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Simplifying complex ideas through fun and insightful sketches. Explore topics from science, creativity, psychology, and more explained in pictures.

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The Automation Paradox

The Automation Paradox is that the better our machines get, the more we struggle when they fail. When heading out for a hike in the woods, it's tempting to skip the map and compass and rely on our phones and apps for navigation. Yet when we encounter no signal or lose power, we can find ourselves in a sticky situation. Or perhaps, like me, you've come to rely on popping your destination into the satnav or Google Maps whenever you get in the car and have nearly forgotten the ability to navigate without it. These situations illustrate the paradox of automation, where the more sophisticated and automated our machines and technologies become, the more bewildered we find ourselves when they inevitably fail. Or: the smarter the machines get, the dumber we might get. In his book Messy, Tim Harford suggests three strands to the paradox as our machines get more sophisticated: Automation covers up our mistakes, hiding our incompetence, meaning we may not learn to correct ourselves—consider autocorrect cleaning up our typos as we go. When we rely on automation, we get less practice for our skills, so even highly skilled individuals may find their expertise diminishing—perhaps you've found yourself using your phone calculator for a trivial calculation. When the easy scenarios are taken care of, failures may occur in complex or unpredictable ways that we may find especially difficult to recover from—like a subtle but persistent failure in the steering of a passenger plane, recovering from a skid on an icy road, or when you're deeply lost in the wilderness. More sophisticated technology can even make it useless or more dangerous when it fails. Older cars used to be reparable forever. Now, if your vehicle fails, it's likely to need plugging in at the dealership to figure out what's up. How many electronic devices are thrown away because somewhere inside, some tiny loose connection or component makes the whole thing worthless? Were pilots and flight crews better prepared and able to improvise before the autopilot became ubiquitous? I often wish our devices would fail more like an escalator or an electric toothbrush. If an escalator fails, you can still walk up it. If your electric toothbrush dies, you can still use it to brush your teeth. These could be called Technology-Enhanced Products, perhaps. But when most of our devices die, they're often rendered worthless. Automation and sophisticated machines help me so much. I did use Grammarly to help check this post. I use Google Maps nearly every time I put in my destination to home, and I often use a calculator to check my maths. But I do pay attention to grammar corrections, bring a paper map when I can, and keep trying to do the maths in my head. But as Tim Harford explains it, we still face "the paradox of automation: the better the machines get, the more bewildered we are when the machines fail." Also see: The bus factor Normalisation of deviance Chaos monkey Know your tech Jevon's paradox The law of unintended consequences The Dunning-Kruger effect (send me proof of purchase of Big Ideas Little Pictures, and I'll send the sketch to you) More paradoxes: The coastline paradox The transparency paradox The Abilene paradox The paradox of choice The liar paradox Tolkein-style landscape inspired by the excellent Lord of Maps.…The Automation Paradox is that the better our machines get, the more we struggle when they fail. When heading out for a hike in the woods, it's tempting to skip the map and compass and rely on our phones and apps for navigation. Yet when we encounter no signal or lose power, we can find ourselves in a sticky situation. Or perhaps, like me, you've come to rely on popping your destination into the satnav or Google Maps whenever you get in the car and have nearly forgotten the ability to navigate without it. These situations illustrate the paradox of automation, where the more sophisticated and automated our machines and technologies become, the more bewildered we find ourselves when they inevitably fail. Or: the smarter the machines get, the dumber we might get. In his book Messy, Tim Harford suggests three strands to the paradox as our machines get more sophisticated: Automation covers up our mistakes, hiding our incompetence, meaning we may not learn to correct ourselves—consider autocorrect cleaning up our typos as we go. When we rely on automation, we get less practice for our skills, so even highly skilled individuals may find their expertise diminishing—perhaps you've found yourself using your phone calculator for a trivial calculation. When the easy scenarios are taken care of, failures may occur in complex or unpredictable ways that we may find especially difficult to recover from—like a subtle but persistent failure in the steering of a passenger plane, recovering from a skid on an icy road, or when you're deeply lost in the wilderness. More sophisticated technology can even make it useless or more dangerous when it fails. Older cars used to be reparable forever. Now, if your vehicle fails, it's likely to need plugging in at the dealership to figure out what's up. How many electronic devices are thrown away because somewhere inside, some tiny loose connection or component makes the whole thing worthless? Were pilots and flight crews better prepared and able to improvise before the autopilot became ubiquitous? I often wish our devices would fail more like an escalator or an electric toothbrush. If an escalator fails, you can still walk up it. If your electric toothbrush dies, you can still use it to brush your teeth. These could be called Technology-Enhanced Products, perhaps. But when most of our devices die, they're often rendered worthless. Automation and sophisticated machines help me so much. I did use Grammarly to help check this post. I use Google Maps nearly every time I put in my destination to home, and I often use a calculator to check my maths. But I do pay attention to grammar corrections, bring a paper map when I can, and keep trying to do the maths in my head. But as Tim Harford explains it, we still face "the paradox of automation: the better the machines get, the more bewildered we are when the machines fail." Also see: The bus factor Normalisation of deviance Chaos monkey Know your tech Jevon's paradox The law of unintended consequences The Dunning-Kruger effect (send me proof of purchase of Big Ideas Little Pictures, and I'll send the sketch to you) More paradoxes: The coastline paradox The transparency paradox The Abilene paradox The paradox of choice The liar paradox Tolkein-style landscape inspired by the excellent Lord of Maps.

21 Jul

Point Nemo

Point Nemo is the furthest point in the ocean from any land. Imagine falling overboard and needing to swim to the nearest shore; the longest possible swim would start at Point Nemo. This puzzle, known as the Longest Swim Problem, finds its solution far into the Pacific Ocean at Point Nemo. The furthest point from land is a point with a maximum equal distance to three points of land. If you moved in any direction from there, you'd be closer to one of the points. The three nearest landmasses to Point Nemo, each about 2,688 km away, are: Dulcie Atoll in the Pitcairn Islands Moto Nui, a small islet off the coast of the well-known Rapa Nui (Easter Island) Maher Island, off the coast of Antarctica If you’ve ever been somewhere with only the sea in all directions, imagine what it would feel like to begin a 2,688 km swim from there. The antipode to Point Nemo, the point directly opposite it on Earth's surface, lies somewhere in Kazakhstan. Croatian survey engineer Hrvoje Lukatela identified and named Point Nemo after Captain Nemo from Jules Verne's classic "Twenty Thousand Leagues Under the Sea." Lukatela faced challenges in determining its exact coordinates, such as choosing the edge of Ducie Atoll's tidal sandbar and Maher Island being beneath ice for most of the year. Being so remote, space agencies use the area around Point Nemo as a spacecraft cemetery, sending old satellites and space debris to fall there. Likely, the closest people to Point Nemo are often those in the International Space Station passing overhead a mere 400km above. Point Nemo is also known as the Oceanic Pole of Inaccessibility. In contrast, the continental point of inaccessibility—the point on land furthest from the ocean—is in northwestern China near Kazakhstan, a remarkable 2,645 km from the nearest shore. Point Nemo has a lovely spread in Simon Kuestenmacher's book Marvellous Maps. Writing about Point Nemo makes me want to rewatch Life of Pi (and listen to the captivating music). Also see: The three tallest mountains The coastline paradox Antipodes Know your poles Orbit…Point Nemo is the furthest point in the ocean from any land. Imagine falling overboard and needing to swim to the nearest shore; the longest possible swim would start at Point Nemo. This puzzle, known as the Longest Swim Problem, finds its solution far into the Pacific Ocean at Point Nemo. The furthest point from land is a point with a maximum equal distance to three points of land. If you moved in any direction from there, you'd be closer to one of the points. The three nearest landmasses to Point Nemo, each about 2,688 km away, are: Dulcie Atoll in the Pitcairn Islands Moto Nui, a small islet off the coast of the well-known Rapa Nui (Easter Island) Maher Island, off the coast of Antarctica If you’ve ever been somewhere with only the sea in all directions, imagine what it would feel like to begin a 2,688 km swim from there. The antipode to Point Nemo, the point directly opposite it on Earth's surface, lies somewhere in Kazakhstan. Croatian survey engineer Hrvoje Lukatela identified and named Point Nemo after Captain Nemo from Jules Verne's classic "Twenty Thousand Leagues Under the Sea." Lukatela faced challenges in determining its exact coordinates, such as choosing the edge of Ducie Atoll's tidal sandbar and Maher Island being beneath ice for most of the year. Being so remote, space agencies use the area around Point Nemo as a spacecraft cemetery, sending old satellites and space debris to fall there. Likely, the closest people to Point Nemo are often those in the International Space Station passing overhead a mere 400km above. Point Nemo is also known as the Oceanic Pole of Inaccessibility. In contrast, the continental point of inaccessibility—the point on land furthest from the ocean—is in northwestern China near Kazakhstan, a remarkable 2,645 km from the nearest shore. Point Nemo has a lovely spread in Simon Kuestenmacher's book Marvellous Maps. Writing about Point Nemo makes me want to rewatch Life of Pi (and listen to the captivating music). Also see: The three tallest mountains The coastline paradox Antipodes Know your poles Orbit

14 Jul

Iceberg orientation

Nearly every iceberg you see in a picture or diagram is probably floating the wrong way. This was what I learned (from Megan Thompson-Munson) after sketching Biz Stone's brilliant saying about the myth of overnight success. With some approximation, the density of ice is around 900 kg/m3, and seawater is around 1,000 kg/m3. Therefore, the fraction of an iceberg that's submerged is around ~900/1000 or 0.9. So, about 90% of an iceberg is below the surface and 10% above, which is partly why they can be so dangerous. While most iceberg pictures get this part more or less correct, most of these icebergs will be floating vertically. In reality, a tall, thin iceberg will likely topple, so most icebergs end up floating on their side, not their tips, even though we rarely draw them this way. I remember learning about a fascinating experiment with children of different ages estimating which glass holds more water: a tall, slender one filled high or a wider glass filled to a lower level. Younger children almost always chose the glass with the higher water level as the most water, even when it was significantly less than the shorter and wider glass. I wonder if it's part of why we draw icebergs vertically, at least when we're using them as a metaphor. It's easier to grasp quantities vertically, and we commonly underestimate volume spread over a wider area. We may still want to draw our icebergs tall and deep to make our point, but now, at least, we can do so with the knowledge that they're not like the real ones. If you want to see it yourself, Joshua Tauberer made a brilliant draw-an-iceberg-and-see-how-it-will-float game. I recommend you give it a go so it sinks in forever (sorry). Also see: Overnight success Why ice doesn't sink Ice-cream, gelato, sorbet Know your poles: penguins or polar bears, frozen ice or land…Nearly every iceberg you see in a picture or diagram is probably floating the wrong way. This was what I learned (from Megan Thompson-Munson) after sketching Biz Stone's brilliant saying about the myth of overnight success. With some approximation, the density of ice is around 900 kg/m3, and seawater is around 1,000 kg/m3. Therefore, the fraction of an iceberg that's submerged is around ~900/1000 or 0.9. So, about 90% of an iceberg is below the surface and 10% above, which is partly why they can be so dangerous. While most iceberg pictures get this part more or less correct, most of these icebergs will be floating vertically. In reality, a tall, thin iceberg will likely topple, so most icebergs end up floating on their side, not their tips, even though we rarely draw them this way. I remember learning about a fascinating experiment with children of different ages estimating which glass holds more water: a tall, slender one filled high or a wider glass filled to a lower level. Younger children almost always chose the glass with the higher water level as the most water, even when it was significantly less than the shorter and wider glass. I wonder if it's part of why we draw icebergs vertically, at least when we're using them as a metaphor. It's easier to grasp quantities vertically, and we commonly underestimate volume spread over a wider area. We may still want to draw our icebergs tall and deep to make our point, but now, at least, we can do so with the knowledge that they're not like the real ones. If you want to see it yourself, Joshua Tauberer made a brilliant draw-an-iceberg-and-see-how-it-will-float game. I recommend you give it a go so it sinks in forever (sorry). Also see: Overnight success Why ice doesn't sink Ice-cream, gelato, sorbet Know your poles: penguins or polar bears, frozen ice or land

7 Jul

Pillars of hope

"Pillars of Hope" is a tongue-in-cheek name for steel starter bars, also known as starter rods or rebar extensions, that protrude from the roofs of houses after construction. Leaving starter bars sticking out is a pragmatic approach, saving time and money when adding the next floor, as the structure is already partially prepared for the expansion. The "hope" in the name reflects the anticipation and optimism of adding to their homes in the future when the family grows or their financial situation improves. Growing up in the UK, I never encountered the practice of leaving exposed starter bars on houses. However, while travelling through Central America and Asia, I was surprised to see these exposed rods in many towns and cities. At first, I couldn't understand why so many buildings seemed unfinished, making the skyline somewhat messy. Only when someone explained their purpose to me did it make complete sense. Steel bars in concrete combine the tensile strength of steel with the compressive strength of concrete, creating a remarkably effective and widely used building method. The starter bars embedded in and protruding from the existing structure provide a strong and stable connection between a new addition and the existing building. The bars transfer loads and anchor the two together. Pillars of Hope are a conspicuous example of futureproofing. Other examples in buildings are electrics or plumbing, where you might leave capped-off pipes or electrical connection points in anticipation of future work. Laptops and desktop computers with empty expansion slots also use this approach, as does a first edition of software that includes an update manager. In software and agile development, I like the sentiment from the book Rework: "A kick-ass half is better than a half-assed whole." Have no parts of your product not yet working or "under construction" that are visible to users. Don't leave any visible "starter bars" sticking out of your product. And try not to solve problems that you don't yet have. While it might seem worth adding something now to make a future feature easier to build, it's a tricky balance. So often, you choose to do something else in the future instead and are left with some software pillars of hope sprinkled throughout your code—technical debt you may have to pay off later. While my first reaction to steel rods sticking out of houses seemingly willy-nilly was that it was chaotic and messy, when I think about them as Pillars of Hope I now find it kind of beautiful—looking out over a skyline and seeing the aspirations and future development of families, homes and a city sketched out on the rooftops. Edit: Several people told me that leaving starter bars sticking out of a roof makes the building 'unfinished' and not liable to tax on the work. While this is repeated in many places, I'm not 100% sure of the truth. If you have experience with it, please get in touch! Also see: Hope Hofstadter's Law Forcing functions for foolproofing…"Pillars of Hope" is a tongue-in-cheek name for steel starter bars, also known as starter rods or rebar extensions, that protrude from the roofs of houses after construction. Leaving starter bars sticking out is a pragmatic approach, saving time and money when adding the next floor, as the structure is already partially prepared for the expansion. The "hope" in the name reflects the anticipation and optimism of adding to their homes in the future when the family grows or their financial situation improves. Growing up in the UK, I never encountered the practice of leaving exposed starter bars on houses. However, while travelling through Central America and Asia, I was surprised to see these exposed rods in many towns and cities. At first, I couldn't understand why so many buildings seemed unfinished, making the skyline somewhat messy. Only when someone explained their purpose to me did it make complete sense. Steel bars in concrete combine the tensile strength of steel with the compressive strength of concrete, creating a remarkably effective and widely used building method. The starter bars embedded in and protruding from the existing structure provide a strong and stable connection between a new addition and the existing building. The bars transfer loads and anchor the two together. Pillars of Hope are a conspicuous example of futureproofing. Other examples in buildings are electrics or plumbing, where you might leave capped-off pipes or electrical connection points in anticipation of future work. Laptops and desktop computers with empty expansion slots also use this approach, as does a first edition of software that includes an update manager. In software and agile development, I like the sentiment from the book Rework: "A kick-ass half is better than a half-assed whole." Have no parts of your product not yet working or "under construction" that are visible to users. Don't leave any visible "starter bars" sticking out of your product. And try not to solve problems that you don't yet have. While it might seem worth adding something now to make a future feature easier to build, it's a tricky balance. So often, you choose to do something else in the future instead and are left with some software pillars of hope sprinkled throughout your code—technical debt you may have to pay off later. While my first reaction to steel rods sticking out of houses seemingly willy-nilly was that it was chaotic and messy, when I think about them as Pillars of Hope I now find it kind of beautiful—looking out over a skyline and seeing the aspirations and future development of families, homes and a city sketched out on the rooftops. Edit: Several people told me that leaving starter bars sticking out of a roof makes the building 'unfinished' and not liable to tax on the work. While this is repeated in many places, I'm not 100% sure of the truth. If you have experience with it, please get in touch! Also see: Hope Hofstadter's Law Forcing functions for foolproofing

30 Jun

Parallax

Parallax is the change in the apparent position of objects from different viewpoints. For example, from one viewpoint, a nearby house may appear in front of a hill, and from another, it may be in front of a lake. Objects at different distances appear to move by different amounts. As you move between viewpoints, say when driving along a road, nearby objects move past you quickly, while distant objects appear to move by slowly. This difference in motion from near to far objects helps us determine how far objects are away. I remember learning parallax from video games, like playing Sonic the Hedgehog on the old Sega Mega Drive. As the character moves in the foreground, elements at different distances in the background move progressively slower, creating a sense of depth. Saturation and contrast change at with distance also, known as atmospheric perspective. I also enjoy observing parallax while looking out of a train window; nearby hedges and trees race by, buildings in the middle distance move more slowly, and distant hills or mountains barely seem to change. It's fascinating how our brains interpret this relative movement to judge distances. One of the more intriguing applications of parallax is stellar parallax in astronomy. The basic geometry of parallax allows us to measure the distance of (relatively) nearby stars by observing relative shifts against the background of distant stars. Here's how it works: we observe the stars from different points in our orbit around the Sun. As a result, the stars appear to move relative to each other. By measuring this apparent shift, we can calculate the distance of the stars. Also see: Redshift The Doppler effect Atmospheric perspective Two-point perspective Pace layers Time hierarchy…Parallax is the change in the apparent position of objects from different viewpoints. For example, from one viewpoint, a nearby house may appear in front of a hill, and from another, it may be in front of a lake. Objects at different distances appear to move by different amounts. As you move between viewpoints, say when driving along a road, nearby objects move past you quickly, while distant objects appear to move by slowly. This difference in motion from near to far objects helps us determine how far objects are away. I remember learning parallax from video games, like playing Sonic the Hedgehog on the old Sega Mega Drive. As the character moves in the foreground, elements at different distances in the background move progressively slower, creating a sense of depth. Saturation and contrast change at with distance also, known as atmospheric perspective. I also enjoy observing parallax while looking out of a train window; nearby hedges and trees race by, buildings in the middle distance move more slowly, and distant hills or mountains barely seem to change. It's fascinating how our brains interpret this relative movement to judge distances. One of the more intriguing applications of parallax is stellar parallax in astronomy. The basic geometry of parallax allows us to measure the distance of (relatively) nearby stars by observing relative shifts against the background of distant stars. Here's how it works: we observe the stars from different points in our orbit around the Sun. As a result, the stars appear to move relative to each other. By measuring this apparent shift, we can calculate the distance of the stars. Also see: Redshift The Doppler effect Atmospheric perspective Two-point perspective Pace layers Time hierarchy

23 Jun

Word spectrum

A word spectrum highlights different aspects of a concept from one extreme to another. By arranging words on a spectrum, we can see their subtle differences and nuances. For example, a word spectrum of happiness might range from "Miserable" on one side to "Ecstatic" on the other, passing through "Gloomy", "Content", and "Happy" along the way. Or a word spectrum of tiredness might be: Asleep - Drowsy - Groggy - Awake - Alert - Energised It's not a science, and there's a fair amount of latitude for people to place different words in different positions. Looking at many spectrums, it strikes me that some writers excel at selecting specific and perhaps more intriguing words such as "scrumptious" or "mouth-watering" over the more common "delicious." Roald Dahl often had his characters "guzzle" instead of "eat hungrily," for example. I became curious about word spectrums when I realised that my understanding of the spectrum of approval was different from that of many of my American friends. In British English, "quite" is often used to mean "a bit less than," but in the U.S., I found it was more commonly used to mean "a lot" or "very." So, my British English word spectrum of approval would be: OK - Quite good - Good - Excellent While the word spectrum of approval for many of my U.S. friends might be: OK - Good - Quite good - Excellent It left me confused several times before I figured it out. For other variations in interpretation, such as where you might put "awesome", there's an excellent table as a Guide for U.S. students interpreting feedback from faculty trained in the U.K. (and vice versa). At times, it really matters what someone means with a descriptive word. In the "intelligence" trade "words of estimative probability" relate to specific odds meant by certain terms. For instance, if an attack is "highly likely," just how likely is it? If something is "almost certainly an airfield," how certain is that? Clearly, the choice and interpretation of these terms can be very significant. For a fascinating insight on this, see CIA analyst Sherman Kent's previously classified report Words of Estimative Probability (pdf). Other research has studied individual differences in people's perceptions of probability—and created some fun graphics showing the results. Estimative probability is also critical in medicine. If exact numbers aren't shared, how frequent is a side effect that occurs "rarely"? Specific guides have been created listing associated probabilities for terms such as "likely", "frequent", "occasional" and "rare". A reader also shared with me a classic chocolate advert of Fry's five boys, with the face of a boy moving from: desperation, pacification, expectation, acclamation and the realisation "it's Fry's". More word spectrums, including those illustrated here: Size: tiny - small - medium - large - huge - gigantic Frequency: never - rarely - occasionally - sometimes - often - always Talk volume: whisper - murmur - talk - shout - yell - scream Intelligence: stupid - dim - average - bright - brilliant - genius Tastiness: disgusting - bland - tasty - delicious Smell: foul - stinky - scented - sweet More fun scales and spectrums: Fahrenheit and Celsius The Bortle scale The fun scale Solar system scale The Scoville scale The square-cube law Do a 2x2…A word spectrum highlights different aspects of a concept from one extreme to another. By arranging words on a spectrum, we can see their subtle differences and nuances. For example, a word spectrum of happiness might range from "Miserable" on one side to "Ecstatic" on the other, passing through "Gloomy", "Content", and "Happy" along the way. Or a word spectrum of tiredness might be: Asleep - Drowsy - Groggy - Awake - Alert - Energised It's not a science, and there's a fair amount of latitude for people to place different words in different positions. Looking at many spectrums, it strikes me that some writers excel at selecting specific and perhaps more intriguing words such as "scrumptious" or "mouth-watering" over the more common "delicious." Roald Dahl often had his characters "guzzle" instead of "eat hungrily," for example. I became curious about word spectrums when I realised that my understanding of the spectrum of approval was different from that of many of my American friends. In British English, "quite" is often used to mean "a bit less than," but in the U.S., I found it was more commonly used to mean "a lot" or "very." So, my British English word spectrum of approval would be: OK - Quite good - Good - Excellent While the word spectrum of approval for many of my U.S. friends might be: OK - Good - Quite good - Excellent It left me confused several times before I figured it out. For other variations in interpretation, such as where you might put "awesome", there's an excellent table as a Guide for U.S. students interpreting feedback from faculty trained in the U.K. (and vice versa). At times, it really matters what someone means with a descriptive word. In the "intelligence" trade "words of estimative probability" relate to specific odds meant by certain terms. For instance, if an attack is "highly likely," just how likely is it? If something is "almost certainly an airfield," how certain is that? Clearly, the choice and interpretation of these terms can be very significant. For a fascinating insight on this, see CIA analyst Sherman Kent's previously classified report Words of Estimative Probability (pdf). Other research has studied individual differences in people's perceptions of probability—and created some fun graphics showing the results. Estimative probability is also critical in medicine. If exact numbers aren't shared, how frequent is a side effect that occurs "rarely"? Specific guides have been created listing associated probabilities for terms such as "likely", "frequent", "occasional" and "rare". A reader also shared with me a classic chocolate advert of Fry's five boys, with the face of a boy moving from: desperation, pacification, expectation, acclamation and the realisation "it's Fry's". More word spectrums, including those illustrated here: Size: tiny - small - medium - large - huge - gigantic Frequency: never - rarely - occasionally - sometimes - often - always Talk volume: whisper - murmur - talk - shout - yell - scream Intelligence: stupid - dim - average - bright - brilliant - genius Tastiness: disgusting - bland - tasty - delicious Smell: foul - stinky - scented - sweet More fun scales and spectrums: Fahrenheit and Celsius The Bortle scale The fun scale Solar system scale The Scoville scale The square-cube law Do a 2x2

16 Jun

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