Review of Peter Norton's Autonorama: The Illusory Promise of High-Tech Driving
What’s the book’s main argument?
Norton says carmakers promote an ideal of “zero crashes, zero emissions, and zero congestion” through more advanced cars (145). In contrast, Norton argues that AVs won’t solve traffic congestion or make driving safe; additionally, the pursuit of AVs distracts (and actually hurts) other more practical solutions for mobility. “Our most essential mobility needs can be better met with tools we already have,” Norton says (21).
Car manufacturers (“motordom”) know AVs won’t solve traffic issues; instead, Norton says the AV’s main purpose is to sell more cars by projecting a techno-futuristic utopia that draws consumers in, thinking that by purchasing the car they will be one step closer to the utopia — an approach called solutionism. (For a current example, see this Nissan commercial presenting a magical future, with the Nissan car being one step.) To keep selling cars, however, that utopia can never actually be achieved. It’s just an illusion that encourages car buying. Carmakers embrace this vision so that ongoing “demand for its products would be permanently assured” (33). It’s a principle Charles Kettering, an early innovator at GM, espoused to “keep the consumer dissatisfied” and thus always buying (25, 94).
Ultimately, AVs don’t solve traffic problems; they “offer only high-tech car dependency,” Norton says (19). Car makers “do not sell particular products; they sell idealized futures in which their products will be in endless demand. These futures are not meant to be achieved. They are to be pursued, for in the pursuit lies the endless demand for vehicles, technology, and pavement” (13).
In Norton’s view, there aren’t any car dependency models that solve the issues of traffic congestion, safety, and sustainability — no matter the amount of advanced tech. He wants readers to recognize the illusion and to focus on practical mobility solutions instead, arguing that “our most essential mobility needs can be better met with tools we already have” (21).
What does “autonorama” mean?
Norton approaches the transportation topic from a historical perspective, asking what history can teach us about AVs. As such, Norton begins by looking at ways automakers have pitched their earlier visions of transportation of the future, initially through dioramas at world fairs.
A diorama is a small scale representation (a physical model) of something. In this context, the dioramas depict futuristic transportation scenarios. “Futurama” is a blend of future + diorama — a diorama showing the future. Norton says “Futuramas depict utopian futures of about twenty years hence: soon enough to be relevant to consumers, but sufficiently distant to avert distrust and disillusionment when reality disappointed” (37).
More specifically, Futurama was what GM’s dioramas were called at the 1939 and 1964-65 World Fairs. (By the way, you can watch GM’s 1938 New Horizons film and their Futurama 2 ride at the 64-65 fair on Youtube.) Norton coined the term autonorama as a blend of autonomous vehicles + diorama. Autonorama is the depiction of AVs as the future of transportation. The word connotes the hocus-pocus illusion of autonomous vehicles.
What are Norton’s arguments about AVs and traffic congestion?
Let’s start with the argument that AVs can reduce traffic congestion. This focus occupies the bulk of the book, so I’ve expanded on this section more than others. Norton says carmarkers have historically gained prominence for government-sponsored highway and road building with the argument that Americans prefer to drive and that wider roads and more roads would alleviate the traffic congestion, which is only getting worse from year to year. For example, Norton says the argument at a Mobility 2000 conference was that “Car dependency is a given. Congestion is costly and worsening, but advanced technology can make car dependency work” (90). Supporting the need for more roads, films like Disney’s Magic Highway (definitely worth watching!) depict highway building as a great American achievement to enable mobility.
But just how would AVs alleviate traffic congestion? Norton says that transportation models that involve car dependency — no matter whether the car is manually driven or autonomously driven — fail not due to poor tech but because of the car’s spatial constraints. Cars just take up too much space per person, leading inevitably to traffic congestion. Changing the way cars are driven won’t address the fundamental reason why cars don’t work: cars take up too much space. The problem of congestion is “due to the car’s inherent properties: its space demands relative to people moved, its storage demands, and the cost of accommodating them…,” Norton says (93-94). Carmakers try to sidestep the spatial issues and instead focus on self-driving technology, furthering the car’s tech. But tech isn’t the reason for congestion; it’s the car’s space. Space issues aren’t solved through auto-driving technology.
Could congestion be solved by reducing the distance between cars?
Some have argued that AVs could travel close together (in platoons, or linked together) at high speeds, which would reduce congestion. However, Norton says these arguments never explain how the cars will flow through dropoff destinations or where the increased number of cars will park (high-rise automatic-parking garages?). If all cars drop off passengers at popular destinations, this will create immense lines of cars (like at school dropoffs), even if the cars can self-park.
Norton says, “High-capacity conventional highways with no electronic gadgetry had already proved sufficient to channel so many cars into American cities that whole blocks of real estate had been cleared for car storage. Platooning threatened to double cities’ parking woes” (124). In other words, cities are already choking with traffic from manually driven cars. Increasing car density through high-speed AV driving in platoons (or links), fitting more cars per square foot into the same city spaces and roads, will only make congestion worse. And higher density of cars on roads means more parking needs. Where will all of these AVs park?
What about transportation-as-a-service car fleets that don’t need to park?
Some argue that transportation-as-a-service AV fleets (where no one owns the cars) would alleviate parking because the cars could pick up and drop off passengers continuously, without the need to park anywhere. But the problems of Lyft and Uber would likely befall driverless AV fleets as well, Norton explains. Studies have found that ride-hailing services don’t reduce traffic congestion but instead exacerbate congestion — see Impacts of transportation network companies on urban mobility. This is because ride-hailing services encourage more people to travel in cars rather than take public transportation or other modes. And with more people traveling in cars, you end up with more cars on the road and hence more congestion.
Further, services like Lyft and Uber make congestion worse because when the cars aren’t carrying passengers, they continue driving on the roads or waiting (called “deadheading”) between passenger trips. As a result, you have more cars on the road without carrying any passengers at all.
Again, the problem has nothing to do with whether the cars are self-driving or manually driven — the problem is that cars take up too much city space per passenger. The Impacts of transportation report says that “approximately half of TNC [transportation network companies] trips are ones that would otherwise have been made by walking, cycling, PT [public transportation] or would not have been made at all.” By discouraging other modes of travel and instead promoting car dependency, congestion worsens. Norton says, “AVs are likely to worsen the very aspects of passenger transportation they are supposed to improve… AVs are, more than anything else, an attempt to perpetuate car dependency when car dependency itself is the problem” (149).
Norton doesn’t think that autonomous operated car fleets (driverless Ubers) would have a different outcome from manually operated car fleets (like driver-based Ubers). In short, if you encourage a mobility model where more passengers travel around in individual cars, you increase congestion.
Can’t we just build more roads to reduce congestion?
Another argument is that we need to build more roads to reduce congestion. Norton says more roads won’t fix the congestion issue because as something becomes easier to use, more people start using it. “To relieve congestion by eliminating delays to drivers no matter the cost is only to invite more driving”, Norton says (142). “The devices become more advantageous to use and are therefore used more” (168). He gives an example of a faster internet, which encourages people to be online more. He also cites Stanley Jevons, an English polymath, who explained that “efficiency gains in the use of a resource tend to increase total consumption, not diminish it” (referring to steam engines) (168-169). At the time, it was thought that making steam engines more efficient would reduce the use of coal; in reality, the efficiency gains only encouraged more use of steam engines (and thus exhausted more coal resources) because the easier something is to use, the more it gets used.
The only way to solve traffic congestion in cities is by destroying the city with so many roads, parking areas, and other pavement that the city pedestrians, cyclists, and other mobility options become unsafe. You’d need to destroy all the vibrants parts of the city (parks, plazas, outdoor malls) with parking lots, freeways, more roads, etc. However, Norton quotes urbanist Victor Gruen to remind us that “urban vitality depends upon people, who must not be confined within vehicles or crowded out by them” (81). In other words, a city that consists of nothing but roads and driving will lose its vibrancy and appeal. Even Disney’s EPCOT city (Experimental Prototype Community of Tomorrow) excluded vehicles from the city, requiring them to park outside and then enter. Inside the city, a monorail helped people get around that park. Disney knew that cars driving inside of Disneyland would ruin the experience, just as the many roads and cars in big cities diminish the urban vitality of cities today.
What about mapping applications that can reroute traffic around congested areas?
Another argument is that advanced routing systems can route cars around congested areas. However, Norton says there have been many attempts at this in the past — Driver Aid, Information and Routing (DIAR), Electronic Route Guidance System (ERGS), Etak Navigator, PathFinder, TravTek, and more. Unfortunately, these efforts “were of only marginal help,” Norton says (104).
But given that Americans insist on driving, don’t we have to find a way to make driving work?
Norton questions this assumption, which has often been made by carmakers to justify more road building. Do Americans actually prefer to drive as their form of mobility? Just because Americans drive nearly everywhere doesn’t mean they want to be driving. Their “choice” to drive doesn’t mean Americans preferred driving in the first place over other forms of transportation. Our infrastructure has made it so that driving is the only practical way to get around. Norton says, “…because of systematic effects, they [the car-driving infrastructure and poor public transportation options] have the effect of degrading all other choices until, for millions, there is no choice. The car is a practical necessity” (227). By eroding the viability of public transportation options, carmakers have managed to lock in car dependency.
Arguments against AV safety
Let’s turn our focus now from traffic congestion to safety. Even if AVs don’t solve congestion, couldn’t they at least improve safety by reducing collisions? Norton says AVs won’t be safer because if the cars do drive with 100% safety, they’ll go so slow, stopping at every paper bag out of caution that it might be a small child playing, that people won’t use AVs but will instead prefer to drive their own cars (at 10+ mph over the speed limit, whizzing around curves, and making their own decisions using their own judgement, which is usually smarter than a programmed computer).
Norton also says that technology that reduces the need to pay attention to the road will likely lull drivers into a comatose state (the highway hypnosis effect), or encourage them to focus their attention elsewhere. This was what the military learned about sonar radar operators back in the 1940s — it was nearly impossible to keep one’s attention on such a monotonous task. One military report essentially said, “Don’t trust humans, no matter how diligent and conscientious, to pay attention to nothing. They cannot do so reliably for more than a half hour” (158).
Paradoxically, by removing the need for humans to pay attention to the road (because self-driving features do the driving), this might increase the chances of accidents and collisions. Norton explains that conventional cars might be safer because they require more of the driver’s attention:
Driving a conventional car, of course, demands vigilance, too, but humans sustain their attention far better when they have things to pay attention to, and when their attention is constantly needed (158).
When that human attention drifts, as soon as the smallest issue arises (blown tire, error, whatever), they’ll likely not be ready to react. Many Tesla drivers who activate Autopilot might have begun with the intention of staying alert to the road, with hands ready to retake control, only to find that their brains can’t focus on nothing for very long. Pretty soon, the drivers fall asleep or turn their attention to their smartphones. And with their attention elsewhere, they increase the risk of collisions.
The self-driving features could also encourage drivers to take higher risks, thinking that the autopilot features will protect them from accident. This is a phenomenon known as risk compensation. Norton says, “A sleepy driver may be tempted to keep driving, rather than pull over and reset, confident of the protection that such safety features afford” (153). The way these features are named, e.g., “auto-pilot,” may deceive drivers into thinking that the features are more self-driving than they actually are (154).
AVs and sustainability
Another argument in favor of AVs is their contribution to sustainability. Most AVs are electric vehicles (EVs), operated by batteries, which create far less pollution. Norton doesn’t have as much to say about sustainability as other topics, but he does say that a massive influx of batteries would likely overwhelm our power grid. The strip mining for the lithium in the batteries also threatens environmental harm.
But his largest argument is that a car-dependent vision for mobility encourages more driving, which has negative consequences. Norton says, “Since the 1970s, sustainability has been and remains primarily an effort to make each car cleaner, even as the total number of cars, and miles of car travel, proliferate, thereby offsetting the gains” (142). In other words, gains made with cleaner cars are offset by having more cars on the road. If AVs make it easier to drive, and mobility options increase car-dependent models, then more people will be driving. “To relieve congestion by eliminating delays to drivers no matter the cost is only to invite more driving,” Norton says (142).
What would be the impact of AVs on sustainability? AVs might also encourage people to live in farther-away destinations, settling down for long car rides to get into the city. If AVs encourage people to spend more time in cars, traveling greater distances, then not only will this model exacerbate urban sprawl, the more spread-out distances will encourage more and more driving. Areas of urbran sprawl “make it harder for cycling and walking options” (197).
Overall, this increased driving time works against sustainability goals. More driving time does, however, work in favor of carmakers. “For those in the business of selling driving, this result [more driving] was not a bug but a feature,” Norton says (142).
AVs and tech companies as partners
With all of these arguments against AVs as a solution for “zero crashes, zero congestion, zero emissions” (145) — their common mantra — how have automakers persuaded the public to embrace high-tech, autonomous driving, as depicted in videos such as 2030 Xing (full version, short version)? Let’s return to that initial idea of solutionism in the sales techniques. If you can persuade the public that driving utopia is just around the corner, you can convince them to buy cars that get them one step closer. However, given that each of the previous futuramas failed to achieve their vision, these failures created a credibility gap (a distrust) with consumers. It became harder and harder to persuade consumers that this driving utopia was a feasible reality.
To help bridge the credibility gap, Norton says that automakers are now leveraging advanced technology. Many high tech companies have shown that they can work magical solutions that achieve the seemingly impossible, so these high tech companies make the perfect partner to help persuade consumers to believe again in the viability of the driving utopia. Norton explains:
In the early 2000s, as the smart highway promises of just a decade earlier proved extravagant, lavish promises grew scarce. …Big claims that smart highways without congestion pricing would diminish traffic jams and improve safety were proved wrong. A new credibility gap deterred more promise making… But the lull was brief. Cell phones, laptop computers, and the internet ensured that new technology retained the power to make the impossible seem possible (129-30).
Whereas carmakers in the early 2000s (Futurama 3) envisioned smart highways to enable driverless mobility, Futurama 4 (which Norton calls Autorama) shifts from smart highways to smart cars. Advanced tech such as LiDAR (light detection and ranging), AI (artificial intelligence), and other “disruptive innovations” have once again given consumers hope that the driving utopia can actually be realized, that “… routes will be high-speed and congestion-free even in a city of twenty million in which everyone rides in a car” (140).
In other words, to address the credibility gap (the distrust from consumers when the futuramas fail), carmakers have enlisted high-tech partners to achieve the impossible.
Why would tech companies go along with the automaker illusion?
What prompts tech companies to go along with the automaker illusion about the impossible car-dependent utopia? Many engineers might believe the solution is possible, for sure. In many ways, driverless cars are the ultimate robotics challenge, which is like a Siren song for engineers.
However, tech companies also have huge business opportunities with automakers. Norton says tech companies form mutually beneficial partnerships with automakers because tech companies can extract endless data from the AV integrations, which essentially convert the cars into computers. The more time users spend in cars, especially driverless ones (smartphones on wheels) where you might come in from further out of the city (spending more time in the car), the more data you can extract. As drivers no longer need to focus on the road, they can refocus their attention on [ad-driven] media consumption. Norton explains:
Digital data collection … has imparted a new degree of distortion to the mobility landscape, by making transport a means of collecting monetizable data. … in 2006, a consultant named Clive Humby told a conference of advertisers: “Data is the new oil.” By then, Humby had already proved that he could extract crude data streams from customers and refine them into a profitable resource. In transport, data extraction entails getting people into vehicles more often, and for longer periods. (181)
In short, Norton views the motivations behind tech-auto partnerships as capitalistic, with tech companies eyeing another landscape (the car) from which to track, profile, and extract data from consumers (just like with smartphones; in fact, the smart car is now just an extension of your smartphone). With this model, more driving time, especially when the driver’s attention need not focus on the road, helps tech companies gather more data about drivers. Norton cynically concludes: “Rather than “self-driving mobility,” the effects might better be termed “self-driving data generation” (183)
Citing a report from McKinsey & Company, Norton continues: “If tech companies and automakers make the most of the ‘car data monetization arena,’ they could develop a world market worth ‘up to USD 450-750 billion by 2030.’ To do this, AV developers must make car occupancy ‘social and fun.’ They must offer passengers ‘a social and interactive experience,’ like social media on wheels” (184).
In this distrusting view about the partnerships of automakers and high-tech companies, the goal is not to reduce time spent in the car but to lengthen it, to promote car dependence. Even if the cost of AV technology exceeds what drivers can pay, these costs can be offset by the data extracted from consumers. It’s a case where the consumer becomes the product, not the mobility.
Norton spends most of the book overturning the promises and illusions of AV, but he does offer some proposed solutions at times. He believes, “The biggest obstacle in the path toward a more sustainable mobility future is not technology but public policies, laws, and engineering standards that prioritize driving at the expense of everything else” (199). Focusing just a fraction of our attention on improving public transportation (such as putting “next arrival” times on bus stop signs, for example, or by implementing toll pricing to discourage independent car use) could have big effects on mobility.
Norton says, “If 10 percent of the public resources that have gone into high-tech driving had instead gone into real mobility–practical opportunities to walk, to bike, or to ride a bus, a streetcar, or a train, we might have good mobility choices that would serve the mobility needs that the promoters of high-tech driving merely promise to meet, and at extraordinary expense” (233). His book is not really about solutions, though. The solution, in his view, does not involve advanced AV technology. It is a simple matter of changing policies and laws to discourage car dependency.
Norton’s book is eye-opening and presents an alarming view of the auto industry that assumes darker, profit-only motives toward car-dependency at the expense of actually solving mobility. What’s my reaction to the book? He’s probably right most of the time, but I think he over-indexes on the traffic congestion problem. This may have been a larger point of emphasis for advanced tech in cars in the past than it is today. Today, I think most carmakers are focused on using advanced technology to increase driver safety. EVs will also help a lot with sustainability. Both safety and sustainability don’t receive nearly as much treatment in Norton’s book as traffic congestion.
Additionally, other books on the future of transportation talk about transportation-as-a-service models being the disruptive innovation. Norton does talk about these services briefly (for example, Lyft, Uber — see pages 165-71 and 217), but much of his argument is against car dependency in general, and these shared transportation services are grouped implicitly as a car dependency model.
For sure, automobiles have allowed housing to spread further out, which then requires car dependency due to lack of public transportation in suburban areas. I’ve written about urban sprawl previously, and how there aren’t any good bike routes (such as protected bike paths or multi-use paths) from my house to the train station. But despite all the drawbacks, cars do work more or less all right in suburban areas. It’s mostly in downtown areas where you see massive congestion. The book’s argument might come across as more balanced if he were to nuance the context of location a bit more, for example, to say car dependency in cities is bad but acceptable in rural areas.
Also, in Norton’s book, advanced tech in cars often gets assumed to be serving the larger goal of full-autonomy. But at least in our current point in time, most automaker efforts focus on the L2 level of autonomy and are much more humble in scope, hoping to assist with curve speed adaptation, adaptive cruise control, automatic lane changes, hard-braking events, and so on. If automakers can get the needed data for these ADAS safety controls coming directly to the car, without even driver awareness, that must certainly be a good thing. I wanted Norton to acknowledge more of the potential benefits of advanced tech in cars. It’s not all about data extraction.
Are automakers actively presenting an illusion of an unattainable utopia to sell cars, as Norton depicts? That’s one interpretation, but their motivation just as well could be driven by fear — fear of missing out (“FOMO”). Tesla has threatened to leave traditional car manufacturers behind. Teslas, with their electric drivetrain and large touchscreen controls, symbolize the future car as much as possible, and they’re saturated with computer tech. Automakers might simply be trying to keep pace, to not be left behind but to swim in this disruptive space in which cars are evolving. There’s a fear that if they don’t follow Tesla’s lead, in 20 years they’ll be obsolete. Their commercials to present their cars as one step toward the future might actually be an attempt to put them in the same category as Tesla.
As far as tech companies being the complicit partners to enable solutionist sales appeals about car utopias, again I think Norton assumes the worst about motives here. Extracting data from drivers in cars is no worse than data extraction from other devices (smartphones, televisions, medical equipment, etc.) that people use. This is how the attention economy works. For an excellent history of the attention industry, see Tim Wu’s The Attention Merchants. From radio to TV to the internet, advertising has been engaging in a constant bartering with consumers. Consumers have come to accept advertising’s tradeoffs — trading some of their attention for worthwhile content. If advertising asks too much, consumers disengage. I’ll watch a TV program or sports event even though there are frequent commercials. But I won’t watch a show that is more commercial than content. Again, it’s all about the accepted tradeoff.
The Mckinsey & Company report suggests that many drivers are willing to share their data for some benefits. In Monetizing car data: New service business opportunities, the authors explain, “Consumers understand they will share personal information as part of their digital lives — they just expect to get a fair value in return.” The type of data consumers are more willing to share varies, but “At the low-sensitivity end, external environment conditions, the vehicle’s technical status, and vehicle usage are the data categories in which consumers are most willing to share information. This is perceived to be ‘objective’ data and generally less critical” (16).
So drivers seem open to sharing information that they feel will ultimately come back to benefit them — information about the road, their car’s status, how they’re using the car, etc. Sharing this information is a type of economic bartering — producers and consumers arriving at an exchange of goods [information] acceptable to both.
I definitely agree with Norton that the solutions for mobility don’t require advanced technical innovation and can be achieved using our existing tools. As someone who commutes in a multi-modal way to work, I’m frustrated that state governments in my area don’t experiment with Open Street models like New York City, Copenhagen, or Amsterdam. The solution to congestion could be fixed overnight. Just put up Closed Street barricades in half the roads downtown — this would allow people to bike safely to their destinations. With more closed streets, driving would slow down and parking would be reduced, de-incentivizing more drivers.
To win the battle against car dependency, you have to make driving a car less comfortable and convenient than taking other modes of transportation, period. When this happens, we’ll see a massive shift to public transportation. The trains and buses would be full of people. People would carry scooters and bikes to get them from the train or bus to their final destinations (the last mile). We don’t need AVs to solve urban mobility — we just need a state government courageous enough to open the streets to cyclists and pedestrians. We need to stop prioritizing driving in downtown urban hubs.
Also, I personally don’t see the use case for AVs. 95% of my driving is the short commute (20 minutes) from my house to the train station. During short commutes, having an AV do the driving isn’t something I need. And for the longer drives (5+ hours)? It’s usually cheaper to fly or take public transportation; in those modes, I can fully detach with a book or movie.
I find it interesting to compare GM’s New Horizons Futurama video from 1938 with the current GMC hands-free driving commercials. Is this the future of transportation? Why would I want hands-free driving anyway? The hands-free driving pitch reminds me of the hands-free ads for Fire TV. When I worked at Amazon, I spent countless hours working on documentation to allow app developers to voice-enable their apps for Fire TV, making it so people could control and navigate the TV with their voice rather than the remote. I found that controlling the TV with my voice was novel for a while, but I quickly grew tired of it. It was just easier to use the remote control.
The only situations where voice control helped was typing out long movie titles in search — but was this scenario worth the millions of hours required for AI controls to listen, parse, and interpret the nuances of voice? At Amazon, I watched as seemingly half of all engineering resources (or more) were devoted to the voice infrastructure to make this all work. It was way more work than anyone imagined, and the end result? Most of the time I end up shouting at my TV, frustrated that it misunderstood my commands (same with my Echo devices). I never wanted hands-free TV watching. The commercials couldn’t “demand-engineer” a problem I didn’t think I had.
At least at this point in time, with L2 level, partial driving automation, there’s not much purpose for self-driving features, in my view. It actually makes driving more difficult because, as Norton says, the human ability to pay attention to nothing is impossible. Staring at an empty road, waiting to possibly take over but not needing to do anything for potentially hours, seems excruciating.
Even in the hands-free GM commercial, as soon as the driver doesn’t have to drive, he’s immediately doing something else — pounding on an air drum (or his lap) to music. I actually wouldn’t mind getting a stick-shift just so that I can more fully engage and interact with driving. At least shifting gears would give me something to attend to, keeping me more focused on driving and the road (and hence safer).
Even if AVs might not be all that applicable for consumer driving, they could be useful for many other scenarios. In Autonomy: The Quest to Build the Driverless Car―And How It Will Reshape Our World, the motivations for AV development seem much more focused on military scenarios, allowing self-driving Humvees to navigate in war zones without risking the life of soldiers. (Of course, autonomy in war can easily lead to massive clashes where remotely operated tanks and drones engage emotionlessly in battle — one step away from a Black Mirror episode, but I digress.)
Even outside of war, there are many use cases for self-driving vehicles, such as lunar rovers, bomb-defusing robots, hazardous waste cleanup, coal mine mapping, security monitoring, and more. Even when technology sometimes fails in one goal, the tech can be serendipitously used for another. I would have liked to read a bit more optimism in Norton’s book, more perspective on the possible benefits of advanced tech in the auto space. America’s highway system is pretty incredible. I don’t mind my short drives much of the time. The technologist in me wanted to see a bit more optimism toward the future.
About Tom Johnson
I'm a technical writer / API doc specialist based in the Seattle area. In this blog, I write about topics related to technical writing and communication — such as software documentation, API documentation, visual communication, information architecture, writing techniques, plain language, tech comm careers, and more. Check out simplifying complexity and API documentation for some deep dives into these topics. If you're a technical writer and want to keep on top of the latest trends in the field, be sure to subscribe to email updates. You can also learn more about me or contact me.