Nothing about this family is unusual. They are living inside two price curves at once. One curve keeps falling, and it carries screens, phones, software, solar panels, and now artificial intelligence. The other keeps rising, and it carries the bills that decide whether a household feels secure: rent, health care, college, and child care. Understanding why those curves split apart is the first step toward bending the expensive one down.

The Curve That Keeps Falling

In 1936, an aircraft engineer named Theodore Paul Wright published a paper in the Journal of the Aeronautical Sciences called “Factors Affecting the Cost of Airplanes.” He had noticed a steady pattern. Each time the total number of airplanes built doubled, the labor needed for each new plane dropped by a predictable share. Cost, he found, follows experience rather than the calendar.

That observation became known as Wright’s Law, and it describes almost every manufactured product that is built at scale. Workers learn shortcuts. Engineers redesign parts. Suppliers find cheaper materials.

Solar, Batteries, and Screens

Solar power is the textbook case. A watt of solar module capacity cost about $96 in 1976, measured in today’s dollars. By 2024 it cost about $0.26. Lithium-ion battery packs tell a similar story. BloombergNEF’s annual survey found average pack prices of roughly $790 per kilowatt-hour in 2013 and about $115 in 2024.

Consumer electronics ride the same curve. According to Bureau of Labor Statistics price data compiled by economist Mark Perry of the American Enterprise Institute, the price of televisions fell about 98 percent between January 2000 and late 2025. Computer software fell about 75 percent. Toys fell about 74 percent, and cell phone service fell about 43 percent.

AI Joins the Club

Artificial intelligence is now on the fastest version of this curve yet. The Stanford AI Index 2025 reports that the cost of querying a model performing at the level of GPT-3.5 fell more than 280-fold between November 2022 and October 2024. A task that once cost real money per request now costs a fraction of a cent.

That matters because AI is not a product sitting on a shelf. It is a tool that can be applied to other work. If cheap intelligence can reach the expensive side of the economy, it could do something TVs never could. It could lower the price of services, not just gadgets.

The Curve That Keeps Rising

Now look at the other half of Perry’s chart, which he has called the “chart of the century.” Over the same stretch from 2000 to late 2025, overall consumer prices rose about 92 percent. Hospital services rose about 275 percent. College tuition and fees rose about 196 percent. Child care and nursery school rose about 185 percent. Medical care overall rose about 129 percent, and housing rose about 111 percent.

Average hourly earnings rose about 131 percent over the same period. That number explains a great deal. Wages beat general inflation, so the typical hour of work buys more of most things than it did in 2000. Yet hospital care, tuition, and child care rose faster than wages. For those bills, an hour of work now buys less than it did a generation ago.

Why These Bills Hurt More

The categories that got cheaper are mostly things people buy occasionally. A family replaces a TV every several years. The categories that got expensive are paid every month or come in large, unavoidable lumps. Rent arrives on the first. Child care is often the second-largest bill a young family pays. A single hospital stay can erase a year of savings.

So averages can mislead. A household that rents, has small children, and carries a health condition lives almost entirely on the rising curve. Cheaper electronics are pleasant. They do not cover the gap.

What Happened to Wages

Wage stagnation is real, but the details matter. The Bureau of Labor Statistics tracks median usual weekly earnings for full-time workers, adjusted for inflation. In constant 1982 to 1984 dollars, that figure was $332 in 1979, $334 in 2000, and $374 in 2025. That is growth of about 13 percent over more than four decades, and almost all of it arrived after 2014.

Economists debate how to read this. Some point out that average hourly earnings, total compensation including benefits, and different inflation measures show stronger gains. Others note that rising health insurance premiums have absorbed much of what employers spend on workers, so take-home pay grew slowly even when total compensation grew faster. Both views can be true. Either way, the typical worker gained modestly, while the price of the biggest essentials rose sharply.

Why the Expensive Curve Will Not Bend on Its Own

The rising categories share a few traits. They are services rather than goods. They cannot be imported. They depend on land or on licensed people. And they often face limited competition. Each trait points to a specific cause.

These causes do not belong to one political party. They are structural, which means they respond to structural fixes.

Baumol’s Cost Disease

In the 1960s, economists William Baumol and William Bowen studied live performance. A string quartet in 1800 needed four musicians and about the same amount of time as a string quartet today. Productivity did not rise. Yet musicians must be paid wages that compete with factories and offices where productivity did rise. So the price of a concert climbs.

Teaching, nursing, and child care work the same way. One caregiver can safely watch only so many toddlers. A nurse can attend only so many patients per shift. When wages rise across the economy, these labor-heavy services get more expensive even if nothing about them changes. That is not a failure. It is arithmetic.

Land, Zoning, and Gatekeeping

Housing has a different problem. A home is a building plus the land under it, and land in high-demand cities is scarce by definition. Zoning rules that ban apartments on most residential lots, require large minimum lot sizes, or mandate parking make that scarcity worse. When cities limit what can be built, rising demand turns into rising rent.

Health care and higher education add licensing and gatekeeping. Licensing protects quality, but it also limits who may perform a task and how many new providers can enter. Hospital mergers have reduced competition in many regions. Accreditation and prestige make it hard for cheaper colleges to win students. Each barrier may have a reason. Together they keep prices high.

Can AI Bend the Expensive Curve?

Here is the honest answer. In some places, yes. In others, only if policy changes first. The difference depends on whether the cost comes from labor and paperwork, which software can shrink, or from land and permission, which software cannot create.

Hype in either direction does damage. Promising that AI will fix rent creates cynicism. Dismissing it entirely leaves real savings on the table.

Where AI Plausibly Helps

Several costs on the rising curve are made of paperwork and routine cognitive work, which is exactly what cheap AI does well.

• Tutoring. A capable AI tutor can give one-on-one practice to students whose families could never afford a private tutor, easing one source of the Baumol problem in education.
• Health care administration. Billing, coding, prior authorization, and documentation consume a large share of clinician time and hospital budgets. Automating that work could free staff for patients.
• Design and permitting. Software can check building plans against codes, speed reviews, and help standardize designs, cutting months from projects where delay itself costs money.

None of these replaces a nurse at a bedside or a teacher in a room. They shrink the overhead around those people, which is where much of the cost has quietly grown.

Where AI Cannot Help Without Policy

No algorithm can create land in a city where zoning forbids building. A faster permit review means little if the answer is still no. AI can draft a perfect apartment plan, but only a city council can make that plan legal on most lots.

Credentialing works the same way. If a task requires a specific license, cheaper software does not lower the price until rules allow trained people, supported by good tools, to do more of the work. In these areas, technology is ready before the law is. Savings arrive only when reform catches up.

Building Abundance That Reaches Every Household

Michael Ten’s mission at IdeaRiff is abundance for all, and the two price curves show why that goal needs more than one tool. Cheaper technology handles half the job. Reforms in housing, health care, and education handle the other half. Without both, families keep buying cheaper TVs while falling behind on rent.

There is also a role for income floors. A basic income, delivered through trusted community channels such as credit unions and nonprofit networks, can give households stability while slower reforms take hold. Delivery through local institutions keeps money close to the people it serves. Ownership matters as well. When communities can own and use open tools, the savings from cheap AI flow to them rather than collecting with a few platforms.

What to Push For

Readers who want the expensive curve to bend can support concrete, nonpartisan steps that already have backing across the political spectrum.

1. Zoning reform that legalizes apartments, duplexes, and accessory dwellings near jobs and transit.
2. Faster, digital permitting with clear timelines.
3. Scope-of-practice updates that let nurse practitioners, pharmacists, and other trained professionals do more.
4. Price transparency and competition review in hospital markets.
5. Open educational tools and lower-cost credential paths.
6. Pilots of income floors run through credit unions and nonprofits.

None of these requires picking a side. Each simply removes a barrier between people and cheaper essentials.

What to Watch For

The best test is simple. Track the next annual update of the BLS price data. If AI is truly reaching the rising curve, hospital services, tuition, and child care should start growing more slowly than wages. If they do not, the savings are being captured somewhere along the way.

Watch local decisions too. City council votes on housing and state votes on licensing will shape your budget more than any new gadget. The TV will keep getting cheaper on its own. The rent will not.

This article is for educational purposes only and is not financial advice.

Healthspan is the variable budgets can see

Lifespan is years alive. Healthspan is years lived without severe disability or with manageable illness. Public statistics already try to track the second idea through healthy life expectancy and disability-free years. Those series are imperfect. They still tell a clearer fiscal story than a celebrity protocol. A population that lives longer while spending more years frail will demand more care, more support, and often more public money. A population that postpones frailty can add years of ordinary activity before intensive care begins.

Compression of morbidity is the research name for that postponement: serious sickness squeezed toward a shorter period near death. It is a hypothesis and, in some places, a partial description of past gains, not a law. Cardiovascular treatment, tobacco control, and safer workplaces already moved death and disability for large groups. Further gains would have to show up in the same public series. A lab note by itself would not be enough. Policy can value those series without claiming that aging has been solved.

Escape velocity is a forecast, not a line in the budget

Longevity escape velocity is a phrase from biogerontology and futurist writing. It names a possible slope: therapies improve fast enough that expected healthy years for people still alive rise by more than one year per calendar year. The phrase is a way to talk about compounding research results. It is not a clinical guideline, not a product, and not a date a treasury can book. Treating it as a scheduled arrival would make pension math and research budgets depend on a metaphor.

A sober use is a sensitivity case. Planners already model life expectancy with high and low paths. An escape-velocity case is an extra high path in which age-related disability falls quickly across successive waves of intervention. A stalled-research case is the opposite path. Publishing both, with the assumptions written down, is more useful than a single slogan. If the high path fails to appear in mortality tables, the budget should not keep the slogan and drop the table.

Where the metaphor helps and where it misleads

The metaphor helps when it forces a distinction between one successful drug and a pipeline. A treatment that delays one disease can be valuable and still leave most age-related decline in place. Escape-velocity talk, stripped of hype, asks whether gains keep arriving. It also helps journalists and legislators ask for human outcomes over years, rather than for a press release about a marker.

The metaphor misleads when it becomes a sales pitch. Unproven supplements, loosely regulated wellness products, and early biological experiments do not become public policy because a curve looks steep on a slide. Public agencies that approve medicines and that police advertising already have jobs here. This article does not rank those products and does not tell any person what to take. Consumer-protection rules and trial registries are the relevant tools.

Spending near the end of life

Health-economics research on Medicare in the United States has for many years associated a large share of annual Medicare spending with beneficiaries in the last year of life. Summaries often put that share near one quarter, with the exact figure moving by year and by method. The finding is real enough to matter in a budget conversation. It is also easy to abuse. Much of that spending is care for serious illness. People with advanced disease account for high costs whether death falls in the current year or a later one. The last-year share is not a stack of optional charges that a slogan can delete.

Cutting care because death is near would be an ethical and legal decision, not an accounting trick, and this article does not argue for withholding appropriate care. The policy-relevant hope is different: fewer people arriving at that intensity of illness at a given age, because disability and major disease start later. If healthspan rises, some intensive costs move later or shrink per person. If lifespan rises and disability rises with it, late-life costs and pension years can grow together. Those are different fiscal futures, and they should not be collapsed into one story called longevity.

Work, care, and the public ledger

Healthier later years can change the labor force. Some older adults stay in paid work when health allows it and when jobs exist. Some leave earlier by choice or because industries do not hire them. A healthspan gain does not by itself set a retirement age. It changes the feasible set. Legislatures that link pension age to life expectancy are making a distributional choice about who works and who draws a benefit. They should say so, and they should look at disability rates in addition to average age at death.

Unpaid care sits on the same ledger even when it is missing from wage tables. Adult children and spouses provide large amounts of support when late-life disability is long. If serious disability shortens, some of that unpaid load may shrink, and some paid long-term care costs may shrink with it. If families simply support people for more calendar years at the same level of need, the load grows. Housing patterns, immigration, and birth rates move these totals as much as any biomedical forecast. Models that include only a new drug price will miss the larger terms.

What public institutions can fund without selling a cure

Governments already fund the slow contributors to longer healthier lives: vaccination programs, clean-air rules, tobacco control, road safety, and treatment of common diseases through ordinary health systems. Those programs are public health and health-care finance. They are not a promise of rejuvenation, and listing them here is not personal medical direction. They belong in a longevity discussion because they move population curves that already exist. Dropping them in favor of a speculative research story would be a bad trade on present evidence.

Biomedical research on aging mechanisms is a separate appropriation. It can be funded as basic and translational science with shared measures, pre-registered trials, and publication of negative results. The payoff is uncertain. That uncertainty is a reason to describe milestones, not a reason to ban the work or to treat it as a near-term revenue source. Regulatory review of any future product stays with the agencies that review products. An essay, a company blog, or a wellness brand is not a substitute for that review. No part of this article offers access to a therapy or a relationship of care.

Scoreboards that keep the debate empirical

Useful national scoreboards are already defined in outline: life expectancy, healthy life expectancy, disability-free years, age-specific mortality, and the share of health spending by age and by proximity to death. They should be published on a fixed calendar so a good year cannot be framed as a new era and a bad year cannot be buried. Biomarker fashions can sit in an appendix. They should not replace mortality and function.

Distribution belongs on the same page. Averages hide gaps by income, region, and race that are larger than many speculative therapy effects discussed in public. A longevity policy that improves the mean and leaves those gaps untouched has a political and ethical record that the mean will not describe. Cost series should separate research outlays, routine care, and long-term services so a reader can see which bill actually moved.

Access, work rules, and hype

Early biomedical tools, when they exist and when regulators allow them, tend to arrive at high prices and in limited clinics. A public policy that talks about population healthspan while only a narrow group can obtain the tool will lose trust. Access rules, coverage decisions, and research inclusion are part of the aging agenda for that reason. They are decisions for payers and legislatures under existing law. They are not a service this article can arrange.

Hype has a budget cost. Money and attention that chase an advertised escape date are not available for the statistical systems, the trial infrastructure, and the disability supports that make a real gain visible and bearable. A practical stance is dual and dull: keep measuring healthspan, fund rigorous research without a promised arrival date, maintain the public-health programs that already extend healthier years, and refuse marketing that treats a forecast as a product. The economy may benefit if people stay healthier for longer. That benefit is a scenario to test, not a slogan to spend.

Longevity as public policy means planning for healthspan, for the real concentration of serious-illness costs, and for work and retirement rules that match those facts. Escape velocity can be one modeled path. It should not be the base case until population data show the slope. Longer healthier lives could ease some care burdens and support more years of activity. They could also raise pension costs if the added years are frail. The honest public stance is to measure the difference and to fund science and basic health protection without a promised arrival date. Individual medical decisions stay outside this essay.