Hello World: how to be human in the age of the machine

Computers, algorithms, and data are controlling our lives, powering our economy and changing our world. Unlike a few decades ago, the larger companies on the planet deal mostly with data manipulation, processed by powerful algorithms that help us decide what we buy, which songs we like, where we go and how we get there. More and more, we are becoming unwitty slaves to these algorithms, which are with us all the time, running on cell phones, computers, servers, and smart devices. And yet, few people understand what an algorithm is, what artificial intelligence really means, or what machine learning can do.

Hannah Fry’s new book opens a window on this world of algorithms and on the ways they are changing our lives and societies. Despite its name, this book is not about programming nor is it about programs. The book is about algorithms, and the ways they are being used in the most diverse areas, to process data and obtain results that are of economic or societal value.

While leading us through the many different areas where algorithms are used these days, Fry passes on her own views about the benefits they bring but also about the threats they carry with them. The book starts by addressing the issue of whether we, humans, are handling too much power to algorithms and machines. This has not to do with the fear of intelligent machines taking over the world, the fear that a superintelligence will rule us against our will. On the contrary, the worry is that algorithms that are effective but not that intelligent will be trusted to take decisions on our behalf; that our privacy is being endangered by our willingness to provide personal data to companies and agencies; that sub-optimal algorithms working on insufficient data may bring upon us serious unintended consequences.

As Fry describes, trusting algorithms to run our lives is made all the more dangerous by the fact that each one of us is handing over huge amounts of personal data to big companies and government agencies, which can use them to infer information that many of us would rather keep private. Even data that we deem most innocent, like what we shop at the grocery, is valuable and can be used to extract valuable and, sometimes, surprising information. You will learn, for instance, that pregnant women, on their second trimester, are more likely to buy moisturizer, effectively signaling the data analysts at the stores that a baby is due in a few months. The book is filled with interesting, sometimes fascinating, descriptions of cases like these, where specific characteristics on the data can be used, by algorithms, to infer valuable information.

Several chapters are dedicated to a number of different areas where data processing and algorithmic analysis have been extensively applied. Fry describes how algorithms are currently being used in areas as diverse as justice, transportation, medicine, and crime prevention. She explains and analyses how algorithms can be used to drive cars, influence elections, diagnose cancers, make decisions on parole cases and rulings in courts, guess where crimes will be committed, recognize criminals in surveillance videos, predict the risk of Alzheimer from early age linguistic ability, and many other important and realistic applications of data analysis. Most of these algorithms use what we now call artificial intelligence and machine learning but it is clear that, to the author, these techniques are just toolboxes for algorithm designers. The many examples included in these chapters are, in themselves, very interesting and, in some cases, riveting. However, what is most important is the way the author uses these examples to make what I feel is the central point of the book: using an algorithm implies a tradeoff and every application brings with it benefits and risks, which have to be weighted. If we use face recognition algorithms to spot criminals, we have to accept the risk of an algorithm sending an innocent person to jail. If we police more the locations where crimes are more likely to take place, people on those areas may feel they are treated unfairly. If we use social data to target sale campaigns, then it can also be used to market political candidates and manipulate elections. The list of tradeoffs goes on and on and every one of them is complex.

As every engineer knows, there is no such thing as 100% reliability or 100% precision. Every system that is designed to perform a specific task will have a given probability of failing at it, however small. All algorithms that aim at identifying some specific targets will make mistakes. They will falsely classify some non-target cases as targets (false positives) and will miss some real targets (false negatives). An autonomous car may be safer than a normal car with a human driver but will, in some rare cases, cause accidents that would not have happened, otherwise. How many spurious accidents are we willing to tolerate, in order to make roads safer to everyone? These are difficult questions and this book does a good job at reminding us that technology will not make those choices for us. It is our responsibility to make sure that we, as a society, assess and evaluate clearly the benefits and risks of each and every application of algorithms, in order to make the overall result be positive for the world.

The final chapter addresses a different and subtler point, which can be framed in the same terms that Ada Lovelace put it, more than 150 years ago: can computers originate new things, can they be truly creative? Fry does not try to find a final answer to this conundrum, but she provides interesting data on the subject, for the reader to decide by him- or herself. By analyzing the patterns of the music written by a composer, algorithms can create new pieces that, in many cases, will fool the majority of the people and even many experts. Does this mean that computers can produce novel art? And, if so, is it good art? The answer is made the more difficult by the fact that there are no objective measures for the quality of works of art. Many experiences, some of them described in this chapter, show clearly that the beauty is, in many cases, in the eye of the beholder. Computer produced art is good enough to be treated like the real thing, at least when the origin of the work is not known. But many people will argue that copying someone else’s style is not really creating art. Others will disagree. Nonetheless, this final chapter provides an interesting introduction to the problem of computer creativity and the interested reader can pick on some of the leads provided by the book to investigate the issue further.

Overall, Hello World is definitely worth reading, for those interested in the ways computers and algorithms are changing our lives.

Note: this is an edited version of the full review that appeared in Nature Electronics.

 

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AlphaZero masters the game of Chess

DeepMind, a company that was acquired by Google, made headlines when the program AlphaGo Zero managed to become the best Go player in the world, without using any human knowledge, a feat reported in this blog less than two months ago.

Now, just a few weeks after that result, DeepMind reports, in an article posted in arXiv.org, that the program AlphaZero obtained a similar result for the game of chess.

Computer programs have been the world’s best players for a long time now, basically since Deep Blue defeated the reigning world champion, Garry Kasparov, in 1997. Deep Blue, as almost all the other top chess programs, was deeply specialized in chess, and played the game using handcrafted position evaluation functions (based on grand-master games) coupled with deep search methods. Deep Blue evaluated more than 200 million positions per second, using a very deep search (between 6 and 8 moves, sometimes more) to identify the best possible move.

Modern computer programs use a similar approach, and have attained super-human levels, with the best programs (Komodo and Stockfish) reaching a Elo Rating higher than 3300. The best human players have Elo Ratings between 2800 and 2900. This difference implies that they have less than a one in ten chance of beating the top chess programs, since a difference of 366 points in Elo Rating (anywhere in the scale) mean a probability of winning of 90%, for the most ranked player.

In contrast, AlphaZero learned the game without using any human generated knowledge, by simply playing against another copy of itself, the same approach used by AlphaGo Zero. As the authors describe, AlphaZero learned to play at super-human level, systematically beating the best existing chess program (Stockfish), and in the process rediscovering centuries of human-generated knowledge, such as common opening moves (Ruy Lopez, Sicilian, French and Reti, among others).

The flexibility of AlphaZero (which also learned to play Go and Shogi) provides convincing evidence that general purpose learners are within the reach of the technology. As a side note, the author of this blog, who was a fairly decent chess player in his youth, reached an Elo Rating of 2000. This means that he has less than a one in ten chance of beating someone with a rating of 2400 who has less than a one in ten chance of beating the world champion who has less than a one in ten chance of beating AlphaZero. Quite humbling…

Image by David Lapetina, available at Wikimedia Commons.

Portuguese Edition of The Digital Mind

IST Press, the publisher of Instituto Superior Técnico, just published the Portuguese edition of The Digital Mind, originally published by MIT Press.

The Portuguese edition, translated by Jorge Pereirinha Pires, follow the same organization and has been reviewed by a number of sources. The back-cover reviews are by Pedro Domingos, Srinivas Devadas, Pedro Guedes de Oliveira and Francisco Veloso.

A pre-publication was made by the Público newspaper, under the title Até que mundos digitais nos levará o efeito da Rainha Vermelha, making the first chapter of the book publicly available.

There are also some publicly available reviews and pieces about this edition, including an episode of a podcast and a review in the radio.

The last invention of humanity

Irving John Good was a British mathematician who worked with Alan Turing in the famous Hut 8 of Bletchley Park, contributing to the war effort by decrypting the messages coded by the German enigma machines. After that, he became a professor at Virginia Tech and, later in life, he was a consultant for the cult movie 2001: A Space Odyssey, by Stanley Kubrick.

Irving John Good (born Isadore Jacob Gudak to a Polish jewish family) is credited with coining the term intelligence explosion, to refer to the possibility that a super-intelligent system may, one day, be able to design an even more intelligent successor. In his own words:

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.

We are still very far from being able to design an artificially intelligent (AI)  system that is smart enough to design and code even better AI systems. Our current efforts address very narrow fields, and obtain systems that do not have the general intelligence required to create the phenomenon I. J. Good was referring to. However, in some very restrict domains, we can see at work mechanisms that resemble the that very same phenomenon.

Go is a board game, very difficult to master because of the huge number of possible games and high number of possible moves at each position. Given the complexity of the game, branch and bound approaches could not be used, until recently, to derive good playing strategies. Until only a few years ago, it was believed that it would take decades to create a program that would master the game of Go, at a level comparable with the best human players.

In January 2016, DeepMind, an AI startup (which was at that time acquired by Google by a sum reported to exceed 500M dollars), reported in an article in Nature that they had managed to master the complex game of Go by using deep neural networks and a tree search engine. The system, called AlphaGo, was trained on databases of human games and eventually managed to soundly beat the best human players, becoming the best player in the world, as reported in this blog.

A couple of weeks ago, in October of 2017, DeepMind reported, in a second article in Nature, that they programmed a system, which became even more proficient at the game, that mastered the game without using any human knowledge. AlphaGo Zero did not use any human games to acquire knowledge about the game. Instead, it played millions of games (close to 30 millions, in fact, played over a period of 40 days) against another version of itself, eventually acquiring knowledge about tactics and strategies that have been slowly created by the human race for more than two millennia. By simply playing against itself, the system went from a child level (random moves) to a novice level to a world champion level. AlphaGo Zero steamrolled the original AlphaGo by 100 to 0,  showing that it is possible to obtain super-human strength without using any human generated knowledge.

In a way, the computer improved itself, by simply playing against itself until it reached perfection. Irving John Good, who died in 2009, would have liked to see this invention of mankind. Which will not be the last, yet…

Picture credits: Go board, picture taken by Hoge Rielen, available at Wikimedia Commons.

 

Homo Deus: A Brief History of Tomorrow

Homo Deus, the sequel to the wildly successful hit Sapiens, by Yuval Harari, aims to chronicle the history of tomorrow and to provide us with a unique and dispassionate view of the future of humanity. In Homo Deus, Harari develops further the strongest idea in Sapiens, the idea that religions (or shared fictions) are the reason why humanity came to dominate the world.

Many things are classified by Harari as religions, from the traditional ones like Christianism, Islamism or Hinduism, to other shared fictions that we tend not to view as religions, such as countries, money, capitalism, or humanism. The ability to share fictions, such as these, created in Homo sapiens the ability to coordinate enormous numbers of individuals in order to create vast common projects: cities, empires and, ultimately, modern technology. This is the idea, proposed in Sapiens, that Harari develops further in this book.

Harari thinks that, with the development of modern technology, humans will doggedly pursue an agenda consisting of three main goals: immortality, happiness and divinity. Humanity will try to become immortal, to live in constant happiness and to be god-like in its power to control nature.

The most interesting part of the book is in middle, where Harari analyses, in depth, the progressive but effective replacement of ancient religions by the dominant modern religion, humanism. Humanism, the relatively recent idea that there is a unique spark in humans, that makes human life sacred and every individual unique. Humanism therefore believes that meaning should be sought in the individual choices, views, and feelings, of humans, replaced almost completely traditional religions (some of them with millennia), which believed that meaning was to be found in ancient scriptures or “divine” sayings.

True, many people still believe in traditional religions, but with the exception of a few extremist sects and states, these religions plays a relatively minor role in conducting the business of modern societies. Traditional religions have almost nothing to say about the key ideas that are central to modern societies, the uniqueness of the individual and the importance of the freedom of choice, ideas that led to our current view of democracies and ever-growing market-oriented economies. Being religious, in the traditional sense, is viewed as a personal choice, a choice that must exist because of the essential humanist value of freedom of choice.

Harari’s description of the humanism schism, into the three flavors of liberal humanism, socialist humanism, and evolutionary humanism (Nazism and other similar systems), is interesting and entertaining. Liberal humanism, based on the ideals of free choice, capitalism, and democracy, has been gaining the upper hand in the twentieth century, with occasional relapses, over socialism or enlightened dictatorships.

The last part of the book, where one expects Harari to give us a hint of what may come after humanism, once technology creates systems and machines that make humanist creeds obsolete, is rather disappointing. Instead of presenting us with the promises and threats of transhumanism, he clings to common clichés and rather mundane worries.

Harari firmly believes that there are two types of intelligent systems: biological ones, which are conscious and have, possibly, some other special properties, and the artificial ones, created by technology, which are not conscious, even though they may come to outperform humans in almost every task. According to him, artificial systems may supersede humans in many jobs and activities, and possibly even replace humans as the intelligent species on Earth, but they will never have that unique spark of consciousness that we, humans, have.

This belief leads to two rather short-sighted final chapters, which are little more than a rant against the likes of Facebook, Google, and Amazon. Harari is (and justifiably so) particularly aghast with the new fad, so common these days, of believing that every single human experience should go online, to make shareable and give it meaning. The downsize is that this fad provides data to the all-powerful algorithms that are learning all there is to know about us. I agree with him that this is a worrying trend, but viewing it as the major threat of future technologies is a mistake. There are much much more important issues to deal with.

It is not that these chapters are pessimistic, even though they are. It is that, unlike in the rest of Homo Deus (and in Sapiens), in these last chapters Harari’s views seem to be locked inside a narrow and traditionalist view of intelligence, society, and, ultimately, humanity.

Other books, like SuperintelligenceWhat Technology Wants or The Digital Mind provide, in my opinion, much more interesting views on what a transhumanist society may come to be.

Europe wants to have one exascale supercomputer by 2023

On March 23rd, in Rome, seven European countries signed a joint declaration on High Performance Computing (HPC), committing to an initiative that aims at securing the required budget and developing the technologies necessary to acquire and deploy two exascale supercomputers, in Europe, by 2023. Other Member States will be encouraged to join this initiative.

Exascale computers, defined as machines that execute 10 to the 18th power operations per second will be roughly 10 times more powerful than the existing fastest supercomputer, the Sunway TaihuLight, which clocks in at 93 petaflop/s, or 93 times 10 to the 15 floating point operations per second. No country in Europe has, at the moment, any machine among the 10 most powerful in the world. The declaration, and related documents, do not fully specify that these machines will clock at more than one exaflop/s, given that the requirements for supercomputers are changing with the technology, and floating point operations per second may not be the right measure.

This renewed interest of European countries in High Performance Computing highlights the fact that this technology plays a significant role in the economic competitiveness of research and development. Machines with these characteristics are used mainly in complex system simulations, in physics, chemistry, materials, fluid dynamics, but they are also useful in storing and processing the large amounts of data required to create intelligent systems, namely by using deep learning.

Andrus Ansip, European Commission Vice-President for the Digital Single Market remarked that: “High-performance computing is moving towards its next frontier – more than 100 times faster than the fastest machines currently available in Europe. But not all EU countries have the capacity to build and maintain such infrastructure, or to develop such technologies on their own. If we stay dependent on others for this critical resource, then we risk getting technologically ‘locked’, delayed or deprived of strategic know-how. Europe needs integrated world-class capability in supercomputing to be ahead in the global race. Today’s declaration is a great step forward. I encourage even more EU countries to engage in this ambitious endeavour”.

The European Commission press release includes additional information on the next steps that will be taken in the process.

Photo of the signature event, by the European Commission. In the photo, from left to right, the signatories: Mark Bressers (Netherlands), Thierry Mandon (France), Etienne Schneider (Luxembourg), Andrus Ansip (European Commission), Valeria Fedeli (Italy), Manuel Heitor (Portugal), Carmen Vela (Spain) and Herbert Zeisel (Germany).

 

The Digital Mind: How Science is Redefining Humanity

Following the release in the US,  The Digital Mind, published by MIT Press,  is now available in Europe, at an Amazon store near you (and possibly in other bookstores). The book covers the evolution of technology, leading towards the expected emergence of digital minds.

Here is a short rundown of the book, kindly provided by yours truly, the author.

New technologies have been introduced in human lives at an ever increasing rate, since the first significant advances took place with the cognitive revolution, some 70.000 years ago. Although electronic computers are recent and have been around for only a few decades, they represent just the latest way to process information and create order out of chaos. Before computers, the job of processing information was done by living organisms, which are nothing more than complex information processing devices, created by billions of years of evolution.

Computers execute algorithms, sequences of small steps that, in the end, perform some desired computation, be it simple or complex. Algorithms are everywhere, and they became an integral part of our lives. Evolution is, in itself, a complex and long- running algorithm that created all species on Earth. The most advanced of these species, Homo sapiens, was endowed with a brain that is the most complex information processing device ever devised. Brains enable humans to process information in a way unparalleled by any other species, living or extinct, or by any machine. They provide humans with intelligence, consciousness and, some believe, even with a soul, a characteristic that makes humans different from all other animals and from any machine in existence.

But brains also enabled humans to develop science and technology to a point where it is possible to design computers with a power comparable to that of the human brain. Artificial intelligence will one day make it possible to create intelligent machines and computational biology will one day enable us to model, simulate and understand biological systems and even complete brains with unprecedented levels of detail. From these efforts, new minds will eventually emerge, minds that will emanate from the execution of programs running in powerful computers. These digital minds may one day rival our own, become our partners and replace humans in many tasks. They may usher in a technological singularity, a revolution in human society unlike any other that happened before. They may make humans obsolete and even a threatened species or they make us super-humans or demi-gods.

How will we create these digital minds? How will they change our daily lives? Will we recognize them as equals or will they forever be our slaves? Will we ever be able to simulate truly human-like minds in computers? Will humans transcend the frontiers of biology and become immortal? Will humans remain, forever, the only known intelligence in the universe?