Listing 1 - 2 of 2 |
Sort by
|
Choose an application
What if you could combine the agility, adaptability, and cohesion of a small team with the power and resources of a giant organization? When General Stanley McChrystal took command of the Joint Special Operations Task Force in Iraq in 2003, he quickly realized that conventional military tactics were failing. The allied forces had a huge advantage in numbers, equipment and training - but none of the enemy's speed and flexibility. McChrystal and his colleagues discarded a century of conventional wisdom to create a 'team of teams' that combined extremely transparent communication with decentralized decision-making authority. Faster, flatter and more flexible, the task force beat back al-Qaeda. In this powerful book, McChrystal and his colleagues show how the challenges they faced in Iraq can be relevant to any leader. Through compelling examples, the authors demonstrate that the 'team of teams' strategy has worked everywhere from hospital emergency rooms to NASA and has the potential to transform organizations large and small. 'A bold argument that leaders can help teams become greater than the sum of their parts' Charles Duhigg, author of The Power of Habit 'An indispensable guide to organizational change' Walter Isaacson, author of Steve Jobs.
Choose an application
The idea of artificial intelligence--job-killing robots, self-driving cars, and self-managing organizations--captures the imagination, evoking a combination of wonder and dread for those of us who will have to deal with the consequences. But what if it's not quite so complicated? The real job of artificial intelligence, argue these three eminent economists, is to lower the cost of prediction. And once you start talking about costs, you can use some well-established economics to cut through the hype. The constant challenge for all managers is to make decisions under uncertainty. And AI contributes by making knowing what's coming in the future cheaper and more certain. But decision making has another component: judgment, which is firmly in the realm of humans, not machines. Making prediction cheaper means that we can make more predictions more accurately and assess them with our better (human) judgment. Once managers can separate tasks into components of prediction and judgment, we can begin to understand how to optimize the interface between humans and machines. More than just an account of AI's powerful capabilities, Prediction Machines shows managers how they can most effectively leverage AI, disrupting business as usual only where required, and provides businesses with a toolkit to navigate the coming wave of challenges and opportunities.--
Artificial intelligence. Robotics. Simulation. Graphics --- Economic sociology --- Quantitative methods (economics) --- AI, change, coachen, creatief, cultuur, customer experience, economie, innovatie, strategie, succes, technologie, transforming, verandering, zelfontwikkeling --- Artificial intelligence --- Decision making --- Forecasting --- Economic aspects --- Statistical methods --- Economic aspects. --- Statistical methods. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- ARTIFICIAL INTELLIGENCE--ECONOMIC ASPECTS --- Artificial intelligence - Economic aspects --- Decision making - Statistical methods --- Forecasting - Statistical methods
Listing 1 - 2 of 2 |
Sort by
|