Hace tiempo que me tope con el libro de Ellen y Julia Lupton, Diseña tu vida, en el conocí la pregunta “Qué te permite”. A través de una graciosa lectura, viví las primeras descripciones sobre nuestras interacciones con objetos de la vida diaria desde ese punto de vista nuevo. No se trata de usar el objeto como esta diseñado para ser usado, si no ver al objeto como ese medio que me permite hacer tantas otras cosas.
El encuentro en mi caso, con las posibilidades del diseño, han estado mucho más tiempo relacionadas con necesidades comerciales y eso me ha enseñado que vender esta lleno de posibilidades para el diseño. Afortunadamente el mundo está girando a gran velocidad y ustedes ahora cuentan con otros recursos, ahora cuentan con más experiencias de las que podrán capitalizar.
Con ese fin les comparto una selección de episodios de un programa que escucho con mucha frecuencia y hace ya años. Se llama 99% Invisible. Visítenlo y sobre todo, les recomiendo escuchen la selección que he hecho para ustedes. Estoy seguro que encontrarán ideas, principios y puntos de vista sobre temas que ya conocen y otros de los que no se imaginaban. Agregue un par de vínculos adicionales pero la verdad es que cada Podcast y sus ligas, ya contienen suficientes referencias para que ustedes tengan una buena inmersión en el.
Hay tres episodios que me parecieron los más relevantes.
Las interfaces gráficas futuristas en su mayoría son azules.
Si hay tantos letreros que dicen que no entres, entonces debe ser un gran lugar.
Suerte y quedo atento a sus propuestas.
by all things. I’m passionate to discover its expressions and find what triggers the best of each.
This manifesto was first published in 1999 in Emigre 51.
There are pursuits more worthy of our problem-solving skills. Unprecedented environmental, social and cultural crises demand our attention. Many cultural interventions, social marketing campaigns, books, magazines, exhibitions, educational tools, television programs, films, charitable causes and other information design projects urgently require our expertise and help.
We propose a reversal of priorities in favor of more useful, lasting and democratic forms of communication – a mindshift away from product marketing and toward the exploration and production of a new kind of meaning. The scope of debate is shrinking; it must expand. Consumerism is running uncontested; it must be challenged by other perspectives expressed, in part, through the visual languages and resources of design.
And a copy of the 164 manifesto written by Ken Garland along with 20 other artists.
STUART LESLIE, PRESIDENT AND FOUNDER OF 4SIGHT INC, OFFERS SIX TIPS FOR PACKAGING YOUR PRODUCT AND CAPTURING CONSUMER ATTENTION.
We know that consumer purchase decisions are often made quickly and subconsciously, but there are opportunities where it’s possible to influence a consumer’s perception of a brand. People often make buying decisions by using all five of their senses and once product designers discover what each of these sensory influencers are, they can develop packaging that strategically speaks to consumers at each stage of the decision-making process. It’s ultimately about designing a complete experience–one that supports the brand every step of the way.
At my company, we developed the 4sight Sensory Lab, pictured above, to uncover these answers. Here, for example, cold beverage drinkers known to prefer their drinks not simply cold, but chilled to the perfect temperature, are taken through a progression of exercises that mimics the various points of contact that consumers have with a product.
IT’S ABOUT DESIGNING A COMPLETE EXPERIENCE–ONE THAT SUPPORTS THE BRAND EVERY STEP OF THE WAY.
We identify which bottle shape, size, color, material, and texture promises that sense of cold refreshment at first glance. As the test subjects move closer, details such as condensation and frost become evident and when they are handed several bottles, each chilled to the exact same temperature–but made of different materials, textures, shapes and finishes–they provide feedback on which one feels like just the right cold.
This is the first impression at a distance, seeing the product in someone else’s hand, on the shelf, or across the room. It’s the first visual promise of what a product will do for your senses. For Pom 100% Pomegranate Juice, the distinctive profile of the bottle featuring those fully rounded spheres, allows the distinct dark red color of the juice to catch the attention of a shopper. It promises a bold, robust taste. A new entry into the tequila segment, SX Tequila chose a distinctive, curvaceous bottle with smooth lines and frosted texture to communicate the sense of a smooth-tasting, chilled beverage.
Here, consumers take a closer look and this is where details begin to hint at tactile sensations. Flowing details etched into the structure of the Aquafina water bottle strongly suggest the refreshment that the product provides.
Orangina, meanwhile, promises its fresh orange flavor through a dimpled finish on the bottle that suggests you are consuming straight from an actual orange.
Next, consumers make that first physical contact and combine the visual with the tactile experience. When grasped, the gentle curvature of the Febreze bottle and the angled spray head convey the soft and pleasant aroma that will fill the air. The smooth, diagonal neck on the new Miller Lite Bottle promises a refreshing flow of beer while the bold taper from the neck to the body provides a strong and confident grip for the hand. Adding the texture of the hops etched in the glass provides further engagement.
When the consumer makes a physical step towards consumption or use of the product, there’s another opportunity to solidify your brand’s perception. When the foil cover is peeled off of a can of San Pellegrino, it offers the sensation of actually peeling fruit. It also incorporates a crinkling sound, which adds to the sensory experience at opening.
The point at which the product is consumed or used and here, all five senses can be at play.
A smooth metal tip on Clinique’s Even Better Eyes product provides a refreshing and reviving cold sensation on the skin. For Gerber Good Start, the designated scoop holder on the side of the container provides for a clean usage experience and preserves the product for future consumption, as fingers do not contaminate the powder.
There’s another opportunity to create a pleasant user experience when the product is disposed of or put away for later use. Wrigley 5 Gum incorporates a lock feature and embossed details to convey a secure and clean resealable pack. The Oreo cookie package also utilizes the sense of sight with a resealable film to promise lasting freshness. Once the film is replaced after each usage, it recreates the look of a fresh, unopened package.
In The Sensory Lab, we’ve gleaned significant insight into how the five senses influence consumer decision-making at six pivotal points. Incorporating a similar approach in your design process will help insure your package effectively communicates key brand attributes at each and every point of influence.
It’s not about selling, it’s about giving control to the people.
The future of branding belongs to storytellers who understand the hero’s journey in the context of modern, mobile life. The hero’s journey is a storytelling structure pervasive across cultures. It starts with a call to adventure, requires that the hero be connected to others, including a mentor. The hero will face extremely difficult challenges along the way. The hero ultimately wins and returns home, armed with new knowledge about herself, other people and the world.
Does your brand inspire people to respond to the call for adventure, whether through providing information, tools or a catalyst? Does it help them overcome the obstacles they will face on the path, either by making sure they have nourishment, transportation, tools, information or access to other people? Does it provide guidance, support, or a framework in which the story of the process, with all its ups and downs, can be documented and shared in real time? If your brand doesn’t serve any of the segments in the hero’s journey, you’re right to be concerned about the future.
Cecelia Wogan-Silva, the director of creative agency development at Google is tasked with growing brand advertising through Google’s platform. She accomplishes this, in large part, by inspiring thoughtful collaboration with intriguing insights and co-ideating with creative agencies at the beginning of the process instead of jumping in when distribution is the last bit of conversation left.
The perceived need to master emerging technologies and engineer a viral video dominates much of the conversation in the world of branding. Clients want measurable proof of eyeballs on the screen, and creatives struggle with the expectation that they’ll be able to engineer a hit. But what is a hit? The trend toward the mean-spirited shock video filled with actors faking real-time reactions to disgusting pranks is the result of the mistaken belief that eyeballs equal success. This mentality is largely a relic of the measurement of success in television advertising, which isn’t surprising. The history of the advertising industry, Wogan-Silva said, is a string of attempts to reincarnate what came before in a new medium.
“There’s this automatic inclination to believe that new technology is creativity’s silver bullet. But invention of technology is different than innovative use of existing things. Great TV wasn’t born from the new platform from the get go. But the stories got better, the use of bookends in commercial buying was a new variation that came from careful, deeper consideration for what could be done with this amazing medium.
Wogan-Silva believes that the concept of being a slave to the latest technology fad or ad unit will become a thing of the past.
My sense of what a brand can do for me doesn’t come in the form of what it promises, but what it delivers to me.
Intimacy will come in many forms in the future. Not only will objects be connected to each other, but they will be connected to you. Businesses will know more about you, your habits, the bits of data that together compose the very shape and texture of your life. All of this will be connected through objects on us and even in us, as well as in the cloud, that nebulous concept that is becoming more tangible all the time.
Drew Ormrod, Ogilvy’s Worldwide Account Director for IBM Midmarket, which serves small and mid-sized companies. Science House, where I’m the EVP for Business Development, is collaborating with IBM on a project that Ormrod manages from the Ogilvy side. In recent years, he has seen the evolution of consumer values head toward a greater need for trust and transparency.
“Customers want to buy what they need and not a bit more,” Ormrod said. “Also, they want to understand what they’re buying. As consumers develop a taste for the new from freshly-hatched web companies without excess baggage, established brands are turning toward a new model for innovation, often called Labs. Smaller, more agile and often beyond the usual rules of a company, Labs are expected to drive innovation to market from within a traditional company to allow them to compete with new brands. The new consumer is better connected, forms opinions faster and has a better understanding of how systems work.” This new knowledge can come paired with distrust toward traditional brands in favor of those born on the web.
The future is built on more intelligent connections.
What does that mean, exactly? It means that brands like Zappos and Seamless, Airbnb, Kickstarter, and others are enabling the digital, mobile realm to serve as a portal into increased real-life access to goods, services, and new experiences. It also means that data is enabling companies to tailor those experiences to customers in real time, right where they are in the physical world.
The brand isn’t the hero, it is an enabler of the journey the customer is on. That requires a lot of listening, in order to understand the challenges each customer faces, and customization, in order to meet those needs. Ultimately, it requires the delivery of simplicity in an increasingly complex world. When the hero does get home after battling the forces of nature and humanity, she might want Uber to get her there and Seamless to deliver tacos right away. Adventure is hard work.
What Astronauts And Toddlers Can Teach You About Consumers. Via: FastCo.
WHEN COLLECTING DATA ON CONSUMER BEHAVIOR, TUNE INTO THE NOISE–THE PATTERNS THAT DRIVE HUMAN PERCEPTION, ARGUES METHOD’S PAUL VALERIO.
This is the newest piece from design and innovation firm, Method, in their10×10 series. Click here to download a PDF of the article.
If you were forced to rely on only two target audiences to guide all your future design work, I’d strongly recommend using astronauts and toddlers. Fortunately, the connection between them goes beyond the design of their underwear to the nature of perception and expertise, and in what we treat as valid data, and what we choose to ignore as “noise”–the extraneous details, out-of-category input, the anecdotal tidbits. As it turns out, noise is much more valuable for useful design insights than you might think.
First, the astronauts. One little-known quirk of the Apollo moon landings was the difficulty the astronauts had judging distances on the Moon. The most dramatic example of this problem occurred in 1971 during Apollo 14, when Alan Shepard and Edgar Mitchell were tasked with examining the 1,000-foot-wide Cone Crater after landing their spacecraft less than a mile away. After a long, exhausting uphill walk in their awkward space suits, they just couldn’t identify the rim of the crater. Finally, perplexed, frustrated, and with the oxygen levels in their suits running low, they were forced to turn back. Forty years later, high-resolution images from new lunar satellites showed they had indeed come close–the trail of their footprints, still perfectly preserved in the soil, stop less than 100 feet from the rim of the crater. A huge, 1,000-foot-wide crater, and they couldn’t tell they were practically right on top of it. Why?
It should have been easy for them, right? These guys were trained as Navy test pilots; landing jets on aircraft carriers requires some expertise in distance judgment. They also had detailed plans and maps for their mission and had the support of an entire team of engineers on Earth. But their expertise was actually part of the core problem. The data their minds were trying to process was too good. All of the “noise” essential to creating the patterns their minds needed to process the data accurately was missing. And patterns are the key to human perception, especially for experts.
Consider everything that was missing up there. First, there’s no air on the Moon, so there’s no atmospheric haze, either. Eyes that grew up on Earth expect more distant objects to appear lighter in color and have softer edges than closer things. Yet everything on the Moon looks tack-sharp, regardless of distance. Second, the lack of trees, telephone poles, and other familiar objects left no reference points for comparison. Third, since the Moon is much smaller than the Earth, the horizon is closer, thus ruining another reliable benchmark. Finally, the odd combination of harsh, brilliant sunshine with a pitch-black sky created cognitive dissonance, causing the brain to doubt the validity of everything it saw.
Ironically, that kind of truthful, distortion-free data is usually what experience designers want to have as input for their decision-making, no matter what they’re trying to do. We tend to believe that complex systems are the tidy, linear sum of the individual variables that create them. But despite the pristine environment of the Moon, the Apollo astronauts were repeatedly baffled when it came to simple distance and size perceptions, even after each team came back from the Moon and told the next team to be aware of it.
Meanwhile, the toddlers I mentioned earlier provide a corresponding example of the power of patterns in perception. When my first child was about 4, we came across a wonderful series of picture books called Look-Alikes, created by the late Joan Steiner. Each book has a collection of staged photographs of miniature everyday scenes like railway stations, city skylines, and amusement parks created entirely from common, found objects (see some examples here). Without any special adornment, a drink thermos masquerades as a locomotive, scissors become a ferris wheel, and even a hand grenade makes for a very convincing pot-belly stove. The entire game is to un-see the familiarity of the scene, and identify all the common objects ludicrously pretending to be something other than what they are. There’s no trick photography involved, but you can look at each picture for hours and not “see” everything that’s right there in front of you. You know it’s a trick, but you keep falling for it over and over.
WE PERCEIVE OUR WAY THROUGH LIFE; WE DON’T THINK OUR WAY THROUGH IT.
The really amazing part is that the toddler, a true novice with only a few years’ experience in seeing, completely understands the scenes she’s looking at, even though every individual piece of “data” she’s looking at is a deliberate lie. Yet the pattern of data that creates the scene is “perfect.” We already know what those scenes are supposed to look like before we even see the book’s version of them, so we unconsciously project that pattern onto what we’re looking at, even to the point of constantly rejecting the contrary data our eyes are showing us. There is in fact no amusement park in the photograph I called an amusement park. But I see it anyway.
In data-processing parlance, the signal-to-noise ratio of the moonscape was perfect (actually, infinitely high), and zero for Look-Alikes pages (the whole joke is that there really was no signal there in the first place). Yet a toddler can read the noisy scene perfectly, and the seasoned test pilots were baffled by the noiseless scene. How can this be?
The lesson is that patterns drive perception more so than the integrity of the data that create the patterns. We perceive our way through life; we don’t think our way through it. Thinking is what we do after we realize that our perception has failed us somehow. But because pattern recognition is so powerfully efficient, it’s our default state. The thinking part? Not so much.
This just might be why online grocery shopping has yet to really take off. The average large U.S. supermarket offers about 50,000 SKUs, yet a weekly grocery shopper can easily get a complete trip done in about 30 minutes. We certainly don’t feel like we’re making 50,000 yes/no decisions to make that trip, but in effect we actually do. Put that same huge selection online, and all of those decisions are indeed conscious. Even though grocery shopping is a repetitive, list-based task, the in-store noise of all those products that aren’t on your list give you essential cues to finding the ones that are, and in reminding you of those that were not on your list but you still need. That’s even before you get to the detail level, where all the other sensory cues tell you which bunch of bananas is just right for you. So despite all the extra effort and hassle involved in going to the store in person, it still works better because of, not in spite of, the patterns of extraneous noise you have to process to get the job done.
THE RESEARCH WE USE USUALLY TRIES TO DISMANTLE COMPLEXITY.
To account for the role of noise within the essential skill of pattern recognition, we need to remind ourselves how complex seemingly simple tasks really are. Visually reading a scene, whether it’s a moonscape, a children’s book illustration, a grocery store, or a redesigned website, is an inherently complex task. Whenever people are faced with complexity (i.e., all day, every day), they use pattern recognition to identify, decipher, and understand what’s going on instantly, instead of examining each component individually. The catch is that all of the valuable consumer thought processes we want to address–understanding, passion, persuasion, the decision to act–are complex.
However, the research we use to help us design for these situations usually tries to dismantle this complexity. It also assumes a user who is actually paying attention, undistracted, in a clean and quiet environment (such as a market research facility), and cares deeply about the topic. Then we “clean” the data we collect, in an attempt to remove the noise. And getting rid of noise destroys the patterns that enable people to navigate those complex functions. So we wind up relying on an approach that does a poor job of modeling the system we’re trying to influence.
The challenge is to overcome the seemingly paradoxical notion that paying attention to factors completely outside our topic of interest actually improves our understanding of that topic. Doing so requires acknowledging that our target audience may not care as much about something as we do, even if that topic represents our entire livelihood. It requires a broader definition of the boundaries of what that topic is, and including the often chaotic context that surrounds it in the real world. It also requires a more than casual comfort level with ambiguity: Truly understanding complex systems involves recognizing how unpredictable, and often counterintuitive, they really are.
Check out how to develop your own “Noisy, Dirty Shortcuts” here.
This is why ethnographic research is so popular with all kinds of designers. The rich context ethnographies offer is full of useful noise; the improvising people do to actually use a product, the ancillary details that surround it, and the unexpected motivations a consumer might bring to its use. These are all easier to access via a qualitative, on-location approach than they are via a set of quantitative crosstabs or sitting behind a mirror watching a focus group. It’s also a powerful human-to-human interface, in which the designer uses his innate pattern-recognition capability to analyze patterns in user behavior.
PAYING ATTENTION TO FACTORS OUTSIDE OUR TOPIC OF INTEREST ACTUALLY IMPROVES OUR UNDERSTANDING OF IT.
What often gets overlooked is the role noise can and should play in quantitative research. Most designers’ avoid quantitative research because of the clinically dry nature of the charts it produces, and the often false sense of authority that statistically projectable data can wield. However, only quantitative research can reveal the kind of perceptual patterns that are invisible to qualitative methods, and the results needn’t be dry at all. The solution is to appropriately introduce the right kind of noise to quantitative research, to deliberately drop in the necessary telephone poles, trees, and haze that allows those higher-level perceptual patterns to be seen and interpreted.
Fortunately, there’s already a model for this. When analog music is digitally recorded, some of the higher highs and lower lows are lost in the conversion. Through a process called dithering, audio engineers can add randomized audio noise to the digital signal. Strangely enough, even though the added noise has nothing to do with the original music, adding it actually improves the perceived quality of the digital audio file. The noise fills in the gaps left by the analog-to-digital conversion, essentially tricking your ear into hearing a more natural-sounding sound. The dithered audio really isn’t more accurate, it just sounds better, which is more important than accuracy. Returning to our opening examples, the moonscape was in dire need of dithering, while the Look-Alikes scenes were already heavily dithered. And the real world in general is heavily dithered.
So, for quantitative research aimed at guiding the design process, the trick is to value meaning above accuracy. Meaning can be gleaned via the noise you can add to the quantitative research process by including metrics outside the direct realm of your topic area. It means considering what else is adjacent to that topic area, acknowledging the importance of respondent indifference as well as their preferences, and recognizing what kind of potentially irrational motivations are behind the respondents’ approach to the topic, or the research itself.
At Method, we’ve developed a technique for observing these perceptual patterns in quantitative data by using perceptions of brands far afield of the category we’re designing for. Essentially, it’s a dithering technique for brand perceptions. This technique often displays an uncanny knack for generating those hiding-in-plain-sight aha moments that drive really useful insights. There are doubtless many other approaches you can employ once you make the leap that acknowledges the usefulness of noise in your analysis.
Read about Method’s brand context research technique.
• A LITTLE HUMILITY WORKS WONDERS.
Recognizing that you’re not the center of your target audience’s universe allows you to understand how you fit in. Be sure to take honest stock of just where your target audience places your topic area on their list of priorities.
• STEP BACK FAR ENOUGH TO ALLOW PATTERNS TO EMERGE.
No matter what metrics you’re using, consider looking several levels above them–or next to them–to identify patterns that are impossible to see when you’re too close to the subject.
• GAUGE THE LEVEL OF EXPERTISE OF YOUR TARGET AUDIENCE.
How familiar is your target audience with your subject? Are they experts or novices, and how are you defining that? Generally, the higher the level of expertise, the higher the dependence on pattern recognition. Novices carefully and slowly compare details; experts read patterns quickly and act decisively.
• CHECK THE DATA DUMPSTER BEFORE EMPTYING.
No matter where your data comes from, think about what has been omitted. Was that distracting noise that was tossed, or crucial context?
By taking a look at the entire picture–instead of isolating a single data point–you open up opportunities for understanding the motivations, reasons, and outlying factors that impact data. Contrary to popular practice of stripping out noise, noise is in fact critical to the generation of deep insights that allow us to design better and more effective brands, products, and services.
The burgeoning Latin American digital media market represents an amazing opportunity for content creators. Representing more than 7% of global Internet users, Latin America is home to emerging markets, Brazil and Argentina, where 79% and 28% of the population consumes content on the Web, respectively — a combined population of more than 100 million. If you add Mexico to the list, where 30% of the country’s 112 million people use the Internet, the list grows to 130 million Internet users.
In Latin America, Facebook accounted for 25% of all time spent online and social networking in general accounted for nearly 30% of online minutes at the end of the year, an increase of 9.5% over the past year. In addition to social media usage, online video consumption increased more than 10% across Brazil, Mexico, Argentina and Chile, and online retail visits increased 30%. The number of searches in 2011 increased 38% to more than 21 billion and, with an average of 173 searches per searcher, Latin America leads the globe in search frequency.
The U.S. Hispanic market represents an equally important demographic. More than 33 million Hispanics were online in September of last year, representing 15% of the U.S. online market, a demographic that is growing three times faster than the general market online. Eighty percent of online Hispanics use a search engine each month and 80% of online Hispanics visit Facebook each month.
Content creators must focus on the Latin American and U.S. Hispanic markets in order to maximize overall content viewership and engagement. Reaching English-speaking content consumers in the U.S. and south of the border has never been more important and will only become more important in the coming years. Moreover, creating and distributing Spanish-language content in the U.S. and Latin America is an equally important objective.
Understanding and working within these communities will enable brands and publishers to attract a portion of the world that will dominate digital content consumption in the coming years. The creation of relevant content and finding partners to help distribute that content must be among your top priorities.
I am always on the lookout for ways to improve my scientific thinking. That’s why I have an interest in the areas of sociology concerned with decision making in groups and how the individual is influenced by this. And this is also why I have an interest in cognitive biases – intuitive judgments that we make without even noticing; judgments which are just fine most of the time but can be scientifically fallacious. Daniel Kahneman’s book “Thinking, fast and slow” is an excellent introduction to the topic.
Kahneman, winner of the Nobel Price for Economics in 2002, focuses mostly on his own work, but that covers a lot of ground. He starts with distinguishing between two different modes in which we make decisions, a fast and intuitive one, and a slow, more deliberate one. Then he explains how fast intuitions lead us astray in certain circumstances.
The human brain does not make very accurate statistical computations without deliberate effort. But often we don’t make such an effort. Instead, we use shortcuts. We substitute questions, extrapolate from available memories, and try to construct plausible and coherent stories. We tend to underestimate uncertainty, are influenced by the way questions are framed, and our intuition is skewed by irrelevant details.
Kahneman quotes and summarizes a large amount of studies that have been performed, in most cases with sample questions. He offers explanations for the results when available, and also points out where the limits of present understanding are. In the later parts of the book he elaborates on the relevance of these findings about the way humans make decision for economics. While I had previously come across a big part of the studies that he summarizes in the early chapters, the relation to economics had not been very clear to me, and I found this part enlightening. I now understand my problems trying to tell economists that humans do have inconsistent preferences.
The book introduces a lot of terminology, and at the end of each chapter the reader finds a few examples for how to use them in everyday situations. “He likes the project, so he thinks its costs are low and its benefits are high. Nice example of the affect heuristic.” “We are making an additional investment because we not want to admit failure. This is an instance of the sunk-cost fallacy.” Initially, I found these examples somewhat awkward. But awkward or not, they serve very well for the purpose of putting the terminology in context.
The book is well written, reads smoothly, is well organized, and thoroughly referenced. As a bonus, the appendix contains reprints of Kahneman’s two most influential papers that contain somewhat more details than the summary in the text. He narrates along the story of his own research projects and how they came into being which I found a little tiresome after he elaborated on the third dramatic insight that he had about his own cognitive bias. Or maybe I’m just jealous because a Nobel Prize winning insight in theoretical physics isn’t going to come by that way.
I have found this book very useful in my effort to understand myself and the world around me. I have only two complaints. One is that despite all the talk about the relevance of proper statistics, Kahneman does not mention the statistical significance of any of the results that he talks about. Now, this is all research which started two or three decades ago, so I have little doubt that the effects he talks about are indeed meanwhile well established, and, hey, he got a Nobel Prize after all. Yet, if it wasn’t for that I’d have to consider the possibility that some of these effects will vanish as statistical artifacts. Second, he does not at any time actually explain to the reader the basics of probability theory and Bayesian inference, though he uses it repeatedly. This, unfortunately, limits the usefulness of the book dramatically if you don’t already know how to compute probabilities. It is particularly bad when he gives a terribly vague explanation of correlation. Really, the book would have been so much better if it had at least an appendix with some of the relevant definitions and equations.
That having been said, if you know a little about statistics you will probably find, like I did, that you’ve learned to avoid at least some of the cognitive biases that deal with explicit ratios and percentages, and different ways to frame these questions. I’ve also found that when it comes to risks and losses my tolerance apparently does not agree with that of the majority of participants in the studies he quotes. Not sure why that is. Either way, whether or not you are subject to any specific bias that Kahneman writes about, the frequency by which they appear make them relevant to understand the way human society works, and they also offer a way to improve our decision making.
In summary, it’s a well-written and thoroughly useful book that is interesting for everybody with an interest in human decision-making and its shortcomings. I’d give this book four out of five stars.
Below are some passages that I marked that gave me something to think. This will give you a flavor what the book is about.