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Human + Machine : Reimagining Work in the Age of AI, by H. James Wilson
Obtenir un ebook gratuit Human + Machine : Reimagining Work in the Age of AI, by H. James Wilson
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Détails sur le produit
Relié: 256 pages
Editeur : Harvard Business Review Press (20 mars 2018)
Langue : Anglais
ISBN-10: 1633693864
ISBN-13: 978-1633693869
Dimensions du produit:
16,5 x 2,5 x 24,1 cm
Moyenne des commentaires client :
5.0 étoiles sur 5
2 commentaires client
Classement des meilleures ventes d'Amazon:
113.053 en Livres (Voir les 100 premiers en Livres)
Très bon livre, très facile à suivre, particulièrement pour une audience non-avertie sur les domaines de l'Intelligence Artificielle et de l'automation. Basé sur des cas d'utilisation réels, il casse le "à priori" d'un monde ou l'homme et la machine seraient en opposition. Il donne aussi un angle de lecture particulier pour identifier des cas d'usage et l'évolution des compétences requises pour des applications très variés.Une lecture obligatoire pour tous ceux qui s'intéressent à titre professionnel ou personnel au futur du travail.
une approche intéressante de ce que sera notre avenir à l'heure de l'intelligence artificielle. Très abordable et bien vulgarisé.
Many companies are already using or intending to use Artificial Intelligence (AI). AI is defined by the authors, Daugherty and Wilson of Accenture, as “systems that extend human capability by sensing, comprehending, acting, and learning.â€There is a widespread misconception that AI systems will gradually replace humans in one industry after another. However, the author’s research indicates that although AI can be used to automate certain functions, the technology’s greater power is in complementing and augmenting human capabilities. Rather than replace the need for humans, AI will perform the tedious grunt work, collecting data and doing the preliminary analysis, and so free human being to perform work only they can.A brief overview of the evolution of businesses is necessary to position the authors’ insights.The first wave of business transformation involved standardized processes. Henry Ford’s extraordinary contribution was to deconstruct the manufacture of automobiles so that they could be made on an assembly lines powered by men. With each step made measurable, the assembly line could be optimized, and standardized with enormous gains in efficiencies.The second wave was the automation of processes that began in the 1970s and reached its peak in the 1990s. This ‘business process re-engineering’, was propelled by the ubiquity of computers, large databases and the automation of numerous back-office tasks. Many people were replaced by machines. At the time Walmart was the gold standard.The third wave rests on the previous two waves, but is a completely new way of doing business. This combination will adapt to the behaviours, preferences, and needs of workers at a given moment. It will be powered by real-time data rather than by a pre-organized sequence of steps.When this third wave is optimised, it will allow organizations who take full advantage of AI. They will be able to produce individualized products and services which are satisfying beyond the capabilities of the mass-production of the past. And deliver more profit.The difference can be compared to travelling to a destination you are unfamiliar with. In the past, you used a map-book, and then you used the early version of the GPS, which was very similar to a map under glass. The third wave is like ‘Waze’. It is a combination of AI algorithms and real-time data to create a living, dynamic, optimized map to get you to your destination on the quickest route possible at that exact time. Waze doesn’t replace the driver; rather it amplifies our navigation skills and collaborates with us to achieve productivity gains in navigation that have previously not been possible.“Humans and machines aren’t adversaries, fighting for each other’s jobs. Instead, they are symbiotic partners, each pushing the other to higher levels of performance,†the authors demonstrate.Infused with AI, factories, for example, are acquiring more humanity, with jobs changing in nature and increasing in number. But AI is also creating brand new roles and new opportunities for people up and down the industrial and even the back-office value chain.In the past engineers would have to program a robot and then re-program it when the job changes. The new robotic arms, developed in Japan, adapt on their own using an AI technique called ‘deep reinforcement learning’, which involves giving the robot a picture of the desired outcome; and then the robot uses trial and error to figure out how to do this. The robot takes 8 hours to become 90% proficient, and then can ‘teach’ hundreds of other robots in the network! The arm is now an autodidact, freeing humans for other tasks.Mechanical arms are perfect for highly repetitive and heavy tasks. However, there are always a subset of tasks that are just too complex to program into a robot. This could be a factory-floor task such as positioning numerous small wires or handling awkward or dynamic objects. Or, it could be a back-office task that requires judgment, after the AI-programmed computer performs an analysis from a data set too large for a person to manage. A human is still needed in the loop.In a pilot project using AI to analyse big data and workers’ routines, Hitachi was able to instruct employees to meet real-time fluctuating demand and on-site kaizen objectives. This produced an 8% productivity improvement in logistics tasks.With all the benefits of the third wave, we need to have a much deeper understanding of how humans and machines must collaborate so that people are augmented and not replaced. The authors call this the “missing middleâ€. There is lots of information and excitement about AI and “almost no one talks about…how to fill this crucial gap.â€The authors’ method requires five deliberate changes which can be summarised by the acronym MELDS.The first is a change of ‘Mindset’. This requires reimagining the work, then discovering how people can improve AI, and how smart machines can give humans superpowers. You can get to your destination as rapidly as possible even if you don’t know the way, or the number of cars on the route, or that an accident has occurred that will block the short cut.The second change is “Experimentationâ€. Businesses need to be actively looking for parts of processes where AI can be introduced, and then learn and scale that process, with the enhancing power of people. Only people could conceive of the entirely new, such as the agricultural model - the “vertical farm†- in which plants are grown in thirty-foot-high stacks of trays in urban warehouses.The third change is the responsible use of AI by the “Leadership†of the business. It is too easy to look for the next quarter’s improvement, and overlook the long-term catastrophe of unemployed people.The fourth change is to see “Data†in its rightful place. Data is the fuel of any intelligent system and, not unlike fossil fuel, requires the building of a data “supply chain†to ensure efficient delivery. Data is not a static body, but an ever growing one that requires the same attention to delivery that is required of any other resource.The fifth change involves a new set of eight “Skills†that need developing, that the authors call ‘fusion skills’. Each skill draws on the fusion of human talent and machine ability within a business process, to create better outcomes than could be achieved working independently. These skills are more than learning what the machine can do; rather it is the machine learning from the person and the person learning from the machine.“The AI revolution is not coming; it is already here, and it is about reimagining your processes, across all functions of the company, to get the most benefit from this technology’s power to augment human capability.â€This book not only makes fascinating reading about the AI revolution, it offers a coherent and practical tool to get the most out of the human and machine interaction. That said, we face the frightening reality of huge unemployment, growing by hundreds of thousands annually. The ‘Leadership’ element of the model have a Herculean challenge.Readability Light ---+- SeriousInsights High -+--- LowPractical High -+--- Low*Ian Mann of Gateways consults internationally on leadership and strategy and is the author of the recently released ‘Executive Update.
Daugherty and Wilson present the clearest and most compelling vision to date for how the artificial intelligence revolution will require leaders to reimagine their processes and enable humans to collaborate with machines. Because in the future, some roles will require machines helping humans. And some roles will require humans helping machines. Human+Machine delves into the new types of jobs that AI will create to fill "the missing middle". And you may be surprised to learn they're not all computer science and coding jobs. A fascinating and approachable read for anyone interested to know what work will look like in the age of AI.
There are plenty of books in the market that paint a picture of the future (good or bad), but stop short of identifying actions you can take today to shape that future. Human + Machine provides a much-needed balanced perspective - giving practical, actionable steps leaders should take now to create new jobs and business growth. The book outlines 8 fusion skills people need to develop to succeed in an AI workplace, and it puts its proceeds where its principles are by donating net revenues to crucial education and retaining programs.
This is indeed one of the first books where many concrete cases of melding human and machine skills are collected and presented in a organized way. But most of the cases are described in only few paragraphs, and the feeling one gets after going through the whole book is that there were many good undeveloped ideas, like droplets of knowledge but nothing more than that. The book also has difficulty to really address the main question about AI: no matter how many new jobs can emerge from human+machine interaction, it is difficult to imagine that anything different from the fact that for each 10,000 traditional jobs lost to AI there will be maybe a couple of trainers, explainers and supporters to be hired. I was particularly happy to discover the "moral crumble zone" concept, which I was not familiar with, in this book, and that was nice. Overall, this is a light view of AI, both because it does not deepen into any specific subject matter and because it treats it under a very optimistic tone.
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