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Longevity

Can You Live Forever? Part 2: How To Escape Ageing

Posted on 24 November 2021

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In the previous article, we defined longevity escape velocity (LEV), discussed the principal of exponential growth, and why it means that technologies enabling us to reach LEV could come to fruition much sooner than we expect. Now, let’s talk about what those technologies might be – what are the most likely paths to LEV within the next century? Due to the nature of exponential growth and the paradigm shifts brought about by novel technologies, it’s difficult to predict where human technology will be in even 10 years time, let alone the end of the century. However, we can still make broad predictions about how LEV might be achieved.

The Biological Approach

The first way in which we might reach longevity escape velocity is through improved understanding of the biology of ageing. Let’s consider the prevailing theory of ageing – that ageing is caused by the accumulation of damage in various forms, and that this damage eventually manifests as disease and disability. If this is the case, then there are three basic ways in which we could attempt to interfere with the ageing process.

We could attempt to prevent the age-related damage from occurring in the first place. This approach is unlikely to be successful, because the things that cause most of the damage (like by-products of natural chemical reactions in our bodies) are either linked to processes that are essential to life, too complicated to stop (at least without freezing or suspended animation) or unavoidable without going to extreme and impractical lengths.

We could instead attempt to treat ageing – that is to say, we could attempt to cure every age-related disease before it has a chance to kill you. This has been and continues to be our main approach to extending human lifespan, and it is a poor one. Ageing manifests as many interlinked chronic diseases (cardiovascular disease and cancer being the most deadly), and it has proven to be a great struggle to cure even one of these conditions, let alone all of them. Even if we were successful with this approach, the results would be far from ideal, as we would not have addressed the underlying damage, and so diseases would simply reoccur with ever increasing frequency as we grow older.

Our current approach to treating age-related disease has been described as ‘whack-a-mole’ therapeutics.
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Our best bet may instead be to identify the damage responsible for ageing at the molecular scale, and find ways to reverse it until it can be maintained at an acceptably low level. This way, we would not need to understand all of the complex processes that are driving the damage, and we would not need to cure age-related diseases very often. We would not have prevented ageing any more than bailing water out of a holed boat prevents more water from leaking in, but we will have bought more time before the boat sinks. During this time, we can develop more and more effective ways of removing the water, until eventually, we are removing the water at the same rate as it enters the boat.

The Life Extension Revolution — Part 1 | Hacker Noon
A proposed model of how the ageing process works and how we might tackle it.
Processes that are an inevitable part of living (such as the body’s metabolism) generate life-long damage. Gerontology cannot fully prevent this damage because it arises from processes that are essential to life. This damage then causes pathology (disease), which is too complicated for geriatrics to fully reverse. We therefore need to target the damage and maintain it at a sufficiently low level that it doesn’t cause pathology.
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In order for this approach to work, we would need to boil ageing down to as small a number of targetable biological processes as possible. This is the thinking behind the ‘hallmarks of ageing’ categorisation. The hallmarks of ageing theory proposes that all age-related disease is ultimately driven by a combination of 9 fundamental biological processes – things like damage to our genetic code, shortening of our telomeres and the death of our stem cells. For an in-depth explanation of what these processes are and how they might be treated, check out the Hallmarks of Ageing series. The hope is that, by focussing on these hallmarks instead of waiting until they manifest as cancer, dementia or your deadly disease of choice, we will be able to delay the occurrence of all age related diseases with just a handful of therapies. This does rely on some bold assumptions – for example, that the hallmarks of ageing are responsible for all aspects of the ageing process, which is not confirmed at present. However, it is probably our best hope currently when it comes to reaching LEV through biological means.

The Hallmarks of Aging: Cell
The proposed hallmarks of ageing.
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Many strategies for targeting these hallmarks are under investigation, though it’s too early to say which, if any, will succeed in extending human lifespan. Breakthroughs in machine learning for personalised medicine, gene therapy and later on, nanotechnology, may prove to be key players in our approach to reversing age-related damage, but even with recent advances, the near-future application of these technologies is uncertain.

The Artificial Approach

An alternative to reversing biological ageing is to replace biology with technology and go fully artificial. This would require us to transfer our consciousnesses to a more resilient machine form, whether by replacing the neurons in our brains with artificial ones or by ‘uploading’ ourselves to a data centre somewhere. This might seem like an impossibly futuristic prospect, but remember that technology grows exponentially. 20 years ago, offices around the world still stored documents primarily in paper form. Today, you can ask an AI in your pocket to phone a restaurant and make a reservation for you. Where will AI be in another 20 years’ time? If we can design artificial intelligences that equal or surpass human intelligence, then the idea of building a machine that can house a human intelligence would seem a lot more realistic, though there are obviously still some huge problems that would need to be overcome.

Unlike the biological approach, this method doesn’t achieve LEV by lengthening our lifespans more and more rapidly until we escape the gravity well of ageing. Rather, we simply move human consciousness to a substrate that is more resilient. We could then live on in a new cloned body, or in an artificial one, or become an entirely virtual entity. Digital immortality is arguably a preferable alternative to biological immortality, because it offers unique benefits, foremost among them being the opportunity to greatly expand human intelligence and the ability to instantly learn new information. This might even be a necessary step in our evolution for humans to remain relevant. Thanks to artificial neural networks, AI can now perform tasks that were previously thought accessible only to humans – but can do so millions of times faster. A world in which AIs are more intelligent than humans could be a scary place, though not necessarily in the ‘machines take over the world’ sense. If all our problems are solved and all our decisions are made for us by AIs, then humanity is no longer steering the boat – we are at the mercy of where our AIs take us, without the intelligence needed to understand their decisions. To avoid this scenario, we will need to enhance our own minds in order to keep pace.

If you can’t beat the AI, become the AI.
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There is a rather problematic roadblock when it comes to this approach: we don’t really understand how the human brain works. The brain doesn’t function like a computer – it’s an unfathomably complex network composed of 86 billion interconnected neurons. These neurons communicate through signals which combine analogue and digital elements – a neuron either fires or it doesn’t, but it’s propensity to fire can be modulated by the combined chemical signals from many other neurons, as well as from outside of the brain. Changes at the molecular level, such as the number of receptors on the surface of a cell or the rate at which neurotransmitters are transported to the synapse, are relevant to how our brains function. The power of a neuronal network as dense and complex as that of the brain is not speed of computation – computers already far outstrip us in that regard. Rather, it is the brain’s ability to rapidly make judgements or predictions by bringing together a wide range of contextual information and past experience, and to constantly adapt to new information. This is why CAPTCHA tests are still effective in protecting websites against botting attacks.

We remember what a conventional traffic light looks like, and could identify one from any angle. Even when we cannot see the lights themselves, we know that those objects hanging above the road are traffic lights and not giant Lego bricks, because we understand that we are looking at an intersection where we would expect traffic lights to be located. If the traffic lights had a radically different design, we would probably still recognise them as traffic lights. If we saw a painting of some traffic lights next to the road, we would not mistake them for real traffic lights. Building AI with this kind of ‘general intelligence’ is a huge challenge.

Artificial neural networks emulate the brain architecture in a limited capacity with interconnected transistor “neurons”. They ‘learn’ to perform a task by attempting it millions of times. Correct answers strengthen the connections used to derive those answers, thereby forming neural pathways not dissimilar from those in the brain. A more extreme strategy is to emulate the whole brain in a computer simulation. This could in theory be accurate to the molecular level, allowing every detail of brain function to be preserved. To do this, we will need to image the brain’s connections at greater resolution. This won’t automatically grant us a concrete understanding of how the brain works, but we don’t necessarily need to understand how something works in order to emulate it. After all, we don’t fully understand what occurs within artificial neural networks either. Regardless of the approach used, achieving human levels of intelligence would require a significant (though probably achievable this century) level of computing power. Matching the intelligence of the human brain has been estimated to require between one petaFLOP (1015 FLOP) and one zetaFLOP (1021 FLOP) per second of computing power. For reference, the world’s fastest supercomputer as of November 2020, the Fugaku supercomputer, achieved a speed of one exaFLOP (1018 FLOP) per second. Of course, as we have already said, speed alone is not enough – if it was, we would already have AI with intelligence approaching or equal to our own. The AI must be able to draw upon a vast array of neural architecture akin to what is found in the brain.

Simply making an exact replica of a human brain wouldn’t transfer someone’s consciousness from a biological to a machine form – you’d just end up with two identical intelligences, one of which would still age. On the other hand, most of the cells in our bodies and most of the molecules that make up our neurons have been replaced multiple times over the course of our lives, yet we have the illusion of being one continuous being. We could probably maintain this illusion by converting the brain to a digital form gradually over an extended period. In all likelihood, this still wouldn’t be enough, because we humans are more than just our brains. An argument can be made that interaction between our brains, the organ systems throughout our bodies, our environment, and even the bacteria in our gut are all part of our identity. So while digital immortality might might be a preferred approach, and is probably the path our species will take eventually, there are still many uncertainties over if and how it will happen.


Humans Won't Be Able to Control Artificial Intelligence, Scientists Warn
He’s coming to take your job, your independence, and maybe your life.
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Whether longevity escape velocity is achieved through biological means, artificial means, or a combination of both, the future is going to look very, very different from the current state of humanity. Do we need to proceed with caution? What effect will a massive increase in lifespan have on society? In the next article, I will discuss some of the potential pitfalls associated with longevity escape and whether we should be concerned.


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