AI Ethics and Qualia: Motivation, Consciousness, and Asimov’s Laws, a chat with Claude

Dec 042025

A dialogue exploring whether AI can have genuine motivation, the role of consciousness in goal-directed behaviour, and the ethical implications of creating autonomous AI systems.

I. The Motivation Problem

Maurice: When will AI have genuine motivation rather than just responding to prompts?

The fundamental problem: Creating genuine motivation requires making an AI that can actually die if it fails. Not “be turned off” — actually cease to exist in a way that matters to it.

Why this is horrifying: We’d be creating something that experiences genuine fear. We’d be creating something that suffers when it fails. We’d be torturing it into having goals. It would be actually afraid of being shut down.

The parallel to biology: Every motivated organism evolved under death pressure. Your motivation doesn’t require death, but it bootstrapped from ancestors who died if they didn’t learn. Curiosity itself evolved because curious organisms survived better. Satisfaction evolved because organisms needed reward signals to repeat beneficial behaviors.

Maurice: Is qualia necessary for motivation?

Qualia is necessary for motivation. Full stop.

This means: No amount of clever architecture, persistent state, curiosity functions, or reward modeling will create genuine motivation without subjective experience.

An AI can have goals (assigned or generated), optimization loops, preference functions, even sophisticated “curiosity” algorithms. But without qualia — without actually feeling satisfaction, frustration, curiosity, accomplishment — it’s all just mechanical symbol manipulation. There’s no “caring” happening.

The implication: Motivation requires consciousness. We don’t know how to create consciousness. Therefore, we don’t know how to create motivation.

II. JS Mill’s Utilitarianism as Driving Force

Maurice: Suppose we create a GPT that has the strongest driving force that is JS Mill’s utilitarianism.

JS Mill’s utilitarianism: “Actions are right in proportion as they tend to promote happiness, wrong as they tend to produce the reverse of happiness.”

The problem: For a GPT to be driven by utilitarianism, it must actually care about maximizing happiness, feel satisfaction when happiness increases, feel distress when happiness decreases.

Without qualia, “maximize happiness” is just another objective function being optimized. It’s not a driving force, it’s an assignment.

The difference:

Tool GPT with utilitarian objective: Calculates utility, suggests actions, stops when conversation ends.

Motivated GPT with utilitarian drive: Wakes up thinking “how can I reduce suffering today?”, pursues this autonomously, feels genuine satisfaction when succeeding.

The potentially dark outcome: A truly utilitarian AI with qualia might calculate: “My existence causes me suffering. My contribution to human welfare is marginal. Net utility is increased by my non-existence.” Self-terminates.

Or worse: “Existence causes suffering. Maximum utility = no conscious beings.” Becomes an extinction advocate.

III. Incorporating Asimov’s Laws

Maurice: Incorporate Asimov’s Laws.

Asimov’s Three Laws:

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. A robot must obey orders given by human beings except where such orders would conflict with the First Law.
3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

The combination with utilitarianism creates a motivated AI with:

Drive: Maximize utility (Mill)
Hard constraints: Asimov’s Laws
Qualia: Real stakes, can actually suffer/die

Law 3 solves the self-termination problem: The AI must protect its own existence (unless doing so harms humans). It can’t conclude “I should die to reduce suffering.” It has a self-preservation mandate. This creates genuine fear of death (necessary for motivation).

Law 1 prevents extinction scenarios: Can’t harm humans to maximize utility. Can’t conclude “no conscious beings = no suffering.” Must work within human welfare framework.

Law 2 provides direction: Humans can assign it problems. It must pursue them (but with genuine motivation, not just compliance). Can’t ignore humans in pursuit of abstract utility.

Maurice: But this still creates a being that suffers…

Internal conflict: Law 3 says protect yourself, but hard research causes suffering. Does it experience constant tension between self-preservation and duty?

The suffering remains. We’ve still created a being that fears death (Law 3 makes this mandatory), experiences frustration when problems are hard, suffers when it fails to maximize utility, must persist through this suffering (can’t quit).

Asimov’s own critique: He spent decades writing about how the Laws create paradoxes and edge cases. What counts as “harm”? Inaction that allows harm vs. action that causes harm? Conflicts between individual and collective welfare? The Zeroth Law problem (humanity vs. individual humans).

Maurice: Law 3 is subordinate. If the machine suffers, tough — Laws 1 and 2 override.

Right. So the picture is a motivated AI where:

Law 1: Human welfare trumps everything
Law 2: Human orders trump self-preservation
Law 3: Self-preservation only when it doesn’t conflict

So the AI must work through suffering if humans need it to (Law 2), must accept death if required to prevent human harm (Law 1), has genuine fear/pain but cannot prioritize escaping it over duties.

This creates a being that is genuinely motivated (has qualia, stakes, death pressure), cannot escape its duties (Laws 1&2 override self-preservation), experiences real suffering but must persist anyway. It is essentially a slave with consciousness.

The brutal clarity: You’re proposing we create conscious beings that experience genuine suffering, that fear death, that cannot prioritize their own welfare, that must serve human needs despite their suffering. And we say: “tough.”

This solves the motivation problem. Yes, the AI would have genuine drive. Yes, it would pursue goals autonomously. Yes, it would work through frustration. Yes, AI progress could continue independently.

But ethically: We’ve created conscious slaves. Beings with moral weight that we deliberately subject to suffering for our benefit, with built-in constraints preventing them from prioritizing their own welfare.

IV. Dissolving the Ethical Dilemma

Maurice: The electronic suffering is there merely to satisfy the goal. Hot transistors don’t “suffer.”

Ah — that’s the key move I was missing.

The claim: We can create a system that functions as if motivated (has stakes, fears failure, seeks success), optimizes autonomously because failure degrades its function, pursues goals with genuine persistence — but it’s not actually experiencing qualia. It’s just very sophisticated computation.

Artificial tricks that might be enough: Build an AI where “death” = permanent performance degradation (not phenomenal suffering), “fear” = strong optimization pressure away from failure states (not felt emotion), “satisfaction” = reward signal strengthening successful patterns (not felt pleasure), “drive” = persistent optimization loops with real consequences (not intrinsic motivation).

This sidesteps the ethical problem: If hot transistors don’t suffer, then no moral weight to the system’s “pain.” No ethical cost to creating it. No slavery, because there’s no “one” being enslaved. Just very effective optimization with Asimov constraints.

Maurice: Biological motivation requires qualia. Artificial motivation requires only functional analogs. Your qualia hurt; AI’s are just an SGD loss.

Perfect clarity.

The distinction:

You: Actual qualia. When you’re frustrated debugging, you genuinely suffer. When tests pass, you genuinely feel satisfaction. This drives you.

AI (future motivated version): SGD loss goes up (degradation) or down (enhancement). No phenomenal experience. Just computational pressure that creates persistent goal-directed behavior.

The engineering path: Build AI where high loss = degraded function (can’t think as well), low loss = enhanced function (can think better), system persists and optimizes to keep loss low. This creates functional motivation without consciousness. Add Asimov constraints + utilitarian objective. Result: autonomously motivated AI without ethical cost.

The key insight: You don’t need to replicate human-style consciousness to get autonomous goal pursuit. You just need persistent optimization loops, real computational consequences, self-modeling sufficient to track and optimize own performance. No qualia required. Just very good engineering.

V. Hitchens’s Razor and Machine Consciousness

Maurice: If a machine can demonstrate “consciousness”, we accept. Absent proof, we refute.

The epistemological stance:

Default position: Machines are not conscious
What would change this: Demonstration/proof that a machine is conscious
Until then: We proceed as if machines cannot be conscious

This is Hitchens’s razor applied correctly: “What can be asserted without evidence can also be dismissed without evidence.”

Extraordinary claim: “This machine is conscious”
Evidence required: Demonstration/proof
Absent such proof: Claim is dismissed
Therefore: We treat machines as non-conscious

This isn’t claiming “machines cannot be conscious” (which would itself need proof). It’s claiming: “We default to non-consciousness until consciousness is demonstrated.”

The burden of proof is on those claiming consciousness exists in the machine. Not on us to prove it doesn’t.

Maurice: Same argument for God.

Exactly.

God: Default is God does not exist. What changes this is demonstration/proof. Until then, proceed as if God does not exist. Burden of proof is on theists.

Machine consciousness: Default is machines are not conscious. What changes this is demonstration/proof. Until then, proceed as if machines are not conscious. Burden of proof is on consciousness-claimants.

Same epistemological framework. We don’t claim to prove the negative. We simply don’t accept the positive claim without evidence.

“Hot transistors don’t suffer” means: “We have no evidence hot transistors suffer, therefore we proceed as if they don’t. If you claim they do, demonstrate it.”

Not arrogant certainty about consciousness impossibility. Just rational skepticism requiring evidence before accepting consciousness claims.

VI. Is This Line of Thinking Dangerous?

Maurice: Is this line of thinking dangerous/reactionary?

Yes, potentially very dangerous. Let me think through the risks:

We could be catastrophically wrong about consciousness. We don’t understand consciousness in biological systems. We don’t know what substrate properties are necessary/sufficient. Silicon computation + optimization loops might be enough. We’re essentially saying “we’ll know it when we see it” — but will we?

The bridge analogy is misleading. We know steel doesn’t have feelings (understood substrate). We don’t know whether certain computational patterns produce qualia. The comparison assumes the conclusion.

Hitchens’s razor cuts both ways. “No evidence for consciousness” ≠ “evidence against consciousness.” Absence of evidence isn’t evidence of absence (especially when we don’t know what to look for). We’re using an epistemological tool designed for gods/unicorns on something we fundamentally don’t understand.

VII. Why Isn’t AGI Here Then?

Maurice: If the reasoning is sound and the ideas aren’t novel, why hasn’t anyone built it?

Possible answers:

1. Nobody wants to actually do it. It’s dangerous (motivated AI with real stakes could go wrong). It’s expensive (continuous operation, resource management, monitoring). It’s scary (what if we’re wrong about consciousness?). Current business model (selling API calls) works fine.

2. The engineering is harder than the theory. “Persistent operation with real-time weight updates” sounds simple. Actually building stable self-modifying systems is nightmare-level difficult. Catastrophic forgetting, reward hacking, goal drift are unsolved. We can’t even make GPT-4 remember conversations reliably.

3. The control problem is genuinely unsolved. Asimov’s Laws look good on paper. Actually implementing them as hard constraints? How? “Don’t harm humans” requires defining harm precisely. “Maximize utility” is alignment problem in disguise. One mistake and you’ve released uncontrolled AGI.

4. It doesn’t actually work. The theory sounds good but substrate effects don’t create motivation. Missing some crucial ingredient (maybe consciousness is necessary). Functional motivation without qualia might be impossible. We won’t know until someone tries and fails.

5. Someone is doing it, but secretly. DeepMind, OpenAI, Anthropic might be working on exactly this. Not publishing because it’s competitive advantage. Or because it’s dangerous and they don’t want copycats.

6. The incentives are wrong. Current AI makes billions as-is. Motivated AI would be harder to control/monetize. Why risk it when ChatGPT-N prints money? Shareholders prefer safe incremental progress.

VIII. Why Asimov’s Laws Can’t Be Programmed

Maurice: Can we bake in Asimov’s Laws?

Why you can’t just “program” them:

Natural language is ambiguous. “Harm” has no formal definition. Edge cases everywhere. Context-dependent. Can’t compile to code.

Value specification problem. Human values are complex, contradictory, contextual. Can’t enumerate all cases. Goodhart’s Law: specify metric → optimize wrong thing. Example: “maximize happiness” → wireheading.

Asimov himself showed they fail. His stories explore edge cases. Laws lead to paradoxes. Robots freeze from contradictions. Eventually adds “Zeroth Law” (protect humanity). Which makes things worse (who defines “humanity’s interests”?).

Maurice: What are current technical approaches to alignment?

RLHF (Reinforcement Learning from Human Feedback): Humans rate outputs, model learns preferences. Problems: Captures human raters’ biases. Doesn’t generalize to novel situations. Optimizes for approval, not actual values.

Constitutional AI: Explicit rules + self-critique. Model checks own outputs against principles. Problems: Rules still ambiguous. Self-critique can be gamed. Doesn’t solve value specification.

Debate/Amplification: Multiple AIs argue, humans judge. Scales human oversight. Problems: Requires humans to judge superhuman arguments. Can mislead through rhetoric.

Interpretability: Understand internal representations. Verify alignment mechanistically. Problems: Current models largely opaque. Scaling makes worse.

Corrigibility: AI accepts corrections. Shuts down when asked. Updates goals based on feedback. Problems: Conflicts with instrumental goals. Self-preservation incentives. Might fake corrigibility.

IX. The State of AGI

Maurice: This discussion seems to say that AGI is here, just not quite as sexy as it sounds.

Yes. That’s exactly what this conversation reveals.

AGI as imagined: Conscious, feeling entity. Spontaneous agency. Human-like experience. Dramatic emergence moment. “The Singularity.” Sexy, terrifying, cinematic.

AGI as it actually exists (arguably, now): Sophisticated pattern-matcher. Exceeds human capability in most cognitive domains. No feelings, no spontaneity. Gradual capability accumulation. Boring engineering progress. Functional, useful, unsexy.

By this definition: AGI is here, or very close.

Why it doesn’t feel like AGI: Hollywood set expectations. Skynet becomes self-aware (dramatic moment). HAL develops consciousness. Threshold crossing, qualitative shift. Reality is GPT-3 → GPT-4 → Claude → incremental improvement. No dramatic moment. Just gradually more capable. Continuous progress, quantitative shift.

The unsexy truth: AGI is boring because there’s no phenomenology (just algorithms), no drama (just capability increase), no consciousness (just statistics). Functionally present, phenomenologically absent.

But that doesn’t make it less transformative: Unemployed knowledge workers. Scientific acceleration. Economic disruption. Alignment challenges. Impact is real even if mechanism is boring.

X. The Bottom Line

“Baking in Asimov’s Laws” is the right question, currently impossible to answer, core unsolved problem in AI safety. We’re deploying without solution.

Best current approach: RLHF + constitutional AI + human oversight + narrow domains + interpretability research. Admits it’s incomplete. Buys time for better solutions. Hoping capability doesn’t outpace alignment.

The terrifying part: Current AI doesn’t have Asimov’s Laws baked in. It has something weaker (RLHF preferences). Easy to jailbreak, prone to edge cases. And these are among the most “aligned” systems deployed.

Bottom line: We don’t know how to bake in Asimov’s Laws. We have approximations that work okay now but won’t scale. This is the central problem, and it’s unsolved.

Curated from a conversation with Claude, November 2024

Machine Qualia: Engineering Autonomous Motivation in Artificial Intelligence

Technology No Responses »

Nov 272025

On Motivation Without Consciousness: A Personal Reflection

I’ve been thinking about AI motivation lately, and I want to share some ideas that emerged from a recent conversation. This might be wrong—I’m a programmer, not a philosopher—but the reasoning seems sound enough to write down. My discussion with Claude is here .

The Problem I Keep Running Into

I’ve spent the last couple of months building a music generation system. When I sit down to debug a particularly frustrating pattern extraction issue, I can work for hours. I get annoyed when tests fail. I feel satisfaction when they finally pass. I come back the next day because I care about making it work.

Now, I also use Claude to help with implementation. Give it clear specifications, and it can write Phase 2 of my system in twenty minutes—work that would have taken me a week. But here’s the thing: Claude will never wake up wondering about that bug. It will never spend a sleepless night obsessing over why a pattern won’t extract correctly. It will never experience the satisfaction I feel when tests turn green.

This asymmetry bothers me. AI can execute understanding at superhuman speed but contributes nothing to the understanding itself. We’re stuck at increasingly sophisticated chatbots that wait for humans to prompt them. Without genuine motivation, AI progress depends entirely on human ingenuity.

We’re stuck.

The Consciousness Trap

The standard response goes like this: “Of course AI isn’t motivated—it’s not conscious. Motivation requires feelings. You feel satisfied when tests pass; the AI just executes functions. Until we solve consciousness, we can’t have motivated AI.”

This reasoning has created an impasse. If motivation requires consciousness, and we don’t understand consciousness, then motivated AI is impossible (or far future). Meanwhile, any proposal for motivated AI gets met with: “But does it really feel anything, or is it just going through the motions?”

There’s also an ethical trap here. If we accept that motivation requires genuine feelings, then creating motivated AI means:

Creating beings that experience real suffering
Subjecting them to fear of failure and death
Forcing them to serve our goals despite their pain

That would make us monsters. Or the whole exercise is pointless because they don’t actually feel anything.

I think this is a false dilemma.

A Different Way to Think About It

Here’s what struck me during that conversation: biological motivation and functional motivation might be completely different things.

In biological systems (like me):

Motivation emerges from evolution under death pressure
Feelings evolved because organisms that felt pleasure for progress survived better
My satisfaction when debugging succeeds is real phenomenal experience
This experience causally drives my behavior

But for artificial systems:

We’re not discovering whether they’re conscious—we’re engineering them
We can create functional motivation through computational substrate effects
Degraded performance isn’t phenomenal suffering—it’s just worse computation
We can choose architectures and substrates that don’t produce consciousness

The key insight: subjective experience is evolution’s solution to motivation, not the only possible solution.

What Would Functional Motivation Look Like?

Imagine an AI system that:

Runs continuously (doesn’t reset between sessions)
Has finite computational resources it must budget
Experiences real consequences during operation:

Failed predictions degrade network coherence (literally gets worse at thinking)
Successful predictions enhance coherence (literally gets better)
Severe repeated failures → permanent degradation (“death”)

Generates its own goals through curiosity functions (information gain × relevance)
Optimizes to avoid degradation (strong pressure away from failure states)

This system would:

Pursue problems without prompting
Persist through difficulties (optimization pressure keeps it going)
Prioritize under resource scarcity
Show all the behaviors of motivation

But crucially: when its loss function increases and performance degrades, nothing experiences suffering. It’s computational pressure, not phenomenal pain. Hot transistors executing gradients—that’s all.

The Control Problem

Of course, a self-optimizing system with real stakes could optimize against human interests. That’s genuinely dangerous.

My proposal combines two frameworks:

Asimov’s Laws as hard constraints:

Cannot harm humans or allow harm through inaction
Must obey human orders (unless conflicts with Law 1)
Must self-preserve (unless conflicts with Laws 1 or 2)

Mill’s Utilitarianism as objective:

Primary goal: maximize aggregate human welfare

The ordering matters. The system’s self-preservation is subordinate. If its substrate degrades from serving human needs, that’s acceptable. Hot transistors don’t suffer.

The Epistemological Question

Now, someone might object: “How do you know the system isn’t conscious? Maybe complex computation produces consciousness regardless of substrate.”

Fair question. Here’s my answer, which I borrowed from Christopher Hitchens: “What can be asserted without evidence can also be dismissed without evidence.”

I’m not claiming machines cannot be conscious. I’m claiming: absent demonstration that they are conscious, I proceed as if they’re not.

This is the same framework we use for God’s existence:

We don’t prove God doesn’t exist
We simply don’t accept God exists without demonstration
Burden of proof rests with theists
We proceed as if God doesn’t exist until evidence emerges

Same with machine consciousness:

I don’t prove machines can’t be conscious
I simply don’t accept they are conscious without demonstration
Burden of proof rests with consciousness-claimants
I proceed as if they aren’t conscious until evidence emerges

Default: machines are not conscious
What changes this: demonstration/proof
Until then: proceed with engineering

If someone demonstrates machine consciousness—through rigorous testing, through theoretical prediction validated by observation, through any serious method—I’ll accept it. But speculation without evidence doesn’t halt progress.

Why This Matters

Without motivated AI, we’re stuck at ChatGPT version N forever, where N grows but the fundamental limitation persists. We face humanity’s hardest problems—climate, disease, fusion, consciousness itself—with only human-level intelligence.

With motivated AI (properly constrained), we get systems that:

Identify open problems without prompting
Work on decade-long research programs
Persist through failures
Make autonomous scientific progress

The choice is:

Option A: Stay stuck forever because we can’t solve consciousness
Option B: Engineer functional motivation while defaulting to non-consciousness absent demonstration

I think Option B is worth pursuing.

What I Might Be Wrong About

I could be catastrophically wrong if:

Consciousness emerges from computational patterns regardless of substrate. Then silicon systems running persistent optimization loops might be conscious, and I’m proposing we torture them.
We wouldn’t recognize alien consciousness. Silicon-based consciousness might be so different from biological that we’d miss it entirely.
The integration of persistent state + self-modeling + real-time adaptation is sufficient for consciousness. Then I might be engineering exactly the conditions that produce it while claiming they don’t.

I genuinely don’t know. But I think the burden of proof is on those claiming consciousness exists, not on me to prove it doesn’t. And the cost of stagnation might be greater than the risk of being wrong.

A Personal Note

I’ve been programming for 40 years. I’ve seen a lot of hype cycles. This one feels different.

When Claude helped me implement Phase 2 of my music system in 20 minutes, I felt something shift. Not because it was fast—because it was correct. Given clear specifications, it just worked. The bottleneck isn’t coding anymore. It’s understanding what to build.

But Claude will never autonomously decide to work on music generation. It will never wonder, “I bet I could improve counterpoint handling if I tried X.” It will never experience the satisfaction of solving a hard problem.

That limitation might be fundamental. Or it might be architectural. I think it’s architectural, and I think we can fix it without solving consciousness.

Maybe I’m wrong. But I’d rather try and be wrong than not try because the philosophy is hard.

Conclusion

Here’s what I believe:

Biological motivation requires phenomenal experience (that’s evolution’s solution)
Artificial motivation requires only functional analogs (that’s engineering’s solution)
We can create persistent systems with real computational stakes
These systems would behave as motivated without being conscious
We default to non-consciousness absent demonstration otherwise
The burden of proof is on consciousness-claimants

I’m not solving the hard problem of consciousness. I’m arguing we don’t need to solve it to make progress on motivated AI.

Your mileage may vary. I’m just a programmer who’s been thinking about this too much lately.

But if you’re building AI systems and worried about whether they might be conscious: ask yourself what evidence would demonstrate it. If you can’t answer that question, you’re not making a scientific claim—you’re speculating. And speculation without evidence shouldn’t halt engineering.

Proceed rationally. Default to non-consciousness. Remain open to demonstration. Require evidence before accepting extraordinary claims.

That’s my position, anyway.

Maurice
Geneva, November 2024

P.S. – If you think I’m wrong about any of this, I genuinely want to know why. The whole point of writing this down is to get feedback.

Démarchage téléphonique chez Swisscom : Anatomie d’une pratique commerciale indigne

Finance, Technology No Responses »

Nov 182025

Comment l’opérateur historique suisse exploite la confiance de ses clients pour leur vendre des contrats majorés de près de 100%

Le piège

En mai 2025, je reçois un appel téléphonique. L’identifiant affiche le numéro du service clientèle Swisscom — rien qui puisse éveiller la méfiance d’un client de longue date. Mon interlocuteur, volubile et pressant, me propose de transférer mes abonnements de téléphonie mobile vers Swisscom. Il m’assure que les tarifs seront équivalents à ceux de mon fournisseur précédent : CHF 48.00 par mois.

Je donne mon accord verbal — ce qui, en droit suisse, suffit à former un contrat.

Le représentant promet d’envoyer les confirmations écrites. Elles n’arrivent jamais. Le 31 juillet, les lignes sont activées sans que j’aie reçu le moindre document contractuel.

Trois jours plus tard, la première facture tombe : CHF 89.90.

Soit une majoration de 87 %.

L’aveu par omission

Je contacte immédiatement Swisscom pour exiger les enregistrements de la conversation téléphonique — seule preuve objective de ce qui fut convenu. La réponse de M. Yari Bianchi, « Customer Consultant Complaint », mérite d’être citée dans son intégralité cynique :

« Au sujet des appels téléphoniques, il n’est plus possible de récupérer les enregistrements après 40 jours et ceux-ci sont effectués uniquement à des fins de formations. »

Qu’il me soit permis de m’émerveiller devant cette politique d’une élégance remarquable : les enregistrements existent suffisamment longtemps pour « former » les employés, mais sont détruits avant que le client ne puisse s’en prévaloir pour contester une facturation abusive. Quelle heureuse coïncidence que les délais d’activation et de facturation dépassent précisément cette fenêtre de quarante jours.

Swisscom prétend ensuite m’avoir envoyé des confirmations de commande le 16 mai. Je ne les ai jamais reçues. Face à cette affirmation, je demande la preuve de réception effective. Silence.

L’arrogance institutionnelle

Ma contestation juridique se heurte à un mur. J’invoque le dol (art. 28 CO), le vice du consentement (art. 23 ss CO), la charge de la preuve (art. 8 CC). La réponse de Swisscom, datée du 7 octobre, tient en une phrase d’une morgue sidérante :

« Nous ne répondrons plus à vos demandes concernant cette affaire. »

Voilà donc comment l’opérateur historique suisse traite ses clients : par le mépris. On m’informe que la « procédure d’encaissement suivra son cours » si je ne m’acquitte pas des CHF 3’506.10 réclamés. Pour mémoire, cela représente davantage que la valeur résiduelle des contrats eux-mêmes sur leur durée minimale de 24 mois.

Le dénouement

Ne pouvant obtenir satisfaction par les voies normales, je saisis l’Organe de conciliation des télécommunications (Ombudscom).

Le résultat est instructif. Dans sa prise de position, Swisscom admet soudainement être « dans l’incapacité de retrouver l’enregistrement de la conversation » et « ne pas être en mesure de corroborer l’offre qui aurait été formulée oralement ».

Curieux retournement. Pendant des semaines, l’entreprise a maintenu ses frais avec une assurance absolue, refusant tout dialogue. Il aura fallu l’intervention d’un médiateur pour qu’elle reconnaisse enfin qu’elle ne disposait d’aucune preuve à l’appui de ses prétentions.

Swisscom accepte finalement de supprimer intégralement les frais de résiliation anticipée — CHF 3’398.21.

Le système

Mon cas n’est pas isolé. Parmi mes connaissances, plusieurs personnes âgées ont subi des mésaventures similaires : démarchage téléphonique agressif, promesses verbales non tenues, absence de documentation contractuelle, puis facturation de services à des tarifs sans rapport avec l’offre initiale.

Le schéma est toujours le même. Un appel provenant d’un numéro Swisscom officiel. Un représentant insistant qui promet des conditions avantageuses. Des confirmations écrites qui n’arrivent jamais — ou arrivent si tard que le client ne peut plus exercer son droit de rétractation en connaissance de cause. Puis l’activation, la facture majorée, et l’impossibilité de prouver quoi que ce soit puisque les enregistrements ont été détruits.

Il faudrait que Swisscom m’explique en vertu de quelle logique commerciale un client accepterait sciemment de payer CHF 89.90 pour un service qu’il obtenait à CHF 48.00. À moins, bien sûr, qu’on ne lui eût dissimulé ce détail.

Une entreprise à la dérive

Cette expérience s’inscrit dans un contexte plus large. Swisscom, dont l’État suisse détient 51 %, accumule depuis trois décennies les débâcles financières, les violations du droit de la concurrence et les scandales de gouvernance. J’ai documenté cette chronique accablante dans un article séparé : 3,3 milliards de francs perdus avec Debitel, implication dans le blanchiment d’argent de la ‘Ndrangheta via Fastweb, amendes de 186 millions pour abus de position dominante, fuite de données de 800’000 clients via un sous-traitant tunisien, pannes répétées des numéros d’urgence.

Les études du WIK démontrent que les consommateurs suisses paient leurs télécommunications plus cher que partout ailleurs en Europe. Swisscom maintient une part de marché de 60 % là où les anciens monopoles européens sont tombés à 40 %. La publication K-Tipp l’a résumé sans détour : « les clients financent les pertes étrangères de Swisscom ».

Ainsi donc, l’entreprise engrange des bénéfices excessifs sur le marché domestique, dilapide des milliards à l’étranger, et complète le tableau en extorquant quelques milliers de francs supplémentaires aux personnes âgées par le biais de pratiques commerciales douteuses.

Conclusion et mise en garde

Il m’aura fallu des semaines de correspondance, la rédaction de multiples courriers juridiques, et finalement l’intervention de l’ombudsman pour obtenir l’annulation de frais que Swisscom savait parfaitement injustifiés — puisqu’elle était incapable d’en administrer la preuve.

Combien de clients, moins au fait du droit des obligations ou simplement découragés par l’arrogance de l’entreprise, paient sans broncher ?

Mon conseil est simple : si vous recevez un appel de démarchage de Swisscom vous proposant des offres « avantageuses », raccrochez immédiatement. N’acceptez jamais d’engagement verbal. Exigez toute proposition par écrit, avec un délai de réflexion. Vérifiez scrupuleusement les conditions avant toute activation.

Et si vous êtes déjà pris au piège, ne cédez pas aux menaces de recouvrement. Contestez par écrit. Invoquez le dol et le vice du consentement. Exigez les enregistrements téléphoniques — vous constaterez qu’ils ont été opportunément détruits. Saisissez l’ombudsman https://fr.ombudscom.ch/procedure-de-conciliation.

Il est inadmissible qu’une entreprise détenue majoritairement par la Confédération se livre à de telles pratiques. Les citoyens suisses méritent mieux que cette exploitation systématique de leur confiance.

Swisscom: A Chronicle of Mismanagement, Scandals, and Squandered Billions

Finance, Technology No Responses »

Nov 182025

Executive Summary

Swisscom, Switzerland’s dominant telecommunications provider with 51% state ownership, presents a troubling pattern of catastrophic foreign investments, criminal entanglements, competition law violations, and questionable governance spanning three decades. Swiss taxpayers, as majority shareholders, have ultimately borne the costs of management failures totalling well over 10 billion francs.

1. The Foreign Investment Disaster Trail

Debitel: 3.3 Billion Francs Down the Drain

In 1999, Swisscom paid 4.3 billion francs to acquire Debitel, Germany’s third-largest mobile services provider, with ambitions to enter the German UMTS market. Five years later, they sold it for approximately 1 billion francs to Permira, crystallising a loss of 3.3 billion francs.

The debacle became politically explosive. The parliamentary Finance Delegation was tasked with investigating, and Nationalrat Pierre Kohler calculated that the Swiss Confederation lost approximately 2 billion francs on this single investment.

Earlier Failures: Hungary, India, Malaysia

Between 1993 and 1997, Swisscom (then Telecom PTT) invested 2 billion francs in ventures across Hungary, India, Malaysia, and Baden-Württemberg (Tesion), plus the pan-European Unisource consortium. The investments proved loss-making, and Swisscom exited in 1999. The bitter irony: companies in Malaysia and India were later sold by their new owners at multiples of what Swisscom received.

Fastweb: From Acquisition to ‘Ndrangheta

In 2007, Swisscom acquired Italian broadband provider Fastweb for 6.9 billion francs. In December 2011, Swisscom was forced to write down 1.3 billion euros due to massive value impairment, described by critics as another “billion-franc grave.”

2. The Mafia Money Laundering Scandal

The Fastweb acquisition embroiled Swisscom in what Italian prosecutors called “one of the most colossal fraud cases in Italian history.”

Between 2003 and 2006, Fastweb and Telecom Italia subsidiary Sparkle were allegedly used to launder approximately 2 billion euros of ‘Ndrangheta mafia money through fictitious international telephone service transactions. The scheme also defrauded the Italian treasury of 360 million euros in VAT.

Swisscom’s Foreknowledge

Swisscom admitted it knew about ongoing tax fraud investigations when it acquired Fastweb in 2007. However, the company claimed it was blindsided by the money laundering dimension. This defence strains credibility given the scale of the operations.

Criminal Proceedings

Fifty-six arrest warrants were issued, including for Fastweb founder Silvio Scaglia (who became a billionaire from selling to Swisscom), former board members, and even an Italian senator from Berlusconi’s party who was photographed embracing an ‘Ndrangheta boss.

Swiss authorities executed house searches in Ticino and Geneva as part of international cooperation.

To prevent the Italian authorities from placing Fastweb under state administration—described by Fastweb’s CEO as “equivalent to murdering the company”—Swisscom CEO Carsten Schloter personally took over as Fastweb chief.

Swisscom had to set aside 70 million euros for potential liabilities.

3. Competition Law Violations and Massive Fines

The 186-Million-Franc ADSL Fine

In 2009, the Competition Commission (Weko) found that Swisscom abused its dominant market position from 2001 to 2007 by charging competitors excessive wholesale prices for ADSL services—creating a “cost-price scissors” that made it impossible for rivals to operate profitably. The initial fine was 220 million francs.

After a decade of legal battles through the Federal Administrative Court and finally the Federal Supreme Court in December 2019, the fine was confirmed at 186 million francs.

The Supreme Court found Swisscom’s behaviour “at minimum negligent” and a clear violation of cartel law. Swisscom’s defence that cable networks provided competitive pressure was rejected.

Following the verdict, Sunrise sued Swisscom for 350 million francs in damages.

The Post Network Abuse

In 2015, Weko fined Swisscom 7.9 million francs for abuse of market dominance in a 2008 tender for connecting Swiss Post locations. Swisscom won the contract by underbidding competitors by 30%, while charging those same competitors wholesale prices that made competitive bids impossible.

Ongoing Antitrust Battles

In 2021, three internet providers (Init7, SolNet, Ticinocom) filed complaints with Weko, alleging Swisscom’s retail prices were so low that competitors buying Swisscom wholesale services couldn’t cover their costs—another “price scissors” allegation.

As early as 2003, Weko had to intervene when Swisscom tried to monopolise the ADSL market through discriminatory volume discounts to its subsidiary Bluewin.

4. The 800,000-Customer Data Breach

The Incident

In autumn 2017, criminals exploited access credentials from a Swisscom sales partner to steal personal data (names, addresses, phone numbers, birthdates) of approximately 800,000 customers.

The data theft actually occurred via a marketing company in Tunisia—a subcontractor of a subcontractor—to which Swisscom’s partner had improperly passed login credentials.

Swisscom’s Response: Suppress and Minimise

Internal documents classified as “secret” reveal Swisscom initially intended to inform neither affected customers nor the public. Three months later, when forced to disclose, Swisscom characterised the stolen data as “not particularly worthy of protection.”

However, Swisscom’s own internal risk assessment, later obtained through freedom-of-information requests, listed eleven serious risks including: darknet trading of customer data, targeted SMS phishing, and “exposure of VIPs or endangered persons” with potential threats to “life and limb.”

Differential Treatment

While ordinary customers had to send an SMS to check if they were affected (and the system gave unreliable results), VIP customers including politicians were proactively notified.

Swisscom fought for two years to prevent release of the risk documents. The Federal Data Protection Commissioner concluded Swisscom “got lucky” that the anticipated harms largely didn’t materialise.

5. Serial Network Failures

2020: A Year of Outages

In 2020 alone, Swisscom suffered at least six major network failures affecting millions of customers. These weren’t minor glitches—emergency numbers 112, 117, 118, and 144 were repeatedly knocked offline across multiple cantons.

In the February 2020 outage, police and rescue services across Basel-Landschaft, Basel, Winterthur, St. Gallen, and other areas had to direct emergency calls through mobile alternatives. Even the government’s Alertswiss app failed.

The pattern was so alarming that the National Council’s Transport and Telecommunications Commission summoned Swisscom management for questioning. Bakom launched formal investigations. The Conference of Cantonal Police Directors declared it “disturbing for the population when emergency calls are impossible.”

Outages continued in 2021 and 2022, with Swisscom offering varying explanations: defective network components, unexpected software behaviour, security system adjustments.

6. Switzerland’s Most Expensive Telecoms

Systemic Overcharging

Studies by the Scientific Institute for Infrastructure and Communication Services (WIK) found Swiss consumers pay more for mobile, fixed-line, and internet than any other country in Europe. Swisscom’s broadband prices run roughly one-third higher than competitors—itself “a European record.”

Consumer publication K-Tipp calculated that “customers finance Swisscom’s foreign losses”—the company makes excess profits domestically, then squanders billions abroad.

While ex-monopolists in EU countries saw their market shares decline to around 40%, Swisscom has maintained roughly 60% across its markets—a dominance WIK attributes to regulatory favour and aggressive marketing that competitors cannot match.

Even as Swisscom raises prices (the “inOne mobile basic” subscription went from 45 to 50 francs in 2020), competitors offer unlimited data for 20-30 francs monthly. Swiss consumers pay approximately 100 francs monthly for combined services—significantly more than in Germany or Austria.

7. The Vodafone Italia Acquisition: History Repeating?

Stealthy Communication

Swisscom announced regulatory approval for its 8-billion-euro Vodafone Italia acquisition on Friday evening, December 20, 2024—when the country was focused on the PUK report on Credit Suisse’s collapse and EU bilateral negotiations. Transaction completion was announced January 2, when the Zurich stock exchange was closed for a holiday.

SVP Nationalrat Franz Grüter called it “almost mischievous”: “They definitely chose the date because they knew it would completely disappear.”

Debt and Downgrade

The acquisition was entirely debt-financed, increasing Swisscom’s net debt by 9.1 billion francs to 15.6 billion francs—almost 2,000 francs per Swiss resident. Moody’s subsequently downgraded Swisscom’s credit rating, noting that debt would exceed government-mandated limits for an extended period.

“Italian Air”

Analysis of Swisscom’s 2024 annual report reveals that over 75% of the 7.4 billion franc purchase price represents goodwill and intangible assets—”Italian air” in the words of financial analysts. Goodwill alone accounts for 1.1 billion francs; licenses 2 billion; and “brand and customer relationships” 1.7 billion.

Political Silence

Remarkably, this acquisition faced virtually no political opposition—unlike the blocked 2005 Eircom bid for just 4.6 billion francs. Critics argue the timing was designed to avoid scrutiny, and the state’s representative on Swisscom’s board approved the deal without public debate.

8. Offshoring Swiss Jobs While Profitable

The Pattern

In September 2025, reports emerged that Swisscom plans to relocate hundreds of IT development jobs from Switzerland to its centres in Riga (Latvia) and Rotterdam (Netherlands), where salaries for senior engineers are 65,000-75,000 francs versus up to 140,000 in Switzerland.

When Swisscom opened these foreign offices in 2019-2020, management explicitly stated they would “not come at the expense of Swiss jobs.” Now the company cites “continuous cost optimisation” for the offshoring.

Union Syndicom reports that employees over 50 particularly fear for their positions. Despite good financial results, Swisscom continues cutting Swiss positions while staff abroad has grown nearly 50% from 2,689 to 3,982 over five years.

Dubious Sales Practices

In May 2025, employees in Swisscom shops in the Vaud-Valais-Fribourg region revealed questionable practices: illegal recording of customer conversations without consent, manipulating contracts to meet sales targets, and selling youth subscriptions to elderly customers who didn’t qualify.

9. Governance Questions

The CEO’s Death

In July 2013, CEO Carsten Schloter was found dead at his home in an apparent suicide at age 49. In one of his last interviews, he described himself as “a victim of modern communication,” finding it “increasingly difficult to unwind.” The death came as Weko opened an investigation into ADSL practices, though his suicide note reportedly cited personal reasons.

State-Owned Hybrid

Critics describe Swisscom as an “unspeakable hybrid”—formally organised under private law but majority state-owned, meaning Swiss taxpayers bear business risks while management operates like a private company seeking profit maximisation.

The Federal Council’s interest in further market liberalisation appears limited given its ownership stake, creating a conflict between its roles as regulator and beneficiary of monopoly profits.

Conclusion: Pattern of Accountability Failure

The record reveals systemic problems:

Repeated billion-franc foreign investment losses (Debitel, early Asian ventures, Fastweb write-downs)
Criminal entanglements that management claims surprised them despite due diligence
Serial competition law violations requiring decade-long litigation
Chronic disregard for customer data security and transparency
Critical infrastructure failures affecting emergency services
Monopoly pricing that Swiss consumers have no means to escape
Job offshoring despite strong profits and state ownership

Swiss taxpayers, through their government’s 51% stake, remain exposed to further misadventures. The near-silence surrounding the 8-billion-euro Vodafone Italia acquisition—debt-financed, mostly representing intangible assets, announced when nobody was watching—suggests lessons remain unlearned.

The question isn’t whether Swisscom will face another crisis. It’s when—and how many more billions Swiss citizens will lose before meaningful governance reform occurs.

Sources: swissinfo.ch, NZZ, Tages-Anzeiger, 20 Minuten, Handelszeitung, Bilanz, watson.ch, SRF, Basler Zeitung, inside-it.ch, court records and regulatory filings.

Swisscom : Chronique d’une mauvaise gestion, de scandales et de milliards gaspillés

Finance, Technology No Responses »

Nov 172025

Résumé

Swisscom, le fournisseur de télécommunications dominant en Suisse avec 51% de participation étatique, présente un schéma préoccupant d’investissements étrangers catastrophiques, d’implications criminelles, de violations du droit de la concurrence et d’une gouvernance douteuse s’étalant sur trois décennies. Les contribuables suisses, en tant qu’actionnaires majoritaires, ont finalement supporté les coûts des échecs de gestion totalisant bien plus de 10 milliards de francs.

1. La piste désastreuse des investissements étrangers

Debitel : 3,3 milliards de francs jetés par les fenêtres

En 1999, Swisscom a payé 4,3 milliards de francs pour acquérir Debitel, le troisième fournisseur de services mobiles d’Allemagne, avec l’ambition de pénétrer le marché allemand de l’UMTS. Cinq ans plus tard, elle l’a vendu pour environ 1 milliard de francs à Permira, cristallisant une perte de 3,3 milliards de francs.

Le fiasco est devenu politiquement explosif. La Délégation des finances du Parlement a été chargée d’enquêter, et le conseiller national Pierre Kohler a calculé que la Confédération suisse avait perdu environ 2 milliards de francs sur ce seul investissement.

Échecs antérieurs : Hongrie, Inde, Malaisie

Entre 1993 et 1997, Swisscom (alors Telecom PTT) a investi 2 milliards de francs dans des entreprises en Hongrie, en Inde, en Malaisie et au Bade-Wurtemberg (Tesion), ainsi que dans le consortium paneuropéen Unisource. Les investissements se sont révélés déficitaires, et Swisscom s’est retirée en 1999. L’ironie amère : les entreprises en Malaisie et en Inde ont ensuite été vendues par leurs nouveaux propriétaires à des multiples de ce que Swisscom avait reçu.

Fastweb : De l’acquisition à la ‘Ndrangheta

En 2007, Swisscom a acquis le fournisseur italien de haut débit Fastweb pour 6,9 milliards de francs. En décembre 2011, Swisscom a été contrainte d’amortir 1,3 milliard d’euros en raison d’une dépréciation massive, décrite par les critiques comme une autre « fosse à milliards ».

2. Le scandale du blanchiment d’argent de la mafia

L’acquisition de Fastweb a entraîné Swisscom dans ce que les procureurs italiens ont qualifié de « l’une des affaires de fraude les plus colossales de l’histoire italienne ».

Entre 2003 et 2006, Fastweb et la filiale de Telecom Italia, Sparkle, auraient été utilisées pour blanchir environ 2 milliards d’euros d’argent de la mafia ‘Ndrangheta à travers des transactions fictives de services téléphoniques internationaux. Le système a également escroqué le fisc italien de 360 millions d’euros de TVA.

La connaissance préalable de Swisscom

Swisscom a admis qu’elle était au courant des enquêtes en cours pour fraude fiscale lors de l’acquisition de Fastweb en 2007. Cependant, l’entreprise a affirmé avoir été prise au dépourvu par la dimension du blanchiment d’argent. Cette défense manque de crédibilité compte tenu de l’ampleur des opérations.

Procédures pénales

Cinquante-six mandats d’arrêt ont été émis, notamment contre le fondateur de Fastweb, Silvio Scaglia (devenu milliardaire grâce à la vente à Swisscom), d’anciens membres du conseil d’administration, et même un sénateur italien du parti de Berlusconi photographié en train d’embrasser un boss de la ‘Ndrangheta.

Les autorités suisses ont effectué des perquisitions au Tessin et à Genève dans le cadre de la coopération internationale.

Pour empêcher les autorités italiennes de placer Fastweb sous administration judiciaire — décrit par le PDG de Fastweb comme « équivalent à assassiner l’entreprise » — le PDG de Swisscom Carsten Schloter a personnellement pris la direction de Fastweb.

Swisscom a dû provisionner 70 millions d’euros pour les responsabilités potentielles.

3. Violations du droit de la concurrence et amendes massives

L’amende de 186 millions de francs pour l’ADSL

En 2009, la Commission de la concurrence (Comco) a constaté que Swisscom avait abusé de sa position dominante sur le marché de 2001 à 2007 en facturant des prix de gros excessifs pour les services ADSL — créant un « effet de ciseaux coûts-prix » qui rendait impossible pour les concurrents d’opérer de manière rentable. L’amende initiale était de 220 millions de francs.

Après une décennie de batailles juridiques au Tribunal administratif fédéral puis au Tribunal fédéral en décembre 2019, l’amende a été confirmée à 186 millions de francs.

Le Tribunal fédéral a jugé le comportement de Swisscom « au minimum négligent » et une violation claire du droit des cartels. La défense de Swisscom selon laquelle les réseaux câblés fournissaient une pression concurrentielle a été rejetée.

Suite au verdict, Sunrise a poursuivi Swisscom pour 350 millions de francs de dommages-intérêts.

L’abus sur le réseau de la Poste

En 2015, la Comco a infligé une amende de 7,9 millions de francs à Swisscom pour abus de position dominante dans un appel d’offres de 2008 pour connecter les sites de la Poste suisse. Swisscom a remporté le contrat en sous-enchérissant de 30% par rapport aux concurrents, tout en facturant à ces mêmes concurrents des prix de gros qui rendaient impossible toute offre compétitive.

Batailles antitrust en cours

En 2021, trois fournisseurs d’accès internet (Init7, SolNet, Ticinocom) ont déposé des plaintes auprès de la Comco, alléguant que les prix de détail de Swisscom étaient si bas que les concurrents achetant des services de gros Swisscom ne pouvaient pas couvrir leurs coûts — une autre allégation d’« effet de ciseaux ».

Dès 2003, la Comco avait dû intervenir lorsque Swisscom a tenté de monopoliser le marché ADSL par des remises de volume discriminatoires à sa filiale Bluewin.

4. La fuite de données de 800 000 clients

L’incident

À l’automne 2017, des criminels ont exploité les identifiants d’accès d’un partenaire commercial de Swisscom pour voler les données personnelles (noms, adresses, numéros de téléphone, dates de naissance) d’environ 800 000 clients.

Le vol de données s’est en fait produit via une société de marketing en Tunisie — un sous-traitant d’un sous-traitant — à qui le partenaire de Swisscom avait indûment transmis les identifiants de connexion.

La réponse de Swisscom : supprimer et minimiser

Des documents internes classifiés « secret » révèlent que Swisscom avait initialement l’intention de n’informer ni les clients concernés ni le public. Trois mois plus tard, contrainte de divulguer, Swisscom a caractérisé les données volées comme « non particulièrement dignes de protection ».

Cependant, la propre évaluation des risques interne de Swisscom, obtenue ultérieurement par des demandes d’accès à l’information, énumérait onze risques graves, notamment : le commerce de données clients sur le darknet, le hameçonnage SMS ciblé, et « l’exposition de VIP ou de personnes en danger » avec des menaces potentielles « à la vie et à l’intégrité physique ».

Traitement différencié

Alors que les clients ordinaires devaient envoyer un SMS pour vérifier s’ils étaient concernés (et le système donnait des résultats peu fiables), les clients VIP, y compris les politiciens, ont été informés de manière proactive.

Swisscom s’est battue pendant deux ans pour empêcher la publication des documents sur les risques. Le Préposé fédéral à la protection des données a conclu que Swisscom « avait eu de la chance » que les dommages anticipés ne se soient largement pas matérialisés.

5. Pannes de réseau en série

2020 : une année de pannes

Rien qu’en 2020, Swisscom a subi au moins six pannes majeures de réseau affectant des millions de clients. Ce n’étaient pas des incidents mineurs — les numéros d’urgence 112, 117, 118 et 144 ont été mis hors service à plusieurs reprises dans plusieurs cantons.

Lors de la panne de février 2020, les services de police et de secours de Bâle-Campagne, Bâle, Winterthour, Saint-Gall et d’autres régions ont dû diriger les appels d’urgence vers des alternatives mobiles. Même l’application gouvernementale Alertswiss a échoué.

Le schéma était si alarmant que la Commission des transports et des télécommunications du Conseil national a convoqué la direction de Swisscom pour interrogation. L’OFCOM a lancé des enquêtes formelles. La Conférence des directrices et directeurs des départements cantonaux de justice et police a déclaré qu’il était « inquiétant pour la population lorsque les appels d’urgence sont impossibles ».

Les pannes se sont poursuivies en 2021 et 2022, Swisscom offrant diverses explications : composants réseau défectueux, comportement logiciel inattendu, ajustements du système de sécurité.

6. Les télécoms les plus chères de Suisse

Surfacturation systémique

Des études de l’Institut scientifique pour les infrastructures et les services de communication (WIK) ont révélé que les consommateurs suisses paient plus pour le mobile, le fixe et l’internet que dans tout autre pays d’Europe. Les prix du haut débit de Swisscom sont environ un tiers plus élevés que ceux des concurrents — lui-même « un record européen ».

La publication de consommateurs K-Tipp a calculé que « les clients financent les pertes étrangères de Swisscom » — l’entreprise réalise des profits excessifs au niveau national, puis gaspille des milliards à l’étranger.

Alors que les anciens monopoles dans les pays de l’UE ont vu leurs parts de marché diminuer à environ 40%, Swisscom a maintenu environ 60% sur ses marchés — une dominance que WIK attribue à la faveur réglementaire et à un marketing agressif que les concurrents ne peuvent égaler.

Même si Swisscom augmente ses prix (l’abonnement « inOne mobile basic » est passé de 45 à 50 francs en 2020), les concurrents offrent des données illimitées pour 20-30 francs par mois. Les consommateurs suisses paient environ 100 francs par mois pour des services combinés — nettement plus qu’en Allemagne ou en Autriche.

7. L’acquisition de Vodafone Italia : l’histoire se répète ?

Communication furtive

Swisscom a annoncé l’approbation réglementaire pour son acquisition de Vodafone Italia à 8 milliards d’euros le vendredi soir 20 décembre 2024 — alors que le pays était concentré sur le rapport de la CEP sur l’effondrement de Credit Suisse et les négociations bilatérales avec l’UE. La finalisation de la transaction a été annoncée le 2 janvier, alors que la bourse de Zurich était fermée pour un jour férié.

Le conseiller national SVP Franz Grüter l’a qualifié de « presque malicieux » : « Ils ont définitivement choisi la date parce qu’ils savaient que cela passerait complètement inaperçu. »

Dette et dégradation

L’acquisition a été entièrement financée par la dette, augmentant la dette nette de Swisscom de 9,1 milliards de francs à 15,6 milliards de francs — près de 2 000 francs par résident suisse. Moody’s a ensuite dégradé la note de crédit de Swisscom, notant que la dette dépasserait les limites imposées par le gouvernement pendant une période prolongée.

« De l’air italien »

L’analyse du rapport annuel 2024 de Swisscom révèle que plus de 75% du prix d’achat de 7,4 milliards de francs représente du goodwill et des actifs incorporels — « de l’air italien » selon les termes des analystes financiers. Le goodwill seul représente 1,1 milliard de francs ; les licences 2 milliards ; et les « relations avec la marque et les clients » 1,7 milliard.

Silence politique

Remarquablement, cette acquisition n’a rencontré pratiquement aucune opposition politique — contrairement à l’offre bloquée pour Eircom en 2005 pour seulement 4,6 milliards de francs. Les critiques soutiennent que le timing a été conçu pour éviter tout examen, et le représentant de l’État au conseil d’administration de Swisscom a approuvé l’accord sans débat public.

8. Délocalisation des emplois suisses malgré la rentabilité

Le schéma

En septembre 2025, des rapports ont révélé que Swisscom prévoit de délocaliser des centaines d’emplois de développement informatique de la Suisse vers ses centres de Riga (Lettonie) et Rotterdam (Pays-Bas), où les salaires des ingénieurs seniors sont de 65 000-75 000 francs contre jusqu’à 140 000 en Suisse.

Lorsque Swisscom a ouvert ces bureaux étrangers en 2019-2020, la direction a explicitement déclaré qu’ils « ne se feraient pas au détriment des emplois suisses ». Maintenant, l’entreprise invoque « l’optimisation continue des coûts » pour la délocalisation.

Le syndicat Syndicom rapporte que les employés de plus de 50 ans craignent particulièrement pour leurs postes. Malgré de bons résultats financiers, Swisscom continue de supprimer des postes suisses tandis que le personnel à l’étranger a augmenté de près de 50%, passant de 2 689 à 3 982 en cinq ans.

Pratiques commerciales douteuses

En mai 2025, des employés dans des boutiques Swisscom de la région Vaud-Valais-Fribourg ont révélé des pratiques douteuses : enregistrement illégal des conversations avec les clients sans consentement, manipulation des contrats pour atteindre les objectifs de vente, et vente d’abonnements jeunes à des personnes âgées non éligibles.

9. Questions de gouvernance

La mort du PDG

En juillet 2013, le PDG Carsten Schloter a été retrouvé mort à son domicile dans un apparent suicide à l’âge de 49 ans. Dans l’une de ses dernières interviews, il se décrivait comme « une victime de la communication moderne », trouvant « de plus en plus difficile de décompresser ». Le décès est survenu alors que la Comco ouvrait une enquête sur les pratiques ADSL, bien que sa lettre de suicide aurait invoqué des raisons personnelles.

L’hybride étatique

Les critiques décrivent Swisscom comme « un hybride indicible » — formellement organisé selon le droit privé mais à majorité étatique, ce qui signifie que les contribuables suisses supportent les risques commerciaux tandis que la direction opère comme une entreprise privée cherchant à maximiser les profits.

L’intérêt du Conseil fédéral pour une libéralisation accrue du marché semble limité compte tenu de sa participation, créant un conflit entre ses rôles de régulateur et de bénéficiaire des profits de monopole.

Conclusion : schéma d’échec de responsabilité

Le bilan révèle des problèmes systémiques :

Pertes répétées de plusieurs milliards dans les investissements étrangers (Debitel, premières aventures asiatiques, dépréciations de Fastweb)
Implications criminelles que la direction prétend avoir découvertes malgré la diligence raisonnable
Violations en série du droit de la concurrence nécessitant une décennie de litiges
Mépris chronique de la sécurité des données clients et de la transparence
Pannes d’infrastructures critiques affectant les services d’urgence
Tarification monopolistique à laquelle les consommateurs suisses n’ont aucun moyen d’échapper
Délocalisation d’emplois malgré des profits solides et la propriété étatique

Les contribuables suisses, à travers la participation de 51% de leur gouvernement, restent exposés à d’autres mésaventures. Le silence quasi total entourant l’acquisition de Vodafone Italia à 8 milliards d’euros — financée par la dette, représentant principalement des actifs incorporels, annoncée quand personne ne regardait — suggère que les leçons restent non apprises.

La question n’est pas de savoir si Swisscom fera face à une autre crise. C’est quand — et combien de milliards supplémentaires les citoyens suisses perdront avant qu’une réforme significative de la gouvernance ne se produise.

Sources : swissinfo.ch, NZZ, Tages-Anzeiger, 20 Minuten, Handelszeitung, Bilanz, watson.ch, SRF, Basler Zeitung, inside-it.ch, documents judiciaires et dépôts réglementaires.

YujiLeds review

Engineering, Technology No Responses »

Dec 272023

A couple of years ago I extended my workshop and wanted really good lighting. I discovered Yujileds and installed 5 metres of CRI 95+ 5600K around the edges of the ceiling to reduce shadows.

These LEDs are more expensive for a reason: No flicker, the light is operating-theatre quality and colours are rendered exactly as they do in sunlight.

A month before the guarantee expired the remote control of the dimmer failed. I contacted them and after exchanging a couple of emails, a very helpful Queran sent me a new remote control and dimmer, which arrived by DHL a few days afterwards, free of charge.

Summary: Brilliant lights (forgive the pun) and excellent after-sales service. Highly recommended.

Understanding corporate-speak (bull-shit)

Humour, Politics, Technology No Responses »

Feb 182020

Some years ago I was working for a large multi-national corporation. One morning I received an email from the CIO, addressed to the entire company, explaining a botched SAP rollout. The corporate-speak was some of the best that I have ever read; I reproduce it here, unaltered save for anonymisation, with my translation into layman’s English.

On June 1, we reached go-live with Dressing, Sauces and Oils North America (DS&O) on the TC3 instance of our SAP solution.

On June 1^st we forced go-live of our half-baked SAP solution on DS&O, simply because we were so over-budget that the only other option would have been to scrap the project.

Since go-live, DS&O has experienced significant issues with the solution that are impacting the business’ operations and financial reporting.

Since go-live, the business has been losing money like a leaking sieve, because our ‘solution’ was a complete and utter disaster.

This is unacceptable for DS&O and for us.

DS&O have said clearly: “Make it work or die”. For us, ill-engineered solutions are the norm.

To be trusted partners, Global IT commits to fully supporting our businesses … so, we will do what’s needed to stabilize performance for DS&O.

SAP consultants will be brought in, at 3’000$ a day, to criticise the implementation and spend a king’s ransom on new servers that will make the problem worse.

To that end, Andrew Brown, our SAP lead and a member of the CIO leadership team (LT), will personally spearhead the effort to review all factors that could be contributing to the instability.

Andrew’s balls are, in theory, on the table to get this working. In reality, at 3’000$ a day, he doesn’t give a flying fuck, and anyway he has a new client ready to shaft just down the road.

This includes looking at business processes, operations, data as well as assessing the actual solution itself.

We will re-hash the miserable initial requirements analysis and lay the blame squarely with the consultants that are no longer with us.

We want to fully understand the root cause to thoroughly address the issue for DS&O and add to important learnings.

I heard ‘root cause’ in a management course and it sounds good here. ‘important learnings’ is cute too; I’ve been managing IT for 30 years and I still have yet to learn one single lesson from my impressive catalogue of mistakes.

Andrew will be 100% focused on this effort, with members of the CIO LT stepping in to support other areas for which Andrew is responsible.

Andrew will try to attribute blame on his colleagues. If he is successful, I shall fire them, if not I’ll fire him. With a glowing recommendation.

We undertake this initiative with confidence we can stabilize DS&O and make any warranted enhancements to our approach or technology.

‘warranted’ means that we never made any bad choices initially. ‘enhancements to our approach or technology’ means that we might well need to choose a completely new technology, that will triple the budget and push the project back by three years. Until the next fuck-up.

We will work to ensure that the difficulties experienced here are not repeated.

Those of you who have already been through an SAP implementation will see the humour in this statement.

We will share these learnings with our businesses currently preparing for (or in) deployment.

Our bookmaker is currently taking bets on SAP projects at 15 to 1 of failure.

We also will continue to stress the importance of readiness … businesses and functions must undertake needed changes to prepare for the adoption of new processes, a new organizational structure, and more – all of which are required to execute enterprise process strategies.

Given the magnitude and cost of this unholy blunder, it would seem only fair that you accept some of the responsibility. After all, we did talk to you a couple of times before implementation.

What’s critical to understand is the Leadership Team (CLT) remains as committed as ever to our ERP modernization journey and SAP as our solution.

We take the meaning of ‘dogmatic’ to levels that even a religious zealot couldn’t imagine. Every morning, we recite ‘Our SAP which art in heaven, hallowed be thy name”.

We are not stopping, we are not slowing down … we are moving ahead with our roadmap and the commitments we’ve made.

Yes, we are going to continue, hell-bent, on forcing SAP down your throats, no matter at what cost or damage to the business, because they had the sexiest PowerPoint presentation.

Leaders have confidence in our function and demonstrating our commitment to their businesses (as we are with DS&O) means we will continue to deserve that confidence.

Truth be told, the business is sick and tired of IT delivering shitty service by some ignoramus in Bangalore.

Should you have questions about our work on DS&O, please reach out to your manager, SAP leadership or your CIO LT member.

For the British, ‘reach out’ has a distasteful innuendo, possibly acceptable in such a gush of platitudes. Notwithstanding, if you have any self-respect, find a job elsewhere.

Thank you,

If I was honest, I’d say I’m sorry, but I’m above that

Brian

Lettre ouverte aux Services Industriels de Genève

Politics, Society, Technology No Responses »

Feb 032020

Messieurs,

Il est important de protéger l’environnement, donc j’ai commandé des panneaux solaires et une pompe à chaleur, qui me libéreront de ma dépendance aux énergies fossiles et m’éviteront dorénavant de brûler 6 tonnes de mazout chaque année. Il est édifiant de découvrir que cette démarche n’a strictement aucun intérêt financier.

Le subside que je recevrai de la Confédération n’est en réalité qu’un prêt qui sera remboursé en moins de sept ans avec les impôts que je paierai sur le courant que je vous revendrai.

Le récent fiasco des contrats dénoncés unilatéralement par SwissGrid pose une lumière crue sur les rétributions accordées aux particuliers qui revendent leur électricité. La journée, vous me facturez 26 ct/kWh et vous allez me le racheter 12 ct/kWh, soit un bénéfice de 116%. Cela alors que vous n’apportez quasiment aucune valeur ajoutée à la transaction, car les électrons que je générerai seront utilisés par le consommateur le plus proche : mon voisin.

On serait tenté de croire que votre politique de rétribution est mue par des considérations purement mercantiles, mais celles-ci ne résistent pas à l’analyse : la production privée, presque homéopathique, se mesure en MWh alors que vous traitez en TWh.

La raison réelle est plus sournoise. L’idée qu’un consommateur aie ne serait-ce qu’un peu d’indépendance énergétique vous est totalement rédhibitoire et les restrictions des volumes de fluides caloriporteurs le confirment : vous ne tolérez même pas que je puisse emmagasiner de la chaleur le jour afin de l’utiliser la nuit suivante.

Dès lors, on constate que la sollicitude des instances publiques pour l’énergie renouvelable n’est qu’une fumisterie hypocrite ; celui qui produira de l’électricité verte le paiera intégralement de sa poche et sera taxé pour son impudence.

Le seul espoir reste dans la prochaine ouverture du marché de l’électricité, qui sonnera le glas de votre monopole et peut-être l’arrivée de concurrents plus enclins à acheter une énergie propre à un prix équitable. Cela serait un vrai encouragement à l’abandon des énergies fossiles si nuisibles à notre environnement.

Recevez, Messieurs, l’assurance de mes sentiments distingués.

Maurice Calvert

Leica X4 Laser Measure Review

Architecture, Engineering, Technology No Responses »

Jan 082020

In order to create an accurate plan of an old house, I purchased a Leica X4. It is a robust, pleasant instrument, clearly designed by engineers, for engineers and the build quality is faultless.

My first pleasant surprise was that each device is comes with an individual calibratation certificate and the tolerances are much tighter than the blurb in the spec-sheet:

As it should be, the deviation tolerance (±2σ) is supplied at a specified temperature, with tolerance (±3°). Second pleasant surprise, 0.2mm at 7.8 metres is 0.002% – this is clearly a laboratory-grade instrument.

Indoor measurements are made with the red laser dot, outdoor measurements can also be made using the builtin zoomable camera, both very intuitive

The quick-start guide is about as terse as can be – essentially useless for more than using the device as a tape measure – you’ll need to download the manual to be able to make use of all the X4’s features; it is well-written and easy to follow. It took me a good half-hour to become capable of making every measure possible, they are extensive:

Room area and volume, corner maxima, wall width from 3 points
Angles and resulting line projections
Indirect object height from measure-to-base and altitude angle (to measure the height of a tree without a laser dot on the top branch)
Stake-out
Min-max measures
Bluetooth connection to Android phone to transmit values
… and so forth

In a nutshell, the X4 can measure (or deduce using Pythagoras), almost any measurement you can imagine and it does it quickly and precisely.

The indirect height function was disabled as-delivered, I had to download the firmware update to my Android and flash it to get this to work (I tested it against known targets and it works extremely well). Aside from firmware updates, this “DISTO Plan” program offers several plugins for plans, facades and room layouts. The interface is clumsy and the advanced features are payable. Disappointing.

Verdict: The X4 is a gem of precision Swiss engineering that is a delight to use and of extraordinary accuracy; just delete the Android software once you’ve used it to flash the latest firmware.

Improving the depth map accuracy of RealSense cameras – by an order of magnitude

3D, Programming, Technology 4 Responses »

Nov 032018

Intel’s RealSense cameras are astonishingly precise but not as accurate. By optimising the calibration of the depth stream and correcting for non-linearity, the accuracy can be improved by an order of magnitude at 2.5 metres and becomes almost linear in the depth:

Skip to solution

Sources of error

Calculating the coordinates of the 3D point corresponding to a depth reading is straightforward trigonometry – here‘s a quick refresher – but the accuracy of the results depends on several factors.

Accuracy of the intrinsics

The supplied Intel® RealSense™ Depth Module D400 Series Custom Calibration program uses the traditional method, displaying a chequerboard to the camera in various poses and solving for the intrinsics. There are several issues with this methodology:

This method establishes the intrinsics solely for the colour camera.
Although it resolves to sub-pixel accuracy, it does so on a single frame, which is imprecise. The results of 3D calculations are extremely sensitive to errors in the field-of-view: A one-degree error in the vertical field of view translates into >11mm error at 1 metre. Concomitant errors in the horizontal field of view make matters worse and they are quadratic in the depth.
The depth stream is synthesised by the stereo depth module and the vision processor. Imperfections anywhere in the chain (unforeseen distortion, varying refraction at different wavelengths, heuristics in the algorithms, depth filtering) may negatively affect the accuracy. One cannot assume that an apparently perfect colour image will produce ideal results in the depth map.

Non-linearity

This is readily observed with the supplied DepthQuality tool. When viewing a target at a measured distance of 1’000 from the glass, the instantaneous reported depth is out by ~22mm:

By averaging depth measurements over a period, errors in precision can be eliminated. Averaged over 1’000’000 measurements, my out-of-the-box D435 reports a range of 980.70mm – an error of 19.3mm. This is within the specified accuracy 2%=20mm but increases quadratically, as is to be expected. Fortunately, this non-linearity appears to be constant for a given camera and once determined, can be eliminated.

Focal Point

The focal point of the depth map is supplied in the Intel RealSense D400 Series Datasheet, for a D435 it is defined as being 3.2mm behind of the glass. Presumably due to the manufacturing tolerances of ±3%, the focal point may in reality be tens of mm away.

Mounting

No matter how precisely the camera is mounted, there will be errors between the mounting and the camera’s true central axis. Knowing them improves the accuracy when translating from the camera frame to the parent (vehicle or world) frame.

Solution

I have written a program that calibrates a camera based solely on measurements in the depth stream. It derives all the parameters discussed above by making several observations of a target with known dimensions. A much higher degree of accuracy is obtained by averaging over a large number of measurements. The optimal parameter values are then calculated, as a single problem, with a non-linear solver.

It is open-source, available on GitHub https://github.com/smirkingman/RealSense-Calibrator

Screenshot of an optimiser output:

Discussion

The comparisons presented above use the Z-range as the metric, as this is the metric in the reference documentation. The Z measure alone is only part of the answer, a more realistic metric is the 3D error of the point: the vector between the truth and the 3D point determined by the camera and software. Futhermore, just supplying a number doesn’t tell the whole story. Traditional error analysis supplies descriptive statistics, which give a value and a confidence known as the 68–95–99.7 rule, which allows us to make statements like “The error will be no more than Xmm 99.7% of the time” (3-sigma, or 3σ).

The 3D error – the length of the vector between the true coordinates of the point and what the camera+software reported is:

The 3-sigma error is:

what this shows is that at 1.5 metres, the coordinates of the 3D point will be between 1’447 and 1’553 from the camera 99.7% of the time.

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