Technology Catalysts

In part, the phrase ‘technology evolution’ is being used as an extrapolation of current technology developments along a path towards some possible science-future, which might be separated from science-fiction. So, while this initial outline of a technology-evolution has to be seen as speculative, it will try to put some limits on inference, i.e. what we do not know must be like what we already know, at least, in the short to medium term.

Note: The idea that ‘what we do not know must be like what we already know’ is an axiom of William Clifford’s essay entitled ‘The Ethics of Belief (1877)’ and used to define the ‘limits of inference’. While this axiom has often been used as a general guiding principle, in the context of a technological evolution, we might need to question its unqualified use. For when the rate of change is exponential, as in the case of computer processing, the outcome may be nothing like what we might have previously anticipated. If we estimate the effects of Moore’s law of doubling processing power every 18 months over the last 50 years, then processing power would have increased by a factor of 4 billion. Such change has led to innovations that few could have predicted back in 1965, let alone back in 1877, when Clifford wrote his essay.

The previous diagram is only intended as a general framework in which just 6 key areas of technological evolution might be considered, i.e. energy, AI, robotics, genetics, nanotechnology and space. While limited in scope for practical reasons, it is believed the future evolution of these technologies may have a profound impact on virtually all facets of the human ecosystem, where some of the implications and applications are characterized along the bottom. While there are other areas of technology that might be considered, it is believed that the six selected may provide a reasonable overview of some of the future potential developments, which will also affect other aspects of the human ecosystem.

So what is the justification for prioritising energy?

Today, energy has come to underpin the modern world, therefore innovations in energy technology will be critical to the maintenance of future social, political and economic stability. However, while energy is highlighted as a critical area of technology, it may be more difficult to predict the rate of adoption of new energy sources and the means of energy storage that will have many geopolitical and economic implications, which may be contested and resisted. For in many areas of the world, fossil fuels may remain a viable and preferred source of energy for many decades to come, irrespective of the costs to human health and climate change. As such, changes to the current energy model will have to be considered in the wider perspective of the human ecosystem as a whole, especially in economic terms. This said, it is highly probable that technology developments in solar generation and energy storage will contribute to disruptive change over the next 10-20 years. For example, the uptake of electric cars, possibly powered by a new generation of super-capacitor storage devices, may be just a few of the associated developments contributing to disruptive change.

Note: For much of humanity’s million-year history, its population existed on a knife-edge in that only a few extra deaths, rather than births per year could have resulted in extinction. Two thousand years ago, the global population had increased to 200 million, by the start of the industrial revolution in 1750, it had increased towards 700 million and over the next 250 years, the global population grew to exceed 6,000 million. Within the last 18 years, the global population has increased to 7.4 billion and expected to rise to 9.7 billion before 2050.

While the increases in the note above reflect exponential growth, the table below provides a linear approximation in terms of the increase per year. However, what we may need to realise is that most problems may be related to the impact of population growth on the ecosystem.

Year Years Population Population
Increase
Increase
per year
0 n/a 200,000,000 n/a n/a
1750 1750 700,000,000 500,000,000 285,714
2000 250 6,000,000,000 5,300,000,000 21,200,000
2018 18 7,400,000,000 1,400,000,000 77,777,778
2050 32 9,700,000,000 2,300,000,000 71,875,000

While energy has been a key catalyst of change over the last 250 years, it is probable that AI will become the primary catalyst of change in the immediate future and beyond. For if we assume that the process by which knowledge can be expanded and utilized is critical to any ongoing technological evolution, then it seems reasonable to assume that AI must play an important role in this process. The development of evermore cognitive AI systems will undoubtedly have a complimentary impact on the development of more autonomous robotic systems, which will then become increasingly pervasive throughout the human ecosystem. However, the biggest and immediate impact on the human ecosystem may well be in terms of jobs, where AI expert and robotic systems may increasingly become capable of doing, not only manual blue-collar jobs, but professional white-collar jobs.

Note: In many respects, the technical innovation of the last 50 years has been built on Moore’s law , which initially predicted a doubling of transistor density every 18 months that may have resulted in a scaling factor close to 4 billion. However, many are now predicting that Moore’s law is slowing and will possibly come to an end by 2025, although this somewhat pessimistic prediction is based on the limits of a chip architecture simply reducing in size rather than fundamentally changing in concept. Therefore, it may be possible that a different approach to processor architecture could maintain Moore’s law, or some close approximation, into the future. If so, it might be reasonable to project a revision of Moore’s law, doubling every 3 years rather than every 18 months, but which over 100 years would still equate to a further scaling factor of 4 billion. Of course, over this timeframe processor architecture may evolve in many different ways, e.g. distributed, parallel, multicore, micro-cooled, neural nets, and many others that have not yet even been considered.

In part, energy and AI may also facilitate many other key areas of research, such as genetics, which was ‘catapulted’ into the headlines in 2003, when the human genome was completed ahead of schedule mainly thanks to computer power. In the future, the field of genetics may also be further supported by complementary developments in bio-engineering and nanotechnology, although each field may have expansive scope in different directions. We might initially perceive the scope of genetics in terms of an increasing ability to both understand and manipulate the DNA genome of any specie ranging from bacteria to humanity. However, this ability will undoubtedly be helped by future developments within bio-engineering and nanotechnology. As a broad generalisation, the scope of bioengineering may include any aspect of engineering that facilitates a better understanding of biological processes and/or ability to augment them, e.g. brain scanners through to prosthetics. We might also see the complimentary nature of nanotechnology to genetics and bio-engineering, if it extends the ability to manipulate structures at an atomic or molecular level, which then helps to create new materials and manufacturing processes across the breadth of our ‘brave new world’ of technology evolution.

Note: In terms of the human ecosystem, social, political and economic components may all have very different opinions and priorities regarding the permissible ‘evolution’ in the field of genetics. For there may be considerable social resistance to any perceived manipulation of the ‘natural’ order of life, especially if viewed from a religious perspective. Of course, political and economic considerations may override such concerns in the face of more pragmatic pressures in the form of geopolitical and commercial competition, which might destabilise economic growth. There is also the real possibility that genetically modified crops and livestock might become an increasing necessity in order to help feed a growing global population in a world subject to climate change, irrespective of the cause.

When viewed in conjunction with concurrent developments in AI and robotics, it might also be realised that the sum total of all this potential change could also drive the future evolution of sentient, intelligent life in many unexpected directions. Of course, such profound change may well further destabilise the human ecosystem in some future world. Therefore, at this stage, these potential technology developments should only be seen as ‘possible’ changes within the human ecosystem as a result of a handful of technology innovations. However, while technology may well be a fundamental catalyst of potential change; powerful social, political and economic institutions may still prioritize the direction and adoption of acceptable change. In this wider context, the human ecosystem will include many considerations related to the usage and distribution of natural resources, especially when it comes to those essential to human life, i.e. food and water. For example, while some may see the exploration of space purely as one of scientific interest, it may ultimately come to have more practical motivations. First as an alternative source of vital resources required by new technical developments. Second, as a backup plan for human habitation, which might be linked to the wider implications of climate change here on Earth should it ever come to threaten the quality of human life. However, the impact of climate change also needs to be evaluated in terms of the wider social, political and economic costs to different nation-states around the world.

Note: As outlined, we might reasonably predict that technology will provide new innovative solutions to the current energy model, which might then help to revolutionize today’s transport systems, especially if augmented by AI autonomous control systems. However, whether such developments can simply be extrapolated into shipping and air transport systems may prove to be a more difficult longer-term problem. Likewise, the idea of a wider exploration of space may require further consideration of a number of different problem areas, e.g. lift-off into orbit followed by more effective propulsion systems and finally onboard human habitation, if required. The last caveat on human habitation is highlighted in that AI-robotic systems may well advance to a point that autonomous missions into space, especially for mining purposes, may only be cost-effective if undertaken by a ‘crew’ that requires no special and expensive life-support system.

At this point, we might initially accept that technology has helped improved our lives beyond any reasonable expectations of earlier generations. This said, the benefits of most technologies have also had unexpected consequences that have not always been beneficial to all. However, as a broad prediction, we might reasonably assume that future technology will continue to ‘evolve’ to a point that it might provide the means for humanity to solve all its pressing problems, although this optimistic outcome possibly requires a lot more consideration.