The Design of Future Things
Tags: #technology #design #ai #robotics #future #user experience
Authors: Donald A. Norman
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Overview
This book explores the challenges and opportunities presented by the rise of increasingly ‘intelligent’ machines in our everyday lives. I argue that the simplistic view of machines freeing us from drudgery or enslaving us is misguided. Instead, we are entering a new era of complex, sometimes frustrating, often beneficial partnerships with machines. I delve into the psychology of human-machine interaction, highlighting the crucial role of communication, feedback, and understanding. I show that machines often fail because they lack common ground with humans and cannot adequately perceive or understand our intentions and the nuances of the real world. However, I offer several design principles for creating more human-centered, collaborative technologies, drawing inspiration from the intuitive ways humans interact with the world around them. I explore the potential of ‘natural interaction,’ ‘responsive automation,’ and the importance of designing machines that ‘augment’ rather than simply ‘automate’ human capabilities. The book concludes with a look at the future of design, arguing that we need a more scientific approach to design that integrates insights from engineering, social sciences, and the arts. This book is intended for anyone interested in the future of technology and its impact on our lives, especially designers, engineers, and product managers who are creating the next generation of intelligent devices.
Book Outline
1. Cautious Cars and Cantankerous Kitchens: How Machines Take Control
This chapter introduces the problem of increasingly ‘intelligent’ machines taking control in frustrating and sometimes dangerous ways. People often respond to their car’s automation as if it has more authority than a human passenger, because the communication is one-way and the car can’t be reasoned with. We need to find better ways to interact with our increasingly autonomous machines.
Key concept: Machines have less power than humans, so they have more authority.
2. The Psychology of People & Machines
Humans rely on dialogue and back-and-forth communication to collaborate effectively. Current human-machine interaction is closer to two monologues than a true dialogue. This lack of true communication can breed distrust and makes it difficult to tailor systems to individual needs or handle unexpected situations.
Key concept: Two thousand years ago, Socrates argued that the book would destroy people’s ability to reason. He believed in dialogue, in conversation and debate. But with a book, there is no debate: the written word cannot answer back.
3. Natural Interaction
This chapter explores the concept of natural interaction, drawing inspiration from how humans interact intuitively with the world around them. Examples include the sound of a boiling kettle, ‘road feel’ in a car, and the way people navigate around bicyclists. Machines can be designed to use similar ‘natural signals’ – rich, informative, and nonintrusive – to communicate their state and guide our actions.
Key concept: Note the phrase “informing without overburdening.” That is the secret of calm, natural communication.
4. Servants of Our Machines
While technology can be beneficial, we are increasingly becoming servants to our ever more complex devices. It’s crucial to design technologies that minimize negative side effects and don’t require constant maintenance and troubleshooting. We must remember that the term ‘technology’ encompasses any tool or method, from a pencil to a smartphone.
Key concept: Tech·nol·o·gy (noun ): New stuff that doesn’t work very well or that works in mysterious, unknown ways.
5. The Role of Automation
This chapter emphasizes that automation is not always the best solution. While automation excels in well-defined, controlled environments, it often fails in complex, unpredictable situations that require human flexibility and adaptation. Examples include the Denver Airport baggage handling system and the differences between factory automation and home automation. We need to understand when to automate and when to augment human capabilities.
Key concept: “Automation always looks good on paper. . . . Sometimes you need real people
6. Communicating with Our Machines
This chapter focuses on the crucial role of feedback in human-machine interaction. Machines need to provide clear, understandable feedback about their state and actions to build trust and facilitate successful interaction. Designers often overlook this, as illustrated by the example of an unintelligible elevator system. The failure of the Apple Newton’s handwriting recognition is analyzed as a case of poor feedback.
Key concept: Feedback provides informative clues about what is happening, clues about what we should do. Without it, many simple operations fail, even one as simple as getting into an elevator.
7. The Future of Everyday Things
The future holds exciting possibilities for intelligent devices in our homes, cars, and even our clothing. Robots will become increasingly commonplace, but general-purpose robots are still far off. More immediately, we’ll see the rise of specialized robots in the form of home appliances and educational tools. Material science is also undergoing a revolution, with new materials enabling previously unimaginable possibilities. Designers need to prepare for a future where everyday objects are smart and interconnected.
Key concept: Mirror, mirror, on the wall, Does this clothing match at all?
8. Afterword: The Machine’s Point of View
As we enter a future with ever more intelligent machines, design must become more of a science with rigorous principles and methods. We need a new approach to design that combines the precision of engineering, the understanding of social interactions, and the aesthetics of art. Designers must consider the machine’s point of view as well as the human’s, working towards a future of seamless collaboration and augmentation.
Key concept: Design: The deliberate shaping of the environment in ways that satisfy individual and societal needs.
Essential Questions
1. What is the fundamental challenge in designing effective human-machine interactions?
The fundamental challenge in human-machine interaction stems from the lack of shared understanding or common ground between humans and machines. Machines, however advanced, lack the ability to fully grasp human intentions, the complexities of the real world, and the nuances of social interaction. This gulf in understanding leads to communication breakdowns, distrust, and the potential for dangerous situations. Overcoming this challenge requires designing machines that can better understand human behavior, communicate their own actions clearly, and adapt to the unpredictability of real-world situations.
2. What is the difference between ‘augmentation’ and ‘automation’ in design, and which does Norman advocate for?
Norman advocates for a design philosophy of augmentation, not automation. Augmentative design focuses on creating tools that enhance human capabilities and support human decision-making, rather than attempting to fully replace humans with autonomous systems. This approach keeps humans ‘in the loop,’ allowing them to understand, monitor, and intervene when necessary. Augmentative design prioritizes human control, flexibility, and adaptability, recognizing that machines excel in well-defined tasks but struggle with the complexities and ambiguities of real-world situations.
3. What are the key differences between human and machine cognition, and how should these differences inform design?
Designing effective interactions requires understanding the differences between human and machine cognition. Machines excel in logic, precision, and speed, while humans excel in creativity, adaptability, and social intelligence. Effective designs capitalize on the strengths of both, creating symbiotic partnerships where machines handle well-defined tasks and humans provide oversight, guidance, and handle unexpected situations. This requires careful attention to feedback, communication, and the use of ‘natural signals’ that tap into our intuitive understanding of the world.
Key Takeaways
1. Design for Natural Interaction
Instead of relying solely on explicit alerts and alarms, machines can use subtle, intuitive cues that mimic the natural world to communicate their state and guide our actions. This approach, inspired by the way humans naturally interact with their environment, can be less intrusive, more informative, and facilitate better situation awareness.
Practical Application:
A self-driving car could use subtle vibrations in the steering wheel to communicate to the driver the car’s awareness of nearby vehicles or lane boundaries, creating a ‘natural’ feeling of connection to the road even when the car is in control. This could help maintain situation awareness and facilitate smoother transitions of control when needed.
2. Prioritize Augmentative Design over Automation
Augmentative systems aim to enhance human capabilities rather than replace them. They provide information, suggestions, and tools that support decision-making, allowing users to understand, monitor, and intervene in the operation of the system. This fosters trust, adaptability, and personalization.
Practical Application:
In a smart home, instead of automatically adjusting the temperature based on assumed preferences, the system could offer suggestions like, ‘It looks like you’re home early. Would you like me to warm up the house?’ This gives the user control and helps the system learn individual preferences over time.
3. Design for Understandable Feedback
Clear, understandable feedback is essential for building trust and facilitating effective interaction with machines. When systems can explain their reasoning process and the factors they considered, users can better understand their actions and make informed decisions about whether to trust or override their recommendations.
Practical Application:
An AI-powered medical diagnosis system could explain its reasoning process in a way that is understandable to both doctors and patients, showing which factors it considered and how it arrived at its conclusions. This builds trust, allows for human oversight, and helps identify potential biases or errors in the AI’s reasoning.
Suggested Deep Dive
Chapter: Chapter 3: Natural Interaction
This chapter offers a wealth of concrete examples and design principles for creating more intuitive, human-centered interactions. The discussion of ‘natural signals’ and the ‘playbook’ concept are particularly valuable for AI product engineers.
Memorable Quotes
Chapter 1: Cautious Cars and Cantankerous Kitchens. 9
Machines have less power than humans, so they have more authority.
Chapter 2: The Psychology of People & Machines. 49
Communication and negotiation require what linguists call a “common ground”: a shared basis of understanding that serves as the platform for the interaction.
Chapter 3: Natural Interaction. 149
Note the phrase “informing without overburdening.” That is the secret of calm, natural communication.
Chapter 4: Servants of Our Machines. 95
Tech·nol·o·gy (noun ): New stuff that doesn’t work very well or that works in mysterious, unknown ways.
Chapter 5: The Role of Automation. 131
“Automation always looks good on paper. . . . Sometimes you need real people”
Comparative Analysis
This book stands as a seminal work in the field of human-computer interaction, predating the widespread adoption of smartphones and the current AI boom. While other contemporary works, like Reeves and Nass’s ‘The Media Equation,’ explored how people treat computers as social actors, Norman goes further by analyzing the fundamental differences between human and machine cognition, particularly the lack of common ground. He anticipates the challenges of designing for complex, autonomous systems, a topic that has gained even greater urgency in recent years with the rise of self-driving cars and other AI-powered technologies. His focus on ‘natural interaction’ and ‘augmentative design’ aligns with the principles of ‘human-centered AI’ that are now widely advocated for in the AI ethics community. However, the book predates the significant advancements in machine learning and natural language processing that have since occurred, making some of his technological predictions seem outdated. Nonetheless, Norman’s core insights about the psychology of human-machine interaction remain highly relevant today.
Reflection
This book remains a valuable read for anyone designing or building AI-powered products, even though it was written before the current wave of AI advancements. It provides a psychological foundation for understanding how people interact with machines and highlights enduring design principles that are often overlooked in the rush to create ‘smarter’ technologies. While some of the specific technological examples may seem outdated, Norman’s core message about the importance of common ground, natural interaction, and augmentative design resonates even more strongly today as we face the challenges of integrating ever more autonomous systems into our lives. One potential weakness is the book’s somewhat pessimistic view of machines’ ability to understand and adapt to human behavior. While the ‘gulf of common ground’ is undoubtedly a challenge, recent advances in AI, particularly in natural language processing and machine learning, suggest that machines may become more capable of understanding human intentions and adapting to real-world complexities than Norman envisioned. Nonetheless, this book serves as a powerful reminder that successful technology design requires a deep understanding of human psychology and a commitment to creating systems that augment human capabilities, not simply replace them.
Flashcards
What is an affordance?
The range of activities that an animal or person can perform upon an object in the world.
What is common ground in the context of human-machine interaction?
Shared understanding between humans and machines, which is essential for effective communication.
What is augmentative design?
A design approach that enhances human capabilities and keeps humans ‘in the loop,’ rather than attempting to fully replace them with autonomous systems.
What is automation?
A design approach that focuses on creating tools and systems that operate automatically without human intervention.
What are natural signals?
A design principle that encourages the use of rich, intuitive signals that mimic the natural world to provide feedback and communicate information.
What is overautomation?
A tendency to over-rely on automated systems, even when they exhibit problems, leading to decreased situation awareness and slower response times when human intervention is required.