... Chat GPT è fondamentalmente come una versione molto sofisticata del "completamento automatico": il programma che indovina cosa potresti digitare nella barra di ricerca del tuo browser, in base a ciò che altre cose hanno comunemente seguito ciò che hai digitato finora.

Ora, puoi discutere se un computer possa capire i significati dei concetti che usa, ma anche se potesse, questo programma non prova nemmeno a simulare una tale comprensione. Ciò che mostra è che (forse sorprendentemente) è possibile produrre un testo simile a quello di una persona che "comprende" utilizzando un metodo completamente diverso da quello della persona in questione. Questo, tra le altre cose, dimostra perché il test di Turing è un cattivo test per la consapevolezza...

diritti dei robot

 https://feedly.com/i/entry/osrPmlDZFInp6SMWQP3mml8q6Kt6TihJNu+iYEXtyCE=_1841ae35538:3b4c02:ef30d9e1

UNA CATASTROFE MORALE

Se la tecnologia continua di questo passo dovremo affrontare una catastrofe morale. Creeremo sistemi di intelligenza artificiale che alcune persone considerano ragionevolmente meritevoli di diritti umani o simili. Ma è praticamente impossibile che ci sia consenso sul tema. 

Cosa risponderemo al robot intelligente quando ci chiederà di non essere abusato, di non essere spento, di non essere obbligato a fare determinate cose? L'entità della catastrofe in vista potrebbe potenzialmente rivaleggiare con quella di una guerra mondiale o di un grande genocidio. I "sensibili" saranno giustificati nell'aggredire gli "insensibili"? I John Brown si moltiplicheranno e al diavolo la dialettica aggressore-aggredito.

SCHIAVI DEI ROBOT

SCHIAVI DEI ROBOT

Secondo chi studia queste cose a tempo pieno, i robot intelligenti suscitano due paure:

1) FOOM. Quando il primo robot intelligente saprà costruire un robot più intelligente di lui che saprà costruire un robot più intelligente di lui, l'intelligenza esploderà e il robot monopolista conquisterà il mondo. Questo potrebbe avvenire nel corso di un week-end.

1) AGENCY. Demanderemo molti compiti a robot sempre più intelligenti, i quali ci inganneranno eludendo i nostri controlli. L'intelligenza è soprattutto capacità di ingannare: i bambini più intelligenti, ricordiamolo, sono quelli che dicono più bugie.

Il primo è un classico problema legato alla crescita innovativa, il secondo un classico problema legato ai costi di agenzia.

Ebbene, esiste una vasta e rassicurante letteratura economica sia sul primo tema che sul secondo: storicamente, la stragrande maggioranza dell'innovazione è stata lenta, incrementale e distribuita in settori e luoghi differenziati, difficilmente si diffonde attraverso monopoli; l'azzardo morale puo' essere controllato.

Certo, chi sostiene "questa volta sarà diverso" non dà valore ai precedenti. Io sì.

http://www.overcomingbias.com/2019/04/agency-failure-ai-apocalypse.html

L'INVASIONE DEI ROBOT

L'INVASIONE DEI ROBOT

Ci sono molti lavori messi a rischio dall'arrivo prossimo venturo dei robot "intelligenti".

Uno su tutti: quello del ricercatore.

La cosa dice molto sia sui robot che sulla natura della ricerca scientifica oggi.

L’IMPERATIVO ESTETICO NEL MONDO SENZA LAVORO

Riccardo Mariani

Adesso · 

Amazon

 · 

L’IMPERATIVO ESTETICO NEL MONDO SENZA LAVORO

Pessimisti anni novanta: la macchina ci ruberà il lavoro. Un pensiero che alligna a destra (Pat Buchanan) come a sinistra (Jeremy Rifkin). Best seller: The End of Work.
Ecco, questo pessimismo non tiene conto dell’imperativo estetico che domina sempre più. Difficile pensare che in questo campo la macchina sostituirà l’uomo.
Le macchine svolgeranno il 99% del lavoro ma la macchina è replicabile e se a fare la differenza sarà il tocco estetico dell’uomo tutto il valore si concentrerà in questo gesto.

#Amazon

www.amazon.com

AMAZON.COM

Il paradosso dell’automazione

Automation ‘But what’s happening?’ Flight 447 and the Jennifer unit: When human messiness protects us from computerised disaster – Messy: How to Be Creative and Resilient in a Tidy-Minded World – Tim Harford –

***

Punti chiave: L’automazione diffusa erode le nostre competenze – Il pilota automatico in aeronautica – I guai di un aereo troppo sicuro –  paradosso dell’automazione – multe in automatico, azzeramento capacità d’indagine e deresponsabilizzazione –  I giapponesi finiti nell’oceano con il gps – Il robot che più preoccupa non è quello che ci sostituisce nel lavoro ma nel giudizio – Meteorologi: prima prevedere, poi consultare il computer – I problemoni dell’auto che si guida da sé – Soluzioni al paradosso dell’automazione – Puo’ aiutare un computer che sbaglia più frequentemente – Una strada più incasinata ci rende guitadori più concentrati e prudenti –

***

Yellow highlight | Location: 2,654
Pierre-Cédric Bonin, thirty-two, was young and inexperienced. David Robert, thirty-seven, had more experience but he had recently become an Air France manager and no longer flew full-time. Captain Marc Dubois, fifty-eight, had experience aplenty but he’d been touring Rio with an off-duty flight attendant. It was later reported that he had only had an hour’s sleep.

Note:UNA CREW CON I SUOI DIFETTI

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paradoxically, there is a risk to building a plane that protects pilots so assiduously from even the tiniest error. It means that when something challenging does occur, the pilots will have very little experience to draw on as they try to meet that challenge.

Note:GLI INCONVENIENTI DI UN AEREO TROPPO SICURO

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the real source of the problem was the system that had done so much to keep A330s safe across fifteen years and millions of miles of flying: the fly-by-wire. Or more precisely, the problem was not the fly-by-wire system, but the fact that the pilots had grown to rely on that system…Aggravating this mode confusion was Bonin’s lack of experience in flying a plane without computer assistance. While he had spent many hours in the cockpit of the A330, most of those hours had been spent monitoring and adjusting the plane’s computers rather than directly flying the aircraft….

Note:FLY BY WIRE

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This problem has a name: the paradox of automation…The better the automatic systems, the more out-of-practice human operators will be,…

Note:PARADOSSO DELL’AUTOMAZIONE

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The psychologist James Reason, author of Human Error, wrote: ‘Manual control is a highly skilled activity, and skills need to be practised continuously in order to maintain them.

Note:SKILL E ABITUDINE

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automatic systems accommodate incompetence

Note:INCOMPETENZE SMASCHERATE

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even if operators are expert, automatic systems erode their skills

Note:EROSIONE

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systems tend to fail either in unusual situations or in ways that produce unusual situations, requiring a particularly skilful human response.

Note:SITUAZIONI ECCEZIONALE

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A customer service webpage may be able to handle routine complaints and requests, so that customer service staff are spared repetitive work and may do a better job for customers

Note:TECNOLOGIA SENZA PARADOSSI

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Earl Wiener, a cult figure in aviation safety who died in 2013, coined what’s known as ‘Wiener’s Laws’ of aviation and human error. One of them was, ‘Digital devices tune out small errors while creating opportunities for large errors.’

Note:LA LEGGE DI WIENER

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At 14 seconds after 8.08 p.m. on 20 December 2013, his car had been blocking a bus stop in Bradford, Yorkshire, and had been photographed by a camera mounted in a traffic enforcement van driving past. A computer had identified the licence plate… There was just one problem: Mr Hankins hadn’t been illegally parked at all. He had been stuck in traffic….Yellow highlight | Location: 2,813
There was just one problem: Mr Hankins hadn’t been illegally parked at all. He had been stuck in traffic….

Note:LA MULTA AUTOMATICA AL SIG HANKINS

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In principle, such technology should not fall victim to the paradox of automation. It should free up humans to do more interesting and varied work – checking the anomalous cases

Note:AZZERATA LA CAPACITÀ D’INDAGINE

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Google unveiled a neural network that could identify house numbers in photographs…what if Google improves its accuracy by a factor of a million?…

Note:GOOGLE CI GUARDA IN CASA

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when someone says the computer made a mistake, we will assume they are wrong or lying.

Note:ERRORI DEL COMPUTER

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What happens when private security guards throw you out of your local shopping centre because a computer has mistaken your face for that of a known shoplifter?

Note:LA FACCIA SBAGLIATA

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Rahinah – visiting her home country of Malaysia – was told at the airport that her US student visa had been revoked without notice. Despite being the mother of an American citizen, she would never be able to return to the United States…Rahinah had been put on a no-fly list by mistake – possibly the result of confusion between Jemaah Islamiyah, a terrorist group, which killed 202 people with a car bomb in Bali in 2002, and Jemaah Islah Malaysia, a professional association of Malaysians who have studied overseas. Rahinah was a member of the second group, not the first. Once that error had entered the database it acquired the iron authority of the computer….

Note:RAHINAH

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Yet automatic systems want to be tidy. Once an algorithm or a database has placed you in a particular category, the black-and-white definitions of the data discourage argument and uncertainty.

Note:LA MALEDIZIONE DEPL BIANCO E NERO

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We are now on more lists than ever before: lists of criminals; lists of free-spending shoppers;

Note:LISTE

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we have not yet acknowledged how imperfectly a tidy database maps on to a messy world.

Note:DATI CHIARI MONDO CAOTICO

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the database and the algorithm, like the autopilot, should be there to support human decision-making.

Note:SOLO LA COPPIA FUNZIONA

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In March 2012, three Japanese students visiting Australia decided to drive to North Stradbroke, guided by their GPS system. For some reason the GPS was not aware that their route was blocked by nine miles of the Pacific Ocean…in thrall to their technology, they drove their car on to the beach and across the mud flats towards the ocean….

Note:GIAPPONESI IN AUSTRALIA

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Automated systems tend to lull us into passivity.

Note:PASSIVI

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This tendency to passively accept the default option turns out to apply to automated decisions too; psychologists call it automation bias.

Note:AUTOMATATION BIAS

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Driving your car into the sea is an extreme example of automation bias, but most GPS users will recognise the tendency in a milder form….Not knowing why the GPS failed me, I have no way of predicting when it might do so again….

Note:GPS

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When the algorithms are making the decisions, people often stop working to get better.

Note:MIGLIORARE

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engineers make the problem worse by deliberately designing systems to supplant human expertise by default; if we wish instead to use them to support human expertise, we need to wrestle with the system.

Note:AFFIANCAMENTO E RIMPIAZZO

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We worry that the robots are taking our jobs, but just as common a problem is that the robots are taking our judgement.

ote:ROBOT E LAVORO

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You could even argue that the financial crisis of 2007–8, which plunged the world into recession, was analogous to absent-mindedly driving a car into the Pacific.

Note:CRISI FINANZIARIA

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if that grizzled market participant had been able to talk to the computers, the computers would have been able to demonstrate the catastrophic impact of such a crash on the value of CDOs. Unfortunately, there was no meeting of minds

Note:AUTOMATISMI LASCIATI A SE STESSI

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veteran meteorologists would make weather forecasts first by looking at the data and forming an expert judgement; only then would they look at the computerised forecast

Note:LA STRATEGIA DEI METEOREOLOGI

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Chris Urmson, who runs Google’s self-driving car programme, hopes that the cars will soon be so widely available that his sons will never need to have a driving licence.

Note:SELF DRIVING CAR

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unlike a plane’s autopilot, a self-driving car will never need to cede control

Note:UN PERENNE PILOTA AUTOMATICO

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we can look forward to a more gradual process of letting the car drive itself in easier conditions…‘There will always be some edge cases where things do go beyond anybody’s control.’…

Note:RAJKUMAR E IL GRADUALISMO

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if we expect the human to leap in and take over, how will the human be able to react appropriately?

Note:L’ASPETTO DIFFICOLTOSO

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Human beings are not used to driving automated vehicles, so we really don’t know how drivers are going to react when the driving is taken over by the car,’ says Anuj K. Pradhan

Note:L‘INCOGNITA

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And when the computer gives control back to the driver, it may well do so in the most extreme and challenging situations.

Note:SITUAZIONI AL LIMITE

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No matter how many years of experience a driver has, her skills will slowly erode if she lets the computer take over.

Note:L’ESPERIENZA CONTA POCO

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‘I wasn’t parked illegally, I was stuck in traffic’; or ‘That’s not a terrorist group, it’s an alumni association.’ Does more efficient service in the majority of cases justify trapping a small number of individuals in Kafkaesque battles against bureaucracy?

Note:BUROCRAZIA KAFKIANA

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Until the late 1970s, one could reliably expect at least twenty-five fatal commercial plane crashes a year. In 2009, Air France 447 was one of just eight crashes, a safety record. The cost–benefit analysis seems clear: freakish accidents like Flight 447 are a price worth paying,

Note:IL TREND

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One priority could be to make semi-automated systems give feedback in a way that humans feel more viscerally.

Note:SOLUZIONE FEEDBACK

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Some senior pilots urge their juniors to turn off the autopilots from time to time to maintain their skills.

ote:SOLUZIONE ALLENAMENTO

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An alternative solution is to reverse the role of computer and human. Rather than letting the computer fly the plane with the human poised to take over when the computer cannot cope

Note:SOLUZIONE INVERTIRE I RUOLI

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Unsurprisingly, the scientists showed that reaction times and other measures of performance dramatically deteriorated as the hours ticked by.

Note:TEMPI DI REAZIONE

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behaviour suggests that when humans are asked to babysit computers, the computers themselves should be programmed to serve up occasional brief diversions. Even better might be an automated system that demanded more input, more often, from the human

Note:UN COMPUER CHE SBAGLIA DI FREQUENTE PUÒ AIUTARE

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Control measures such as traffic lights and speed bumps frustrated drivers, who would often speed dangerously between one measure and another.

Note:LIMITARE LA VELOCITÀ

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He suggested that the road through Oudehaske be made to look more like what it already was: a road through a village.

Note:SOLUZIONE MONDERMAN

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Where once drivers had, figuratively speaking, sped through the village on autopilot – not really attending to what they were doing – now they were faced with a messy situation and had to engage their brains…As Tom Vanderbilt describes Monderman’s strategy, ‘Rather than clarity and segregation, he had created confusion and ambiguity.’…

Note:UNA SITUAZIONE INCASINATA CI FA CONCENTRARE

I trafficoni dell’AI

I trafficoni dell’AI

The Hanson-Yudkowsky AI-Foom Debate – Robin Hanson and Eliezer Yudkowsky

***

Trigger warning: domani potranno essere costruiti robot più intelligenti di noi che sapranno costruire robot più intelligenti di loro. Come finirà questa storia? – emulatori o robot? – analogia o modelli? – due stili cognitivi per pensare al futuro lontano – il debole legame tra scienza e innovazione – tre modelli di innovazione radicale a cui ispirarsi per le analogia: nascita dell’homo sapiens, nascita dell’agricoltura, nascita dell’industria –

***

Chapter 1 Fund UberTool?

Sometimes a set of tool types will stumble into conditions especially favorable for mutual improvement.

Note:IL MIGLIORAMENTO RECIPROCO: MEZZI CHE COSTRUISCONO ALTRI MEZZI… E LA CRESCITA ESPLODE

Such favorable storms of mutual improvementusually run out quickly, however, and in all of human history no more than three storms have had a large and sustained enough impact to substantially change world economic growth rates.

Note:STORIA UMANA: TRE TEMPESTE A CUI ISPIRARSI PER PREVEDERE

Imagine you are a venture capitalist reviewing a proposed business plan. UberTool Corp has identified a candidate set of mutually aiding tools, and plans to spend millions pushing those tools through a mutual improvement storm.

Note:SCENARIO: SE UN’ IMPRESA CONQUISTASSE IL MONDO

UberTool does not plan to stop their closed self-improvement process until they are in a position to suddenly burst out and basically “take over the world.” … Now given such enormous potential gains, even a very tiny probability that UberTool could do what they planned might entice you to invest in them.

Note:PROBABILITA’ DI INVESTIMENTO NELL’AI FOOM: ELEVATE

Chapter 2 Engelbart as UberTool? Un antesignano

Yesterday I described UberTool, an imaginary company planning to push a set of tools through a mutual-improvement process;

Note:L’ IDEA DEI PC CHE COSTRUISCONO PC.

Augmenting Human Intellect: A Conceptual Framework … He understood not just that computer tools were especially open to mutual improvement… [Engelbart] is best known for inventing the computer mouse … Now to his credit, Doug never suggested that his team, even if better funded, might advance so far so fast as to “take over the world.” … Doug Engelbart understood what few others did—not just that computers could enable fantastic especially-mutually-improving tools, but lots of detail about what those tools would look like. …

Note:DOUG CONQUISTERÀ IL MONDO?

Chapter 3 Friendly Teams

Just as humans displaced chimps, farmers displaced hunters, and industry displaced farming, would a group with this much of a head start on such a general better tech have a decent shot at displacing industry folks? And if so, shouldn’t the rest of the world have worried about how “friendly” they were?

Note:LA CATENA DEGLI SPIAZZAMENTI. DOBBIAMO TEMERE IL VINCITORE?

In fact, while Engelbart’s ideas had important legacies, his team didn’t come remotely close to displacing much of anything. He lost most of his funding in the early 1970s, and his team dispersed.

Note:IL FALLIMENTO DI ENGELBART

But what makes that scenario reasonable if the UberTool scenario is not?

Note:LA BRUTTA FINE DI ENGELBART CI RASSICURA SUL MONOPOLISTA CATTIVO?

Chapter 4 Friendliness Factors

how much better will the best firm be relative to the average, second best, or worst?

Note:TENDENZA AL MONOPOLIO

Here are a few factors: …Resource Variance—The more competitors vary in resources, the more performance varies. … Cumulative Advantage—The more prior wins help one win again, … Lumpy Design—The more quality depends on a few crucial choices, relative to many small choices, the more quality varies. … Interdependence—When firms need inputs from each other, … Info Leaks—The more info competitors can gain about others’ efforts, the more the best will be copied, reducing variance. … Legal Barriers… Anti-Trust… Network Effects—Users may prefer to use the same product regardless of its quality. …

Note:DA COSA DIPENDE L’ESISTENZA DEL MONOPOLIO?

Some key innovations in history were associated with very high variance in competitor success. For example, our form of life seems to have eliminated all trace of any other forms on Earth.

Note:I PRECEDENTI. L’ HOMO SAPIENS SEMBRA DOMINARE INCONTRASTATO

On the other hand, farming and industry innovations were associated with much less variance.

Note:AGRICOLTURA E INDUSTRIA

attribute this mainly to info becoming much leakier, in part due to more shared standards,

CI SALVERÀ LA FLUIDITÀ DELL INFO?

If you worry that one competitor will severely dominate all others in the next really big innovation, forcing you to worry about its “friendliness,” you should want to promote factors that reduce success variance.

Note:CONSIGLIO POLITICO

Chapter 6 Setting the Stage (come ragionare per prevedere: analisi o analogie?)

We seem to agree that: … Feasible approaches include direct hand-coding, based on a few big and lots of little insights, and on emulations of real human brains.

Note:LE DUE VIE VERSO LA IA: 1 PROGRAMMAZIONE 2 EMULAZIONE DEL CERVELLO UMANO

Machine intelligence will, more likely than not, appear within a century,

Note:ENTRO UN SECOLO. PROB. SUP. 50%

Math and deep insights (especially probability) can be powerful relative to trend fitting and crude analogies.

Note:MATH, PROBABILITÀ E ANALOGIE

Some should be thinking about how to create “friendly” machine intelligences.

Note:LA QUESTIONE CENTRALE

We seem to disagree modestly about the relative chances of the emulation and direct-coding approaches;

Note:IL DISACCORDO

Our largest disagreement seems to be on the chances that a single hand-coded version will suddenly and without warning change from nearly powerless to overwhelmingly powerful; I’d put it as less than 1% and he seems to put it as over 10%…. My style is more to apply standard methods and insights to unusual topics. So I accept at face value the apparent direct-coding progress to date, and the opinions of most old AI researchers …

Note:LO STILE INTUITIVO

putting apparently dissimilar events into relevantly similar categories. … These  suggest a single suddenly superpowerful AI is pretty unlikely.

Note:LO STILE ANALOGICO: PIU’ PROBABILE LA DIVERSITA’

Eliezer seems to instead rely on abstractions he has worked out for himself, not yet much adopted by a wider community of analysts, nor proven over a history of applications to diverse events.

Note:RAZIONALISMO SPECIFICO DELL’INGEGNERE

Chapter 8 Abstraction, Not Analogy

I’m not that happy with framing our analysis choices here as “surface analogies” versus “inside views.”

Note:SURFACE VS INSIDE VIEW… DISTINZIONE SVIANTE

More useful, I think, to see this as a choice of abstractions. An abstraction (Wikipedia) neglects some details to emphasize others.

Note:MEGLIO: ASTRAZIONE VS ANALISI SPECIFICA

For example, consider the oldest known tool, the hammer (Wikipedia). To understand how well an ordinary hammer performs its main function, we can abstract from details of shape and materials. To calculate the kinetic energy it delivers, we need only look at its length, head mass, and recoil energy percentage (given by its bending strength). …To see that it is not a good thing to throw at people, we can note it is heavy, hard, and sharp. To see that it is not a good thing to hold high in a lightning storm, we can note it is long and conducts electricity. To evaluate the cost to carry it around in a tool kit, we consider its volume and mass. … Whether something is “similar” to a hammer depends on whether it has similar relevant features. …

Note:ESEMPIO: IL MARTELLO

The issue is which abstractions are how useful for which purposes, not which features are “deep” vs. “surface.”

Note:LA QUESTIONE INFINE

The future story of the creation of designed minds must of course differ in exact details from everything that has gone before. But that does not mean that nothing before is informative about it.

Note:AI E LE ANALOGIE

Yes, when you struggle to identify relevant abstractions you may settle for analogizing… Analogies are bad not because they use “surface” features, but because the abstractions they use do not offer enough relevant insight for the purpose at hand.

Note:IL DIFETTO DELL’ ANALOGIA

I claim academic studies of innovation and economic growth offer relevant abstractions for understanding the future creation of machine minds,

Note:AI. ANALOGIE CON INNOVAZIONE E CRESCITA ECONOMICA

previous major transitions, such as humans, farming, and industry, are relevantly similar.

Note:ANALOGIE: HOMO SAPIENS AGRICOLTURA INDUSTRIA

You have previously said nothing is similar enough to this new event for analogy to be useful, so all we have is “causal modeling” (though you haven’t explained what you mean by this in this context). This post is a reply saying, no, there are more ways using abstractions; analogy and causal modeling are two particular ways to reason via abstractions, but there are many other ways.

Note:MODELLO CAUSALE… O INGEGNERISTICO

Everything is new to us at some point; we are always trying to make sense of new things by using the abstractions we have collected from trying to understand all the old things.

IL RADICALMENTE NUOVO

Chapter 10 AI Go Foom

hand-coded AI will come soon and in the form of a single suddenly superpowerful AI.

Note:L IPOTESI DI Y (LA MENO PROBABILE PER H)

A machine intelligence can directly rewrite its entire source code and redesign its entire physical hardware. While human brains can in principle modify themselves arbitrarily, in practice our limited understanding of ourselves means we mainly only change ourselves by thinking new thoughts. All else equal this means that machine brains have an advantage in improving themselves. …“object” vs. “meta” … It seems as if you think object ones don’t increase growth rates while meta ones do. …

Note:UN VANTAGGIO DELL’IPOTESI SOFTWARISTICA: LE MACCHINE SI RIPRODUCONO PIÙ EFFICACEMENTE. EUGENETICA INFORMATICA.

Chapter 12 Eliezer’s Meta-level Determinism (il ruolo della scienza nell’avanzamento umano)

it seems the basis for Eliezer’s claim that my analysis is untrustworthy “surface analogies” vs. his reliable “deep causes” is that, while I use long-vetted general social science understandings of factors influencing innovation, he uses his own new untested meta-level determinism theory.

Note:ANCORA ANALOGIA VS CAUSALITÀ

The last three strong transitions were humans, farming, and industry, and in terms of growth rate changes these seem to be of similar magnitude. Eliezer seems to predict we will discover the first of these was much stronger than the other two. And while the key causes of these transitions have long been hotly disputed, with many theories in play, Eliezer seems to pick specific winners for these disputes: intergenerational culture, writing, and scientific thinking.

Note:LE 3 TRANSIZIONI. IL SEGRETO DEL SUCCESSO UMANO

Few could write and what they wrote didn’t help farming much. Farming seems more plausibly to have resulted from a scale effect in the accumulation of innovations in abilities to manage plants and animals

Note:AGRICOLTURA E CUMULO DELLE CONOSCENZE. NO PENSIERO SCIENTIFICO

Also for industry, the key innovation does not seem to have been a scientific way of thinking—that popped up periodically in many times and places, and by itself wasn’t particularly useful. My guess is that the key was the formation of networks of science-like specialists, which wasn’t possible until the previous economy had reached a critical scale and density.

INDUSTRIA: NETWORK DI TRAFFICONI E MASSA CRITICA DEL CAPITALE. IL RUOLO DELLA SCIENZA E’ SECONDARIO.