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President Donald Trump’s tariffs are unpopular and expected to raise costs for Americans, but he’s trying his best to message them in a positive light. When his proposed new tariffs on foreign goods go into effect on Wednesday, he’s calling it liberation day. We have liberation day, Trump said last week. Many countries have taken advantage of us, the likes of which nobody even thought was possible for many, many decades. Trump has long been one for hyperbole, and when it comes to trade, he’s not holding back, calling the word tariff the most beautiful word in the dictionary. But the choice of liberation day to describe tariffs is a true misnomer. In Europe, Liberation Day is observed by countries in celebration of the liberation from Nazi Germany. For Trump, he simply uses the phrase to describe a day on which he enacts his agenda. Already, Trump called his 2025 Inauguration in January liberation day during his speech, and he’s repeating the phrase to apply to tariffs hitting Wednesday. How to make a political phrase stick For words and phrases to take hold, both inside and outside of politics, they must meet the FUDGE test, according to the mnemonic device devised by linguist and Predicting New Words author Allan Metcalf. He wrote that new words need to meet a threshold for frequency, unobtrusiveness, diversity, generating new forms and meanings, and endurance in order to take hold. In other words, they need to be simple to pick up, used a lot, and able to be used flexibly across different groups and in different ways. Trump is a master of bumper sticker-style slogans and political rhetoric, repeating straightforward, memorable phrases to explain his political agenda that becomes widely used, like America first and drain the swamp. Perhaps the best example is his already tired campaign slogan, Make America Great Again, which he cribbed from President Ronald Reagan. That became so ubiquitous in Trump’s rhetoric that it spawned an acronym and inspired spin-offs, like Make America Healthy Again. Whether liberation day can similarly take hold remains to be seen. For Daniel Rogers, a Princeton University history professor who’s studied political rhetoric, the phrase is a distraction tactic. Changing the subject has always been one of Trump’s favorite tactics, Rogers tells Fast Company. Don’t engage with those who want to know on whom the cost of tariffs is going to fall, or what steep new tariffs will mean for the cost of living. Get people to believe that tariffs will free the nation from the oppressive trade policies of the commercial enemies that surround it. Get them to think that there’s a ‘war’ going on, and that tariff is another, beautiful word for victory. Whether voters outside Trump’s base ever find his trade-war rhetoric convincing seems unlikely. A majority of U.S. adults (55%) believe the Trump administration is focusing too much on tariffs and 64% think it’s not doing enough to lower prices, according to a CBS News/YouGov poll released Sunday. It’s not as if Americans squeezed by years of post-pandemic inflation will greet as “liberators” the higher costs that tariffs will add to cars, housing, food, and other regularly purchased goods.
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E-Commerce
A new study confirms what urban residents and advocates have known for decades: that Americas urban highways are barriers to social connection. The research, published this month in the journal PNAS, quantifies for the first time how highways have disrupted neighborhoods across the 50 biggest U.S. cities. Every single city studied showed less social connectivity between neighborhoods where highways are present. Nobody could put a number on the disruption, and now we can give a score to every single highway segment, says Luca Aiello, a professor at the IT University of Copenhagen and the studys lead author. By comparing the social connections among people living on either side of highways to a baseline model of the same city with no highways, researchers found that the three U.S. cities that have experienced the most social disruption from highway infrastructure are Cleveland, Orlando, and Milwaukee. To infer individual social ties, the study relied upon geolocated user data from social media platform X. Researchers assumed that two individuals were connected if they had mutual followers and estimated users home location based on where their posts were sent from. Aiello notes that there has long been qualitative or small-scale evidence that highways and other urban infrastructure are disruptive to local communities, especially Black neighborhoods. The problem is that nobody had any way to quantitatively measure how much this infrastructure impacts or decreases peoples opportunities to connect across these large highways, he says. If we can quantify and put a number on this, we can quantify the damage that it is doing to our social fabric. In all the cities studied, the barrier effect was stronger at shorter distances (less than about 3 miles) and weaker at longer distances (of about 12 miles and more). If someone wants to cross a multilane highway, it takes a lot of effort,�explains�coauthor Anastassia Vybornova of the IT University of Copenhagen. So highways connect over long distances, but divide over short ones. A long history of disruptive infrastructure Researchers found several examples of highways as interracial barriers, where a predominantly Black community lives on one side of the highway and a predominantly white community exists on the other. Detroits Eight Mile Road is a classic example. They also found examples of highways as intraracial barriers, where the highway runs directly through a predominantly Black community. Nashvilles I-40which split up a vibrant middle-class Black neighborhood,�displacing�about 80% of Nashvilles Black businesses, more than 600 homes, and close to 1,500 peopleis one of many such cases. Highway infrastructure has long been connected to racial segregation practices across the United States. In 1956, President Dwight Eisenhower passed the�Federal Aid Highway Act,�allotting $25 billion to build 41,000 miles worth of highways. The goal was to create a way to connect cities and address the poor road conditions. Ultimately, though, building highways through cities provided white suburbanites with convenient commutes to urban centers, while also allowing governments to remove entire communities of color in the name of urban renewal and slum clearance. As Black Americans began migrating to cities to pursue economic opportunities, wealthier white residents left urban areas for the suburbs in a phenomenon known as white flight. The interests of white suburbaniteswho wanted to use highways to access the city for work and entertainment but also wanted to protect their own property values and businessesheavily influenced infrastructure development plans. According to the�U.S. Department of Transportation, these interstates displaced more than 475,000 households and more than 1 million people. Today, community leaders and historians alike acknowledge that highways were a key tool for segregating and displacing Black communities during the 1950s and 60s. A call for policy solutions Research has long established�negative long-term health impacts�for those living and working near highways. The exposure to increased air and noise pollution, particularly with 300 meters of highways, can lead to an increased risk for lung disease, heart problems, premature birth, respiratory diseases, neurological disorders, and more. But more sparse social connections have very real consequences for residents health and economic well-being, too. [Highways] limit social opportunities, and those social opportunities are connected directly to financial opportunities, Aiello says. Over time we see how these communities continue to lose. City governments and urban planners have increasingly begun working to mitigate these effects by removing or capping highways, with former U.S. Transportation Secretary Pete Buttigieg noting in 2021 that there is racism physically built into some of our highways. Last year, the Biden administration announced $3.3 billion for projects to reconnect neighborhoods divided by the federal highway system. Funds for this program, and others with equity goals, have been halted under the Trump administration. This story was originally published by�Next City, a nonprofit news outlet covering solutions for equitable cities. Sign up for Next Citys�newsletter�for the latest articles and events.
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E-Commerce
Spatial intelligence is an emerging approach to deploying AI in the physical world. By combining mapping data with artificial intelligence, it aims to deliver smart data tied to specific locationseven indoors and across multiple stories. With this technology, maps become more intelligent, evolving into 3D representations that offer contextual information not just about places, but also about the people and activities within them. While Google Maps and other platforms have long mapped streets and roads, the vertical, or Z-axis (i.e. spaces above and below ground) has remained largely uncharted. Until now. The ability to project dynamic intelligence into our world has long been a staple of science fiction and has indeed inspired some real world innovations in Silicon Valley such as early cellphones at Motorola, which were inspired by the Star Trek communicator; or the metaverse, which was inspired by Neil Stephensons novel Snow Crash); any one of several technologies inspired by the film Minority Report, and holograms inspired by Star Wars, to name a few. Today, with large language models handling the delivery and interpretation of information, maps are struggling to catch up. Embedding AI more deeply into our physical environments not only gives contextual relevance to the structures and parts of our physical world, it creates new channels for data collection and analysisabout people, behaviors, and interactions. This means, in effect, that information about places is no longer limited to a flat map; it can now be dynamic, hyper-localized, and personal. Whos building spatial intelligenceand why Many companies are working on spatial intelligence from different angles. Some, like Descartes Labs, synthesize satellite, weather, and market data into actionable intelligence. Blacksky supports military and commercial partners by tracking rapid changes in geography. Mapbox customizes route planning by adding layers of intelligencelike dining options, scenic routes, or even music. Carto helps businesses analyze spatial data to identify patterns and turn those insights into strategy or revenue. While companies like Carto work on backend analytics, others like Mapbox provide direct consumer utility. And the AR industry continues to geolocate content. However, todays spatial analysis is still largely limited to flat maps. To broaden its utility, mapping must become more immersiveaccounting for 3D objects, vertical space, and highly localized environments. Another ambitious player in the field, World Labs, was cofounded by Stanford professor Fei-Fei Li, often called the godmother of AI. The company is building Large World Models (LWMs) that can perceive, generate, and interact with 3D worldscomplete with physics, semantics, and control. With $230 million in funding from a sizable roster of Silicon Valley luminary VCs and companies, World Labs aims to generate limitless virtual spaces, essentially layering privatized dimensional data onto the digital world. Dr. Lis dual roleleading this company while also advising the state of California on AI policyraises potential conflicts of interest, especially as other companies lack such access or influence. The energy problem behind the tech Building and operating spatial intelligence systems demands massive power, and already AIs energy consumption is straining the grid. As AIs energy appetite grows, some tech companies are turning to nuclear power. Microsoft, for example, is funding the restart of Three Mile Island in Pennsylvania; and Amazon has acquired land near the plant. Alphabet/Google signed a deal to purchase energy from multiple small modular reactors through Kairos Power, and Nvidia,� has been backing nuclear-powered AI deployments with PG&E at Californias Diablo Canyon by managing the facilitys First Commercial Deployment of an On-Site Generative AI solution for their Nuclear Energy Sector. Meanwhile Meta, whose prior attempts towards nuclear energy were thwarted by bees, has not given up its effort, and has released an RFP seeking nuclear power partners with either small or large reactors to help them reach their energy usage goals.� It is worrying that the companies that have created the move fast and break things ethos are now getting into the nuclear energy gameand selling their generative AI software to run these nuclear power plants. Many small distributed reactors are being proposed by startups with limited nuclear experience, some near population centers. There are also questions about the dangers and resilience of AI-run software and testing practices, especially when applied to systems as critical as nuclear energy. The return of nuclear power in service of AI and spatial intelligence raises serious concerns, given past nuclear efforts in the U.S. have been fraught with issues such as meltdowns, leaks, and equipment failures. Now, with climate change intensifying and weather patterns destabilizing, previously safe waste storage sites may also be at risk. Spatial intelligence holds undeniable appeal to many, both for utility and profit. The ability to access real-time, contextual information about any spaceeven vertical onesis indeed seductive. But underneath that convenience lies a complex reality: a world where every space could be subject to tracking, surveillance, and monetization. And that, combined with a nuclear push, plays into powering the tech sector and governments vision for new kinds of smart cities, hinted to have less regulation and broader experimentation, with big energy needs. As AIs energy demands grow, the quiet revival of nuclear power by tech folks suddenly disrupting power to build, restore, and run private nuclear power plants, may carry many more unforeseen consequences that will impact all of our lives.�
Category:
E-Commerce
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