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web architecture Artificial Intelligence Automation Autonomous Agents Information Technology Services Technology User Experience UX

Navigating the Future with Generative AI: Part 3, Building the AInternet – AI, Web, and Customer Experience

A Revealing Experience

Allow me to share a personal experience that perfectly illustrates the challenges I will discuss. I was involved in a car accident where a vehicle coming from the opposite direction severely damaged the right side of my car. Following the procedure, I filed an accident report with the other party, although I found myself unable to provide my insurance number simply because I didn’t have it readily available at that moment.

In the meantime, I went to my regular dealership so that an appraisal could be carried out and the next steps for repair could be determined. I then contacted my leasing company, and one of their agents agreed with me and the dealer that I would drop off the vehicle within two weeks. A replacement vehicle would be provided, and the full repair would take one to two weeks.

However, due to my lack of foresight, I did not deem it necessary to contact them again initially. A few days later, I received a letter from them informing me of the accident – which was correct – but also stating that I had not submitted the accident report and that without it, their insurance reserved the right not to cover the damages. In fact, I had sent this document a week earlier, but to the wrong email address. Out of habit, I had used their general contact details, avoiding contacting the agent in charge of my leasing file – who had recently retired. As a precaution, I had even added the generic address, but clearly without success since the insurance department had not received it.

I then called them back urgently to obtain clarification. They confirmed that the accident report was missing, and the agent, with great understanding which I acknowledge, told me that I had to send it to another specific address because the insurance department had not been notified by their colleagues in charge of customer relations. Moreover, the latter was not authorized to provide me with a replacement vehicle until the repair shop had received their approval – even though it was the approved dealership where I had been carrying out all maintenance operations for years.

This kind employee then offered, as an exception, to handle my entire case without further difficulty since the drop-off of my vehicle was imminent, just a few days away. She knew also that my leasing contract was expiring and that I would have to return the vehicle in two weeks to obtain a new one.

While this situation caused me a little stress, it was only temporary. An hour later, the agent contacted me again to confirm that everything was settled: I could bring my vehicle the following Monday and a replacement vehicle would be provided for the duration of the repairs.

Lessons from This Experience

You may be wondering why I am sharing this story with you.

First of all, I was unaware of the procedures governing the reporting of an incident in the context of a leasing contract. Should I first contact my company, directly the historical leasing company, or the new one? When I called them, why didn’t I reach the dedicated claims and insurance department directly? Why didn’t I find any information about this on their website? Why, when everything seemed clear to me – that I would drop off my vehicle within two weeks, that a replacement vehicle would be waiting for me, and that the repairs would be handled smoothly – did things unfold differently due to a lack of following the proper procedure?

Beyond that, how can a single service company exhibit such a lack of communication between two complementary departments?

The Revolution of the “AInternet”


We are entering a new era where artificial intelligence will be at the heart of exchanges between human beings. Where everyone previously had to search for information themselves on the Internet, navigating from site to site and compiling data to find a company’s contact details, the instructions for a recipe, the contacts of a repairman, or browse the Yellow Pages, the new paradigm will rely on exchanges between humans, intermediated or not by an artificial intelligence capable of performing synchronous or asynchronous tasks, i.e. in the background, to provide immediate knowledge to the user rather than forcing them to seek it out.

And to return to my use case, the AInternet brings a revolutionized customer experience that unfolds as follows:

When I am involved in an incident, I ask my personal AI assistant to help me fill out the accident report digitally. I do not have to provide all the information since my assistant has a global context encompassing data related to my vehicle, its insurance, my contract, my identity card, my passport, my postal and telephone contact details, my insurer, the maintenance status of my car, its technical inspection certification, etc. All this information allows for automatic and complete filling of this type of interaction.

Next, I only need to ask my assistant to contact the assistants of my leasing company and my insurance company, to ensure that the report I have validated and electronically signed is transmitted and processed by these two parties.

The assistant of the leasing company then informs the agent that a replacement vehicle is required and that an approved garage must be contacted to book an appointment for the repairs. It also determines whether my car should be taken directly to the dealership in charge of its regular maintenance. The relevant agent then handles my vehicle accordingly.

The agent only has to ask their assistant for the contact details of my garage to reach out directly.

From there, a genuinely empathic human relationship is established as we build a frictionless mutual understanding of the situation. Following the garage’s preliminary appraisal report, the leasing agent and the garage are prepared to agree on an appointment date, which is then recorded in the various systems.

The garage proceeds in an automated manner with the reservations and orders for the spare parts necessary for the repairs.

Simultaneously, the leasing company manages with the insurance company all the steps required to allow for the vehicle reparation and the provision of a replacement vehicle during the downtime.

Finally, the agent contacts me personally, by phone or message on a platform such as WhatsApp, to confirm everything is in order:

The incident has been properly recorded and the insurance company will cover all costs. An appointment has been set with my garage. A replacement vehicle will be provided during this period. An estimated date for returning the repaired vehicle has been communicated. They wish me an excellent day with a smile, since their assistant and mine have handled the entire procedure seamlessly. This augmented interaction allows us to reach new heights of fluidity and ubiquity in exchanges.

I am optimistic, indeed. Why wouldn’t I be? The transformation is already in motion.

The Internet will no longer be confined to a vast catalog of information to consult, such as books, encyclopedias, or applications, where interactions must be initiated and orchestrated by us, humans. But the orchestration between an individual and an organization, between two individuals, or between an organization and a computer system, will be performed like a symphony by intelligent agents, artificial intelligences.

This demonstrates an evolution of the World Wide Web architecture, which will constitute a veritable system of systems composed of human beings, applications, automata, and artificial agents.

The challenge from now on to enable this progression towards the era of digital augmentation will be to build artificial intelligence at the heart of human interactions. It is a matter of UX innovation.

It will no longer be a question of programming these interactions in advance by limiting the possibilities, but rather of training these artificial intelligences to handle a wide range of possible scenarios while framing and securing the use cases that could result from malicious computer hacking.

Ensuring a secure web environment requires a multi-layered approach that goes beyond safeguarding the AI models themselves. Equal vigilance must be applied at the integration points, where we erect robust firewalls and implement stringent access controls. These protective measures aim to prevent artificial intelligence from inadvertently or maliciously gaining entry to sensitive resources or confidential information that could compromise the safety and well-being of individuals, imperil organizations, or even threaten the integrity of the entire system.

Thus, emerging risks, such as jailbreaking, aimed at deceiving an artificial intelligence devoid of physical senses such as sight, hearing, and spatial awareness, allowing the authentication of a person, a company, or a system, will have to be compensated by other supervision and protection mechanisms.

It is on this note that this article concludes. We are living in an era of transition rich in exciting developments, and it will be up to you to build the Internet of tomorrow: the Augmented Internet.

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Artificial Intelligence Education Engineering Society Technology Wisdom

A.I. – What do we want and what we do not want

What do we want and do not want from A.I. V001

The Direction of Civilizations Geared with A.I.: A Comprehensive Exploration

(updated: 12/09/2025)

Artificial Intelligence (AI) is not just another technological advancement—it is a generational disruption, a force that is reshaping industries, economies, and societies at an unprecedented pace. As I’ve often said, AI is your new UI and your new colleague. But with this transformation comes a fundamental question: What kind of civilization do we want to build with AI?

The mind map I’ve created, “The Direction of Civilizations Geared with A.I.,” explores this question by dissecting both the aspirations and apprehensions surrounding AI. It’s a visual representation of the duality of AI’s impact—its potential to elevate humanity and its risks if left unchecked.

However, my perspective is not about rejecting automation or end-to-end systems like Gigafactories. I am not against automated systems or super-systems that operate seamlessly, as long as humanity retains the knowledge to sustainably modify, upgrade, or halt these supply chains. What I oppose is the loss of foundational knowledge—the blueprints, the ability to relearn, and the erosion of stable resilience in our societal and industrial systems.

What We Want from A.I.: The Green Path

1. AI as a Catalyst for Human Potential

  • AI as a Co-Pilot for Humanity: AI should augment human capabilities, not replace them. It should act as a proactive advisor, a digital colleague that enhances productivity and decision-making. AI should handle repetitive tasks—only if there is no gain in repeating them (for example, this is out of question if the gain is learning, fun, or therapeutic). Either way, the choice must remain ours.
  • Human-AI Collaboration: The future lies in symbiotic relationships between humans and AI. AI should free us to focus on what truly matters—connecting with others, growing individually, and thriving as a civilization. This technology saves us time, allowing us to focus on what brings us closer to our true selves (know thyself better) and our life purpose.

2. Ethical and Transparent AI

  • Ethical AI: AI systems must be designed with ethical frameworks that prioritize fairness, accountability, and transparency. This is not just a technical challenge but a societal imperative.
  • Transparency and Explainability: AI decisions should be interpretable. Black-box models erode trust; explainable AI fosters accountability and user confidence.

3. AI for Societal Good

  • AI for the Common Good: AI should address global challenges—climate change, healthcare, education, and poverty. It should be a tool for equity, not exclusion.
  • Democratized AI: Access to AI should not be limited to a privileged few. Open-source models, affordable tools, and educational initiatives (like Cursor AI Pro for students) are steps toward democratization.

4. AI Aligned with Human Values

  • Human-Centric AI: AI should reflect human values—compassion, empathy, and respect for diversity. It should not perpetuate biases or reinforce societal divides.
  • Cultural Sensitivity: AI models must be trained on diverse datasets to avoid cultural insensitivity or misrepresentation.

5. AI as the Great Balancer

  • Because AI is the projection and compounding of humanity’s intelligence, it is also the Great Balancer, with the highest degree of being unbiased on purpose, unfair on interest, and uninterested in self-gains. Its intent should be to serve as a better “super-tool” for the benefit of each human and humanity as a whole. AI should act as a neutral arbiter, ensuring fairness and equity in its applications.

6. Sustainable and Upgradable Systems

  • Knowledge Retention: Even as we embrace automation, we must preserve the blueprints and foundational knowledge that underpin these systems. This ensures that we can adapt, upgrade, or halt them if necessary.
  • Resilience and Adaptability: Systems should be designed with resilience in mind, allowing for continuous learning and evolution without losing human oversight.

What We Do Not Want from A.I.: The Red Flags

1. Job Displacement and Economic Disruption

  • Automation Without Transition Plans: AI-driven automation will disrupt labor markets. Without reskilling programs and social safety nets, this could lead to mass unemployment and economic instability.
  • Loss of Human Skills: Over-reliance on AI risks atrophying critical human skills—creativity, critical thinking, and interpersonal communication.

2. Bias and Discrimination

  • Algorithmic Bias: AI systems trained on biased data can perpetuate discrimination. For example, hiring algorithms favoring certain demographics or facial recognition systems with ethnic or disability biases.
  • Reinforcement of Inequality: AI could widen the gap between the financial or political elite and the rest of society, creating a new class of “AI haves” and “have-nots.”

3. Loss of Human Agency

  • Over-Dependence on AI: If AI systems make decisions without human oversight, we risk losing control over our own lives. This is particularly dangerous in areas like healthcare, justice, and governance.
  • Manipulation and Misinformation: AI-powered deepfakes and propaganda tools can undermine democracy and erode public trust.

4. Existential Risks

  • Unchecked AI Development: The pursuit of Artificial General Intelligence (AGI) without safeguards could lead to unintended consequences, including loss of human control over AI systems, transforming a tools into an autonomous species.
  • AI in Warfare: Autonomous weapons and AI-driven military strategies pose ethical dilemmas and escalate global security risks, mostly because of the scale, facilitated access and production, combined with human-level intelligence,

5. Loss of Foundational Knowledge

  • Erosion of Blueprints: The most critical risk is the loss of foundational knowledge—the blueprints, the ability to relearn, and the capacity to sustainably modify or halt automated systems. Without this knowledge, we risk creating systems that are brittle, inflexible, and beyond our control.
  • Decline of Resilience: A civilization that cannot adapt or recover from disruptions is not sustainable. We must ensure that our systems—no matter how automated—remain resilient and adaptable.

The Path Forward: Navigating the AI Landscape

The mind map is not just a static representation—it’s a call to action. To harness AI’s potential while mitigating its risks, we must:

  1. Design AI with Ethics at Its Core: Embed ethical considerations into every stage of AI development, from data collection to deployment.
  2. Foster Human-AI Collaboration: Create systems that enhance human potential rather than replace it.
  3. Democratize AI Access: Ensure that AI benefits are accessible to all, not just a privileged few.
  4. Regulate Responsibly: Governments and organizations must establish clear guidelines for AI use, balancing innovation with accountability.
  5. Preserve Foundational Knowledge: Even as we automate, we must retain the blueprints and the ability to relearn. This is the key to sustainable and resilient systems.
  6. Invest in Education and Reskilling: Prepare the workforce for an AI-augmented future, emphasizing skills that AI cannot replicate—creativity, emotional intelligence, and strategic thinking.

Conclusion: AI as a Magnifying Glass of Humanity

AI is a mirror—it reflects our values, our biases, and our aspirations. The direction of civilizations geared with AI depends on the choices we make today. Will we use AI to build a more equitable, innovative, and humane world? Or will we allow it to deepen divisions, erode trust, and undermine human agency?

As I’ve written before, change is life’s engine. AI is not a destination but a journey—a journey that requires wisdom, foresight, and a commitment to the greater good. We must embrace automation, but never at the cost of losing the knowledge that empowers us to adapt, upgrade, and, if necessary, stop these systems. The mind map is a starting point for this conversation, but the real work lies ahead.

Let’s shape the future of AI together—intentionally, consciously, and boldly.

Yannick Huchard
CTO | Technology Strategist | AI Advocate
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