Independence and autonomy might seem quite similar but there is a substantial difference: autonomy does not preclude asking for support and help, while independence does.
Before proceeding further, let’s note that we apply those terms here in the personal sense and not in the diplomatic sense.
This distinction between the two concepts is essential because it shows that being independent is far more limiting than being autonomous. Autonomy implies being able to take one own’s decisions but at the same draw on help and support from others to reach one’s goals.
This is why we should strive personally for autonomy, not independence.
Democracy is the political regime best adapted to complexity. The reason is that it allows bifurcations to happen at every election, i.e. depending on the country every 4 to 7 years. Those changes can be unexpected and worrying, but they happen more frequently and -one hopes- less abruptly than in other political regimes.
Elections are always creating surprises in particular in troubled times, and this has been demonstrated heavily in 2016 where in several western countries there has been a reaction against the establishment and from people who feel left aside from the world’s transformation (Brexit, Trump election).
It is a good property of a system setup to manage a complex world to be able to implement those important changes with this frequency.
Other political regimes will in fact only allow such changes much less frequently and therefore, they will be more abrupt and can even degenerate into civil wars.
We concur heavily with Churchill saying that “democracy is the worst form of government except all the others that have been tried“! And this conclusion on democracy should be kept in mind when we are not happy with election results.
Enhancing lessons learnt and redistributing them to the entire ecosystem is a cornerstone of safety enhancement. It is much facilitated in the case of Artificial Intelligence (AI) thanks to the remote update possibility, as demonstrated successfully by Tesla.
Implementing a statistical approach instead of a deterministic one. Some statistical risk analysis approaches are already available for years in the form of fault trees to determine the statistical probability of a feared accident. However this only works in environments where statistical failure data of components is available, and with limited changes to the environment and the system. New statistical approaches will have to be developed based on specific testing of the entire AI-related system. These approaches need to be developed theoretically and empirically and remain the major challenge of the years to come.
Rules governing operability of the system in case of component failure will have to be strictly defined and enforced (with how many sensors out of order is it safe to drive autonomously?), because the degraded situations are the most difficult and cumbersome to regulate.
The problem of the new statistical approaches to safety demonstration is an exciting problem facing all regulators. I am looking for some science behind this, if any reader has useful links please share!
Our current approaches to the regulation of system risk management and prevention of deadly accidents remains very much deterministic. In the most critical applications such as in nuclear power plants or aircraft controls, regulatory authorities require a deterministic demonstration of the links between input and outputs. Superfluous code that is not used needs to be removed, just in case. Older processors are used which reactions are fully known.
With the advances of Artificial Intelligence, this won’t be possible any more. In particular because the devices become black boxes that have learned to behave in a certain manner most of the time when exposed to certain stimulus. However deterministic proof of the relationship between input and output is impossible and we don’t quite know how it really works inside. It can only be a statistical measure.
This situation is an extensive challenge for the regulatory authorities that will have to regulate safety-critical applications based on AI such as automatic driving. Most current regulatory approaches will become obsolete.
Some regulatory authorities have identified this challenge but most have not, although this will constitute a real revolution in regulation.
There are numerous definitions of leadership. Seen from the complexity view, a leader is someone that is able to create locally, more or less broadly, some alignment inside a complex organization.
In a complex system it is certainly difficult to create any sort of alignment. Contributors all have their own interest and are very inter-dependently linked and related to other contributors. However when one is able to create a dynamic movement and bring along the necessary contributors, astonishing things can happen. That’s probably what leadership in a complex world means.
This may be a new definition of leadership. At the same time I believe it is a useful approach to this issue. Seen from that perspective, a number of leadership practices become clearer and more founded in actual science.
As a leader, impress movement in complexity. It is will be even more powerful than what you believe.
Complex and chaotic systems can be described by mathematical equations that are in fact an extension and generalization of Quantum Mechanics equation. That’s what Ilya Prigogine (Nobel-price winner in 1977) explains in his excellent book “the laws of chaos” (apparently not available in English unfortunately).
We have argued numerous times that one of the precursors of the Fourth Revolution is the emergence of Quantum Mechanics, or at least the limits found to Newtonian Mechanics which founded the Industrial Age. The science of complexity and chaos is even newer. By finding that an extension and generalization of the maths of Quantum Mechanics is needed to describe it, we are indeed confirmed in our observation that it constitutes a further step towards the underlying paradigm of the Collaborative Age.
Complexity is still vastly misunderstood because it creates a rupture with the comfortable deterministic view of the world which we entertained during centuries. Its probabilistic nature, the fact that mere observation changes the observed world (like in Quantum Mechanics) makes it even more fascinating.
Welcome to the world beyond Quantum Mechanics and the Uncertainty Principle.
The premise is that the intrinsic complexity and sophistication of the empire or organization increases over time up to a point where additional complexity is detrimental, in particular in the face of sudden external change. The institution is then unable to cope with the change. “When societies fail to respond to reduced circumstances through orderly downsizing, it isn’t because they don’t want to, it’s because they can’t.”
I find this model intriguing because from my perspective, complexity rather increases reactivity and adaptation. I think the author mistaken complication and complexity. Adding layers of bureaucracy in a futile attempt at control is complication. Properly maintained complexity is rather an antidote at inflexibility. We should certainly fight organizational complication (and its representative, bureaucracy) but rather welcome complexity.
Research shows that we definitely have different ethical standpoints depending on the language we use. In particular it would seem we are more deliberate (rational) when using a foreign language. There are several explanations for this – the effort needed to operate in the foreign language, or the fact that our original language is related to so many emotions, which the foreign language is less.
Whatever the deep explanation, this creates significant issues when working internationally, for example when negotiating an agreement with someone in his native language. The fact that the foreign speaker will be more deliberate and less emotional is rarely considered.
While concentration of power is quite unavoidable in today’s complex world, we still can thrive in this world. Of course, those institutions that have the power and the wealth might not have the best intentions and we should not be too naive. But thanks to the newly available technology of the Fourth Revolution, there is an intrinsic counter-power to this situation.
anybody can publish to the world, for free (or close to it),
we can coordinate, re-group and communicate globally, for free (or close to it),
it is possible to start a business for a lot less money than before, and have instantaneously a global footprint,
we can travel anywhere for much cheaper than anytime before (compared to the average earning power).
The sheer size of those actors has also an interesting drawback, that can be increasingly observed: they don’t know what to do with their money. Share buy-backs are more and more widespread, a sure sign that those organizations don’t know what to invest their resources in. This is great news because it has probably never been easier to get money to fund new initiatives and ventures. And these resources will necessarily flow into much smaller setups, that are nimble enough to take advantage of the opportunities of today’s world.
One can also argue that these huge organizations are also struggling with controlling themselves and what they are actually doing.
Hence although this might be a problem on some aspects, I do not find the concentration of power we can observe to be a major impediment of taking initiative and developing new stuff, on the contrary.
Power and ownership get concentrated into a few hands. This is clearly shown in the TED talk of James B. Glattfelder: ‘Who controls the world?‘. In this 2012 talk, he shows by analyzing the ownership links between various global companies how a limited number of financial institutions control most of the economy.
This is not surprising and is the natural consequence of the evolution of the complex, increasingly inter-related economic system. We should not be surprised and still it is an issue from the governance and political perspective.
“It turns out that the 737 top shareholders have the potential to collectively control 80 percent of the Trans National Companies (TNCs)’ value. Now remember, we started out with 600,000 nodes, so these 737 top players make up a bit more than 0.1 percent. They’re mostly financial institutions in the U.S. and the U.K. And it gets even more extreme. There are 146 top players in the core, and they together have the potential to collectively control 40 percent of the TNCs’ value.”
This kind of studies produced the concept of “systemic” or “too big to fail” institutions. We may take regulatory measures to limit the phenomenon, but it is intrinsic to the increased complexity of the world. So my view is that we should rather learn how to deal with it.
Human behavior doesn’t always conform to what seems sensible to us, and that what seems sensible to us isn’t necessarily valuable in evaluating how a person thinks or acts.”
This makes any kind of judgment on people’s behavior difficult. As explained in the book in certain situations, suspension of judgment is required. That is the case for example during coaching, or during interviews to determine trustworthiness.
Establishing rituals is important for our effectiveness but it is also a way to establish change. If we want to change, we need to setup rituals. This will allow us to consistently implement the new approach.
Rituals are not just routines or habits. They have a link to a higher purpose, which can be personal success or the success of the organization.
Setting up rituals as a way to change is true personally and also in organizations. The most effective change programs involve creating a set of new rituals (meetings, type of encounters, new process steps and meeting points etc) up to the point where it becomes a habit with purpose.
Purpose is very important here because it will justify the effort and always re-frame the actions taken with a higher level justification.
When do you establish the rituals that will allow you to change?