Working with AI: Real Stories of Human-Machine Collaboration
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- Type：Epub+TxT+PDF+Mobi
- Create Date：2022-10-28 06:52:38
- Update Date：2025-09-06
- Status：finish
- Author：Thomas H Davenport
- ISBN：0262047241
- Environment：PC/Android/iPhone/iPad/Kindle
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Summary
Two management and technology experts show that AI is not a job destroyer， exploring worker-AI collaboration in real-world work settings。
This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled--"smart"--systems at work。 Management and technology experts Thomas Davenport and Steven Miller show that， contrary to widespread predictions， prescriptions， and denunciations， AI is not primarily a job destroyer。 Rather， AI changes the way we work--by taking over some tasks but not entire jobs， freeing people to do other， more important and more challenging work。 By offering detailed， real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor， Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation。 It is happening now to many companies and workers。
These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time， allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy， a robotic assistant for fast food preparation。 For each one， Davenport and Miller describe in detail the work context for the system， interviewing job incumbents， managers， and technology vendors。 Short "insight" chapters draw out common themes and consider the implications of human collaboration with smart systems。
This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled--"smart"--systems at work。 Management and technology experts Thomas Davenport and Steven Miller show that， contrary to widespread predictions， prescriptions， and denunciations， AI is not primarily a job destroyer。 Rather， AI changes the way we work--by taking over some tasks but not entire jobs， freeing people to do other， more important and more challenging work。 By offering detailed， real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor， Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation。 It is happening now to many companies and workers。
These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time， allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy， a robotic assistant for fast food preparation。 For each one， Davenport and Miller describe in detail the work context for the system， interviewing job incumbents， managers， and technology vendors。 Short "insight" chapters draw out common themes and consider the implications of human collaboration with smart systems。
Reviews
Brian Clegg
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There have been plenty of books on the use of artificial intelligence （AI） and how it will impact our lives from the dire warnings of Cathy O'Neil's Weapons of Math Destruction to Melanie Mitchell's in-depth exploration of the technology Artificial Intelligence， but in Working with AI， Thomas Davenport and Steven Miller give us a new viewpoint that is interesting， if a little worrying。 If we compare writing about AI with the Star Wars movies， it's as if almost every AI book I've read so far， lik There have been plenty of books on the use of artificial intelligence （AI） and how it will impact our lives from the dire warnings of Cathy O'Neil's Weapons of Math Destruction to Melanie Mitchell's in-depth exploration of the technology Artificial Intelligence， but in Working with AI， Thomas Davenport and Steven Miller give us a new viewpoint that is interesting， if a little worrying。 If we compare writing about AI with the Star Wars movies， it's as if almost every AI book I've read so far， like the films， has been written from the viewpoint of the rebels。 But this is a book that solidly takes the viewpoint of the empire。Unfortunately， although it covers a fair number of AI applications， it's also written more like a business book that a popular science/technology book， and as such it's pretty dull。 Anyone familiar with the business book genre will recognise that deadly moment when you get to a box that's a case study。 It's going to be boring。 This book contains 29 case studies， one after the other， by the end of which I was quietly groaning。However， there were definitely some insights to be gained here。 In that range of case studies， there were several standouts。 The main thesis that Davenport and Miller are proposing is that， despite some issues， artificial intelligence will not destroy vast swathes of jobs， but will instead improve them by taking on the boring bits， not （on the whole） displacing humans， but working alongside them。 Perhaps the best example of this was the robotic weed picker， which made a farm worker's job more interesting and did something that， frankly， no human really wants to do。 Admittedly， in this kind of application there would be fewer humans employed， but it feels like a genuinely beneficial change。What was worrying， though， in the dark side orientation of this book was that there was very little consideration of some of the other potential negatives of AI - in fact， it felt the authors were almost celebrating some of these。 Several case studies highlighted this approach， for example one on using AI to support a help desk， a couple on making decisions on issuing insurance policies and mortgages and one on policing。The help desk example felt particularly insidious。 The idea was that the software monitored conversations between customers and the help desk to improve the quality of interactions。 But apart from a passing mention of it， the authors don't really acknowledge the Big Brother aspect of software checking your every word， rating your performance and pushing you into conformity with the required groupthink。 Similarly， we heard about all the advantages for the companies using software to decide if customers should be given an insurance policy or mortgage， but not the well-documented problems raised by opaque machine learning systems using entirely unsuitable data to reject individuals。 The policing example is an infamous one， and the authors had to acknowledge there have been serious problems with such systems producing racist results and making particular areas even worse than they were before， but merely say this has to be avoided， without giving any evidence that this is even possible to do。I'm sure Davenport and Miller thought they were doing something useful in focusing on the ways that AI will not necessarily replace human workers but rather would augment their abilities。 But I don't think it's possible， as was done here， to ignore some of the other dangers of AI like lack of transparency， misuse of data， surveillance and more。 You have to take the view across the board。 I'd suggest this book is important reading to get a balanced picture of AI， if you can cope with the kind of mangled business-speak sentences that crop up， such as 'She works particularly at the top of the prospect funnel， trying to move leads along in the sales process and operationalize a disciplined prospecting and selling process。' The book does illustrate a few examples where having an AI helper can be genuinely beneficial to workers。 And plenty more where it can benefit companies to the disadvantage of either workers or customers。 This is surely valuable data， whether you side with Luke Skywalker or Darth Vader。 。。。more
Kevin Postlewaite
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