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Want more housing market stories from Lance Lamberts ResiClub in your inbox? Subscribe to the ResiClub newsletter. During the pandemic housing boom, we saw red-hot housing demand quickly absorb much of the available slack in the housing market. Back in 2021, active housing inventory for sale, unsold completed new builds, and available lot supply all plunged to historic lows. But ever since the pandemic housing boom fizzled out in mid-2022, housing slack has been building back up in the housing marketespecially in certain pockets of the Sun Belt and Mountain West. Look no further than Zondas “New Home Lot Supply Index,” which measures lot supply based on the number of single-family vacant developed lots and the rate at which those lots are absorbed via housing starts. A higher index value indicates a greater supply of single-family vacant developed lots, while a lower index value indicates a tighter lot supply/new construction market. That index in Q2 2025 climbed to 68.4well above the all-time low of 35.8 set at the height of the pandemic housing boom in Q2 2022, when builders were buying as much entitled land as they could find. The timing of land and lot deliveries is a growing challenge in todays housing market,” wrote Zonda chief economist Ali Wolf on August 12. “While builders had planned to increase housing starts in 2025, they slowed production as the year progressed due to choppy consumer demand and rising resale supply. This slower pace of construction contributed to the five-year high in Zondas Lot Supply Index, as fewer lots were converted into starts.” According to Zonda, homebuilder lot supply loosened/rose in 22 of the 30 major metro-area housing markets tracked over the past 12 months. Housing markets like Tampa, Florida; Austin; Nashville; and Charlotte, North Carolina, experienced some of the most significant year-over-year loosening of lot supply. That said, despite an uptick in available lots in some markets on a year-over-year basis, most housing markets are still what Zonda considers significantly undersupplied. Zondas New Home Lot Supply Index has five groupings: significantly oversupplied = plus 125 score slightly oversupplied = 115 to 124 score appropriately supplied = 85 to 114 score slightly undersupplied = 75 to 84 score significantly undersupplied = below 75 score According to Zonda, three major metro-area housing markets now are appropriately supplied for lot/land supply: Austin, Atlanta, and Dallas. Note: If Zonda had analyzed more than 30 markets, the count would likely have been higher than just threeespecially in some softer pockets of Southwest Florida.
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While Sam Altman, Elon Musk, and other AI industry leaders cant stop singing the praises of the technology, a growing number of average Americans are forming a different opinion. According to YouGov data from July, Americans are increasingly likely to believe that AI will be bad for humans. Specifically, 43% of Americans say they fear AI will end the human race (up 6% since March), and 47% believe that AI will have a net adverse effect on society (up 7% since March). With this rise in AI pessimism, there has been a surge in new slurs and slang terms that capture the negative connotations people increasingly associate with AIand the individuals who use it. Here’s a guide to the five terms you need to know: “AI washing,” “clanker,” “Groksucker,” “slop,” and “slopper.” AI washing No, AI hasnt suddenly found a way to do your laundry while you do art. If you hear someone talking about AI washing, they are referring to a deceptive marketing practice where companies exaggerate the role AI plays in their product or service. This deceptive marketing practice gets its name from green washing, where a company falsely or misleadingly touts its environmentally friendly policies. Any company can be guilty of AI washing if it misstates the role AI plays in its products. Companies in industries that are more prone to doing this are those in the technology and finance sectors, which is why the Securities and Exchange Commission (SEC) has publicly warned against the practice. AI washing, whether it’s by financial intermediaries such as investment advisers and broker dealers, or by companies raising money from the public, that AI washing may violate the securities laws, former chairman of the SEC Gary Gensler warned in 2024. The current Trump administration also seems to be cracking down on AI washing as well, according to Holland & Knight’s SECond Opinions Blog. If someone is said to be an AI washer, it means they are being accused of offering a product that doesnt rely on AI as much as they say it does. Clanker This is the newest AI slur on this list, and its use has exploded in recent months. As Fast Company previously reported, clanker is a derogatory term for robots. The term comes from the fictional Star Wars universe, where droids are often treated as second-class citizens at best. But increasingly, the term is being adopted not just to describe our real-world AI-powered robots, but AI systems that threaten our jobs or remove human connections from our lives. One system often referred to as a clanker is the AI chatbot that people are now forced to talk to when they call a customer support line. I called my bank to ask about my balance, but had to talk to a clanker instead of a human. Groksucker While clanker is a slur aimed at bots and AI systems, several slurs have arisen to define humans who are overly engaged with certain AI systems, particularly generative AI chatbots. Perhaps the most visceral one in this category is Groksucker (you can figure out for yourself what other word the term mimics). The term gets its name from Elon Musks xAI chatbot Grok. And Grok itself says the term describes people who frequently interact with me, Grok, in a way some find repetitive or annoying, adding that the term is tied to concerns about AI overuse or privacy on X. While Groksucker is generally limited to describing a subsection of Grok users, another term exists for those who are overreliant on the most popular chatbot, ChatGPT. But more on that below. Slop If there is one term that has become synonymous with AI-generated content, it is slop. Slop refers to low-quality, high-output content generated by AI tools that are increasingly overrunning our feeds. Slop is Shrimp Jesus proliferating on Facebook and Instagram. Slop is YouTube videos with completely AI-generated scripts, images, and thumbnails that crowd out high-quality human-made creators. Slop is articles written by a machine instead of a person. And slop is what is causing the dead internet theory to transition from fringe conspiracy to prophetic foresight. Slop is everywhere now, and its only going to get worse. Sloppers This list wouldnt be complete without including a slang term that has recently been adopted to describe people who are overreliant on the worlds most popular AI chatbot, ChatGPT. That word is sloppers. The slur gained popularity after a TikTok posted by user intrnetbf went viral last month. In the video, the user said his friend came up with the term sloppers to describe people who are using ChatGPT to do everything for them. If someone is a slopper, it means that they have offloaded most of their cognitive processes to ChatGPT. This cognitive offloading involves asking ChatGPT for guidance on various tasks a person should be mentally well-equipped to handle on their own, such as planning what to do for the evening, how to respond to a text message from a family member, or whether to make a significant life change, like quitting a job. Technological slurs can change how the public viewds a product While many reading this may find some of the above AI slang humorous (and even fitting), the fact that these terms are entering the public lexicon is likely to alarm some companies operating in the AI space. When the public adopts new derogatory names for products, technologies, and the people who use them, it usually signals that popular perception isn’t heading in a positive direction. This can trigger a snowball effect, where peope en masse reject the technology. The glasshole backlash against Google Glass is a well-known example of this. Artificial intelligence is, of course, a much larger and more transformative force than Google Glassand its unlikely to disappear despite the increasing slurs directed at it. However, this emerging slang does indicateas YouGovs polling also showsthat the public is increasingly wary of the technology, and isnt afraid to voice it.
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Businesses have long leaned on cutting-edge technology to maximize profits, while the nonprofit sector has traditionally been slower to incorporate innovations such as AI. But if we want to tackle the worlds most pressing social problems, that must change, says philanthropist and MacArthur Genius grant recipient Jim Fruchterman in a new book. In Technology for Good: How Nonprofit Leaders Are Using Software and Data to Solve Our Most Pressing Social Problems, out September 2nd, Fruchterman highlights social good organizations that are using technology to solve real-world problemshomelessness, mental illness, climate change, child abuse, and more. Fruchterman is a tech-for-good leader and the founder of the nonprofit Benetech, which created Bookshare, an online library for people who are blind or visually impaired. He spoke with Fast Company about some of the ways technology is being used to make the world a better place and what he hopes readers glean from his book. Its refreshing to talk to a business leader about how to use technology for social good instead of how to use it to drive profits. [Laughs.] I call it moving from money to meaning. What are the challenges that nonprofits and social-good organizations face when it comes to technology? One is a lack of money. Funding is tight. And while tech is often cost-effective, if you have a hard time coming up with the money to buy the tech, it’s hard to use. There are also often low levels of tech capacity among the staff. People are used to using the telephone as opposed to going on a Zoom call. The social sector also prioritizes different things than the for-profit sector. Its not just about efficiency. People are still pretty important in the social change sector. Saying, Hey, you can get rid of a bunch of people (by implementing a new technology) may not be the best sales pitch for a charity that is trying to help people. What are some social problems that technology could help solve? I spotlight in my book TalkingPoints, which helps teachers communicate with kids parents who dont speak English. If you can get the parents more engaged, kids are a lot more successful in school. Thats a great example of a technology that fills a need for immigrant parents. Community Solutions Built for Zero initiative is trying to end homelessness. For years, we treated the symptoms: Lets build temporary housing, get people food and clothing. Theyre asking, Can we say that everyone who was homeless three months ago is now housed? The key tech innovation is a by-name list keeping track of everyone across community places that these people go into. When shelters say, Our beds have been 80% used this month, that measures output, but it doesnt say anything about whether were solving the homelessness problem. So much of what the social sector does is move information aroundwell, thats what information technology is for. What would you say to a nonprofit leader who feels overwhelmed by or unqualified to make decisions around technology? Find people in your field who are ahead of you on the technology journey and learn from them. Talk to your peers. If theyre saying, Were writing a third more grants with the same amount of staff using ChatGPT or Claude, then thats worth paying attention to, because its not their business to sell you things. In your book, you highlight some bad ideas in tech-for-good efforts. Which do you see repeated the most? The cult of the custom. Its the idea that my nonprofit is such a unique snowflake that I need custom software built to solve my organizations problem. And businesses stopped writing custom software 20 years ago because no golf course, no restaurant, no dentist needs to be writing software to run their company. When you write your own software, youre the only customer. It means that every bug that needs to be fixed, youre the only one paying for it. You should look for a product that can be adapted to your needs. Also: I see lots of people building an app that no one will download. Or people following whatever the latest fad isfive or eight years ago, that was blockchain. That didnt work out. Three to five years ago, it was the metaverse. That didnt work out. Right now, its generative AI. Im glad you brought up AI. Whats your take on where AI should and shouldnt be used in social impact work? I think you shouldnt replace human empathy and understanding with AI that doesnt understand what its saying and have any empathy whatsoever. People in the nonprofit sector turn to human beings to help them. The best applications of AI in social good are around making the people on the frontlines of social change more effective. Lets say Im trying to automate a mental health counselor. Do I want to replace the counselor with a chatbot? Right now, its not a great idea. But if we can instead cut their amount of data entry time or paperwork time in half, then thats time they can spend with another person who needs their help.
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