Enterprise companies do not know how to decide with public and private blockchain technologies. Here, we will dig deeper and understand the features and compare public vs private blockchain.
A public blockchain network is a blockchain network where anyone can join whenever they want. Basically, there are no restrictions when it comes to participation. More so, anyone can see the ledger and take part in the consensus process. For example, Ethereum is one of the public blockchain platform models. Let us check out the best features in this public blockchain vs private blockchain guide.
Enterprise companies do not know how to decide with public and private blockchain technologies. Here, we will dig deeper and understand the features and compare public vs private blockchain.
Basically, digital currencies exchanged in a private blockchain are like Monopoly money, while in a public blockchain if in an exchange can be traded for any other digital or traditional currency.
Public Blockchain: Best Features High Security Public blockchain companies always design every single platform in a way that offers full security. Every single day, enterprises and organizations deal with online hacks. It is becoming a big hindrance as time is going by. Furthermore, it causes billions and billions of dollar losses every year. But with all the security protocols of a public blockchain, they can easily stop all the hacking issues they face. More so, they can finally ensure true value or better data quality for any project. The security protocols may vary based on the platform, but I can safely say that public blockchains are robust.
Open Environment As you already know, the public blockchain is open for all, just like its name. So, no matter where you reside, you can log into these platforms. You would only need a good internet connection and a computer.
Anonymous Nature This is one of most criticized features of public blockchains that most of the users love.As it is a public domain, this feature is mainly for the safety of one’s possessions. However, people did use it for illegal reasons as well. People can use any new technology for bad and good purposes. Thus, it should not reflect on public blockchain technology in any way, and as a matter of fact cash is still king since criminals prefers cash for money laundering.1
According to the United Nations, the estimated amount of money laundered globally in one year is 2 to 5% of the global GDP, or $800 billion to $2 trillion, with more than thank 90% of money laundering going undetected today.
Concurrently, the cryptocurrency industry has also been criticized for being a tool for money laundering, despite statistics stating otherwise. It is estimated that only 1.1% of all cryptocurrency transactions are illicit.2
Why Use This? True Decentralization In a public blockchain, you will get true decentralization. This is something that is quite absent in private blockchain networks. As everyone has a copy of the ledger, it creates a distributed nature as well.
Full Transparency Well, nothing can compare to a fully transparent platform to anything else. Basically, the public blockchain companies tend to design the platforms so that it is fully transparent to anyone on the ledger.
Immutability The public blockchain network is fully immutable. But what does that mean? Well, it means that once a block gets on the chain, there is no way to change it or delete it. So, it makes sure that no one can just alter a certain block can get benefits from others.
Full User Empowerment Typically, in any network, the user must follow a lot of rules and regulations. In many cases, the rules might not even be fair ones. But not in public blockchain networks. Here, all the users are empowered as there is no central authority to look over their every move.
Private Blockchain: Best Features High Efficiency Even though public blockchain came first, they tend to lack inefficiency. Why? Well, it is because they introduce everyone to the network.
Empowering Enterprises Private blockchain solutions work to empower the enterprises rather than individual employees. Companies do need great technology to back up their processes. More so, these solutions are mainly for the internal systems of an enterprise.
Why Use This? Saves Money Maintaining a private blockchain is rather simple compared to public blockchains. Private blockchain platforms take up only a few resources. But on the other hand, public blockchain takes up a lot to support the platforms’ enormous crowd. Thus, in the long run, it saves a lot of money.
A detail from the digital collage Everydays: The First 5,000 Days, by artist Beeple, aka Mike Winkelmann. Photograph: AP
Public Vs Private Blockchain: The Ultimate Comparison
Businesses need to be acquainted with the benefits and drawbacks of public and private blockchains to ascertain which blockchain type will prove the most beneficial for their specific requirements.
The general consensus is that public blockchain and private blockchain are competitors. However, that is not the case. Both platforms serve different business scenarios. Public blockchains tend to better serve B2C players whereas private blockchain platforms are better suited to B2B scenarios. Thus, businesses should adopt a blockchain platform, i.e., public blockchain or private blockchain depending upon the desired goal.
The Proof of Stake consensus mechanism has recently been in the spotlight for quite some time in the context of blockchain scalability issues.
Without going into details about its advantage over Proof of Work, Proof of Stake eliminates the need to spend a huge amount of electricity to validate blocks.
Instead, blockchain participants with the most coins are selected by the algorithm for the right to validate blocks. The assumption behind Proof of Stake is as follows: those who hold a stake in a network have an incentive to act in its interest. Other things being equal, the higher the stakes, the greater should be their interest in preserving the system. Just as in PoS, in the PoA consensus, identity as a form of stake is also scarce. But unlike in PoS, there is only one identity per person. Identity staking means voluntarily revealing who you are in exchange for the right to validate blocks. Identity staking can act as a great equalizer, empathised and valued equally by all actors. Individuals whose identity (and reputation by extension) is at stake for the security of a network have an incentive to preserve the network. For the concept to work in real, live contexts, certain conditions must be met: Identity must be true: this means that there must be a standard and robust process to verify that validators are indeed who they claim to be. Eligibility for identity staking should be hard to achieve so that the right to be a validator is earned, valued and costly to lose.
This is the big PoA identity issue at stake: whoever decides to approve the two conditions above may have an interest in controlling the blockchain through the individuals they have given permission to or pursue economic goals that are increasingly oppressive to them.
AURA is a combination of a permissioned PoA blockchain (for obvious reasons, having to ask permission to participate in the stake) and several applications that use it as a backend for supply chain tracking and anti-counterfeiting of objects.
In Aura since consent is permissioned, the cryptocurrency used therein cannot be valuable or trusted, as it is controlled by a few parties
OTICHAIN is a permissionless PoS blockchain (so anyone can participate in the consensus to secure the network, without censorship or bias) and 1TrueID provides a number of applications that use OTICHAIN as a backend for supply chain tracking, anti-counterfeiting of objects, certifying the ownership of the object to an individual, giving the certification to a third party (in case of sale/gift), using the cryptocurrency embedded in OTICHAIN to transmit value to objects or individuals using it.
From the information retrieved, becoming an AURA node means setting up a server as the consortium says and paying a significant start-up fee.
About Quadrans, I am happy to revise with a note from a member of the Quadrans Foundation technical team, Piersandro Guerrera, original quote:
[quote] Becoming a node of Quadrans (another PoA blockchain used by TextileChain) means paying 1000 euros a year, plus their cryptos at the price they deem appropriate for the client.[/quote]
As written in the Quadrans Foundation website, Quadrans “uses both Proof of Stake and Proof of Work protocols and combines them into a modified Proof of Authority.”
Becoming a node of OTICHAIN means investing (not paying) the amount you want to have a significant return and not having to pass any visa or censorship of any kind.
A bit of technique: Premised on the attached scheme I would add a comparison with the audience: An important detail with Hedera is that OTICHAIN uses a transaction security system based UTXO and node confirmations, Hedera uses Hashgraph which accepts all blocks on principle creating a multitude of sidechains. Which does not allow to “reject” a block and does not allow to change the rules of the game (Fork) for code improvement because everything applies.
https://otichain.com/Businesses need to be acquainted with the benefits and drawbacks of public and private blockchains to ascertain which blockchain type will prove the most beneficial for their specific business requirements.
A detail from the digital collage BE by Emanuele Bertoli aka BE. Photograph: RB
Images in this post are considered to be in the public domain since found on the web and media therefore supposed to be copyright-free images – it’s not intended from the author of the post to violate any copyright right infringement laws, or to offend anyone; in the case you advise a violation, would you advise me and I’ll promptly remove them. The post it’s also an expression of my personal opinion.
Freely inspired from the article of Youval Noah Harari with my opinions
Yuval Noah Harari is a historian and philosopher at the Hebrew University of Jerusalem and the author of 21 Lessons for the 21st Century.
Artificial intelligence could erase many practical advantages of democracy, and erode the ideals of liberty and equality. It will further concentrate power among small elite of Corporate and Government Agencies.
Artificial Intelligence, If chess is our canary in the coal mine, we have been duly warned that the canary is dying
There
is nothing inevitable about democracy. For all the success that democracies have
had over the past century or more, they are blips in history. Monarchies, oligarchies, and other forms of authoritarian rule have been
far more common modes of human governance.
The emergence of liberal
democracies is associated with ideals of liberty and equality that may seem
self-evident and irreversible. But these ideals are far more fragile than we
believe. Their success in the 20th
century depended on unique technological conditions that may prove ephemeral.
Opinion
In Italy for example television at the beginning helped to unify the country and to educate the masses on Italian language, high quality theatrical comedies live filmed, opera, classic concert, shows composed of highly qualified dance bodies and anchormen where the routine and an intellectual democracy widespread well-being saw the light, afterwards came the decadence.
In the second decade of the 21st century, liberalism has begun to lose credibility. Questions about the ability of liberal democracy to provide for the middle class have grown louder;politics have grown more tribal.
Information technology is
continuing to leap forward; biotechnology is beginning to provide a window into
our inner lives—our emotions, thoughts, and choices. Together, infotech and
biotech will create unprecedented upheavals in human society, eroding human
agency and, possibly, subverting human desires. Under such conditions, liberal democracy and free-market economics
might become obsolete.
Ordinary people may not understand artificial
intelligence and biotechnology in any detail, but they can sense that the
future is passing them by. In 1938 the common man’s
condition in the Soviet Union, Germany, or the United States may have been
grim, but he was constantly told that he was the most important thing in the
world, and that he was the future (provided, of course, that he was an
“ordinary man,” rather than, say, a Jew or a woman). He looked at the propaganda posters—which typically depicted coal
miners and steelworkers in heroic poses—and saw himself there: “I am in that
poster! I am the hero of the future!”
In 2018 the common person feels increasingly
irrelevant. Lots of mysterious terms are bandied about
excitedly in ted Talks,
at government think tanks, and at high-tech conferences—globalization, blockchain, genetic
engineering, AI, machine learning—and common
people, both men and women, may well suspect that none of these terms is about
them.
In the 20th century, the
masses revolted against exploitation and sought to translate their vital role
in the economy into political power. Now the masses fear irrelevance, and they
are frantic to use their remaining political power before it is too late. Brexit and the rise of Donald Trump may therefore
demonstrate a trajectory opposite to that of traditional socialist revolutions.
The Russian, Chinese, and Cuban revolutions were made by people who were vital
to the economy but lacked political power; in 2016, Trump and Brexit were supported by many people who still enjoyed
political power but feared they were losing their economic worth. Perhaps
in the 21st century, populist revolts will be staged not against economic elite
that exploits people but against an economic elite that does not need them
anymore. This may well be a losing
battle. It is much harder to struggle against irrelevance than against
exploitation.
The revolutions in information technology and
biotechnology are still in their infancy, and the extent to which they are responsible for the
current crisis of liberalism is debatable. Most people in Birmingham, Istanbul,
St. Petersburg, and Mumbai are only dimly aware, if they are aware at all, of
the rise of AI and its potential impact on their lives. It is undoubtable,
however, that the technological revolutions now gathering momentum will in the next few decades confront humankind
with the hardest trials it has yet encountered.
Let’s start with jobs and incomes, because whatever
liberal democracy’s philosophical appeal, it has gained strength in no small
part thanks to a practical advantage: The decentralized approach to
decision making that is characteristic of liberalism—in both politics and
economics—has allowed liberal democracies to outcompete other states, and to
deliver rising affluence to their people.
This is why the people see the blockchain as a genuine social impact cushion to the raising technology oligarchy.
Liberalism reconciled the proletariat with the
bourgeoisie, the faithful with atheists, natives with immigrants, and Europeans
with Asians by promising everybody a larger slice of the pie. With a constantly growing pie, that was possible. And
the pie may well keep growing. However, economic growth may not solve social
problems that are now being created by technological disruption, because such
growth is increasingly predicated on the invention of more and more disruptive
technologies.
Fears of machines pushing
people out of the job market are, of course, nothing new, and in the past such
fears proved to be unfounded. But artificial
intelligence is different from the old machines. In the past, machines competed
with humans mainly in manual skills. Now they are beginning to compete with us
in cognitive skills. And we don’t know of any third kind of skill—beyond
the manual and the cognitive—in which humans will always have an edge.
At least for a few more
decades, human intelligence is likely to far exceed computer intelligence in
numerous fields. Hence as computers take over more routine cognitive jobs, new
creative jobs for humans will continue to appear. Many of these new jobs will
probably depend on cooperation rather than competition between humans and AI.
Human-AI teams will likely prove superior not just to humans, but also to
computers working on their own.
However, most of the new jobs
will presumably demand high levels of expertise and ingenuity, and therefore
may not provide an answer to the problem of unemployed unskilled laborers, or
workers employable only at extremely low wages. Moreover, as AI continues to improve, even jobs that demand high intelligence and
creativity might gradually disappear. The world of chess serves as
an example of where things might be heading. For several years after IBM’s computer Deep Blue defeated Garry Kasparov in 1997, human
chess players still flourished; AI was used to train human prodigies, and teams
composed of humans plus computers proved superior to computers playing alone.
Yet in recent years, computers have become so good at
playing chess that their human collaborators have lost their value and might
soon become entirely irrelevant. On December 6, 2017, another crucial milestone was reached when Google’s AlphaZero program defeated the Stockfish 8
program. Stockfish 8 had won a world
computer chess championship in 2016. It had access to centuries of accumulated
human experience in chess, as well as decades of computer experience. By
contrast, AlphaZero had not been taught
any chess strategies by its human creators—not even standard openings. Rather,
it used the latest machine-learning principles to teach itself chess by playing
against itself. Nevertheless, out of
100 games that the novice AlphaZero played against Stockfish 8, AlphaZero won
28 and tied 72—it didn’t lose once. Since AlphaZero had learned nothing
from any human, many of its winning moves and strategies seemed unconventional
to the human eye. They could be described as creative, if not downright
genius.
Can you guess how long
AlphaZero spent learning chess from scratch, preparing for the match against
Stockfish 8, and developing its genius instincts? Four hours[1]. For centuries, chess was considered one of the
crowning glories of human intelligence. AlphaZero went from utter ignorance to
creative mastery in four hours, without the help of any human guide.
AlphaZero is not the only
imaginative software out there. One of the ways to catch cheaters in chess
tournaments today is to monitor the level of originality that players exhibit. If they play an exceptionally creative
move, the judges will often suspect that it could not possibly be a human move—it
must be a computer move. At least in chess, creativity
is already considered to be the trademark of computers rather than humans! So if chess is
our canary in the coal mine, we have been duly warned that the canary is dying. What is happening today to human-AI teams in chess
might happen down the road to human-AI teams in policing, medicine, banking,
and many other fields.
What’s more, AI enjoys
uniquely nonhuman abilities, which makes the difference between AI and a human
worker one of kind rather than merely of degree. Two particularly important nonhuman abilities that AI possesses are
connectivity and updatability.
For example, many drivers are
unfamiliar with all the changing traffic regulations on the roads they drive,
and they often violate them. In addition, since every driver is a singular
entity, when two vehicles approach the same intersection, the drivers sometimes
miscommunicate their intentions and collide. Self-driving cars, by contrast, will know all the traffic regulations
and never disobey them on purpose, and they could all be connected to one
another. When two such vehicles approach the same junction, they won’t
really be two separate entities, but part of a single algorithm. The chances that they might miscommunicate
and collide will therefore be far smaller.
Similarly, if the World Health Organization identifies
a new disease, or if a laboratory produces a new medicine, it can’t immediately
update all the human doctors in the world. Yet even if you had billions of AI doctors in the
world—each monitoring the health of a single human being—you could still update
all of them within a split second, and they could all communicate to one
another their assessments of the new disease or medicine. These potential advantages of connectivity and updatability are so huge
that at least in some lines of work, it might make sense to replace all humans
with computers, even if individually some humans still do a better job than
the machines.
This is what is actually happening for
algorithms that I am helping to develop for High Frequency Traders, a hobby for
me a multimillion key success tool for them.
The same technologies that
might make billions of people economically irrelevant might also make them
easier to monitor and control.
All of this leads to one very important conclusion:
The automation revolution will not consist of a single watershed event, after which the job market will settle into some new
equilibrium. Rather, it will be a cascade of ever bigger disruptions. Old jobs
will disappear and new jobs will emerge, but the new jobs will also rapidly
change and vanish. People will need to retrain and reinvent themselves not just
once, but many times.
Just as in the 20th century
governments established massive education systems for young people, in the 21st
century they will need to establish massive reeducation systems for adults. But
will that be enough? Change is always stressful, and the hectic world of the
early 21st century has produced a global epidemic of stress. As job volatility
increases, will people be able to cope? By
2050, a useless class might emerge, the result not only of a shortage of jobs
or a lack of relevant education but also of insufficient mental stamina to
continue learning new skills. Let’s travel trough
the future years.
As many people lose
their economic value, they might also come to lose their political power. The same technologies that might make billions of
people economically irrelevant might also make them easier to monitor and
control.
AI frightens many people
because they don’t trust it to remain obedient. Science fiction makes much of
the possibility that computers or robots will develop consciousness—and shortly
thereafter will try to kill all humans. But there is no particular reason to
believe that AI will develop consciousness as it becomes more intelligent. We should instead fear AI because it will
probably always obey its human masters, and never rebel. AI is a tool and a
weapon unlike any other that human beings have developed; it will almost
certainly allow the already powerful to consolidate their power further.
IN ALL THIS high-tech commercial world there is nothing that looks particularly democratic, (except blockchain).
Artificial Intelligence lends itself to surveillance as well as liberty, to new forms of manipulation and covert control as well as new kinds of participation, to skewed, unjust market outccomes as well as greater productivity.
The consumer Society and the open society are not quite synonymous. Capitalism and democracy have a relationship, but it is something less than a marriage
Consider surveillance.
Numerous countries around the world, including several democracies, are busy
building unprecedented systems of surveillance. For example, Israel is a leader
in the field of surveillance technology, and has created in the occupied West
Bank a working prototype for a total-surveillance regime[2]. Already today whenever Palestinians make a phone
call, post something on Facebook, or travel from one city to another, they are
likely to be monitored by Israeli microphones, cameras, drones, or spy
software. Algorithms analyze the gathered data, helping the Israeli security
forces pinpoint and neutralize what they consider to be potential threats. The
Palestinians may administer some towns and villages in the West Bank, but the
Israelis command the sky, the airwaves, and cyberspace. It therefore takes
surprisingly few Israeli soldiers to effectively control the roughly 2.5
million Palestinians who live in the West Bank.
In one incident in October
2017, a Palestinian laborer posted to his private Facebook account a picture of
himself in his workplace, alongside a bulldozer. Adjacent to the image he
wrote, “Good morning!” A Facebook translation algorithm made a small error when
transliterating the Arabic letters. Instead of Ysabechhum (which
means “Good morning”), the algorithm identified the letters as Ydbachhum (which
means “Hurt them”). Suspecting that the man might be a terrorist intending to
use a bulldozer to run people over, Israeli security forces swiftly arrested him[3]. They released him after they realized that the
algorithm had made a mistake. Even so, the offending Facebook post was taken
down—you can never be too careful. What Palestinians are experiencing today in
the West Bank may be just a primitive preview of what billions of people will
eventually experience all over the planet.
Imagine, for instance, that
the current regime in North Korea gained a more advanced version of this sort
of technology in the future. North Koreans might be required to wear a
biometric bracelet that monitors everything they do and say, as well as their
blood pressure and brain activity. Using the growing understanding of the human
brain and drawing on the immense powers of machine learning, the North Korean
government might eventually be able to gauge what each and every citizen is
thinking at each and every moment. If a North Korean looked at a picture of Kim
Jong Un and the biometric sensors picked up telltale signs of anger (higher
blood pressure, increased activity in the amygdala), that person could be in
the gulag the next day.
The conflict between democracy
and dictatorship is actually a conflict between two different data-processing
systems. AI may swing the advantage toward the latter.
And yet such hard-edged
tactics may not prove necessary, at least much of the time. A facade of free
choice and free voting may remain in place in some countries, even as the
public exerts less and less actual control. To be sure, attempts to manipulate
voters’ feelings are not new. But once somebody (whether in San Francisco or
Beijing or Moscow) gains the technological ability to manipulate the human
heart—reliably, cheaply, and at scale—democratic politics will mutate into an
emotional puppet show.
We are unlikely to face a
rebellion of sentient machines in the coming decades, but we might have to deal
with hordes of bots that know how to press our emotional buttons better than
our mother does and that use this uncanny ability, at the behest of a human
elite, to try to sell us something—be it a car, a politician, or an entire
ideology. The bots might identify our deepest fears, hatreds, and cravings and
use them against us. We have already been given a foretaste of this in recent
elections and referendums across the world, when hackers learned how to
manipulate individual voters by analyzing data about them and exploiting their
prejudices. While science-fiction
thrillers are drawn to dramatic apocalypses of fire and smoke, in reality we
may be facing a banal apocalypse by clicking.
The biggest and most frightening impact of the AI
revolution might be on the relative efficiency of democracies and
dictatorships. Historically, autocracies
have faced crippling handicaps in regard to innovation and economic growth. In
the late 20th century, democracies usually outperformed dictatorships, because
they were far better at processing information. We tend to think about the
conflict between democracy and dictatorship as a conflict between two different
ethical systems, but it is actually a conflict between two different
data-processing systems. Democracy
distributes the power to process information and make decisions among many
people and institutions, whereas dictatorship concentrates information and
power in one place. Given 20th-century technology, it was inefficient to
concentrate too much information and power in one place. Nobody had the ability
to process all available information fast enough and make the right decisions.
This is one reason the Soviet Union made far worse decisions than the United
States, and why the Soviet economy lagged far behind the American economy.
OPINION
Philosophically,
intellectually—in every way—human society is unprepared for the rise of
artificial intelligence. – Henry A. Kissinger
AI developers, as inexperienced in politics and philosophy as I am in law, should ask themselves some of the questions I have raised here in order to build answers into their engineering efforts. The U.S. government in particular should consider a presidential commission of eminent thinkers to help develop a national vision. This much is certain: if we do not start this effort soon, before long we shall discover we started too late
However, artificial intelligence may soon swing the
pendulum in the opposite direction. AI makes it possible to process enormous
amounts of information centrally. In fact, it might make centralized systems far more efficient than diffuse
systems, because machine learning works better when the machine has more
information to analyze. If you disregard all privacy concerns and concentrate
all the information relating to a billion people in one database, you’ll wind
up with much better algorithms than if you respect individual privacy and have
in your database only partial information on a million people. An authoritarian
government that orders all its citizens to have their DNA sequenced and to
share their medical data with some central authority would gain an immense
advantage in genetics and medical research over societies in which medical data
are strictly private. The main handicap
of authoritarian regimes in the 20th century—the desire to concentrate all
information and power in one place—may become their decisive advantage in the
21st century.
New technologies will continue
to emerge, of course, and some of them may encourage the distribution rather
than the concentration of information and power. Blockchain technology, and the
use of cryptocurrencies enabled by it, is currently touted as a possible
counterweight to centralized power. But blockchain
technology is still in the embryonic stage, and we don’t yet know whether it
will indeed counterbalance the centralizing tendencies of AI. Remember that
the Internet, too, was hyped in its early days as a libertarian panacea that
would free people from all centralized systems—but is now poised to make
centralized authority more powerful than ever.
Even if
some societies remain ostensibly democratic, the increasing
efficiency of algorithms will still shift more and more authority from
individual humans to networked machines. We might willingly give up more and more authority
over our lives because we will learn
from experience to trust the algorithms more than our own feelings, eventually
losing our ability to make many decisions for ourselves. Just think of the
way that, within a mere two decades, billions of people have come to entrust
Google’s search algorithm with one of the most important tasks of all: finding
relevant and trustworthy information. As we rely more on Google for
answers, our ability to locate information independently diminishes. Already today, “truth” is defined by the
top results of a Google search. This process has likewise affected our
physical abilities, such as navigating space. People ask Google not just to
find information but also to guide them around. Self-driving cars and AI
physicians would represent further erosion: While these innovations would put
truckers and human doctors out of work, their larger import lies in the
continuing transfer of authority and responsibility to machines.
Humans are used to thinking
about life as a drama of decision making. Liberal democracy and free-market
capitalism see the individual as an autonomous agent constantly making choices
about the world. Works of art—be they Shakespeare plays, Jane Austen novels, or
cheesy Hollywood comedies—usually revolve around the hero having to make some
crucial decision. To be or not to be? To listen to my wife and kill King
Duncan, or listen to my conscience and spare him? To marry Mr. Collins or Mr.
Darcy? Christian and Muslim theology similarly focus on the drama of decision
making, arguing that everlasting salvation depends on making the right choice.
What will happen to this view
of life as we rely on AI to make ever more decisions for us? Even now we trust Netflix to recommend
movies and Spotify to pick music we’ll like. But why should AI’s
helpfulness stop there?
Every year millions of college
students need to decide what to study. This is a very important and difficult
decision, made under pressure from parents, friends, and professors who have
varying interests and opinions. It is also influenced by students’ own
individual fears and fantasies, which are themselves shaped by movies, novels,
and advertising campaigns. Complicating matters, a given student does not
really know what it takes to succeed in a given profession, and doesn’t
necessarily have a realistic sense of his or her own strengths and weaknesses.
It’s not so hard to see how AI could one day make
better decisions than we do about careers, and perhaps even about
relationships. But once we begin to count on
AI to decide what to study, where to work, and whom to date or even marry,
human life will cease to be a drama of decision making, and our conception of
life will need to change. Democratic
elections and free markets might cease to make sense. So might most religions
and works of art. Imagine Anna Karenina taking out her smartphone and
asking Siri whether she should stay married to Karenin or elope with the
dashing Count Vronsky. Or imagine your favorite Shakespeare play with all the
crucial decisions made by a Google algorithm. Hamlet and Macbeth would have
much more comfortable lives, but what kind of lives would those be? Do we have
models for making sense of such lives?
OPINION
This is why the future of retail, it so important and
a core of our new human renaissance, with an eye on the past, but gaining
advantage from the modern technologies.
In my opinion the future commercial centre that will
have more success will be the ones who put the human enlightenment and his
emotions at the centre, therefore like in the old artisans village, the goods
will be made on demand or to measure, and cultural events and museum will be at
the centre of the stage.
Can parliaments
and political parties overcome these challenges and forestall the
darker scenarios? At the current moment this does not seem likely. Technological disruption is not even a leading item
on the political agenda. During the 2016 U.S. presidential race, the main
reference to disruptive technology concerned Hillary Clinton’s email debacle,
and despite all the talk about job loss, neither candidate directly addressed
the potential impact of automation. Donald
Trump warned voters that Mexicans would take their jobs, and that the U.S.
should therefore build a wall on its southern border. He never warned voters
that algorithms would take their jobs, nor did he suggest building a firewall
around California.
So what should we do?
For starters, we need to place a much higher priority on understanding how the human mind works—particularly how our own wisdom and compassion can be cultivated.
If we invest too much in AI and too little in developing the human mind, the very sophisticated artificial intelligence of computers might serve only to empower the natural stupidity of humans, and to nurture our worst (but also, perhaps, most powerful) impulses, among them greed and hatred.
To avoid such an outcome, for every dollar and every minute we invest in improving AI, we would be wise to invest a dollar and a minute in exploring and developing human consciousness.
More practically, and more immediately, if we want to
prevent the concentration of all wealth and power in the hands of small elite,
we must regulate the ownership of data. In ancient times, land was the most
important asset, so politics was a struggle to control land. In the modern era, machines and factories became
more important than land, so political struggles focused on controlling these
vital means of production. In the 21st
century, data will eclipse both land and machinery as the most important asset,
so politics will be a struggle to control data’s flow.
Unfortunately, we don’t have
much experience in regulating the ownership of data, which is inherently a far
more difficult task than regulating land or machines. Data are everywhere and nowhere at the same time, they can move at the
speed of light, and you can create as many copies of them as you want. Do the
data collected about my DNA, my brain, and my life belong to me, or to the
government, or to a corporation, or to the human collective?
The race to accumulate data is already on, and is
currently headed by giants such as Google, Amazon and Facebook and, in China,
Baidu and Tencent. So far, many of these
companies have acted as “attention merchants”—they capture our attention by
providing us with free information, services, and entertainment, and then they
resell our attention to advertisers. Yet their true business isn’t merely selling
ads. Rather, by capturing our attention they manage to accumulate immense
amounts of data about us, which are worth more than any advertising revenue. We aren’t their customers—we are their
product.
Ordinary people will find it
very difficult to resist this process. At present, many of us are happy to give
away our most valuable asset—our personal data—in exchange for free email
services and funny cat videos. But if,
later on, ordinary people decide to try to block the flow of data, they are
likely to have trouble doing so, especially as they may have come to rely on
the network to help them make decisions, and even for their health and physical
survival.
Nationalization of data by
governments could offer one solution; it would certainly curb the power of big
corporations. But history suggests that
we are not necessarily better off in the hands of overmighty governments.
So we had better call upon our
scientists, our philosophers, our lawyers, and even our poets to turn their
attention to this big question: How do you regulate the ownership of data?
Currently, humans risk becoming similar to
domesticated animals. We have bred docile cows that produce enormous amounts of
milk but are otherwise far inferior to their wild ancestors. They are less agile, less curious, and less
resourceful. We are now creating tame humans who produce enormous amounts of
data and function as efficient chips in a huge data-processing mechanism, but
they hardly maximize their human potential. If we are not careful, we will end
up with downgraded humans misusing upgraded computers to wreak havoc on
themselves and on the world.
If you find these prospects alarming—if you dislike the idea of living in a digital dictatorship or some similarly degraded form of society—then the most important contribution you can make is to find ways to prevent too much data from being concentrated in too few hands, and also find ways to keep distributed data processing more efficient than centralized data processing.
These will not be easy tasks. But achieving them may be the best safeguard of democracy.
