IEEE Spectrum special issue on whether we can duplicate a brain

Maybe you have read The Digital Mind or The Singularity is Near, by Ray Kurzweil, or other similar books, thought it all a bit farfetched, and wondered whether the authors are bonkers or just dreamers.

Wonder no more. The latest issue of the flagship publication of the Institute for Electrical and Electronic Engineers, IEEE Spectrum , is dedicated to the interesting and timely question of whether we can copy the brain, and use it as blueprint for intelligent systems.  This issue, which you can access here, includes many interesting articles, definitely worth reading.

I cannot even begin to describe here, even briefly, the many interesting articles in this special issue, but it is worthwhile reading the introduction, on the perspective of near future intelligent personal assistants or the piece on how we could build an artificial brain right now, by Jennifer Hasler.

Other articles address the question on how expensive, computationally, is the simulation of a brain at the right level of abstraction. Karlheinz Meier’s article on this topic explains very clearly why present day simulations are so slow:

“The big gap between the brain and today’s computers is perhaps best underscored by looking at large-scale simulations of the brain. There have been several such efforts over the years, but they have all been severely limited by two factors: energy and simulation time. As an example, consider a simulation that Markus Diesmann and his colleagues conducted several years ago using nearly 83,000 processors on the K supercomputer in Japan. Simulating 1.73 billion neurons consumed 10 billion times as much energy as an equivalent size portion of the brain, even though it used very simplified models and did not perform any learning. And these simulations generally ran at less than a thousandth of the speed of biological real time.

Why so slow? The reason is that simulating the brain on a conventional computer requires billions of differential equations coupled together to describe the dynamics of cells and networks: analog processes like the movement of charges across a cell membrane. Computers that use Boolean logic—which trades energy for precision—and that separate memory and computing, appear to be very inefficient at truly emulating a brain.”

Another interesting article, by Eliza Strickland, describes some of the efforts that are taking place to use  reverse engineer animal intelligence in order to build true artificial intelligence , including a part about the work by David Cox, whose team trains rats to perform specific tasks and then analyses the brains by slicing and imaging them:

“Then the brain nugget comes back to the Harvard lab of Jeff Lichtman, a professor of molecular and cellular biology and a leading expert on the brain’s connectome. ­Lichtman’s team takes that 1 mm3 of brain and uses the machine that resembles a deli slicer to carve 33,000 slices, each only 30 nanometers thick. These gossamer sheets are automatically collected on strips of tape and arranged on silicon wafers. Next the researchers deploy one of the world’s fastest scanning electron microscopes, which slings 61 beams of electrons at each brain sample and measures how the electrons scatter. The refrigerator-size machine runs around the clock, producing images of each slice with 4-nm resolution.”

Other approaches are even more ambitious. George Church, a well-known researcher in biology and bioinformatics, uses sequencing technologies to efficiently obtain large-scale, detailed information about brain structure:

“Church’s method isn’t affected by the length of axons or the size of the brain chunk under investigation. He uses genetically engineered mice and a technique called DNA bar coding, which tags each neuron with a unique genetic identifier that can be read out from the fringy tips of its dendrites to the terminus of its long axon. “It doesn’t matter if you have some gargantuan long axon,” he says. “With bar coding you find the two ends, and it doesn’t matter how much confusion there is along the way.” His team uses slices of brain tissue that are thicker than those used by Cox’s team—20 μm instead of 30 nm—because they don’t have to worry about losing the path of an axon from one slice to the next. DNA sequencing machines record all the bar codes present in a given slice of brain tissue, and then a program sorts through the genetic information to make a map showing which neurons connect to one another.”

There is also a piece on the issue of AI and consciousness, where Christoph Koch and Giulio Tononi describe their (more than dubious, in my humble opinion) theory on the application of Integrated Information Theory to the question of: can we quantify machine consciousness?

The issue also includes interesting quotes and predictions by famous visionairies, such as Ray Kurzweil, Carver Mead, Nick Bostrom, Rodney Brooks, among others.

Images from the special issue of IEEE Spectrum.

To Be a Machine: Adventures Among Cyborgs, Utopians, and the Futurists Solving the Modest Problem of Death

Mark O’Connell witty, insightful and sometimes deeply moving account of his research on the topic of transhumanism deserves a place in the bookshelf of anyone interested in the future of humanity. Reading To Be a Machine is a delightful trip through the ideals, technologies, places and characters involved in transhumanism, the idea that science and technology will one day transform human into immortal computer based lifeforms.

For reasons that are not totally clear to me, transhumanism remains mostly a fringe culture, limited to a few futurists, off-the-mainstream scientists and technology nuts. As shared fictions go (to use Yuval Harari’s notation), I would imagine transhumanism is one idea whose time has come. However, it remains mostly unknown by the general public. While humanists believe that the human person, with his/her desires, choices, and fears, should be the most important value to be preserved by a society (check my review of Homo Deus), transhumanists believe that biological based intelligence is imperfect, exists purely because of historical reasons (evolution, that is) and will go away soon as we move intelligence into other computational supports, more robust than our frail bodies.

O’Connell, himself a hard-core humanist, as becomes clear from reading between the lines of this book, pursued a deep, almost forensic, investigation on what transhumanists are up to. In this process, he talks with many unusual individuals involved in the transhumanist saga, from Max More, who runs Alcor, a company that, in exchange for a couple hundred dollars, will preserve your body for the future in liquid nitrogen (or 80k for just the head) to Aubrey de Grey, a reputed scientist working in life extension technologies, who argues that we should all be working on this problem. In de Grey’s words, cited by O’Connell “aging is a human disaster on an unimaginably vast scale, a massacre, a methodical and comprehensive annihilation of every single person that ever lived“. These are just two of the dozens of fascinating characters in the book interviewed in place by O’Connell.

The narrative is gripping, hilarious at times, but moving and compelling, not the least because O’Connell himself provides deep insights about the issues the book discusses. The characters in the book are, at once, alien and deeply human, as they are only trying to overcome the limits of our bodies. Deservedly, the book has been getting excellent reviews, from many sources.

In the end, one gets the idea that transhumanists are crazy, maybe, but not nearly as crazy as all other believers in immortality, be it by divine intervention, by reincarnation, or by any other mechanisms so ingrained in mainstream culture.

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?

 

Taxing robots: a solution for unemployment or a recipe for economic disaster?

In a recent interview with Quartz, Bill Gates, who cannot exactly be called a Luddite, argued that a robot tax should be levied and used to help pay for jobs in healthcare and education, which are hard to automate and can only be done by humans (for now). Gates pointed out that humans are taxed on the salary they make, unlike the robots who could replace them.

Gates argued that governments must take more control of the consequences of increased technological sophistication and not rely on businesses to redistribute the income that is generated by the new generation of robots and artificial intelligence systems.

Although the idea looks appealing, it is in reality equivalent to taxing capital, as this article in The Economist explains. Taxing capital investments will slow down increases in productivity, and may lead, in the end, to poorer societies. Bill Gates’ point seems to be that investing in robots does indeed improve productivity, but also causes significant negative externalities, such as long term unemployment and increased income distribution inequalities. These negative externalities might justify a specific tax on robots, aimed at alleviating these negative externalities. In the end, it comes down to deciding whether economic growth is more important than ensuring everyone has a job.

As The Economist puts it: “Investments in robots can make human workers more productive rather than expendable; taxing them could leave the employees affected worse off. Particular workers may suffer by being displaced by robots, but workers as a whole might be better off because prices fall. Slowing the deployment of robots in health care and herding humans into such jobs might look like a useful way to maintain social stability. But if it means that health-care costs grow rapidly, gobbling up the gains in workers’ incomes, then the victory is Pyrrhic.”

Gates´ comments have been extensively analyzed in a number of articles, including this one by Yanis Varoufakis, a former finance minister of Greece, who argues that the robot tax will not solve the problem and is, at any rate, much worse than the existing alternative, a universal basic income.

The question of whether robots should be taxed is not a purely theoretical one. On February 17th, 2017, the European Parliament approved  a resolution with recommendations to the European Commission, which is heavily based on the draft report proposed by the committee on legal affairs, but leaves out the recommendations (included in the draft report) to consider a tax on robots. The decision to reject the robot tax was, unsurprisingly, well received by the robotics industry, as reported  in this article by Reuters.

PHOTO DATE: 12-12-13 LOCATION: Bldg. 32B - Valkyrie Lab SUBJECT: High quality, production photos of Valkyrie Robot for PAO PHOTOGRAPHERS: BILL STAFFORD, JAMES BLAIR, REGAN GEESEMAN

Image courtesy of NASA/Bill Stafford, James Blair and Regan Geeseman, available at Wikimedia Commons.

 

 

Will the fourth industrial revolution destroy or create jobs?

The impact of the fourth industrial revolution on jobs has been much discussed.

On one side, there are the traditional economists, who argue that technological advances have always created more and better jobs than the ones they destroyed. On the other side, the people that believe that with the arrival of artificial intelligence and robotics, there will simply not exist enough jobs that cannot be done by machines.

So, in this post, I try to present a balanced analysis on the subject, as deeply as allowed by the space and time available.

Many studies have addressed the question of which jobs are more likely to be destroyed by automation.  This study, by McKinsey, provides a very comprehensive analysis.

lixo

Recently, The Economist also published a fairly balanced analysis of the topic, already posted in this blog. In this analysis, The Economist makes a reference to a number of studies on the jobs that are at high risk but, in the end, it sides with the opinion that enough jobs will be created to replace the ones technology will destroy.

A number of books and articles have been written on the topic, including “Raising the Floor“, “The Wealth of Humans: Work, Power, and Status in the Twenty-first Century“, “The Second Machine Age“, and “No More Work“, some of them already reviewed in this blog.

In most cases, the authors of these books advocate the need for significant changes in the way society is organized, and on the types of social contracts that need to be drawn. Guaranteeing every one a universal basic income is a proposal that has become very popular, as a way to address the question of how humanity will live in a time when there are much less jobs to go around.

Further evidence that some deep change is in the cards is provided by data that shows that, with the begining of the XXI century, income is being moved away from jobs (and workers) towards capital (and large companies):

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On the other side of the debate, there are many people who believe that humans will always be able to adapt and add value to society, regardless of what machines can or cannot do. David Autor, in his TED talk, makes a compelling point that many times before it was argued that “this time is different” and that it never was.

Other articles, including this one in the Washington Post, argue that the fears are overblown. The robots will not be coming in large numbers, to replace humans. Not in the near future, anyway.

Other economists, such as  Richard Freeman, in an article published in Harvard Magazine agree and also believe that the fears are unwarranted: “We should worry less about the potential displacement of human labor by robots than about how to share fairly across society the prosperity that the robots produce.

His point is that the problem is not so much on the lack of jobs, but on the depression of wages. Jobs may still exist, but will not be well paid, and the existing imbalances in income distribution will only become worst.

Maybe, in the end, this opinion represents a balanced synthesis of the two competing views: jobs will still exist, for anyone who wants to take them, but there will be competition (from robots and intelligent agents) for them, pushing down the wages.

European Parliament committee approves proposal to give robots legal status and responsibilities

The committee on legal affairs of the European Parliament has drafted and approved a report that addresses many of the legal, social and financial consequences of the development of robots and artificial intelligence (AI).

The draft report addresses a large number of issues related with the advances of robotics, AI and related technologies, and proposes a number of european regulations to govern the utilization of robots and other advanced AI agents.

The report was approved with a 17-2 vote (and two abstentions) by the parliament’s legal affairs committee.

epstrasbourg

Among many other issues addressed, the report considers:

  • The question of legal status: “whereas, ultimately, robots’ autonomy raises the question of their nature in the light of the existing legal categories – of whether they should be regarded as natural persons, legal persons, animals or objects – or whether a new category should be created”, advancing with the proposal of “creating a specific legal status for robots, so that at least the most sophisticated autonomous robots could be established as having the status of electronic persons with specific rights and obligations…”
  • The impact of robotics and AI on employment and social security, and concludes that “consideration should be given to the possible need to introduce corporate reporting requirements on the extent and proportion of the contribution of robotics and AI to the economic results of a company for the purpose of taxation and social security contributions; takes the view that in the light of the possible effects on the labour market of robotics and AI a general basic income should be seriously considered, and invites all Member States to do so;”
  • The need for a clear and unambiguous registration system for robots, recommending that “a system of registration of advanced robots should be introduced, and calls on the Commission to establish criteria for the classification of robots with a view to identifying the robots that would need to be registered;”

 

Tesla announces full self-driving ability for all its cars

Tesla motors announced all current and future Tesla cars will be built with a ‘Full Self Driving Hardware’ package. This package is the next step in the development of Autopilot, and it will enable Model S, Model X and Model 3 cars to handle junctions, twisting rural roads and parking lots.

According to the press release, this hardware includes eight surround cameras providing 360 degree visibility around the car at up to 250 meters of range, twelve updated ultrasonic sensors, and a forward-facing radar with enhanced processing ability.

tesla_parking

The video released by Tesla, on Tesla website, shows the car driving autonomously in a number of different road conditions and parking itself after searching for a free parking space. Elon Musk tweeted “When searching for parking, the car reads the signs to see if it is allowed to park there, which is why it skipped the disabled spot.” He added that in 2017 a driverless Tesla will travel from LA to NYC.