10 Charts That Capture How the World Is Changing (July 2023)
From Higher Education to AI Art, Therapy to Venture Capital Funding
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10 Charts That Capture How the World Is Changing (July 2023)
Last fall, I started a series called “10 Charts That Capture How the World Is Changing.” I’ve written a few versions since then, and the most recent version from March is actually the most-read Digital Native ever.
This week, we’re again diving into 10 charts. I’ve always been a visual learner, and charts help me process information. They’re also an efficient way to encapsulate how the world is changing. The goal here is to share charts that I find interesting and emblematic of broader themes.
The charts this week again cover a broad range of themes—
Confidence in Higher Education
Confidence in Institutions
Is Art Created by AI Still Art?
A Venture Capital Reset
The Highs and Lows of Threads
More Americans Are Living Alone
Therapy Goes Mainstream
A Climate Reckoning
My hope is that this is an engaging way to visualize how the world is changing.
Let’s jump in 📈
1️⃣ Confidence in Higher Education
Americans are losing confidence in higher education. And that confidence is slipping fast: in 2015, 57% of Americans had a “Great deal” or “Quite a lot” of confidence in higher-ed; by 2023, that number was down to 36%.
This is driven by a series of factors: ballooning student loan debt; COVID; a fast-changing job market. The ROI on a college education is poor, particularly for non-STEM majors and for students who don’t attend a top school. What’s more, college doesn’t prepare a learner for the modern labor market; the college system made sense for a post-Industrial Revolution world in which one skill might last you a career, but it makes less sense in a technology-fueled world in which skills rapidly become obsolete. With AI coming for our jobs, why shell out $100K+ for an education that doesn’t even insulate you from automation?
One interesting stat: 85% of today’s college students will have jobs in just 11 years that don’t currently exist. This requires worker reskilling and yet, only 0.1% of GDP is spent on helping workers retrain—less than half of what was spent 30 years ago. This means that we’ll rely on the private sector to reskill, and there are compelling startups tackling that challenge like Guild and Reforge. Yet there clearly need to be more, particularly with AI creating a shock in the labor markets.
There’s another factor—one that’s overlooked—powering the backlash to higher-ed: generational change. The man who coined the word “Millennial” back in 1991, Neil Howe, is out with a new book, and I like his descriptor of the Millennial generation: “The struggle to achieve, behave, fit in, risk-manage, and please others—all at the same time—is pushing Millennials toward an optimizing, menu-driven, even perfectionist approach to life that often leaves them chronically stressed,” he writes. Howe paints the Millennial generation as a generation that fully trusted in the idea of meritocracy, enduring an extraordinary amount of schooling, testing, and examination (alongside mountains of student loan debt) with the promise of getting ahead.
As Millennials struggled to translate that effort into economic reality, though, those values calcified into skepticism, nihilism, and anger toward capitalism. We see these traits even more pronounced in Gen Z, which grew up under the Great Recession, rising populism, and the pandemic.
Younger generations are more often skipping college altogether, preferring to seek alternative forms of learning and preferring to begin earning income sooner—on their own terms. New forms of work have underpinned these new behaviors: it’s now possible to make a living as a YouTuber or a TikToker, a Whatnot seller or Flagship merchant, a Roblox developer or Overwolf modder. These “digitally-native jobs” offer an alternative to traditional forms of work, and they don’t rely on a college education. I expect we’ll see higher-ed enrollment continue to decline, with emergent forms of vocational schooling and lifelong learning taking its place.
2️⃣ Confidence in Institutions
Related to confidence in higher education is confidence in institutions writ large. Americans’ confidence in institutions is down across the board:
This is a decades-long shift. I’ve always liked how the below visual from Night Media captures the evolution of public influence and trust—Americans used to admire NASA and aspire to be an astronaut; then they admired corporations and wanted to be Bill Gates; now, they admire individuals and see a path to themselves cultivating a community and online influence.
We see this shift in how people shop: many consumers—particularly young consumers—prefer Rihanna’s Fenty over Coty, Kim K’s SKIMS over Spanx, and George Clooney’s Casamigos over Patrón.
The lack of trust in institutions is also alarming when paired with the rise of fake news on social media and, more recently, the rise of deepfakes. (Here’s a great video from my friend Johnny Harris on what’s happening in deepfake-land.) Trust may continue to be eroded, with people disagreeing on which authority figures can be arbiters of truth and sources of reliability.
3️⃣ AI Mania
AI may be the defining technology trend of the decade. In last week’s Barbie and the AI-Generated Internet, I shared this chart—Bloomberg expects generative AI to swell to a $1.3 trillion market and to reach 12% of total tech spend within 10 years:
We’ve seen this playing out in the startup landscape. AI is a consumer phenomenon, with the rise of ChatGPT, Midjourney, and other consumer-facing tools. AI is seeping into the enterprise, led by companies like Glean (workplace search) and Runway (creative tooling). And vertical SaaS is giving way to vertical AI, with every sector being ripe for reinvention—CaseText (legal) was scooped up by Thomson Reuters for $650M in cash last month.
Alongside the rise of AI comes a rise in AI incidents and controversies. This chart chronicles the number of incidents concerning the misuses of AI. The data is about a year old, though it includes some incidents from 2022 like a deepfake of Ukraine President Volodymyr Zelenskyy surrendering and news that Intel had developed a system for monitoring student emotions over Zoom, a technology that raised privacy and discrimination concerns.
The rise of AI-related incidents creates the need for startup solutions. Companies like Abnormal Security protect against AI-driven cyberattacks, while companies like Dust help enterprises use their proprietary data in large language models (while ensuring personally identifiable information remains safe).
4️⃣ Is Art Created by AI Still Art?
Last week’s piece also honed in on emerging questions in AI-generated art. The ongoing actors strike in Hollywood positions AI as a key issue: actors are worried about studios using their likeness. In a statement about the strike, the Alliance of Motion Picture and Television Producers (AMPTP) said that its proposal included “a groundbreaking AI proposal that protects actors’ digital likenesses for SAG-AFTRA members.” The response from the Screen Actor Guild’s top negotiator didn’t mince words:
“This ‘groundbreaking’ AI proposal that they gave us yesterday, they proposed that our background performers should be able to be scanned, get one day’s pay, and their companies should own that scan, their image, their likeness and should be able to use it for the rest of eternity on any project they want, with no consent and no compensation. So if you think that’s a groundbreaking proposal, I suggest you think again.”
As AI seeps into the creative world, it creates fascinating questions. When movies and TV shows are fully generated by AI, do they lose their artistic integrity? How are these tools different than CGI explosions or photoshop?
I found this chart interesting: younger generations are much more likely to consider AI-created art to be art.
Last year, an AI-generated work took first place at the Colorado State Fair. The work—“Théâtre D’opéra Spatial” by Jason Allen—stirred up controversy. Should it even have been eligible if AI was the artist? Who even is the artist—the technology, the person who entered the prompt, the creators of works the model was trained on?
As AI invades every creative sector, these questions will become more pressing and more complicated.
5️⃣ A Venture Capital Reset
In March’s “10 Charts” piece, I shared this chart of tech valuations:
I wrote in that piece:
In 2021, it wasn’t uncommon to see startups raising at 50x or even 100x ARR multiples. Many companies will struggle to grow into those valuations. As Elad Gil points out, a company that raised at 50X ARR will take 9 years growing 20% a year to just grow into its current valuation (assuming a 10X exit multiple). A company that raised at 100x ARR would take 6-7 years, growing 85% year-over-year, to grow into that last round price. That’s to say nothing of being a 2-3x step-up in valuation for the next fundraise.
The venture world got ahead of its skis, and we’re seeing a necessary correction. Venture capital investment is down meaningfully in 2023:
The worst is yet to come—there’s a lag effect at play, in which well-funded startups can survive with high burn for multiple quarters (or even years). We’re about to see many companies come back to market and be unable to raise capital. One report from Insider shows that most early-stage startups had less than 12 months runway at the end of 2022:
Expect a few difficult quarters, with many companies winding down. The best companies will be okay—though it may take years for them to grow back into their valuations. It took Microsoft 14 years (!) to break even after its frothy dotcom-era valuation.
But the downturn is also a necessary correction, one that could create a seminal moment for startup creation and seed investing. The downturn may be a talent unlock, producing a new generation of entrepreneurs leaving their jobs to build new companies. When paired with the rise of radically new behaviors (Gen Z is now the largest generation in the world and is coming of age) alongside promising technology shifts (generative AI, mixed reality), that talent unlock may produce iconic new businesses. The years after the Great Recession, after all, coincided with the rises of mobile and cloud and produced dozens of enduring tech companies. (Examples on the mobile side: Instagram, Snap, WhatsApp, Robinhood, Uber, Coinbase. Examples on the cloud side: Slack, Datadog, Figma, Airtable, Stripe, Snowflake, Databricks. All of those companies were founded between 2009 and 2013.)
6️⃣ The Highs and Lows of Threads
In early July, Meta’s Twitter competitor, Threads, got off to a roaring start. The app became the fastest-downloaded app in history, reaching 1M users in under an hour and 100M users in just a few days.
The launch was impressive, as Threads piggybacked on Instagram’s userbase to jumpstart its growth.
In my mind, the result was most indicative of one thing: the power of built-in distribution. It’s never been easier to start a company (products like AWS and Stripe offer affordable building blocks for getting started), but it’s never been harder to grow—companies face customer acquisition headwinds and Big Tech has never been bigger. It’s especially hard for startups to compete with Big Tech distribution. How is a new consumer social company supposed to compete with Instagram’s 2B+ users? And in the new AI wars, how can an AI productivity tool compete with the 1B+ people already using Microsoft Office 365 and Google Workspace? (More about AI distribution in April’s The AI Interface Revolution.) Cracking distribution is the hair-on-fire problem facing startups in 2023.
The answer is that startups need 1) to build a better product, and 2) to get creative with distribution. Threads’ decline since launch offers one additional lesson: if the product isn’t exceptional, or if it isn’t something that people really want, no amount of built-in distribution can fuel strong engagement and retention.
We’ll see if Threads can keep lightning in the bottle, but the launch offers another proofpoint of the distribution challenges facing startups in 2023.
7️⃣ More Americans Are Living Alone
About 30% of U.S. households comprise just a single person—an all-time record. This compares to ~4% in the 1940s.
Of course, this doesn’t mean that 30% of Americans live alone—though 30% of households are single-person, about 13% of American adults live alone. This share rises with age—from a 2017 research paper:
The population of solitaries rises from 4 percent of adults at ages 18-24 to 9 percent at 25-34, dips to 8 percent at 35-44, then rises again, to 12 percent at 45-54, 17 percent at 55-64 and 26 percent at 65 and up.
What are the ripple effects of solitary households? For one, I’d imagine increased screen time—I’m sure there’s a correlation between living alone and higher usage of social media, content platforms, and streaming services.
Another ripple effect: increased loneliness. The last “10 Charts” piece focused heavily on our loneliness epidemic. In the last 30 years, the percentage of people with <=1 close friend has nearly tripled to 20% of the population. The percentage of people who report 10+ close friends has dropped from 40% to 15%.
The rise of solitary households is likely a contributing factor here, creating a need for more ways to find community. Another new development is the rise of work-from-home. I found this stat from Dan Frommer’s New Consumer report interesting:
This goes hand-in-hand with office occupancy rates, which have plateaued around ~50%:
On the one hand, work-from-home offers flexibility and autonomy. On the other hand, its rise comes at a moment when the nation is undergoing a loneliness crisis and when living alone is more common than ever before. Living alone + working from home fuel increased isolation, which further precipitates the need for new forms of community and belonging.
8️⃣ Therapy Goes Mainstream
Here’s an interesting stat: 91% of users of the dating app Hinge say they’d prefer to date someone in therapy. (Maybe that stat will convince more people to go to therapy!)
Therapy is becoming more and more popular: 23% of U.S. adults visited a mental health professional in 2022, up from 13% in 2004. Unsurprisingly, younger generations and women are leading the charge:
The destigmatization of mental health is one of the most interesting shifts of this generation. This is a decades-long shift that we’re only in the middle of, and we still have a long way to go—in 2033, what share of adults will seek mental health treatment? Gen Z will have come of age, and Gen Alpha may be even more radically open about mental health; lingering stigmas around therapy in the Boomer generation will fade away. I wouldn’t be surprised to see 1 in 3 adults in therapy within the next decade.
I’m always interested in how startups build along tectonic shifts like these. There are many emerging companies and business models that both ride and accelerate this shift—B2C marketplaces like Headway and Grow, B2B solutions like Modern Health and Lyra, and even new AI mental health chatbots like Woebot and Wysa.
9️⃣ Secondhand Explosion
I’ve written in the past about secondhand, but it continues to be one of the most underrated segments of the commerce world. U.S. secondhand will be a $70B market by 2027, with resale growing 5x the pace of the broader retail sector. (That pace will accelerate to a 9x multiple in the next few years.)
Take data from a biased source with a grain of salt, but ThredUp’s recent secondhand report had some interesting pieces of information:
52% of consumers shopped secondhand apparel in 2022. 1 in 3 apparel items bought in the last 12 months was secondhand, and 2 in 5 items in Gen Z’s closet are secondhand.
Buying and wearing secondhand clothing instead of new reduces carbon emissions by an average of 25%.
The number of retail stores that launched branded resale programs exploded last year, jumping from 36 to 124.
In my mind, the biggest trend in retail this decade is sustainability—every brand is expected to be sustainable, and every retailer needs to clean up its supply chain. March’s piece The Retail Revolution unpacked how dirty retail is, with large chunks of product going unsold and ending up in landfills.
Secondhand is one of the most promising segments of sustainable commerce. And I see no reason that secondhand shouldn’t be simpler for consumers. One example: resale should show up at checkout. According to the ThredUp report, 82% of Gen Z has considered the resale value of apparel before buying it. Naturally, consumers are more likely to convert (and spend more) if they know the estimated resale value of the item they’re buying. If this flow can also lessen the future logistics burden of resale (pulling in product details, for example), it can unlock latent supply. Every time I go to buy something online, I should be shown its future resale value. This is a no-brainer for brands, and creates a better experience for the shopper. (If you’re building something in this space, I’d love to chat; there’s a big opportunity to go after here.)
🔟 A Climate Reckoning
It’s been a (very) hot summer. More specifically, a record-breaking summer. Check out this visualization:
As the world reckons with more obvious crises—Trump’s impeachment, the war in Ukraine, concerns around AI—the biggest crisis of all continues simmering.
The good news is that venture funding into climate tech is rising:
In 2021, climate tech funding swelled to a record $37B, +64% over 2020. And last year, as the broader funding market cooled, that growth actually accelerated: according to HolonIQ, climate tech startups raised $70.1B in 2022, +89% year-over-year.
I’ll do another “10 Charts” series in a couple months. In the meantime, I’d love to see any charts that you’ve been struck by. You can reply to this email, or send me a DM on Twitter (X?) at @rex_woodbury.
Until next week 👋
Sources & Additional Reading
Low Faith in Institutions | Gallup
The Fourth Turning | Fortune
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