Robin Hanson:

First, we should seriously worry about which aspects of our modern civilization system are rotting. Human culture has lasted a million years, but many parts of our modern world are far younger. If the first easiest version of a system that we can find to do something is typically be a rotting system, and if it takes a lots more work to find a non-rotting version, should we presume that most of the new systems we have are rotting versions? Farming-era empires consistently rotted; how sure can we be that our world-wide industry-era empire isn’t similarly rotting today? We may be accumulating a technical debt that will be expensive to repay.

Bob Lutz, ex vicepresidente di General Motors, scrive che l’industria automobilistica così come la conosciamo finirà nel prossimi 15-20 anni. Non servirà che il pubblico accetti la transizione dall’inizio, basterà che lo facciano le grandi aziende — Uber, FedEx, UPS, etc.

Gli spostamenti avverano per mezzo di moduli standardizzati, i produttori di questi moduli (= le aziende automobilistiche che riusciranno ad adattarsi) perderanno importanza, profitti e potere rispetto ai gestori del servizio — gli Uber e Amazon del futuro:

The companies that can move downstream and get into value creation will do OK. But unless they develop superior technical capability, the manufacturers of the modules, the handset providers, if you will, will have their specifications set by the big transportation companies.

The fleets will say, “We want a module of a certain length, a certain weight and a certain range. They will prescribe the mileage and the acceleration and take bids.”

Yuval Harari e l’uomo inutile

Ezra Klein di Vox ha intervistato Yuval Harari, autore di Sapiens e, più recentemente, di Homo Deus. Parlando di AI, Harari distingue fra intelligenza e coscienza — che vanno di pari passo negli umani, ma non per forza devono coesistere (o la seconda deve essere necessaria affinché la prima esista) in un’intelligenza artificiale:

Intelligence is not consciousness. Intelligence is the ability to solve problems. Consciousness is the ability to feel things. In humans and other animals, the two indeed go together. The way mammals solve problems is by feeling things. Our emotions and sensations are really an integral part of the way we solve problems in our lives. However, in the case of computers, we don’t see the two going together.

Over the past few decades, there has been immense development in computer intelligence and exactly zero development in computer consciousness. There is absolutely no reason to think that computers are anywhere near developing consciousness. They might be moving along a very different trajectory than mammalian evolution. In the case of mammals, evolution has driven mammals toward greater intelligence by way of consciousness, but in the case of computers, they might be progressing along a parallel and very different route to intelligence that just doesn’t involve consciousness at all.

Un passaggio importante del libro è la possibilità che, come conseguenza dell’automatizzazione, una larga fetta dell’umanità possa perdere la sua valenza economica (e di conseguenza politica) — ovvero diventare ‘inutile’ per lo stato e l’economia. Quando e se questo succederà, il sistema perderà anche l’incentivo di investire su questa classe di persone (la ragione per cui abbiamo università, assistenza sanitaria, etc. etc. è che queste cose ci rendono produttivi).

A questo punto che facciamo? Una possibilità spesso menzionata è che si finisca col nascondersi e col cercare di dare un significato alla propria esistenza tramite la realtà virtuale. Scenario triste, ma non nuovo, dice Harari: sono migliaia di anni che troviamo conforto, significato e modelliamo la nostra esistenza attorno a realtà virtuali che fino ad oggi abbiamo chiamato ‘religione’:

You can think about religion simply as a virtual reality game. You invent rules that don’t really exist, but you believe these rules, and for your entire life you try to follow the rules. If you’re Christian, then if you do this, you get points. If you sin, you lose points. If by the time you finish the game when you’re dead, you gained enough points, you get up to the next level. You go to heaven.

People have been playing this virtual reality game for thousands of years, and it made them relatively content and happy with their lives. In the 21st century, we’ll just have the technology to create far more persuasive virtual reality games than the ones we’ve been playing for the past thousands of years. We’ll have the technology to actually create heavens and hells, not in our minds but using bits and using direct brain-computer interfaces.

Nel suo ultimo libro, The Complacent Class, Tyler Cowen — blogger ed economista — sostiene che la società americana abbia smesso di rischiare e si sia seduta — preferendo miglioramenti marginali a tecnologie pre-esistenti piuttosto che cambiamenti radicali, il che ha contribuito col portare l’economia a una situazione di stagnazione. A cambiamenti radicali nel modo di creare, consumare e organizzare l’informazione si sono affiancati cambiamenti marginali nel mondo fisico: treni, aerei, infrastruttura, ad esempio, non sono progrediti di pari passo con il mondo virtuale.

Secondo Tyler, questo ritmo di ‘non cambiamento’ non è sostenibile:

The Complacent Class argues that this cannot go on forever. We are postponing change, due to our near-sightedness and extreme desire for comfort, but ultimately this will make change, when it comes, harder. The forces unleashed by the Great Stagnation will eventually lead to a major fiscal and budgetary crisis: impossibly expensive rentals for our most attractive cities, worsening of residential segregation, and a decline in our work ethic. The only way to avoid this difficult future is for Americans to force themselves out of their comfortable slumber—to embrace their restless tradition again.

Eliezer Yudkowsky risponde su LessWrong ad alcune domande riguardo all’automatizzazione e alla disoccupazione, due cose che (dice lui, riporto io, semplificando molto: leggetelo per intero) potrebbero essere correlate in un futuro (molto) distante – quando e se avremo un AI superintelligente –, ma che per il momento non sono causa ed effetto:

A: 

Many people would hire personal cooks or maids if we could afford them, which is the sort of new service that ought to come into existence if other jobs were eliminated – the reason maids became less common is that they were offered better jobs, not because demand for that form of human labor stopped existing. Or to be less extreme, there are lots of businesses who’d take nearly-free employees at various occupations, if those employees could be hired literally at minimum wage and legal liability wasn’t an issue. Right now we haven’t run out of want or use for human labor, so how could “The End of Demand” be producing unemployment right now? The fundamental fact that’s driven employment over the course of previous human history is that it is a very strange state of affairs for somebody sitting around doing nothing, to have nothing better to do. We do not literally have nothing better for unemployed workers to do. Our civilization is not that advanced.

[…]

Q. But AI will inevitably become a problem later?

A. Not necessarily.  We only get the Hansonian scenario if AI is broadly, steadily going past IQ 70, 80, 90, etc., making an increasingly large portion of the population fully obsolete in the sense that there is literally no job anywhere on Earth for them to do instead of nothing, because for every task they could do there is an AI algorithm or robot which does it more cheaply. That scenario isn’t the only possibility.

Harvard Business Review:

Technological revolutions tend to involve some important activity becoming cheap, like the cost of communication or finding information. Machine intelligence is, in its essence, a prediction technology, so the economic shift will center around a drop in the cost of prediction. The first effect of machine intelligence will be to lower the cost of goods and services that rely on prediction. This matters because prediction is an input to a host of activities including transportation, agriculture, healthcare, energy manufacturing, and retail.

When the cost of any input falls so precipitously, there are two other well-established economic implications. First, we will start using prediction to perform tasks where we previously didn’t. Second, the value of other things that complement prediction will rise.

Uno dei camion che si guidano da soli di OTTO — un’azienda recentemente acquistata da Uber — ha completato il suo primo viaggio, di 120 miglia, in completa autonomia, per consegnare 50,000 birre.

Scrive Wired:

Unlike Tesla’s Autopilot, Otto’s system offers true ‘Level 4’ autonomy. Once the rig hits the interstate, it is entirely capable of the job at hand, letting the human deal with paperwork, thumb her phone, or even catch a few Z’s.

“The technology is ready to start doing these commercial pilots,” says Otto co-founder Lior Ron. “Over the next couple of years, we’ll continue to develop the tech, so it’s actually ready to encounter every condition on the road.”

Arstechnica:

There are two main problems for any brain simulator. The first is that the human brain is extraordinarily complex, with around 100 billion neurons and 1,000 trillion synaptic interconnections. None of this is digital; it depends on electrochemical signaling with inter-related timing and analogue components, the sort of molecular and biological machinery that we are only just starting to understand.

Even much simpler brains remain mysterious. The landmark success to date for Blue Brain, reported this year, has been a small 30,000 neuron section of a rat brain that replicates signals seen in living rodents. 30,000 is just a tiny fraction of a complete mammalian brain, and as the number of neurons and interconnecting synapses increases, so the simulation becomes exponentially more complex—and exponentially beyond our current technological reach.

This yawning chasm of understanding leads to the second big problem: there is no accepted theory of mind that describes what “thought” actually is.

Un post da leggere per intero. Per il futuro prossimo, credo che possiamo stare tranquilli.

Tim O’Reilly ha indetto una conferenza, Next Economy, su uno degli argomenti più interessanti e attuali (IMHO), ovvero l’impatto della tecnologia (automatizzazione, seria, che stiamo sottovalutando, non quella a cui siamo abituati fatta da macchinari stupidi) sul lavoro.

Scrive su Medium:

AIs are flying planes, driving cars, advising doctors on the best treatments, writing sports and financial news, and telling us all, in real time, the fastest way to get to work. They are also telling human workers when to show up and when to go home, based on real-time measurement of demand. The algorithm is the new shift boss. […]

What is the future when more and more work can be done by intelligent machines instead of people, or only done by people in partnership with those machines? What happens to workers, and what happens to the companies that depend on their purchasing power? What’s the future of business when technology-enabled networks and marketplaces are better at deploying talent than traditional companies? What’s the future of education when on-demand learning outperforms traditional universities in keeping skills up to date?

(Un video sull’argomento: Un futuro senza lavori)

Martin Ford scrive sul NY Times che l’automatizzazione sta avvenendo molto più in fretta del previsto — e di quanto avvenga in Europa o America — in Cina. Foxxcon, ad esempio, ha intenzione di automatizzare circa il 70% della sua forza lavoro entro tre anni:

In 2014, Chinese factories accounted for about a quarter of the global ranks of industrial robots — a 54 percent increase over 2013. According to the International Federation of Robotics, it will have more installed manufacturing robots than any other country by 2017.

Midea, a leading manufacturer of home appliances in the heavily industrialized province of Guangdong, plans to replace 6,000 workers in its residential air-conditioning division, about a fifth of the work force, with automation by the end of the year. Foxconn, which makes consumer electronics for Apple and other companies, plans to automate about 70 percent of factory work within three years, and already has a fully robotic factory in Chengdu.

Non è che siamo pronti: più o meno ce li abbiamo di già. Gli aerei su cui viaggiamo oggi sono perlopiù automatizzati; uno studio (segnalato da Vice) riporta che in media un pilota spende 7 minuti del volo a “pilotare” l’aereo. Non è neppure che la scelta sia o completa automatizzazione o nulla: l’idea è che vi sia un pilota in cabina (se non altro sugli aerei di linea) e un co-pilota — un robot (o un gruppo di piloti) — a terra.

Scrive Vice:

It doesn’t have to be an either/or proposition. A purely auto piloted plane would probably crash from time to time, but leaving complete control of the plane to those on board, 100 percent of the time, hasn’t worked either.

So Cummings and others have looked into a system in which one pilot is in the cockpit, and the other is a robot—or at the very least, a group of humans—on the ground. For one, it would eventually save a massive amount of money for airlines in terms of pilots’ salaries, which is why it’s attractive to airlines (whether we want to automate pilots out of existence is another question). But, secondly, it could prevent disasters like this week from occurring.

Come rivelano alcuni brevetti, Boeing sta lavorando a un sistema che permetterebbe di comandare l’aereo da terra — e in caso di problemi, di assumerne il controllo.

Se vi è piaciuto il video dell’altro giorno — quello relativo al nuovo magazzino di Amazon, quasi totalmente automatizzato — vi piacerà quest’altro (girato da TIME): una telecamera segue il viaggio di un orsacchiotto all’interno del medesimo magazzino.

Amazon ha costruito un nuovo magazzino, ed è quasi totalmente automatizzato:

Amazon.com, Inc. (NASDAQ: AMZN) today unveiled its eighth generation fulfillment center, which utilizes robotics, Kiva technology, vision systems and almost 20 years’ worth of software and mechanical innovations to fulfill holiday orders. The company is currently operating 10 of this new generation of fulfillment centers across the U.S

Finito il video, guardate quest’altro: un futuro senza lavori.

Cosa succederà al settore dei trasporti quando le macchine che si guidano da sole diventeranno comuni? L’ultimo video di CGP Grey, Humans Need Not Apply, è dedicato a esplorare cosa accadrà quando gran parte dei lavori — anche quelli creativi, che crediamo al sicuro — saranno automatizzati e svolti in larga misura da un robot.

Come in passato, ci troveremo nuovi impieghi che solo noi saremo in grado di svolgere, no? No, purtroppo. E non siamo per nulla preparati a questo scenario.