THE SET-UP: Silicon Valley has produced a lot over the last thirty years. It’s generated a lot of gadgets, a lot of growth, a lot of wealth and a lot of pain. And that pain has been distributed unequally … just like The Valley’s gains.
That’s the takeaway from this year’s installment of the Silicon Valley Pain Index. The annual report by the San Jose State University Human Rights Institute indexes the stark divide between have and have-nots … particularly the housed and the housed-nots … in one of the world’s leading engines of economic growth. The problem is that Silicon Valley is also an engine of inequality. As Anji Buckner-Capone, an assistant professor at San Jose State, said upon the Index’s release, “The 2025 Silicon Valley Pain Index continues to show the pervasiveness of inequality in our communities. The central message is that the challenges we’re facing are rooted in systemic failures.”
The San Jose Mercury News summarized the findings:
According to the report, there are 10,394 unhoused residents in Santa Clara County, which includes 2,200 students in San Jose alone. The report also found that San Jose would need to build almost 8,000 homes each year to reach its 2031 housing goals, when the most homes it’s added in a single year since 2019 was 1,710.
While the nine wealthiest Silicon Valley households earned $136 billion more last year than the year before,100,000 Silicon Valley residents had virtually no net assets, Buckner-Capone said.
It’s worth noting that at the same time Silicon Valley was “disrupting” the cab business with ride-sharing apps, The Valley also generated some of the first stories of workers who had to live in their car because they were priced-out of the rental market or they simply couldn’t recover from the bursting of the housing bubble in 2008.
The housing market quickly left them behind as investors, flush with cash from the Fed’s Quantitative Easing bonanza and fueled by artificially low interest rates, sparked another spike in the housing market. Silicon Valley grew bigger and faster than before. But this wasn’t the Dot-Com Bubble, which was built on network infrastructure and computer hardware ... this boom was built on social media and apps and market disruptive services that fueled billion-dollar start-ups with far less employees than Hewlett-Packard’s consumer product division or the network architecture-builders at Sun Microsystems.
Now you could build a billion-dollar unicorn with a small team of tech bros and wait for the buyout to make ten or fifteen dudes overnight millionaires. They, in turn, spent their money on services … they wanted food delivered and homes cleaned … and the bifurcation in the regional economy expanded. Many of those unicorns were lured to San Francisco and the much-reported “decline” of The City was an outgrowth of tech bros armed with oodles of cash displacing the middle and working classes. By the arrival of the pandemic, The City had become a dystopia of wealth and income disparity. It’s the same story back in The Valley:
Briyana Costa, a graduate student who did research for the index, said residents would need to make about $125,000 annually to afford average rent in San Jose, which is currently $3,209 per month, according to Zillow.
“The high cost of living in the community is forcing people to make impossible choices,” Costa said. “Families are doubling and tripling up in single apartments. People are working multiple jobs, sacrificing their health and well-being to just meet basic needs.”
According to the report, 90% of parents surveyed by San Jose’s Second Harvest Food Bank – which serves half a million people every month – worry that they won’t be able to provide nutritious food for their children.
…but wait, there’s more…
The index also reported stark disparities between schools in different neighborhoods: While public schools in Palo Alto spent $26,000 per student in 2025, public schools in the East Side Union High School District spent about $14,000.
Ruth Melton, an undergraduate student who provided research for the index, said the lack of affordable housing in the Bay Area led to the decreases in enrollment, which itself contributed to the upcoming closure of 14 schools across three school districts on the east side of San Jose.
“How will they get their child to school when their school is no longer walking distance and they don’t own a car?” she asked.
These challenges, Melton said, would have a “domino effect.” The index reported that 1,028 Santa Clara County high school students had dropped out in the 2023-24 school year. Melton, meanwhile, highlighted that 79.2% of residents in the Los Gatos-Saratoga Joint School District had bachelor’s degrees or higher, compared to just 25% in the East Side Union District.
This is the backdrop for the third tech boom—the rise of artificial intelligence. Like the second boom, it is going to shed workers … only more so … a lot more so, in fact. The Tech Overlords have opined about replacing coders and, frankly, any “white collar” worker who can be switched out for a cheaper, more efficient alternative. And when they start cutting and pasting A.I. into those positions, Wall Street will reward them with escalating stock prices. Wall Street loves lower overhead and workforce reductions.
It could mean a deflation of the housing market if fewer people are making enough money to buy a house … supply outstripping demand could put more homes in play. But, then again, private equity is out there buying-up homes with the capital they’ve accrued thanks in part to the unicorns who’ve shown that the one thing Silicon Valley produces better than any other economic sector is … inequality. - jp
TITLE: Differing levels of access to AI create new inequalities
https://betanews.com/2025/07/16/differing-levels-of-access-to-ai-create-new-inequalities/
EXCERPTS: A new survey of 4,000 knowledge workers across the UK, US, Germany, and Canada reveals that higher earners have disproportionate access to the latest AI tools and training, allowing them to reap AI's promised rewards.
In contrast, the study from The Adaptavist Group reveals that lower earners and women are being shut out from AI opportunities, which impacts their skill development, job satisfaction, and time savings, both personally and professionally.
Respondents with household incomes of over £100,000 ($134,000) were more than twice as likely (27 percent versus 11 percent) to have received over 20 hours of AI training in the last year, compared with those on household incomes of £30,000 ($40,200) or less. As a result, 58 percent of those bringing in higher incomes strongly believe they've received sufficient guidance on AI, compared to 25 percent of those on lower pay. More than three-quarters (78 percent) of those with six-figure incomes also say they were provided with access to new AI tools regularly, in stark contrast to less than half (49 percent) of respondents with incomes less than £30k.
In addition 50 percent of high earners report that AI has significantly increased their job satisfaction, compared to 29 percent on average, and just 14 percent of those with incomes less than £30k. 80 percent of high earners say their skills are developing due to AI, versus an average of 68 percent and just 49 percent of lower earners. 69 percent of high earners feel comfortable proving the ROI of AI, compared to 51 percent on average and 37 percent of lower income respondents.
Training divides are also emerging between large enterprises and small businesses. In fact, 24 percent of small businesses (one to 50 staff members) have had no training at all in the last 12 months, and 56 percent have had less than three hours of training. Comparatively, just 12 percent of large organizations (more than 5,000 staff members) had received no training, whereas the majority (64 percent) had received more than three hours.
There’s a developing gender divide too with women receiving less AI training than men. 45 percent of women say they had received more than five hours of training in the last 12 months, compared to 57 percent of men. 21 percent of women have had less than an hour of training on AI, or none at all, whereas just 14 percent of men say the same. 51 percent of women say they have completed a formal AI training accreditation, versus 61 percent of men.
This gap is true at all levels too, only 58 percent of women in director roles received structured training sessions on AI from external providers compared with 73 percent of men in the same position. At intern level, the figures show that men are more than twice as likely to have received external training (47 percent versus 23 percent).
You can find out more and get a copy of the report on the Adaptavist site.
TITLE: From colonialism to AI: How the Global South became the world’s inequality hotspot
https://www.dawn.com/news/1915399/from-colonialism-to-ai-how-the-global-south-became-the-worlds-inequality-hotspot
EXCERPTS: While one half of the world is busy riding the wave of the AI revolution — racing to patent algorithms, train billion-dollar generative models, and automate the future — the other half is still waiting for something as basic as electricity. Nearly 600 million people in Africa remain without reliable access to power — that’s almost half the continent’s population, and more than 80pc of the global electricity access gap. It’s a sobering contrast. One side teaches machines to outthink humans; the other side lights candles to chase away the dark. In an era of satellites, AI, and trillion-dollar tech empires, this scale of inequality is dangerous.
The numbers say it all
When it comes to measuring income inequality, few tools are as widely recognised as the Gini Index. The scale runs from 0 to 1, or 0pc to 100pc, where 0pc means perfect equality and 100pc means total inequality (all wealth concentrated in a single pair of hands). According to World Bank data drawn from recent years, South Africa tops the list with a staggering Gini Coefficient of 63pc, while Slovakia sits at the other end with just 24.1pc. For comparison, the United States clocks in at 41.3pc and China at 36.7pc. In South Asia, Pakistan stands at 29.6pc, India at 32.8pc, and Bangladesh at 33.4pc.
In Asia, a study focused on India reveals something striking. The ‘Billionaire Raj’ is now more unequal than the colonial British Raj ever was. Since the early 2000s, inequality has soared. The top 10pc in India saw their income share jump from 40pc in 2000 to 58pc in 2023.
The real drivers? The top 1pc, whose slice grew from 15pc to 23pc, while the middle 40pc lost ground, shrinking from 39pc to 27pc. The United Nations Development Programme’s (UNDP) Multidimensional Poverty Index 2024 adds another layer. Out of 112 countries surveyed, 1.1 billion people out of 6.3 billion are living in poverty. India alone accounts for 234 million people living in poverty — more than the total populations of at least 29 smaller Asian nations combined.
In Indonesia and Pakistan, the top 10pc claim 46pc and 42pc of national income, respectively — a quiet confirmation that this is no regional fluke, but a structural feature of inequality across the South.
Latin America remains the world’s most unequal region. Here, the richest 10pc earn 12 times more than the poorest 10pc. In countries like Colombia, Chile, and Uruguay, just 1pc of the population controls between 37pc and 40pc of total wealth. The bottom half? They’re left with barely 10pc.
In Africa, the story grows more complex. While economic growth is occurring, it remains unevenly distributed. A joint report by the Agence Française de Développement (AFD) and the World Bank reveals that between 1980 and 2016, the richest 1pc of Africans captured 27pc of total income growth. In 2024, Sub-Saharan Africa — home to just 16pc of the world’s population — carries 67pc of the world’s extremely poor.
The takeaway is clear — economic growth may lift national economies, but it does not guarantee equitable outcomes.
This stark disparity across the Global South can largely be traced back to colonial legacies. Under colonial rule, land and resources were concentrated in the hands of a privileged few, entrenching class divisions that continue to shape social and economic realities today. Even after independence, low social investment, unequal access to education, weak tax systems, and the enduring influence of powerful elites in policymaking have all worked to reinforce these imbalances. And so today, we have a system that not only tolerates but sustains inequality — not just in Latin America, but throughout the Global South.
Even advanced economies like the United States aren’t immune to the rising tide of inequality. A recent survey found that, after immigration, income inequality ranked as the second most pressing concern for Americans, with many hoping Trump would address it within his first 100 days in office. It’s not hard to see why.
Consider this: the collective net worth of America’s top 12 billionaires now exceeds $2 trillion. Between March 18, 2020, and December 3, 2024, their combined wealth soared by $1.3 trillion — a 193pc increase. If evidence of deepening inequality is needed, the pandemic offers it in plain sight. Covid-19 did a lot more than disrupt lives; it supercharged billionaire fortunes, widening an already vast wealth divide.
A 2022 study co-authored by Nobel Laureate Daron Acemoglu highlights another powerful driver of inequality: automation. By replacing human labour in industries like retail, manufacturing, and customer service, automation alone accounted for 50–70pc of the growing income gap between more-educated and less-educated workers from 1980 to 2016 — a sobering reminder that technology, without the right policies in place, can entrench inequality rather than alleviate it.
Now, what about the future? In 2024, the International Monetary Fund (IMF) sounded the alarm, expressing “profound concerns” over labour disruptions and rising inequality as economies begin to adopt generative AI at scale. The Fund warned that generative AI could amplify the market power of already-dominant firms, accelerating the shift toward winner-takes-all dynamics and further concentrating capital in the hands of a few.
TITLE: White collar workers displaced by AI could spark a revolution
https://nypost.com/2025/07/14/opinion/white-collar-workers-displaced-by-ai-could-spark-a-revolution/
EXCERPTS: Earlier this month, Microsoft announced plans to lay off 9,000 employees, joining the ranks of tech companies cutting headcounts while touting the productivity gains enabled by artificial intelligence.
According to CEO Satya Nadella, up to 30% of the company’s code is now being written by AI. Salesforce CEO Marc Benioff one-upped him after his own firm’s layoffs, claiming that up to 50% of their work is now being shouldered by AI.
These are not simply corporate earnings call updates. They are previewing the future of work in America.
When the last big economic disruption of globalization struck blue-collar workers, sending manufacturing jobs overseas, the result was hollowed-out communities, an opioid crisis and an unfulfilled promise of “retraining” for “the jobs of the future.”
Now, the AI wave is primed to hit those exact jobs, and the people who built their own prosperity on the wave of globalization that left so many others behind.
The complexity scientist Peter Turchin has shown how, throughout history, an excess of elites with poor economic prospects is the path to political instability. Going back as far as the late Roman Republic, elite overproduction is a key contributor to chaos (alongside stagnating or declining general living standards and increased public debt — which may sound familiar).
The American laptop class is a political powder keg. As the comfortable jobs they were promised become harder to land, and the self-validating stories they told themselves of their own value come unwound, competition will become fierce.
As more and more of them end up on the losing side, Occupy Wall Street may look like a mild preview of what’s to come.
How long will this all take? If we have decades to adapt, older workers will have time to learn new skills while younger workers can adjust their own career paths. New industries can spring forward to use the labor no longer dedicated to litigating in court, speculating in markets and posting on social media.
But if the disruption happens more quickly, we risk creating millions of displaced knowledge workers who will have not only the skills and networks, but also the time and motivation to organize a radical political movement.