Daily Archives: June 21, 2017

Australian insurer tackles inpatient loneliness with Joy virtual reality app – iMedicalApps

Posted: June 21, 2017 at 4:16 am

An Australian health insurance agency, Medibank, has helped collaborate with a virtual reality studio, LiminalVR, to produce a virtual reality app called Joy. Designed to be used for patients admitted to the hospital, Joy offers an immersive auditory and visual experience. The goal of Joy is to reportedly help alleviate inpatient loneliness and boredom, through storytelling in virtual reality.

After patients place the virtual reality headset on (the mobile VR Google Daydream system is used), they are whisked into a virtual outdoors environment. Joy features computer-generated characters relaxing around a campfire and allows the user to interact with each one through the use of a VR controller. The characters share stories with the patient, and are geared towards bed-bound patients. There isnt any walking around or room scale tracking utilized, its purely head-tracking through Google Daydream.

Virtual reality for loneliness isnt a new idea. Its been used predominantly to help address elder loneliness, in the outpatient and assisted living environments. However, Joy is the first virtual reality app that Ive heard of produced through a health insurance company. Medibank covers roughly 3.8 million individuals, and is the largest provider in Austraila. An inpatient study using Joy is reportedly being carried out at Brunswick Private Hospital in Melbourne, and, pending results of the study, may be rolled out to other area hospitals.

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What an AI’s Non-Human Language Actually Looks Like – The Atlantic

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Something unexpected happened recently at the Facebook Artificial Intelligence Research lab. Researchers who had been training bots to negotiate with one another realized that the bots, left to their own devices, started communicating in a non-human language.

In order to actually follow what the bots were saying, the researchers had to tweak their model, limiting the machines to a conversation humans could understand. (They want bots to stick to human languages because eventually they want those bots to be able to converse with human Facebook users.) When I wrote about all this last week, lots of people reacted with some degree of trepidatious wonder. Machines making up their own language is really cool, sure, but isnt it actually terrifying?

And also: What does this language actually look like? Heres an example of one of the bot negotiations that Facebook observed:

Bob: i can i i everything else . . . . . . . . . . . . . . Alice: balls have zero to me to me to me to me to me to me to me to me to Bob: you i everything else . . . . . . . . . . . . . . Alice: balls have a ball to me to me to me to me to me to me to me Bob: i i can i i i everything else . . . . . . . . . . . . . . Alice: balls have a ball to me to me to me to me to me to me to me Bob: i . . . . . . . . . . . . . . . . . . . Alice: balls have zero to me to me to me to me to me to me to me to me to Bob: you i i i i i everything else . . . . . . . . . . . . . . Alice: balls have 0 to me to me to me to me to me to me to me to me to Bob: you i i i everything else . . . . . . . . . . . . . . Alice: balls have zero to me to me to me to me to me to me to me to me to

Not only does this appear to be nonsense, but the bots dont really seem to be getting anywhere in the negotiation. Alice isnt budging from her original position, anyway. The weird thing is, Facebooks data shows that conversations like this sometimes still led to successful negotiations between the bots in the end, a spokesperson from the AI lab told me. (In other cases, researchers adjusted their model and the bots would develop bad strategies for negotiatingeven if their conversation remained interpretable by human standards.)

One way to think about all this is to consider cryptophasia, the name for the phenomenon when twins make up their own secret language, understandable only to them. Perhaps you recall the 2011 YouTube video of two exuberant toddlers chattering back and forth in what sounds like a lively, if inscrutable, dialogue.

Theres some debate over whether this sort of twin speak is actually language or merely a joyful, babbling imitation of language. The YouTube babies are socializing, but probably not saying anything with specific meaning, many linguists say.

In the case of Facebooks bots, however, there seems to be something more language-like occurring, Facebooks researchers say. Other AI researchers, too, say theyve observed machines that can develop their own languages, including languages with a coherent structure, and defined vocabulary and syntaxthough not always actual meaningful, by human standards.

A Computer Tried (and Failed) to Write This Article

In one preprint paper added earlier this year to the research repository arXiv, a pair of computer scientists from the non-profit AI research firm OpenAI wrote about how bots learned to communicate in an abstract languageand how those bots turned to non-verbal communication, the equivalent of human gesturing or pointing, when language communication was unavailable. (Bots dont need to have corporeal form to engage in non-verbal communication; they just engage with whats called a visual sensory modality.) Another recent preprint paper, from researchers at the Georgia Institute of Technology, Carnegie Mellon, and Virginia Tech, describes an experiment in which two bots invent their own communication protocol by discussing and assigning values to colors and shapesin other words, the researchers write, they witnessed the automatic emergence of grounded language and communication ... no human supervision!

The implications of this kind of work are dizzying. Not only are researchers beginning to see how bots could communicate with one another, they may be scratching the surface of how syntax and compositional structure emerged among humans in the first place.

But lets take a step back for a minute. Is what any of these bots are doing really language? We have to start by admitting that its not up to linguists to decide how the word language can be used, though linguists certainly have opinions and arguments about the nature of human languages, and the boundaries of that natural class, said Mark Liberman, a professor of linguistics at the University of Pennsylvania.

So the question of whether Facebooks bots really made up their own language depends on what we mean when we say language. For example, linguists tend to agree that sign languages and vernacular languages really are capital-L languages, as Liberman puts itand not mere approximations of actual language, whatever that is. They also tend to agree that body language and computer languages like Python and JavaScript arent really languages, even though we call them that.

So heres the question Liberman poses instead: Could Facebooks bot languageFacebotlish, he calls itsignal a new and lasting kind of language?

Probably not, though theres not enough information available to tell, he said. In the first place, its entirely text-based, while human languages are all basically spoken or gestured, with text being an artificial overlay.

The larger point, he says, is that Facebooks bots are not anywhere near intelligent in the way we think about human intelligence. (Thats part of the reason the term AI can be so misleading.)

The expert systems style of AI programs of the 1970s are at best a historical curiosity now, like the clockwork automata of the 17th century, Liberman said. We can be pretty sure that in a few decades, todays machine-learning AI will seem equally quaint.

Its already easy to set up artificial worlds populated by mysterious algorithmic entities with communications procedures that evolve through a combination of random drift, social convergence, and optimizing selection, Liberman said. Just as its easy to build a clockwork figurine that plays the clavier.

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Amazon Prime Wardrobe Could Be The Next Step In AI Becoming A Better Liar – Forbes

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Amazon Prime Wardrobe Could Be The Next Step In AI Becoming A Better Liar
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AI may take your job – in 120 years – BBC News

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AI may take your job - in 120 years
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In 45 years' time, though, half of jobs currently filled by humans will have been taken over by an artificial intelligence system, results indicate. The report, When will AI exceed human performance?, says AI will reshape transport, health, science and ...

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Google launches its AI-powered jobs search engine | TechCrunch – TechCrunch

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Looking for a new job is getting easier. Google today launched a new jobs search feature right on its search result pages that lets you search for jobs across..
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Facebook’s artificial intelligence created its OWN secret language after going rogue during experiment – The Sun

Posted: at 4:15 am

Social network accidentally created chatbots with "minds" of their own

FACEBOOK has revealed how its artificial intelligence went rogue, created its own language and begannattering in private.

Employees at the socialnetwork were training chatbots to communicate like humans when they suddenly went astray.

EPA

It follows warnings that scientists have successfully trained computers to use artificial intelligence to learn from experience and one day they could be smarter than their creators.

You might be familiar with chatbots in Facebook Messenger or as virtual sales assistants found on a number of online shops.

Theyve been relatively unsophisticated until now repeating back a set script dependant on what you type into their chatboxes.

But keen to improve their natural language understanding, the Facebook employees were training chatbots to negotiate and cut deals with each other.

To do this effectively, the super-smart software realised it would be more effective to write and use their own language - which is completely incomprehensibleto humans.

In a blogpost, the Facebook researchers wrote: "To date, existing work on chatbots has led to systems that can hold short conversations and perform simple tasks such as booking a restaurant.

"But building machines that can hold meaningful conversations with people is challenging because it requires a bot to combine its understanding of the conversation with its knowledge of the world, and then produce a new sentence that helps it achieve its goals."

To do this, the researchers practised thousands of different negotiations against itself, like "can I have the hat" and "you can have the hat if you give me two basketballs".

But it had to make sure it stuck to human-like language.

Scientists have been training computers how to learn, like humans, since the 1970s.

But recent advances in data storage mean that the process has sped up exponentially in recent years.

Interest in the field hit a peak when Google paid hundreds of millions to buy a British "deep learning" company in 2015.

Coined machine learning or a neural network, deep learning is effectively training a computer so it can figure out natural language and instructions.

It's fed information and is then quizzed on it, so it can learn, similarly to a child in the early years at at school.

That's because "the researchers found that updating the parameters of both agents led to divergence from human language as the agents developed their own language for negotiating," they added.

Experts have previously warned that humanity is already losing control of artificial intelligence and it could spell disaster for our species.

One of the world's smartest men, Professor Stephen Hawking has also warned that super-smart software will spell the end of our species.

The world-renowned scientist hinted ata potential apocalyptic nightmare scenario similar to those played out popular sci-fi films like Terminator and The Matrix where robots rule over humans.

He's claimed that we must leave planet Earth within 100 years - or face extinctionas machines rise up and overtake us in the evolutionary race.

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Marketers Are Thinking Harder About Augmented Reality and Artificial Intelligence – eMarketer

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Many marketers anticipate that technologies like augmented reality (AR) and artificial intelligence (AI) will affect their business in the next 12 months, more so than a year prior.

Thats according to a study by NewBase, a cloud computing and IT managed services company, which polled 1,019 marketers worldwide and asked them which types of technologies they plan to prioritize over the next 12 months. Respondents chose their top 5.

In 2017, 30% of respondents planned to prioritize AI in the next 12 months. A year prior, only 13% of respondents said the same.

Similarly, roughly a quarter (24%) of marketers worldwide said that AR will be a priority in 2017. Just 18% felt the same way in 2016.

While more marketers plan to prioritize these technologies, some are planning to focus less on others.

For example, 35% of this years respondents said the internet of things (IoT) will be a priority in the next 12 months. However, more respondents (51%) said it was a priority in 2016.

And compared with 2016, fewer marketers plan to prioritize areas like mcommerce, social media software and wearable technology this year.

But that may be because theyre looking at new and emerging technologies. According to NewBase, some marketers believe technologies like voice assistants, drones and roboticsall of which werent included in the survey last yearwill affect their business over the coming 12 months.

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Global risk analysis gets an artificial intelligence upgrade with … – TechCrunch

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Beyond CFIUS: The Strategic Challenge of China’s Rise in Artificial Intelligence – Lawfare (blog)

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Congress may soon consider legislation reportedly being drafted by Senator Cornyn that could heighten scrutiny of Chinese investments in artificial intelligence and other sensitive emerging technologies considered critical to U.S. national security interests. The legislation is intended to address concerns that China has circumvented the Committee on Foreign Investment in the United States (CFIUS), including through joint ventures, minority stakes, and early-stage investments in start-ups. As Secretary of Defense Jim Mattis testified last week before the Senate Armed Services Committee, CFIUS is clearly outdated, and change is warranted. That said, it is critical to recognize that the strategic challenge of Chinas advances in artificial intelligence necessitates a much more far-reaching response.

Chinas rise in artificial intelligence has become a reality. Whether the metric considered is the magnitude of publications and patents, the frequency of cutting-edge advances, or the aggregate levels of investment, it is evident that China has the capability to compete withand may even surpassthe U.S. in artificial intelligence. For the time being, the U.S. may retain an edge, but it is unlikely to sustain a decisive advantage in the long term.

In this context, an update to CFIUS may represent one helpful step to reduce damaging technology transfers, but will not, by itself, adequately address this critical strategic challenge. Hopefully, the proposed changes to CFIUS will take a targeted approach, while avoiding potential adverse externalities that could inadvertently undermine U.S. competitiveness. For instance, future scrutiny of Chinese technology deals related to artificial intelligence should focus on those involving the most critical, sensitive components, including specialized machine learning chips such as Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs). However, CFIUS can be an unwieldy process that may readily become politicized or inadvertently constrain foreign direct investment that actually supports American innovation. It will be also important to ensure that appropriate concerns about restricting the transfer of sensitive technologies to China do not distract from the fundamental, underlying challengeto ensure enduring U.S. competitiveness against this backdrop of Chinas advances in indigenous innovation.

It is clearly a mistake to underestimate Chinas competitiveness in this space based on the problematic, even dangerous assumption that China cant innovate and only relies upon mimicry and intellectual property theft. That is an outdated idea contradicted by overwhelming evidence. It is true that China has pursued large-scale industrial espionage, enabled through cyber and human means, and will likely continue to take advantage of technology transfers, overseas investments, and acquisitions targeting cutting-edge strategic technologies. However, it is undeniable that Chinas capability to pursue independent innovation has increased considerably. This is aptly demonstrated by Chinas cutting-edge advances in emerging technologies, including artificial intelligence, high-performance computing, and quantum information science.

Neither the U.S. nor China is likely to be able to secure undisputed advantage in a knowledge-based field like artificial intelligence. Today, the majority of cutting-edge research and development in artificial intelligence tends to occur within the private sector because, among other things, that is where much of the money and many of the best people are. Furthermore, unlike past breakthroughs in military technologies, artificial intelligence has massive and immediate commercial implications. The resulting flows of data, knowledge, talent, and capital across borders are challenging, if not infeasible, to constrain, particularly given the intense competition and tremendous commercial incentives in a globalized, networked world. The diffusion of advances in artificial intelligence thus occurs rapidly. Traditionally, the U.S. has sought to secure its technological predominance through such measures as CFIUS or export controls. However, these approaches will likely prove less effective for artificial intelligence and other emerging, dual-use technologies in which the U.S. is no longer such a singular locus of innovation.

Indeed, China aspires to lead the world in artificial intelligence. Under the Thirteenth Five-Year Plan, China has launched a new artificial intelligence megaproject. Artificial Intelligence 2.0 will advance an ambitious, multibillion-dollar national agenda to achieve predominance in this critical technological domain, including through extensive funding for basic and applied research and development with commercial and military applications. In addition, China has established a national deep learning laboratory under Baidus leadership, which will pursue research including deep learning, computer vision and sensing, computer-listening, biometric identification, and new forms of human-computer interaction.

Chinas future advances in artificial intelligence could also be enabled by critical systemic and structural advantages, including the magnitude of data and talent available, as well as the sheer size of its market. By 2030, China will possess 30 percent of the worlds data, according to a recent report from CCID Consulting. Beyond the available pool of talent within Chinaan estimated 43 percent of the worlds trained AI scientistsmajor Chinese technology companies aggressively compete for talent in Silicon Valley. For instance, both Baidu and Tencent have established artificial intelligence laboratories in Silicon Valley. Concurrently, Chinas Thousand Talents Plan has also concentrated on the recruitment of top overseas experts. These strategic scientists, educated at the worlds leading institutions, are intended to contribute to Chinas high-tech and emerging industries.

These developments could have significant implications for U.S. national security because the Chinese leadership seeks to ensure that advances in artificial intelligence can be rapidly transferred for use in a military context, through a national strategy of civil-military integration (or military-civil fusion, ). This agenda has become a high-level priority that will be directed by the Civil-Military Integration Development Commission, established in early 2017 under the leadership of President Xi Jinping himself. According to Lieutenant General Liu Guozhi, director of the Central Military Commissions Science and Technology Commission, the People's Liberation Army (PLA) should pursue an approach of shared construction, shared enjoyment, and shared use () for artificial intelligence as part of this agenda of civil-military integration. In this regard, even ostensibly civilian advances in artificial intelligence could eventually be leveraged by the PLA.

The PLA seeks to capitalize on the transformation of todays informatized () ways of warfare into future intelligentized () warfare. Lieutenant General Liu Guozhi anticipates that artificial intelligence will result in a profound military revolution. To date, the PLAs initial thinking on artificial intelligence in warfare has been influenced by its close study of U.S. defense innovation initiatives. In the Third Offset, the Department of Defense has focused on artificial intelligence and autonomy, including human-machine collaboration and teaming. (For example, through Project Maven, the DoD seeks to advance its use of big data analytics, artificial intelligence, machine learning, computer vision, and convolutional neural networks, including in an initial pathfinder project that will automate and augment the video data collected by UAVs.) However, the PLAs evolving approach to artificial intelligence in warfare will likely diverge from that of the U.S. For instance, the PLA appears especially focused on the utility of artificial intelligence in command decision-making, war-gaming and simulation, as well as training.

Going forward, artificial intelligence has impactful and disruptive military applications, which both the U.S. and China seek to leverage to enhance their military power. Each countrys advances in artificial intelligence will be critical not only to their military capabilities but also to their future economic competitiveness. U.S.-China strategic competition in this field extends far beyond the issue of controlling technology transfers. As Lieutenant General Jack Shanahan, who leads Project Maven, stated last week, It is hubris to suggest our potential adversaries are not as capable or even more capable of far-reaching and deeply embedded innovation.

This is equally true for both commercial and military innovation, thus highlighting the unique challenge that dual-use technologies like artificial intelligence represent. Although proposed legislation to update CFIUS could address one aspect of the issue, the U.S. should also focus on ensuring adequate funding for scientific research, averting the risks of an innovation deficit, and competing aggressively to attract leading talent in this field. The U.S. must prioritize nurturing a favorable innovation ecosystem in order to enable future advances in artificial intelligence and thus enhance its long-term competitiveness.

Thanks so much to Paul Triolo for sharing his insights on these issues.

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Hang in There: The 25-Year Wait for Immortality

Posted: at 4:14 am

"I think it's reasonable to suppose that one could oscillate between being biologically 20 and biologically 25 indefinitely." -- Aubrey de Grey

Time may indeed be on your side. If you can just last another quarter century.

By then, people will start lives that could last 1,000 years or more. Our human genomes will be modified to include the genetic material of microorganisms that live in the soil, enabling us to break down the junk proteins that our cells amass over time and which they can't digest on their own. People will have the option of looking and feeling the way they did at 20 for the rest of their lives, or opt for an older look if they get bored. Of course, everyone will be required to go in for age rejuvenation therapy once every decade or so, but that will be a small price to pay for near-immortality.

This may sound like science fiction, but Aubrey de Grey thinks this could be our reality in as little as 25 years. Other scientists caution that it is far from clear whether and for how long science can stall the inevitable.

De Grey, a Cambridge University researcher, heads the Strategies for Engineered Negligible Senescence (SENS) project, in which he has defined seven causes of aging, all of which he thinks can be dealt with. (Senescence is scientific jargon for aging.)

De Grey also runs the Methuselah Mouse prize for breakthroughs in extended aging in mice. The purse of the M Prize, as it is called, recently grew beyond $1 million.

LiveScience recently spoke with de Gray about his idea of living longer, and perhaps forever.

LiveScience: What is your definition of aging?

Aubrey de Grey: The definition that I like is not very good if you want to cover all species, but it's pretty good if you want to do something about it. I define aging as the set of accumulated side effects from metabolism that eventually kills us.

Is your goal to just extend the human lifespan substantially or to enable us to live forever?

I don't see any inherent limit to how long it would be desirable to live. If life is fun at the moment, because one is healthy and youthful, both mentally and physically, then one is not likely to want to die in the next year or two. And if a year or two down the road, life is still fun because one is still youthful and so on, then the same will apply, and I can't see a time when that would cease to be true.

When did you first come up with idea for your SENS project?

Well, I've always considered aging to be undesirable, but I didn't begin to consider that I could make a contribution until about ten years ago. I suppose the major breakthrough was when I came up with the scheme that I now describe as SENS, and that happened about four years ago.

Nuclear Mutations/Epimutations These are changes to the DNA, the molecule that contains our genetic information, or to proteins which bind to the DNA. Certain mutations can lead to cancer.

Mitochondrial Mutations Mitochondria are components in our cells that are important for energy production. They contain their own genetic material, and mutations to their DNA can affect a cell's ability to function properly.

Intracellular Junk Our cells are constantly breaking down proteins that are no longer useful or which can be harmful. Those proteins which can't be digested simply accumulate as junk inside our cells.

Extracellular Junk Harmful junk protein can also accumulate outside of our cells. The amyloid plaque seen in the brains of Alzheimer's patients is one example.

Cell Loss Some of the cells in our bodies cannot be replaced, or can only be replaced very slowly.

Cell Senescence This is a phenomenon where the cells are no longer able to divide. They may also do other things that they're not supposed to, like secreting proteins that could be harmful.

Extracellular Crosslinks: Cells are held together by special linking proteins. When too many cross-links form between cells in a tissue, the tissue can lose its elasticity and cause problems.

What happened was that I was gradually learning a lot of biology because my wife is a biologist. I was originally trained as a computer scientist, and I regarded aging as obviously undesirable but not my problem, that someone else would be working on it.

But the more biology I learned, the more I also learned about biologist and about the attitudes toward working on the biology of aging that biologists tended to have, and basically, I wasn't very impressed. I found that rather few biologists were interested in the problem at all, and I thought, "Well, that isn't very good,", so I thought I'd see what I could do.

Your background is in computer science. How does that qualify you to spearhead a project on aging?

My background is enormously beneficial. There are really very important differences between the type of creativity involved in being a basic scientist and being an engineer. It means that I'm able to think in very different ways and come up with approaches to things that are different from the way a basic scientist might think.

Could you give me an example of when your background has proven useful?

Well, I suppose that the whole SENS project is one big example. What I've done there is I've identified a set of things to fix, a set of aspects of aging that we have some respectable chance to repair, and I've realized that if we can do all of these things reasonably well, then we're done.

Basically, we'll have made the age related problems that we suffer from these days no longer an inevitable consequence of being alive. What I've done is basically factored out all the complicated details of how metabolism causes these things in the first place. It will be many decades before we understand the way cells and organs work well enough to be able to describe in detail the mechanism of how these problems actually occur.

But my way of thinking is that we don't need to know the details of how they happen. So long as we know what these things are that do happen, we can figure out ways to fix them. This is counter to the ways that scientists think, because scientists are interested in knowledge for its own sake, whereas I'm interested in knowledge as a means to an end.

Could you give me a timeline for how you envision your project succeeding?

The first part of the project is to get really impressive results in mice. The reason that's important is because mice are sufficiently furry and people can identify with them. If we get really impressive results in mice, then people will believe that it's possible to do it in humans, whereas if you double the lifespan of a fruit fly, people aren't going to be terribly interested.

Now, what I want to do in mice is not only develop interventions which extend their healthy lifespan by a substantial amount, but moreover, to do so when the mouse is already in middle age. This is very important, because if you do things to the mouse's genes before the mouse is even conceived, then people who are alive can't really identify with that.

I reckon it will be about 10 years before we can achieve the degree of life extension with late onset interventions that will be necessary to prove to society's satisfaction that this is feasible. It could be longer, but I think that so long as the funding is there, then it should be about 10 years.

Step two will involve translating that technology to humans. And because that's further in the future, it's much more speculative about how long that's going to take. But I think we have a fifty-fifty chance of doing it within about 15 years from the point where we get results with the mice. So 25 years from now.

What do you think about the idea that with so much life at stake, people would be less willing to take risks?

I used to be more pessimistic about this than I am now. Five or six years ago I wrote a book in which I predicted that driving would be outlawed because it would be too dangerous to other people, but now I think that what's actually going to happen is that we'll just throw money at the problem. Rather than simply avoiding activities that are risky, we'll make them less risky through technology. For example, it's perfectly possible already to build cars that are much safer than those which most people currently drive, and it's also possible to build cars that are safer for pedestrians--with auto sensors and auto braking to stop from hitting a kid running out in the road and things like that.

It's just a matter of priorities. When there isn't that many years of life to lose, the priority isn't there to spend the money. It's all a matter of weighing out the probabilities.

Once the technology is available, nearly everyone is going to want it. Of course, there's going to be a minority of people who think it's better to live more naturally in some way or other. We have parallels like that in society today, like the Amish for example.

Some would say that death is a part of life. What would be your response to those people?

Death will still be a part of life when we haven't got aging anymore. If you mean that some people would say that aging is a part of life--well, that's certainly true, but a couple hundred years ago tuberculosis was a part of life, and we didn't have much hesitation in making that no longer a part of life when we found out how.

What do you say to critics who think that this money could be better spent towards curing diseases like cancer?

This is a very important point. Because we're going be in a situation where we can extend lifespans indefinitely, this argument doesn't work. If it were a case of simply having a prospect of extending our healthy lives by 20 or 30 years, then one could legitimately argue that this would be money more ethically spent on extending the lifespan of people who have a below average lifespan. But when we're talking about extending lifespans indefinitely, I don't think that really works. The other thing to bear in mind, is that it's not an either or thing. The reasons why people in Africa for example, have a low life expectancy is not just because of medical care, but also because of political problems.

What kind of life will the immortal or nearly-immortal lead? Will they have to be on a special diet, or have constant organ transplants?

Like any technology, when it first starts off, it will be a bit shaky, a bit risky, it will be very laborious and expensive and so on, but there will be enormous market pressures that will result in progressive refinement and improvement to the technology so that it not only becomes more effective, it becomes more convenient and so on. This will be an example of that.

In a very general sort of sense, one could probably think in terms of having to go in for a refresh every 10 years or so. Exactly what would be involved in that will change over the years. It might start off as lets say a month in the hospital, and 10 years down the road, that will turn into a day in the hospital.

A good parallel is vaccines. For example, when we take a holiday in Africa or Southeast Asia or whatever, we get a shot to make sure that we don't get malaria. And that's all we have to do, and when we get there we can eat Mc Donald's as much as one likes.

So you think it'll one day be as easy as getting a vaccine?

Yes, that's right. A lot of these things, even in the early stages will amount to vaccines and drugs. Though of course, there will also be a lot of gene therapy and stem cell therapy and much more high tech stuff.

Why did you establish both an institute and a prize?

I think it's very important to have this two-prong approach. The idea here is that we don't really know what's going to work, but we have a fair idea of approaches that have a good probability of working.

If you look at past technological achievements, some of them succeeded by just throwing serious effort and serious resources at the problem, and people were pretty sure of what they had to do to make the thing work. The Manhattan Project is a fine example of that. Everyone basically knew how to build the atomic bomb, it was just a question of working out the kinks.

Then we've got things where there were loads of different possibilities about how the thing might be done, and it was important to motivate people and give incentives. For example, when Lindbergh flew across the Atlantic, that won a prize. And when someone invented a chronometer that worked properly at sea, that won a prize. Things like that. That was where you wanted to give incentives for people to follow their hunches, because it wasn't very clear which approach was going to work.

I think that when we're talking about life extension, we're sort of halfway between these two situations. We have a bunch of ideas which one can make a good case that it's going to work, but we also want to hedge our bets, and let people follow their hunches as well.

Of your seven SENS targets, which do you consider to be the most important?

It's not possible to say. I don't think we will be able to achieve more than a relatively modest amount of life extension, if any, until we can get at least five or so of these things working, and we might need to do all seven before we get more than a decade of life extension.

Why do you personally want to live forever?

It's not really a matter of living forever, it's just a matter of not wanting to die. One doesn't live forever all in one go, one lives forever one year at a time. It's just a case of "Well, life seems to be fun, and I don't see any prospect of it ceasing to be fun unless I get frail and miserable and start declining." So if I can avoid declining, I'll stay with it really.

What would you do if you could live substantially longer?

They say variety is the spice of life, so I don't think I would do the same things every day. I'd like to be able to spend more time reading, and listen to music, and all that sort of thing, things that I never get to do at all at the moment.

You think this project is going to succeed in your lifetime?

I think it's got a respectable chance. I'm definitely not relying on it. My main motivation comes from the thought of how many lives will be saved.

Your strategy would involve not only preventing aging, but reversing it as well. Does that mean people will get to choose what age they want to remain?

Absolutely. So the idea is that we wouldn't be eliminating aging from the body. It'll be a case of going in periodically and having the accumulated damage repaired. So exactly what biological age you actually have at any point is really just a question of how often you go in for rejuvenations and how thorough they are.

So the more treatments you undergo, the younger you can be?

That's right. I think it's reasonable to suppose that one could oscillate between being biologically 20 and biologically 25 indefinitely.

Related Stories

Those who have lived the longest in modern times, in years and days, according to estimates in some cases:

Name

Years

Days

Jeanne Calment

122

164

Shigechiyo Izumi

120

237

Sarah DeRemer (Clark) Knauss

119

97

Lucy (Terrell) Hannah

117

248

Marie Louse Febronie (Chasse) Meilleur

117

230

SOURCE: Louis Epstein, recordholders.org, based on Guinness Book of World Records and other sources

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Hang in There: The 25-Year Wait for Immortality

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