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Human + Machine: Reimagining Work in the Age of AI
AI is radically transforming business. Are you ready?
Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on?
In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate.
Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business.
Human + Machine provides the missing and much-needed management playbook for success in our new age of AI.
BOOK PROCEEDS FOR THE AI GENERATIONThe authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.
Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on?
In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate.
Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business.
Human + Machine provides the missing and much-needed management playbook for success in our new age of AI.
BOOK PROCEEDS FOR THE AI GENERATIONThe authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.
246 pages, Kindle Edition
Published March 20, 2018
356 people are currently reading
2650 people want to read
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Displaying 1 - 30 of 117 reviews
May 29, 2018
A collection of news headlines with doubtful generalizations
Maybe this book will be useful for people who don’t follow the topics of AI/Machine Learning. For me it looked like a compilation of Google search results for AI-related keywords.
I don’t buy the concepts authors try to establish. Trainers, Explainers, Sustainers? If you worked on integrating AI in business processes, it is clear that the variety of new jobs and roles enabled by the technology is wider.
After reading about 30% of the book and not having any “aha!” moments, I have skimmed through the rest, reading selected sentences. The only use of this book is as a collection of AI-related case studies.
Maybe this book will be useful for people who don’t follow the topics of AI/Machine Learning. For me it looked like a compilation of Google search results for AI-related keywords.
I don’t buy the concepts authors try to establish. Trainers, Explainers, Sustainers? If you worked on integrating AI in business processes, it is clear that the variety of new jobs and roles enabled by the technology is wider.
After reading about 30% of the book and not having any “aha!” moments, I have skimmed through the rest, reading selected sentences. The only use of this book is as a collection of AI-related case studies.
February 22, 2025
My takeaways from reading this book:
How can people help machines?
- Page 106: People can help machines in situations where there is little or no data.
- Page 107: People can train machines to perform tasks.
- Page 107: People can explain machine outcomes.
- Page 117: People can teach AI systems how to display compassion.
- Page 118: People can help AI systems develop personality and become more humanlike.
- Page 119: People can help AI chatbots become more sensitive to different ways of thinking.
- Page 129: AI safety engineers can anticipate unintended consequences of AI systems and address any harmful occurrences with the appropriate strategy.
- Page 129: Ethics and compliance managers uphold generally accepted norms of human values and morals.
- Pages 154-157: People can reimagine how things are done. Often, identifying opportunities for process reimagination is an iterative process. Important is understanding the current business context, making observations to get knowledge and identifying potential value of reimagining processes.
- Page 172: Allow rating systems to be used for algorithms or machines, not just for people.
- Page 172: Giving users some control over the algorithm makes them more likely to continue to use the AI system.
- Page 174: Today, about 90% of the time of people, who train AI applications, is spent on data preparation and feature engineering, rather than on writing algorithms.
- Page 178: People can facilitate AI feedback loops, which create cycles of learning and improvement.
How can machines help humans?
- Page 2: Robots are becoming smaller, more flexible as well as better able to sense their environment, understand, act and learn.
- Page 5: Machines are good at doing repetitive, routine work and analyzing large data sets.
- Page 35: Precision agriculture requires a vast network of Internet of Things sensors. This information might include images by satelites or drones, sensors in the field and sensors on farm equipment.
- Page 36: Artificial intelligence (AI) is enabling vertical farming in which plants can be grown in city warehouses in 10 meter stacks of trays. Such vertical farms require less water and fertilizer than traditional farms.
- Page 51: HireVue is an AI work interview app that notes words, body language and tone of people, who are interviewed.
- Page 69: AI will disrupt every phase of the scientific process: 1. Ask questions and make observations. 2. Devise hypotheses. 3. Design experiment and test predictions based on hypotheses. 4. Run tests and collect data. 5. Develop generalized theories.
- Page 74: Nike 3D prints protitypes and tests them, and repeats the cycle until it finds the premier design.
- Page 85: To manage Coca-cola cooler cabinets in stores and other places, the app Einstein was developed which uses artificial intelligence (AI). A person can take a photo of a Coca-Cola cooler cabinet and upload it to the app. The app will predict and recommend restocking order - using customer relationship management data, weather forecasts, promotional levels, inventory levels and historical data.
- Page 87: Philips smart lighting uses AI to predict when light bulbs will lose their efficiency., which ties into the company's recycling and replacement service.
- Page 93: 98% of online customers would be likely or very likely to make another purchase if they have a good experience.
- Page 151: Drones can deliver healthcare to remote places.
- Page 197: Robots can help surgeons reach hard to access organs, perform precise cuts, and suture at angles with previously impossible dexterity.
How can people help machines?
- Page 106: People can help machines in situations where there is little or no data.
- Page 107: People can train machines to perform tasks.
- Page 107: People can explain machine outcomes.
- Page 117: People can teach AI systems how to display compassion.
- Page 118: People can help AI systems develop personality and become more humanlike.
- Page 119: People can help AI chatbots become more sensitive to different ways of thinking.
- Page 129: AI safety engineers can anticipate unintended consequences of AI systems and address any harmful occurrences with the appropriate strategy.
- Page 129: Ethics and compliance managers uphold generally accepted norms of human values and morals.
- Pages 154-157: People can reimagine how things are done. Often, identifying opportunities for process reimagination is an iterative process. Important is understanding the current business context, making observations to get knowledge and identifying potential value of reimagining processes.
- Page 172: Allow rating systems to be used for algorithms or machines, not just for people.
- Page 172: Giving users some control over the algorithm makes them more likely to continue to use the AI system.
- Page 174: Today, about 90% of the time of people, who train AI applications, is spent on data preparation and feature engineering, rather than on writing algorithms.
- Page 178: People can facilitate AI feedback loops, which create cycles of learning and improvement.
How can machines help humans?
- Page 2: Robots are becoming smaller, more flexible as well as better able to sense their environment, understand, act and learn.
- Page 5: Machines are good at doing repetitive, routine work and analyzing large data sets.
- Page 35: Precision agriculture requires a vast network of Internet of Things sensors. This information might include images by satelites or drones, sensors in the field and sensors on farm equipment.
- Page 36: Artificial intelligence (AI) is enabling vertical farming in which plants can be grown in city warehouses in 10 meter stacks of trays. Such vertical farms require less water and fertilizer than traditional farms.
- Page 51: HireVue is an AI work interview app that notes words, body language and tone of people, who are interviewed.
- Page 69: AI will disrupt every phase of the scientific process: 1. Ask questions and make observations. 2. Devise hypotheses. 3. Design experiment and test predictions based on hypotheses. 4. Run tests and collect data. 5. Develop generalized theories.
- Page 74: Nike 3D prints protitypes and tests them, and repeats the cycle until it finds the premier design.
- Page 85: To manage Coca-cola cooler cabinets in stores and other places, the app Einstein was developed which uses artificial intelligence (AI). A person can take a photo of a Coca-Cola cooler cabinet and upload it to the app. The app will predict and recommend restocking order - using customer relationship management data, weather forecasts, promotional levels, inventory levels and historical data.
- Page 87: Philips smart lighting uses AI to predict when light bulbs will lose their efficiency., which ties into the company's recycling and replacement service.
- Page 93: 98% of online customers would be likely or very likely to make another purchase if they have a good experience.
- Page 151: Drones can deliver healthcare to remote places.
- Page 197: Robots can help surgeons reach hard to access organs, perform precise cuts, and suture at angles with previously impossible dexterity.
November 9, 2018
This book is definitely written for CEOs and CFOs who are looking for ideas on how to implement AI into their business models.
This book is mainly a collection of how companies are using AI in 2016, and therefore will likely not age well.
In this reader's opinion, the authors take an overly optimistic view of worker displacement. "Oh, all the workers displaced by AI will be retrained to do jobs we haven't even imagined yet! Nothing to see here. Move along!"
The authors state over and over again that corporate management will take an altruistic view towards all these new-found worker efficiencies by having the displaced workers retrained into jobs that the company's current model doesn't need. History seems to suggest that corporations are far more likely to take the new worker efficiencies and have one worker do the work that used to be done by many, while showing the others the door.
I read books like this to get an insight into what everyone is going to do when AI starts displacing large quantities of jobs (I'm looking at you, transportation industry, as the tip of the iceberg). It seems unlikely that a 55 year old truck driver will be easily retrained as a robot whisperer, or whatever term the authors used for the workers who will translate the decisions of the AI into understandable English.
This book offered no insights of any kind to that end, though.
Finally, every wave of industrial evolution had its group of naysayers wondering "what is everyone going to do?" Maybe this time is the same in that everything will work out and there will be positions with consistent employment and livable wages for everyone looking for one. However, maybe this time is different; considering that the "roaring" economy of 2018Q4 with its sub-4% unemployment can't even seem to fit that bill (with a considerable percentage of the workforce working multiple jobs just to make ends meet), this time does feel different.
This book is mainly a collection of how companies are using AI in 2016, and therefore will likely not age well.
In this reader's opinion, the authors take an overly optimistic view of worker displacement. "Oh, all the workers displaced by AI will be retrained to do jobs we haven't even imagined yet! Nothing to see here. Move along!"
The authors state over and over again that corporate management will take an altruistic view towards all these new-found worker efficiencies by having the displaced workers retrained into jobs that the company's current model doesn't need. History seems to suggest that corporations are far more likely to take the new worker efficiencies and have one worker do the work that used to be done by many, while showing the others the door.
I read books like this to get an insight into what everyone is going to do when AI starts displacing large quantities of jobs (I'm looking at you, transportation industry, as the tip of the iceberg). It seems unlikely that a 55 year old truck driver will be easily retrained as a robot whisperer, or whatever term the authors used for the workers who will translate the decisions of the AI into understandable English.
This book offered no insights of any kind to that end, though.
Finally, every wave of industrial evolution had its group of naysayers wondering "what is everyone going to do?" Maybe this time is the same in that everything will work out and there will be positions with consistent employment and livable wages for everyone looking for one. However, maybe this time is different; considering that the "roaring" economy of 2018Q4 with its sub-4% unemployment can't even seem to fit that bill (with a considerable percentage of the workforce working multiple jobs just to make ends meet), this time does feel different.
April 26, 2018
The best take on "AI as process redesign" to date. Lots of examples and a simple model where we "reimagine" business processes by building them around analytic decision centres and the reorganising human workers to care and feed these decision centres.
Has the usual failings of this sort of thing though, that show that the authors can't see their own biases. Apparently 'AI' is machine learning with some other fluff around the edges. Nor do the authors ever think of asking the question "why do we have processes when we can plan in real time with AI?" (But then, apparently 'AI' doesn't include all the interesting planning stuff that's been done over the years.)
Ultimately the book shows how we might incrementally improve current business practices, rather than revolutionise them as it promises.
Has the usual failings of this sort of thing though, that show that the authors can't see their own biases. Apparently 'AI' is machine learning with some other fluff around the edges. Nor do the authors ever think of asking the question "why do we have processes when we can plan in real time with AI?" (But then, apparently 'AI' doesn't include all the interesting planning stuff that's been done over the years.)
Ultimately the book shows how we might incrementally improve current business practices, rather than revolutionise them as it promises.
March 13, 2019
This is Artificial Intelligence 101 for executives. A good summary of the latest headlines over the last couple of years, ICYMI. The overwhelming narrative here is a bit one-sided... that machines can only be a good thing. There is little to no discussion of the other side of the coin.
February 25, 2020
Though there is no original content. This book is a collection of news on AI through out the world (mostly in developed countries). Some of them are thought provoking by seeing them from a different perspective with respect to Job loss, man machine collaboration. At the same it concerns me about the penetration of AI and privacy issues. I am just feel little secure that there are privacy laws, otherwise you won't even know how deep the AI tech have already penetrated.
February 23, 2019
One substantive high level idea, but a lot of media anecdote as well. Frustrating that so many of the research citations refer to press articles rather than the original work.
July 13, 2024
This book has a summary feel, like an executive summary. Still it is fairly encompassing and interesting enough to be worth reading on the topic of AI, including its current impact and possible future directions. AI is here to stay and will only become more common and pervasive.
Throughout the book, the authors return to two ideas:
1. The concept of the "Missing Middle," which is the class of jobs that sits between the jobs that only machines can do and the jobs that only humans can do. In the missing middle, humans and machines cooperate to be more effective than either could be individually, with humans providing judgment and creativity and machines providing processing power, memory, and excellence at automation. The vast majority of jobs in the future will come from the missing middle, and it is only blindness to the existence of the missing middle that causes doomsayers to predict widespread unemployment as a result of AI. There are also examples of successes and real-world instances of human-AI collaboration in this area. Largely it seems to come from greater interpretation of nuance and application of manual dexterity. Also, this space is where robots move from job killers to enablers and human-directed tools.
2. To help elucidate the missing middle to corporate leaders, to whom this text seems directed, the authors provide their original MELDS framework, which stands for Mindset, Experimentation, Leadership, Data, and Skills. They try to demonstrate how this framework can help corporate leaders make wise decisions so their companies can leverage artificial intelligence effectively.
Here is a summary of interesting points I abstracted from another's review
How can humans help machines?
- Page 106: Humans can help machines in situations where there is little or no data.
- Page 107: Humans can train machines to perform tasks.
- Page 117: Empathy trainers can teach AI systems how to display compassion.
- Page 118: Personality trainers can help AI systems become more humanlike.
- Page 119: Worldview and localization trainers help chatbots become more sensitive to different ways of thinking and communicating across the globe.
- Page 129: AI safety engineers anticipate unintended consequences of AI systems and address any harmful occurrences with the appropriate strategy.
- Page 129: Ethics and compliance managers uphold generally accepted norms of human values and morals.
- Pages 154-157: Reimagine processes / how things are done. Often, identifying opportunities for process reimagination is an iterative process. Important is understanding the current business context, making observations to get knowledge and identifying potential value of reimagining processes.
- Page 172: Giving users some control over the algorithm makes them more likely to continue to use the AI system.
- Page 174: Today, about 90% of the time of people, who train AI applications, is spent on data preparation and feature engineering, rather than on writing algorithms.
How can machines help humans?
- Page 2: Robots are becoming smaller, more flexible as well as better able to sense their environment, understand, act and learn.
- Page 5: Machines are good at doing repetitive, routine work and analyzing large data sets.
- Page 35: Precision agriculture requires a vast network of Internet of Things sensors. This information might include images by satelites or drones, sensors in the field and sensors on farm equipment.
- Page 36: Artificial intelligence (AI) is enabling vertical farming in which plants can be grown in city warehouses in 10 meter stacks of trays. Such vertical farms require less water and fertilizer than traditional farms.
- Page 69: AI will disrupt every phase of the scientific process: 1. Ask questions and make observations. 2. Devise hypotheses. 3. Design experiment and test predictions based on hypotheses. 4. Run tests and collect data. 5. Develop generalized theories.
- Page 74: Nike 3D prints AI-designed prototypes and tests them, and repeats the cycle until it finds the premier design.
- Page 85: To manage Coca-cola cooler cabinets in stores and other places, the app Einstein was developed which uses artificial intelligence (AI). A person can take a photo of a Coca-Cola cooler cabinet and upload it to the app. The app will predict and recommend restocking order - using customer relationship management data, weather forecasts, promotional levels, inventory levels and historical data.
- Page 87: Philips smart lighting uses AI to predict when light bulbs will lose their efficiency., which ties into the company's recycling and replacement service.
- Page 93: 98% of online customers would be likely or very likely to make another purchase if they have a good experience.
- Page 151: Drones can deliver healthcare to remote places.
- Page 197: Robots can help surgeons reach hard to access organs, perform precise cuts, and suture at angles with previously impossible dexterity.
Throughout the book, the authors return to two ideas:
1. The concept of the "Missing Middle," which is the class of jobs that sits between the jobs that only machines can do and the jobs that only humans can do. In the missing middle, humans and machines cooperate to be more effective than either could be individually, with humans providing judgment and creativity and machines providing processing power, memory, and excellence at automation. The vast majority of jobs in the future will come from the missing middle, and it is only blindness to the existence of the missing middle that causes doomsayers to predict widespread unemployment as a result of AI. There are also examples of successes and real-world instances of human-AI collaboration in this area. Largely it seems to come from greater interpretation of nuance and application of manual dexterity. Also, this space is where robots move from job killers to enablers and human-directed tools.
2. To help elucidate the missing middle to corporate leaders, to whom this text seems directed, the authors provide their original MELDS framework, which stands for Mindset, Experimentation, Leadership, Data, and Skills. They try to demonstrate how this framework can help corporate leaders make wise decisions so their companies can leverage artificial intelligence effectively.
Here is a summary of interesting points I abstracted from another's review
How can humans help machines?
- Page 106: Humans can help machines in situations where there is little or no data.
- Page 107: Humans can train machines to perform tasks.
- Page 117: Empathy trainers can teach AI systems how to display compassion.
- Page 118: Personality trainers can help AI systems become more humanlike.
- Page 119: Worldview and localization trainers help chatbots become more sensitive to different ways of thinking and communicating across the globe.
- Page 129: AI safety engineers anticipate unintended consequences of AI systems and address any harmful occurrences with the appropriate strategy.
- Page 129: Ethics and compliance managers uphold generally accepted norms of human values and morals.
- Pages 154-157: Reimagine processes / how things are done. Often, identifying opportunities for process reimagination is an iterative process. Important is understanding the current business context, making observations to get knowledge and identifying potential value of reimagining processes.
- Page 172: Giving users some control over the algorithm makes them more likely to continue to use the AI system.
- Page 174: Today, about 90% of the time of people, who train AI applications, is spent on data preparation and feature engineering, rather than on writing algorithms.
How can machines help humans?
- Page 2: Robots are becoming smaller, more flexible as well as better able to sense their environment, understand, act and learn.
- Page 5: Machines are good at doing repetitive, routine work and analyzing large data sets.
- Page 35: Precision agriculture requires a vast network of Internet of Things sensors. This information might include images by satelites or drones, sensors in the field and sensors on farm equipment.
- Page 36: Artificial intelligence (AI) is enabling vertical farming in which plants can be grown in city warehouses in 10 meter stacks of trays. Such vertical farms require less water and fertilizer than traditional farms.
- Page 69: AI will disrupt every phase of the scientific process: 1. Ask questions and make observations. 2. Devise hypotheses. 3. Design experiment and test predictions based on hypotheses. 4. Run tests and collect data. 5. Develop generalized theories.
- Page 74: Nike 3D prints AI-designed prototypes and tests them, and repeats the cycle until it finds the premier design.
- Page 85: To manage Coca-cola cooler cabinets in stores and other places, the app Einstein was developed which uses artificial intelligence (AI). A person can take a photo of a Coca-Cola cooler cabinet and upload it to the app. The app will predict and recommend restocking order - using customer relationship management data, weather forecasts, promotional levels, inventory levels and historical data.
- Page 87: Philips smart lighting uses AI to predict when light bulbs will lose their efficiency., which ties into the company's recycling and replacement service.
- Page 93: 98% of online customers would be likely or very likely to make another purchase if they have a good experience.
- Page 151: Drones can deliver healthcare to remote places.
- Page 197: Robots can help surgeons reach hard to access organs, perform precise cuts, and suture at angles with previously impossible dexterity.
June 22, 2024
Vào một buổi tối cuối tuần, khi đọc bài báo trên Business Insider về tác động của AI tới việc làm trong tương lai, tôi tình cờ biết đến cuốn sách "Human + Machine: Reimagining Work in the Age of AI". Sự tò mò về AI và ảnh hưởng của nó tới công việc của con người đã thôi thúc tôi tìm đọc ngay cuốn sách này. Ban đầu, tôi dự định tìm bản tiếng Anh, nhưng khi thấy có bản dịch tiếng Việt trên Tiki, tôi quyết định thử để xem chất lượng dịch thuật các sách AI này ra sao.
Tên cuốn sách "Human + Machine" thực sự thu hút và đúng như tên gọi, nhấn mạnh rằng con người luôn ở vị trí chủ đạo, hợp tác với máy móc để tạo nên những thành tựu đáng kinh ngạc. Điều này khẳng định tầm quan trọng của sự tương tác và hợp tác giữa con người và công nghệ trong thời đại mới.
Cuốn sách bắt đầu bằng việc giải thích về "phần giữa bị bỏ lỡ" (missing middle), một khái niệm cho rằng có những nhiệm vụ chỉ con người mới làm được, có những nhiệm vụ chỉ máy móc mới thực hiện được, và phần giữa là những công việc kết hợp giữa con người và máy móc để tạo ra những khả năng đặc biệt. Một ví dụ điển hình là nhà máy của BMW, nơi công nhân và robot cùng làm việc trên dây chuyền lắp ráp ô tô. Robot chịu trách nhiệm lắp đặt các bộ phận nặng, sau đó công nhân sẽ kiểm tra và cố định chúng, tạo nên một sự hợp tác hiệu quả và an toàn.
Cuốn sách cũng đề cập đến năm nguyên tắc quan trọng để thích nghi với cuộc cách mạng AI: tư duy, thử nghiệm, lãnh đạo, dữ liệu và kỹ năng. AI giúp loại bỏ những công việc nhàm chán như nhập liệu, phân tích dữ liệu thô, và đọc hình ảnh, tạo ra nhiều thời gian hơn để tập trung vào các công việc có giá trị cao hơn. Tác giả ví AI như việc cung cấp cho con người "một cánh tay thứ ba" hay "một con mắt thứ ba", giúp chúng ta làm việc hiệu quả và năng suất hơn.
Mặc dù cuốn sách diễn đạt khá rõ ràng và dễ hiểu, nhưng sẽ dễ tiếp cận hơn nếu có thêm các sơ đồ hay mindmap để minh họa các quy trình và tổng hợp nội dung. Điều này sẽ giúp người đọc dễ dàng nắm bắt và tổng kết lại những ý chính quan trọng.
Cuốn sách đặc biệt hữu ích cho những ai đang làm việc trong lĩnh vực IT, liên quan đến IT, hoặc đang tìm hiểu về tác động của AI đối với công việc và cuộc sống. Sách đưa ra nhiều ví dụ về ứng dụng của AI trong các lĩnh vực từ văn phòng, y tế cho tới kinh doanh, giúp người đọc dễ hiểu hơn. Đặc biệt, bản dịch tiếng Việt giữ nguyên các thuật ngữ chuyên ngành, giúp người đọc nắm bắt được những từ vựng trong lĩnh vực AI.
Tên cuốn sách "Human + Machine" thực sự thu hút và đúng như tên gọi, nhấn mạnh rằng con người luôn ở vị trí chủ đạo, hợp tác với máy móc để tạo nên những thành tựu đáng kinh ngạc. Điều này khẳng định tầm quan trọng của sự tương tác và hợp tác giữa con người và công nghệ trong thời đại mới.
Cuốn sách bắt đầu bằng việc giải thích về "phần giữa bị bỏ lỡ" (missing middle), một khái niệm cho rằng có những nhiệm vụ chỉ con người mới làm được, có những nhiệm vụ chỉ máy móc mới thực hiện được, và phần giữa là những công việc kết hợp giữa con người và máy móc để tạo ra những khả năng đặc biệt. Một ví dụ điển hình là nhà máy của BMW, nơi công nhân và robot cùng làm việc trên dây chuyền lắp ráp ô tô. Robot chịu trách nhiệm lắp đặt các bộ phận nặng, sau đó công nhân sẽ kiểm tra và cố định chúng, tạo nên một sự hợp tác hiệu quả và an toàn.
Cuốn sách cũng đề cập đến năm nguyên tắc quan trọng để thích nghi với cuộc cách mạng AI: tư duy, thử nghiệm, lãnh đạo, dữ liệu và kỹ năng. AI giúp loại bỏ những công việc nhàm chán như nhập liệu, phân tích dữ liệu thô, và đọc hình ảnh, tạo ra nhiều thời gian hơn để tập trung vào các công việc có giá trị cao hơn. Tác giả ví AI như việc cung cấp cho con người "một cánh tay thứ ba" hay "một con mắt thứ ba", giúp chúng ta làm việc hiệu quả và năng suất hơn.
Mặc dù cuốn sách diễn đạt khá rõ ràng và dễ hiểu, nhưng sẽ dễ tiếp cận hơn nếu có thêm các sơ đồ hay mindmap để minh họa các quy trình và tổng hợp nội dung. Điều này sẽ giúp người đọc dễ dàng nắm bắt và tổng kết lại những ý chính quan trọng.
Cuốn sách đặc biệt hữu ích cho những ai đang làm việc trong lĩnh vực IT, liên quan đến IT, hoặc đang tìm hiểu về tác động của AI đối với công việc và cuộc sống. Sách đưa ra nhiều ví dụ về ứng dụng của AI trong các lĩnh vực từ văn phòng, y tế cho tới kinh doanh, giúp người đọc dễ hiểu hơn. Đặc biệt, bản dịch tiếng Việt giữ nguyên các thuật ngữ chuyên ngành, giúp người đọc nắm bắt được những từ vựng trong lĩnh vực AI.
July 29, 2025
A very interesting read. I was reading this while also studying “Artificial Intelligence for Business” at university, so it was extremely useful and relevant.
I think it should be mandatory reading for any manager or executive looking to use AI in their company, especially if they think they could replace workers with AI (which they should not).
This book demonstrates how & why humans should always have a spot in the workforce, as AI is a wonderful tool, not a replacement for humankind.
I think it should be mandatory reading for any manager or executive looking to use AI in their company, especially if they think they could replace workers with AI (which they should not).
This book demonstrates how & why humans should always have a spot in the workforce, as AI is a wonderful tool, not a replacement for humankind.
August 25, 2023
This book is mids, way too general in that the author just talks about AI headlines. Book does not age well since all of the applications seem to be unheard of as of 2023. I skimmed the book after page 83, nothing helpful to learn really that I didn't already know.
October 21, 2024
Pretty good overview of what's happening in the age of AI. Although, at times, the authors seem to be overly optimistic.
December 14, 2023
It is an interesting topic, but a poorly executed book.
June 30, 2018
Artificial Intelligence (AI) - what will the future of work look like as AI continues to fulfill more of its potential?
The authors suggest that Humans + Machines are more effective and productive than just humans or just machines. Although AI may replace some human workers, eliminate some jobs, the real power of AI will to compliment and augment human capabilities..
They offer examples of how AI is starting to affect work on the factory floor, in banks, R&D, Sales and Marketing. They also offer a number of types of jobs that will be created as AI becomes more ubiquitous in the work place and offer some suggestions about how business might begin to take advantage of this newer technology and some of the skills people will need to learn to be successful in this proposed new world.
Good research, interesting read. Recommend.
The authors suggest that Humans + Machines are more effective and productive than just humans or just machines. Although AI may replace some human workers, eliminate some jobs, the real power of AI will to compliment and augment human capabilities..
They offer examples of how AI is starting to affect work on the factory floor, in banks, R&D, Sales and Marketing. They also offer a number of types of jobs that will be created as AI becomes more ubiquitous in the work place and offer some suggestions about how business might begin to take advantage of this newer technology and some of the skills people will need to learn to be successful in this proposed new world.
Good research, interesting read. Recommend.
September 7, 2020
Started reading this book using my org design lenses and then stopped doing this when I figured that the book falls short of delivering on the promise of "reimagining work in the age of AI".
3 takeaways:
1. Question for reflection: "What's the impact of AI adoption on how organizations will be (re)designed?" - see the progress in the Organizational Network Analysis field
2. The 3 ways AI can have an impact on employee productivity: amplification (giving people data-driven insights), interaction (facilitating interactions between or on behalf of people), embodiment (physical collaborative work) - I wonder if these 3 examples will be the main value adding use cases
3. 1 of the 8 "fusion" skills: Intelligent Interrogation (knowing how to best ask questions of AI algos) - same as above, I wonder if some researchers could come up with some better, less "buzzwordy" skills
3 takeaways:
1. Question for reflection: "What's the impact of AI adoption on how organizations will be (re)designed?" - see the progress in the Organizational Network Analysis field
2. The 3 ways AI can have an impact on employee productivity: amplification (giving people data-driven insights), interaction (facilitating interactions between or on behalf of people), embodiment (physical collaborative work) - I wonder if these 3 examples will be the main value adding use cases
3. 1 of the 8 "fusion" skills: Intelligent Interrogation (knowing how to best ask questions of AI algos) - same as above, I wonder if some researchers could come up with some better, less "buzzwordy" skills
August 29, 2018
Decent if you are reading for conceptual awareness. Answers the “what” question at a satisfactory level for the casual reader. For practitioners in the digital, AI/analytics and robotics space - it comes up short on the “how question” other than some conceptual niblets on borrowed principals from design thinking; it does not provide any depth or quantitative research on where and how to implement AI-enabled man and machine capabilities for productivity gains in various industries.
Wouldn’t dissuade the casual reader but would not recommend to friends and practitioners in the digital transformation, AI / robotics fields.
Wouldn’t dissuade the casual reader but would not recommend to friends and practitioners in the digital transformation, AI / robotics fields.
April 7, 2019
Its an OK book. Its a book written by consultants. Not a technologist or an innovator. It simply does not go too deep.
The authors talk about the missing middle, where humans and machines work symbiotically together. (the extremes are humans working alone or machines working alone)
Most of the book did not share anything new to me... and it will not be novel to those in the midst of a digital transformation. However, I did learn some new concepts like "model drift" or found new jobs such as "vehicle design anthropologist" or "empathy trainer" very intriguing.
This book is for those who have yet to embark on a digital transformation journey.
The authors talk about the missing middle, where humans and machines work symbiotically together. (the extremes are humans working alone or machines working alone)
Most of the book did not share anything new to me... and it will not be novel to those in the midst of a digital transformation. However, I did learn some new concepts like "model drift" or found new jobs such as "vehicle design anthropologist" or "empathy trainer" very intriguing.
This book is for those who have yet to embark on a digital transformation journey.
September 27, 2019
Remember how Robots were extension of Humans in Sci fi movies? Well this book explains the extension that is happening in ral world as we speak, how human and robots in Factories are working simultaneously and in harmony
There are alot of answers to some pop-culture questions on the AI subject in this book, he's not giving you answers more than he's showing you results of successful applications of a once Sci Fi concept in a real life scenario and his thoughts on where will we go from here
Recommended for any one interested in knowing more about the automation in the future of Jobs and the industrial relationship between man and machine
And make your own tea.
There are alot of answers to some pop-culture questions on the AI subject in this book, he's not giving you answers more than he's showing you results of successful applications of a once Sci Fi concept in a real life scenario and his thoughts on where will we go from here
Recommended for any one interested in knowing more about the automation in the future of Jobs and the industrial relationship between man and machine
And make your own tea.
January 15, 2025
Book Review:
https://www.jcerejo.com/humanandmachine
A good book that brings attention to the new challenges that businesses, and especially management layers, face with the rise of AI possibilities. The authors provide several examples of how technology is shaping businesses. Unfortunately, those examples are very superficial. The book left aside reflections about the impact and moral implications that AI is raising on many levels and its respective social impacts.
https://www.jcerejo.com/humanandmachine
A good book that brings attention to the new challenges that businesses, and especially management layers, face with the rise of AI possibilities. The authors provide several examples of how technology is shaping businesses. Unfortunately, those examples are very superficial. The book left aside reflections about the impact and moral implications that AI is raising on many levels and its respective social impacts.
April 15, 2023
The authors offer not only a fascinating reading about the AI revolution, but also a coherent and practical tool to get the most out of the human and machine interaction. Capacitating corporate human resources to cope and co-work with such advances in AI is crucial in preventing massive automation and unemployment.
February 25, 2023
I had this gem hiding on my shelf for far too long. Great insight on the future of AI in many different sectors and how it could affect future jobs. Super thought-provoking; after reading, I’ve recommended this book to several of my friends and even bought shares of an artificial intelligence ETF.
February 2, 2021
This reminded me of the HBR case studies we read in college and challenged me to think outside of the status quo of standard processes.
January 6, 2025
A Visionary Playbook for Thriving in the Age of AI
Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty and H. James Wilson is a groundbreaking exploration of how artificial intelligence is reshaping the way we work, innovate, and compete. This book is more than a theoretical discussion—it’s a practical guide for leaders, employees, and organizations to embrace AI as a collaborative partner in driving success.
Daugherty and Wilson expertly articulate the shift from traditional processes to adaptive, AI-powered systems that redefine productivity and innovation. Their insights are grounded in extensive research across 1,500 organizations, offering real-world examples of how companies are leveraging AI to create entirely new types of human-machine roles and revolutionize business operations. The authors' "six hybrid roles" framework is especially compelling, providing a roadmap for developing the fusion skills necessary to thrive in this new era.
What makes this book stand out is its balance between optimism and pragmatism. While it celebrates AI’s transformative potential, it also acknowledges the disruptions it brings and the need for thoughtful education and retraining to prepare the workforce for these changes. The authors' commitment to this vision is evident in their decision to donate all royalties to fund programs that develop these essential fusion skills.
The Leader's Guide is another highlight, distilling the principles of AI adoption into actionable steps that any organization can implement. From fostering a collaborative culture between humans and machines to reimagining processes entirely, the book provides a clear blueprint for success in an AI-driven world.
Human + Machine is a must-read for executives, business leaders, and anyone eager to understand how to harness AI for competitive advantage. It’s an inspiring, forward-thinking, and practical resource for navigating the evolving landscape of work in the age of artificial intelligence.
Human + Machine: Reimagining Work in the Age of AI by Paul R. Daugherty and H. James Wilson is a groundbreaking exploration of how artificial intelligence is reshaping the way we work, innovate, and compete. This book is more than a theoretical discussion—it’s a practical guide for leaders, employees, and organizations to embrace AI as a collaborative partner in driving success.
Daugherty and Wilson expertly articulate the shift from traditional processes to adaptive, AI-powered systems that redefine productivity and innovation. Their insights are grounded in extensive research across 1,500 organizations, offering real-world examples of how companies are leveraging AI to create entirely new types of human-machine roles and revolutionize business operations. The authors' "six hybrid roles" framework is especially compelling, providing a roadmap for developing the fusion skills necessary to thrive in this new era.
What makes this book stand out is its balance between optimism and pragmatism. While it celebrates AI’s transformative potential, it also acknowledges the disruptions it brings and the need for thoughtful education and retraining to prepare the workforce for these changes. The authors' commitment to this vision is evident in their decision to donate all royalties to fund programs that develop these essential fusion skills.
The Leader's Guide is another highlight, distilling the principles of AI adoption into actionable steps that any organization can implement. From fostering a collaborative culture between humans and machines to reimagining processes entirely, the book provides a clear blueprint for success in an AI-driven world.
Human + Machine is a must-read for executives, business leaders, and anyone eager to understand how to harness AI for competitive advantage. It’s an inspiring, forward-thinking, and practical resource for navigating the evolving landscape of work in the age of artificial intelligence.
January 7, 2024
"Human + Machine: Reimagining Work in the Age of AI" attempts to delve into the evolving landscape of artificial intelligence in the workplace. However, the book falls short of delivering the insightful and groundbreaking perspectives one might expect from such a topical subject.
The primary issue with "Human + Machine" is its repetitive content. The authors reiterate common ideas about AI and its potential impact on the future of work, most of which have been extensively covered in other publications and media. This lack of originality makes the book less engaging for readers who are already familiar with the subject.
Furthermore, the book's analysis appears superficial in many areas. While it touches on several important topics, such as the integration of AI in various industries and the need for new skill sets, the exploration of these themes lacks depth. The discussions feel more like an overview rather than a detailed or innovative exploration.
Another point of contention is the book's structure. The narrative flow is somewhat disjointed, making it challenging for readers to follow the authors' line of thought. This fragmented approach disrupts the cohesiveness of the book, leaving readers with a collection of loosely connected ideas rather than a comprehensive understanding of the subject.
While it attempts to address a critical and timely topic, the lack of depth, original insights, and cohesive structure significantly detracts from its potential value. Readers seeking a profound understanding of AI's impact on the future of work might find this book underwhelming.
August 27, 2023
Almost every other day, there are news stories about how A.I. is taking over the world or has run amuck in some way or another. And if you stopped there, you might be tempted to think we're all doomed. This book imagines a different future seizing on the possibilities if humans and machines are allowed to do what they do best when they collaborate together. I found this book to be very enlightening and especially enjoyed the new career paths and roles they forecasted for the future as the workforce catches up to the demands of technology. Although, I do think it could have been more balanced in talking about the threats A.I. does pose, I still found it to be a worthwhile read to demystify the industry and cut through the news with practical information and history. The real-world business scenarios and case studies are illustrative and helpful for understanding, and the language is personable, not textbook. If you want a deeper dive beyond the headlines and to build a foundation on which to understand this new world, read this book.
July 19, 2023
Very useful book to understand the artificial intelligence revolution in the business environment.
The authors begin by explaining how different companies around the world are integrating AI into the different processes of the company, making it more efficient. From its integration in the production process, to its integration in marketing and sales processes.
The authors explain the new jobs that companies will demand as well as the skills those workers will need.
The authors' ultimate goal is to explain that artificial intelligence and workers are not competitors, but friends. AI will elevate workers to more creative jobs where they will have to make use of their 'intelligence', making the jobs of the future more 'human' and less repetitive and tired. By the management of this interaction between humans and machines, we wil raise not only the potential of machines, but also the potencial of humans.
The authors begin by explaining how different companies around the world are integrating AI into the different processes of the company, making it more efficient. From its integration in the production process, to its integration in marketing and sales processes.
The authors explain the new jobs that companies will demand as well as the skills those workers will need.
The authors' ultimate goal is to explain that artificial intelligence and workers are not competitors, but friends. AI will elevate workers to more creative jobs where they will have to make use of their 'intelligence', making the jobs of the future more 'human' and less repetitive and tired. By the management of this interaction between humans and machines, we wil raise not only the potential of machines, but also the potencial of humans.
June 21, 2025
حين تقرأ هذا الكتاب، لن تشعر بأنك تتصفح مجرد صفحات تقنية، بل تدخل في حوار عميق مع المستقبل. لقد نجح المؤلفان في تبسيط فكرة معقّدة، وهي أن الذكاء الاصطناعي ليس تهديدًا بل شريكًا جديدًا في العمل. ما يلفت انتباهك هو هذا التوازن الذكي بين الرؤية الاستراتيجية والطرح العملي، حيث تُعرض نماذج واضحة، ومهارات واقعية، وأدوار جديدة لا يمكن تجاهلها. شعرت بأن الكتاب يخاطبك كقائد وصانع قرار، ويمنحك خريطة طريق للاستعداد الواعي للتحوّل الرقمي. أكثر ما يشدّنك هو مفهوم "الفضاء الهجين" الذي يعيد تعريف حدود المهام بينك وبين الآلة. أما الإضافة المتعلقة بالذكاء التوليدي، فهي لُبّ العصر، وقد طُرحت بمسؤولية تستحق التقدير. إن كنت تبحث عن دليل عملي لفهم دورك المستقبلي، فهذا الكتاب موجّه إليك بالدرجة الأولى.
تابعني على شبكات التواصل الاجتماعي
سليمان العوشن
http://about.me/aloshan
تابعني على شبكات التواصل الاجتماعي
سليمان العوشن
http://about.me/aloshan
November 8, 2024
This author is quite bullish on AI, and I have no doubt that some of his predictions will come to pass. After reading this, however, I felt a nagging urge to go read the Dune Trilogy, however, or one better, The Ransom Trilogy.
I have come to really appreciate the value of LLMs to accelerate research and writing workflows, and I think the coming rise of autonomous agents that can take actions on the internet on my behalf may have some amazing utility, but it seems that the author could use a third edition, which has been reviewed, redacted, and upended by a philosopher of science and ethicist.
I have come to really appreciate the value of LLMs to accelerate research and writing workflows, and I think the coming rise of autonomous agents that can take actions on the internet on my behalf may have some amazing utility, but it seems that the author could use a third edition, which has been reviewed, redacted, and upended by a philosopher of science and ethicist.
February 22, 2025
The authors emphasize that AI is **not a substitute for human intelligence** but a **collaborator** that enables businesses to operate in **more adaptive, data-driven, and innovative ways**.
### **Key Takeaways**
1. AI **augments** human capabilities rather than replacing them.
2. The **Missing Middle** concept describes how AI and humans **complement each other**.
3. AI should be used to **reimagine** business processes, not just automate them.
4. **High-quality data** is essential for AI success.
5. **Reskilling and upskilling** are crucial in an AI-driven workplace.
6. AI adoption must prioritize **ethics, transparency, and fairness**.
### **Key Takeaways**
1. AI **augments** human capabilities rather than replacing them.
2. The **Missing Middle** concept describes how AI and humans **complement each other**.
3. AI should be used to **reimagine** business processes, not just automate them.
4. **High-quality data** is essential for AI success.
5. **Reskilling and upskilling** are crucial in an AI-driven workplace.
6. AI adoption must prioritize **ethics, transparency, and fairness**.
July 30, 2024
What an incredibly disappointing book!
If Harvard Business Review and Accenture believed this panoply of abridged press releases from companies and venture capitalists touting their AI wares constitutes a book, I am very concerned about their research abilities.
The only reason I go 1.5 stars and not 1 is that it was interesting to read some of those examples. To get any depth though I’ll have to search elsewhere.
If Harvard Business Review and Accenture believed this panoply of abridged press releases from companies and venture capitalists touting their AI wares constitutes a book, I am very concerned about their research abilities.
The only reason I go 1.5 stars and not 1 is that it was interesting to read some of those examples. To get any depth though I’ll have to search elsewhere.
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