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Architects have long complained about the industry’s relatively paltry pay. Given the amount of expensive education architects require (master’s level), and the years they have to put in (many) before qualifying to take a licensure exam (arduous), they have been rightly upset: Architects can barely expect to crack the $100,000 salary mark after more than eight years in the profession. Now there are some numbers to back that up. Compared to every other design descipline Fast Company has studied in our our ongoing analysis of where the design jobs are, architects are underpaid, particularly as their careers progress. Their compensation increases at the slowest rate, based on years of experience. Fixing the problem requires a nuanced understanding of the outside factors that limit pay, according to Evelyn Lee, president of the American Institute of Architects. “Architecture is an industry that’s always been known to work within tight margins,” she says. Part of the reason is that the industry long ago set standardized fee structuresbasically a percentage of overall construction costsand those numbers haven’t changed much. “Our ability to get paid more is tied back to that,” Lee says. Architecture is also tied to economic cycles, and it can be a bellwether of recessions. “When things are good, and people are spending a lot of money on capital costs, we are doing well. But we’re usually the first service to get cut when people start to hold back, and we’re the last to come on board when the economy starts coming back,” Lee says. And because they’re never quite sure when the next project will come around, many architecture firms end up being conservative with their spending and salaries. Also, the highly competitive nature of the architecture industry means that it is governed by antitrust laws that prohibit price fixing. These laws are meant to encourage competition, but they often end up creating a race to the bottom. Firms underbid each other in order to secure commissions, and then rely on underpaid workers and uncompensated overtime to get the job done. “It’s very internalized in the profession, starting at the university level,” says Jennifer Siqueira, an architect at New York-based Bernheimer Architects who helped organize the first union at an architecture firm in the U.S. “You’re taught to work very hard because it’s like these are passion projects. It’s almost an artistic endeavor to do architecture . . . It’s a very exploitative environment.” All-nighters are common in the field, from university through the working world; Siqueira says that she herself worked through the night multiple times in previous jobs at architecture firms, including some that are very prominent. Part of the unionization effort she led at her current firm was centered around improving working conditions and making the level of pay match the level of effort. She and fellow union organizers even negotiated with the firm’s management to set salary floors based on years of experience. “It’s very rare, especially because in a lot of contracts you’ll see a clause saying you can’t even talk about what you make to another coworker,” Siqueira says. “This is a level of transparency that’s really lacking within the profession.” Lee, at the AIA, says that the association conducts its own compensation surveys in order to fill that void, but she explains that the upwind forces that limit architects’ fees and salaries are largely beyond the industry’s control. Still, that doesn’t mean architects should sit back and wallow in low fees forever. She says that the AIA has increased the number of training programs it provides that are geared toward the business side of running architecture firms, and it encourages architects to be more proactive in offering clients more than just the limited scope of a one-off building design. “I do think there’s an opportunity to get more savvy though about how we package and deliver our services in a way that better reflects the value that we bring to the table,” she says. Changing an industry takes time, especially one that is predominantly made up of small businesses. About 75% of the 19,000 architecture firms operating in the U.S. have 10 employees or fewer, and 28% are run by sole practitioners. Architects are “wearing many hats, as the marketer and the operations person,” Lee says. Other types of designers work within “a much bigger ecosystem, where they have business experts that are brought on to support non-project needs. We architects feel like we have to do that all on our own.” Lee, who has worked as a fractional chief operating officer for multiple small and medium-size architecture firms, says that the AIA is “trying to support our architects and tell them that it’s just as important to design their business as it is to deliver design as a practice.” But that may take longer than some architects are willing to wait. In the meantime, Siqueira says there’s a clear path toward improving pay and working conditions for architects: “The only way is to unionize,” she says. This article is part of Fast Company‘s continuing coverage of where the design jobs are, including this year’s comprehensive analysis of 170,000 job listings.
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E-Commerce
Artificial intelligence is rapidly being adopted to help prevent abuse and protect vulnerable peopleincluding children in foster care, adults in nursing homes, and students in schools. These tools promise to detect danger in real time and alert authorities before serious harm occurs. Developers are using natural language processing, for examplea form of AI that interprets written or spoken languageto try to detect patterns of threats, manipulation, and control in text messages. This information could help detect domestic abuse and potentially assist courts or law enforcement in early intervention. Some child welfare agencies use predictive modeling, another common AI technique, to calculate which families or individuals are most at risk for abuse. When thoughtfully implemented, AI tools have the potential to enhance safety and efficiency. For instance, predictive models have assisted social workers to prioritize high-risk cases and intervene earlier. But as a social worker with 15 years of experience researching family violenceand five years on the front lines as a foster-care case manager, child abuse investigator, and early childhood coordinatorIve seen how well-intentioned systems often fail the very people they are meant to protect. Now, I am helping to develop iCare, an AI-powered surveillance camera that analyzes limb movementsnot faces or voicesto detect physical violence. Im grappling with a critical question: Can AI truly help safeguard vulnerable people, or is it just automating the same systems that have long caused them harm? New tech, old injustice Many AI tools are trained to “learn by analyzing historical data. But history is full of inequality, bias, and flawed assumptions. So are people, who design, test, and fund AI. That means AI algorithms can wind up replicating systemic forms of discrimination, like racism or classism. A 2022 study in Allegheny County, Pennsylvania, found that a predictive risk model to score families risk levelsscores given to hotline staff to help them screen callswould have flagged Black children for investigation 20% more often than white children, if used without human oversight. When social workers were included in decision-making, that disparity dropped to 9%. Language-based AI can also reinforce bias. For instance, one study showed that natural language processing systems misclassified African American Vernacular English as aggressive at a significantly higher rate than Standard American Englishup to 62% more often, in certain contexts. Meanwhile, a 2023 study found that AI models often struggle with context clues, meaning sarcastic or joking messages can be misclassified as serious threats or signs of distress. These flaws can replicate larger problems in protective systems. People of color have long been over-surveilled in child welfare systemssometimes due to cultural misunderstandings, sometimes due to prejudice. Studies have shown that Black and Indigenous families face disproportionately higher rates of reporting, investigation, and family separation compared with white families, even after accounting for income and other socioeconomic factors. Many of these disparities stem from structural racism embedded in decades of discriminatory policy decisions, as well as implicit biases and discretionary decision-making by overburdened caseworkers. Surveillance over support Even when AI systems do reduce harm toward vulnerable groups, they often do so at a disturbing cost. In hospitals and eldercare facilities, for example, AI-enabled cameras have been used to detect physical aggression between staff, visitors, and residents. While commercial vendors promote these tools as safety innovations, their use raises serious ethical concerns about the balance between protection and privacy. In a 2022 pilot program in Australia, AI camera systems deployed in two care homes generated more than 12,000 false alerts over 12 monthsoverwhelming staff and missing at least one real incident. The programs accuracy did not achieve a level that would be considered acceptable to staff and management, according to the independent report. Children are affected, too. In U.S. schools, AI surveillance like Gaggle, GoGuardian, and Securly are marketed as tools to keep students safe. Such programs can be installed on students devices to monitor online activity and flag anything concerning. But theyve also been shown to flag harmless behaviorslike writing short stories with mild violence, or researching topics related to mental health. As an Associated Press investigation revealed, these systems have also outed LGBTQ+ students to parents or school administrators by monitoring searches or conversations about gender and sexuality. Other systems use classroom cameras and microphones to detect aggression. But they frequently misidentify normal behavior like laughing, coughing, or roughhousingsometimes prompting intervention or discipline. These are not isolated technical glitches; they reflect deep flaws in how AI is trained and deployed. AI systems learn from past data that has been selected and labeled by humansdata that often reflects social inequalities and biases. As sociologist Virginia Eubanks wrote i Automating Inequality, AI systems risk scaling up these long-standing harms. Care, not punishment I believe AI can still be a force for good, but only if its developers prioritize the dignity of the people these tools are meant to protect. Ive developed a framework of four key principles for what I call trauma-responsive AI. Survivor control: People should have a say in how, when, and if theyre monitored. Providing users with greater control over their data can enhance trust in AI systems and increase their engagement with support services, such as creating personalized plans to stay safe or access help. Human oversight: Studies show that combining social workers expertise with AI support improves fairness and reduces child maltreatmentas in Allegheny County, where caseworkers used algorithmic risk scores as one factor, alongside their professional judgment, to decide which child abuse reports to investigate. Bias auditing: Governments and developers are increasingly encouraged to test AI systems for racial and economic bias. Open-source tools like IBMs AI Fairness 360, Googles What-If Tool, and Fairlearn assist in detecting and reducing such biases in machine learning models. Privacy by design: Technology should be built to protect peoples dignity. Open-source tools like Amnesia, Googles differential privacy library, and Microsofts SmartNoise help anonymize sensitive data by removing or obscuring identifiable information. Additionally, AI-powered techniques, such as facial blurring, can anonymize peoples identities in video or photo data. Honoring these principles means building systems that respond with care, not punishment. Some promising models are already emerging. The Coalition Against Stalkerware and its partners advocate to include survivors in all stages of tech developmentfrom needs assessments to user testing and ethical oversight. Legislation is important, too. On May 5, 2025, for example, Montanas governor signed a law restricting state and local government from using AI to make automated decisions about individuals without meaningful human oversight. It requires transparency about how AI is used in government systems and prohibits discriminatory profiling. As I tell my students, innovative interventions should disrupt cycles of harm, not perpetuate them. AI will never replace the human capacity for context and compassion. But with the right values at the center, it might help us deliver more of it. Aislinn Conrad is an associate professor of social work at the University of Iowa. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Gen Zers are putting their money where their mouths are when it comes to shopping. Nearly all Gen Z consumers96%say they shop with intention, and 66% believe their purchases should reflect their personal values, according to the newly released Lightspeed Commerce report, which surveyed over 2,000 North American shoppers. Spending habits have never been more visible, thanks to social media. Todays consumers have more ways than ever to signal their morals and valuesand more platforms to share those choices. Posting shopping hauls and empties videos, or filming a fit check with coffee in hand has become prime social media fodder. In an age where everything is content, more consumers are choosing brands that reflect who they are and what they stand for. A hallmark of Gen Z is coming to age in a hyper-connected world. In this world, every follow, like, repost, and even purchase is a direct reflection of a persons identity and values, Lightspeed CEO Dax Dasilva tells Fast Company. Through this connected world, there is a never-ending exposure to global issues, where activism, accountability, and cancel culture move at the speed of light. Today, the wrong purchase can carry social consequencesnot just from peers, but from the broader judgment of the internet. This pressure is especially strong among Gen Z: Thirty-two percent fear being canceled for supporting the wrong brands, which is more than five times higher than for boomers (6%). In many ways, this fear of being judged or canceled and the understanding of the weight of their buying decisions differentiates Gen Z from older generations, who have traditionally shopped based on things like price or quality, Dasilva says. This trendwhat Lightspeed calls value spendingis part of a broader consumer shift. Nearly all consumers (92%) identify as at least somewhat intentional in their purchases. While price (78%) and quality (67%) remain top priorities across generations, purchasing decisions that align with personal values or identity are close behind, cited by 62% of respondents. In the past six months, 27% of consumers made purchases based on national pride; 18% supported brands tied to charitable or social causes; another 18% chose products for their sustainability impact; and 15% factored in a CEOs political alignment. For 32% of these value spenders, this is a new behaviorbut half believe their spending carries more influence than ever before. Value for money has taken on a new meaning.
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E-Commerce
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