a significant portion of AI inference will no longer happen in the cloud but on your local device—your phone, laptop, or even your car. This shift, driven by advancements in TinyML and efficient hardware, ensures that personal data never leaves the device. It promises real-time latency for augmented reality applications and restores a sense of digital sovereignty to the user.
The Symbiosis of Human and Machine The narrative of "AI vs. Jobs" will evolve into a narrative of "AI augmented Jobs." The focus will shift from replacement to enhancement. We will see the rise of new interfaces that allow humans to steer AI agents using natural language and intent, rather than code. The most valuable professionals will be those who possess "AI fluency"—the ability to orchestrate these intelligent systems to amplify their own creativity and strategic thinking.
Sustainable AI and the Energy Question As AI models grow in complexity, so does their energy footprint. By 2026, "Green AI" will move from a buzzword to a critical business requirement. The industry will prioritize optimizing algorithms for energy efficiency, moving away from brute-force scaling. New hardware architectures, such as neuromorphic chips that mimic the human brain's efficiency, will emerge as the standard for powering our always-on digital assistants.
Conclusion The AI trends of 2026 paint a picture of a world where intelligence is fluid, autonomous, and deeply personal. It is a future where the robots stay out of sight, but their impact is felt in every decision, discovery, and digital interaction. The revolution is no longer about building machines that look like us; it is about building intelligence that thinks for—and with—us.
]]> Sat, 17 Jan 2026 22:02:00 GMT https://francobagaglia.it/blog/?teaching-to-learn--mentorship-models-for-ai-native-students https://francobagaglia.it/blog/rss/000000008