The Race to Solve World’s Complex Problems

As we are taking steps into returning to normalcy, the big picture starts to reveal itself. We live in a world with unprecedented disruption that presents complex problems

A complex problem is a shared problem that has many variables and for which the outcome is not only uncertain, but also complicated with advanced entanglement. More often, to manage increased complexity, an entire industry is forced to evolve. While science has increased our knowledge dramatically, there are still many more questions unanswered. Applying knowledge the right way at the right moment for the right problem is still a big challenge. Under pressure, people make simple mistakes and overlook the obvious. According to the Future of Humanity Institute the highest priorities that require urgent problem solving are : Development of Artificial Intelligence; Great power conflict; Global governance; Governance of outer space; Cognition optimisation & whole brain emulation; Civilization resilience & extinction risks; and Recommender systems. These are all such complex problems that require solutions to consider the broader system of utilising technology towards transformation. They consist of networks of individuals, companies, jurisdictions, institutions and related norms that govern them, as well as factors that are out of control and unknown.

One must assess a situation from various perspectives to solve complex world and business challenges. Whether ignorance or competing perceptions lead to conflict, the fundamental disagreement may lead to innovative solutions as a means to resolve a dispute. Approach to start up acceleration and collaborative ideas development is key to solving complex challenges. Combined with a holistic perspective, an open-mindedness, and diverse perspectives, complex problems need new methods of realisation. Precedent and experience push people toward familiar ways of seeing things, which can be inadequate for the truly tough challenges that confront the most senior leaders. We know that teams of smart people from different backgrounds are more likely to come up with fresh ideas more quickly than individuals or like-minded groups do. When a diverse range of experts interact, their approach to problems is different from those that individuals use. The solution space becomes broader, increasing the chance that a more innovative answer will be found.

Evolutionary algorithms have won advanced games and solved huge optimisation problems that overwhelm most super and quantum computational resources. Their success rests on the power of generating diversity by introducing randomness and parallelisation into the search procedure and quickly filtering out suboptimal solutions. The consensus is that issues of high complexity and high urgency are problems that urgently need to be solved immediately. The race is on.

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