This interesting and well remarked Scientific American article ‘The Delusion of Infinite Economic Growth‘ reminds us that there are physical limits to growth, whatever more “sustainable” technologies are implemented. Any technology that scales find its physical limits.
“Every stage of the life cycle of any manufactured product exacts environmental costs: habitat destruction, biodiversity loss and pollution (including carbon emissions) from extraction of raw materials, manufacturing / construction, through to disposal. Thus, it is the increasing global material footprint that is fundamentally the reason for the twin climate and ecological crises.”
While “Technological innovation and efficiency improvements are often cited as pathways to decouple growth in material use from economic growth. While technology undoubtedly has a crucial role to play in the transition to a sustainable world, it is constrained by fundamental physical principles and pragmatic economic considerations.”
In addition, economic growth is exponential and not linear: “unfortunately, the situation is even more dire. Economic growth is required to be exponential; that is, the size of the economy must double in a fixed period.” Thus, “the inescapable inference is that it is essentially impossible to decouple material use from economic growth.” As a result, more is required today than to develop ‘sustainable’ solutions: solutions to the future raw material crises also need to be investigated.
Even sustainable growth will find its limits – as the economy and technologies scale, they require increasingly raw material and space, often in an exponential manner. But the world is finite, therefore a change of paradigm may be required.
This excellent article in The Atlantic ‘Why the Energy Transition Will Be So Complicated‘ provides an important reminder and insight into how dependent we are on carbonated fuel, and how tough it will be to change: “The degree to which the world depends on oil and gas is not well understood“.
The article underlines how much we are dependent on oil&gas for a variety of materials in addition to energy, and how pervasive usage of oil can be in our societies. As a result, some warn “that going into overdrive on transitioning away from fossil fuels would lead to major economic shocks similar to the oil crises that rocked the global economy in the 1970s. “Policymakers,” [Jean Pisani-Ferry] wrote, “should get ready for tough choices.”“
“The term energy transition somehow sounds like it is a well-lubricated slide from one reality to another. In fact, it will be far more complex: Throughout history, energy transitions have been difficult, and this one is even more challenging than any previous shift.” In addition, it is supposed to happen much quicker than any other such transitions in the past, necessarily impacting the value of assets and making investment into anything related to energy more hazardous. Previously such energy transitions typically took more than a century to be established and to replace previous energy sources.
I am personally convinced that oil & gas will remain an important industry in the next 2 decades, while coal may start to whither. The solution may lie more in carbon capture than cutting too fact our dependency on oil & gas.
The current energy transition will be more challenging and complex that usually anticipated, in particular because it is supposed to be much quicker than any such historical transition. Let’s not forget this in our anticipations.
This interesting article ‘AI is now learning to evolve like earthly lifeforms‘ provides some insight about advances in AI algorithm development. Researches are trying to find the most effective way for algorithms to go through the process of natural evolution. And this provides interesting learning about our natural world.
The interest of this research is of course also to enlighten our understand of the principles of natural evolution, and how to keep its cost low (as it requires many trials for very few successful variants). “In their new work, the researchers at Stanford aim to bring AI research a step closer to the real evolutionary process while keeping the costs as low as possible. “Our goal is to elucidate some principles governing relations between environmental complexity, evolved morphology, and the learnability of intelligent control,” they write in their paper.“
It involves the simulation of robotic agents in an environment, with some evolution algorithm for the AI algorithm driving the creatures.
Interesting results include: “validating the hypothesis that more complex environments will give rise to more intelligent agents“, and “in line with another hypothesis by DeepMind researchers that a complex environment, a suitable reward structure, and reinforcement learning can eventually lead to the emergence of all kinds of intelligent behaviors.”
Teaching AI algorithms how to evolve provides interesting insights. The fact that more complex environments will give rise to more intelligent agents is definitely a key insight into life’s evolution.
“While many AI and machine learning deployments fail, in most cases, it’s less of a problem with the actual technology and more about the environment around it,” says Harish Doddi, CEO of Datatron. Moving to AI “requires the right skills, resources,?and?systems.“
“While it’s arguably true that AI can add significant value to practically any department across any business, one of the biggest mistakes a business can make is to implement AI for the sake of implementing AI, without a clear understanding of the business value they hope to achieve“. In particular, understanding how data biases or poor data hygiene can affect AI algorithms, understanding those effects and how they influence performance appear to be an essential capability.
In addition, the organization processes and particularly the data production, gathering and structuring appears to be an essential area for review and upgrade when implementing AI-based tools.
Like any new powerful tool, AI has transformational impact on organizations and the way their data is gathered and managed. This should not be overseen when implementing those new capabilities.
This has been observed for a decade now in particular regarding the expression of certain genes, and in general epigenetic changes, which can be transmitted although they don’t change the overall DNA codes. Those changes are deeper when stress is stronger and more repeated. There is now proof that these can be transmitted to children, but also that they can in a certain manner be reversible, as proven by certain studies on post-traumatic stress disorder and the actual impact of psychotherapy.
In the field of chamanism and trance, it is considered known that people can bear within themselves the consequences of acute stress suffered by one’s ascendants and some ceremonies are designed to manage this situation.
DNA expression modification linked to one’s environment is all quite a new investigative domain with interesting consequences on the eternal topic of determination and choice. Expect more to be understood and written on that topic in the next years!
In this excellent post ‘New problems, old problems‘, Seth Godin distinguishes how we should approach known problems and new problems.: “a new problem doesn’t need fresh thinking, it needs clear awareness.”
Seth Godin underlines that most of the issues we face are known, or similar to issues we have already addressed. They don’t require much creativity. Except if we have to find another solution to solve a problem we could not overcome, or a problem which we have never seen. In that case, proper situation awareness is needed to ask the right questions and take the right actions. “We can begin by acknowledging we have a problem, identifying the constraints, the boundaries and the assets involved. And then we can go to work to solve it.”
Known problems can be addressed with known solutions. Resisting or new problems require creativity, and this starts with awareness.
Bent Flyvbjerg is a Danish university professor that has been studying public infrastructure projects for a long time and is now professor at Oxford. He has written numerous articles showing that public infrastructure projects always have their cost underestimated and their benefits overestimated at investment decision, mainly for political reasons.
Anyway in this article, he explains the benefits of having smaller projects that also benefit from some series effect learning curve rather than going for very large, very long and one-of-a-kind projects that are necessarily going to suffer overruns and generate disappointments. “Two factors play a critical role in determining whether an organization will meet with success or failure: replicable modularity in design and speed in iteration. If a project can be delivered fast and in a modular manner, enabling experimentation and learning along the way, it is likely to succeed. If it is undertaken on a massive scale with one-off, highly integrated components, it is likely to be troubled or fail.”
Bent Flyvbjerg continues by explaining why speed is essential for megaprojects, because of our inability to predict the future beyond a few months or years. Iteration is also essential to improve, while picking existing and proven technology is also a major success factor.
There is a definite trend towards smaller infrastructure including series effect. Still, all projects cannot be made in a short time and using only proven technology. However, those are projects where we should accept a measure of cost and schedule overrun; most infrastructure projects can certainly be done using proven technology and on a smaller scale. The question of keeping consistency of a programme combining several smaller, shorter projects is also a challenge.
Still, to tackle excessive cost and delays of large infrastructure projects, splitting large projects into smaller, shorter projects using proven technology is certainly a way to go.
This VOX article poses a great question ‘Why does it cost so much to build things in America?‘ in the context of infrastructure and mass transit construction. This can be generalized probably to all developed countries, with some differences: why has it become (relatively) so expensive to build infrastructure in those countries?
“Research by New York Federal Reserve Bank and Brown University researchers reveals that the cost to construct a “lane mile of interstate increased five-fold” between 1990 and 2008. New construction — widening and building interchanges and building new sections of road altogether — is where the bulk of the problem lies“
Reasons mentioned beyond the density of those locations where infrastructure are being built include institutional reasons (in particular, more power given to opposing groups leading to complaints and lawsuits). The article also mentions the lack of experience of government agencies and construction companies due to the lack of construction in the last decades. I personally suspect also financing mechanisms – long projects like infrastructure will get heavily burdened by financial costs if the government does not step in for part of the financing.
In any case, it is certainly the accumulation of layers of requirements in developed countries that lead to substantial delays and even more substantial increase in cost for transportation and other infrastructure building. This is a concern for our societies that need to be overcome if we want to remain competitive.
This Guardian article ‘I’m a life coach, you’re a life coach: the rise of an unregulated industry‘ explains very well the inherent contradictions of the status of life coach. It is completely unregulated and dominated by a number of well-known figures of sometimes questionable reputation (as exposed in the article). It also obviously responds to a societal need, but isn’t it dangerous to let people getting influenced by unqualified professionals?
Trainings and certifications are diverse in quality and seriousness. The number of candidates to become life coach increases dramatically with each major crisis. In my experience, many do explore this career out of a personal need first, before looking at it as a way to change others for the better. In reality, many life coaches do have a less-than-ideal personal life and happiness, although they try to project a well-balanced impression.
There are drawbacks to a too severe professional certification scheme. It creates institutions that decide what is right from wrong. It can lead to situations where innovative or radical approaches will be rejected while they can be useful. Thus it is not necessarily the best solution in all cases.
At the same time when it comes to mental health, is it reasonable to add a layer of simili-professionalism to general advice on how to feel better? Having a coach implies some seriousness in the commitments taken, but one of the most important functions of a coach is to determine when people need more professional psychological help. It is unsure that all life coach trainings include that element so clearly.
I am definitely in favor of some self-regulation of the life coach industry. The ICF (International Coach Federation) is quite a good and demanding scheme that leaves some leeway in the coaching practices. Similar certifications should be requested from your coaches.
I tend to believe that exploiting cluster behavior of relatively simple robots is probably one of the most innovative applications of robotics and that it will transform approaches focusing today on large machines. Progress of research in this field is also essential to understand the behavior of natural clusters of birds and other animals.
“Particle robots can form into many configurations and fluidly navigate around obstacles and squeeze through tight gaps. Notably, none of the particles directly communicate with or rely on one another to function, so particles can be added or subtracted without any impact on the group. In their paper, the researchers show particle robotic systems can complete tasks even when many units malfunction.”
The best feature of clusters is certainly resilience to the loss or destruction of one component while still be able to continue the mission. In civilian and military applications, clusters will certainly develop to address dangerous situations where resilience is paramount.
Robot clusters will certainly be a common feature in a decade from now, and it is essential to keep up with this interesting development.
In this post ‘Becoming Nimble at Dealing with Ever-Changing Plans‘, Leo Babauta expands on our difficulties to adjust in a world changing increasingly quickly. The ability to be nimble is an essential competency today (and I am still personally working on it!)
He shares some principles to reflect upon:
Every change is a training
Use changes to stay present
Learn to relax with uncertainty
Practice flowing with changes
You can find focus in chaos, with practice
Structure is very helpful, but don’t be attached
Finding joy in the middle of the storm
Developing this competency is certainly essential in an accelerating world where plans change. The Covid situation has added another layer or unpredictability in particular when it comes to travel or work plans. Let’s get better at it!
The 5 principles defended by Elon Musk are the following:
Make the requirement less dumb
Try to delete part of the process and of the design
Simplify or optimize (and don’t optimize something that should not exist in the first place!)
Accelerate cycle time (but not before you have sorted out the 3 first principles)
Automate the design process to move more quickly through the design cycles.
Those principles seem founded quite in common sense, although of course they are very hard to implement as experience shows. In my world of large industrial projects it is a constant battle to try to simplify requirements developed over decades and comprising of layers of knowledge and experience. No surprise that a newcomer like SpaceX can do better without the institutional history.
What I find particularly interesting is the fact that Elon Musk recognizes that automation as a way to accelerate iteration today needs to be an intrinsic part of engineering approaches.
Digitalization provides new possibilities and we definitely need to re-interrogate the traditional engineering processes to take advantage of the new capabilities made available, simplify and produce more straightforward designs.