By Lucia Walinchus
Broadcast version by Mary Schuermann reporting for the Eye on Ohio: The Ohio Center for Investigative Journalism-Ohio News Connection Collaboration.

Meredith Broussard notes in her book, "Artificial Unintelligence," that "AI" is a bit of a misnomer. True artificial intelligence means computers have finally achieved consciousness. Scientists are a long way away - if that is even possible.

Why then has "artificial intelligence" become ubiquitous? Major companies and the state of Ohio refer to AI as vital to speech recognition, self-driving cars and web searches. It's essentially become shorthand for various machine-learning methods to solve a problem which a human can't easily solve.

For example: a programmer has to code image-recognition software to identify dogs in pictures. How can the programmer explain to a computer what a dog is? Chihuahuas are dogs, and so are Great Danes. But not wolves, which look a lot like dogs, or foxes.

The programmer instead could use thousands of pictures of animals hand-labeled "dogs" and "foxes" and have an AI algorithm learn which are which. The computer compares patterns of each animal's eyes, nose and snout to see which sizes and shapes are a "dog." The code tells the computer to decide a shape, such as a dog ear, is more likely a dog.

As François Chollet and J.J. Allaire wrote in their book, Deep Learning with R, from a geometric standpoint, the computer is trying to see how to fold a piece of paper so that the maximum number of data points can be included.

Counterintuitively though, extremely high accuracy is not an end goal because of "overfitting." A model that follows data too closely might not be good at making predictions in new data it hasn't seen before. If your dog dataset has too few Chihuahuas and not enough Great Danes, you might miss bigger dogs later.

Machine learning is powerful because it flips the script on computer programming: instead of telling the machine what's important, programmers study the data points that influence various outcomes to see what's important. Then they test for better outcomes.

For the past year, Eye on Ohio has been working on an AI project to see how cities and land banks choose to take over decrepit properties. This effort involved hundreds of public-records act requests, 5,225 lines of code and countless hours of planning, researching, programming, writing, fact-checking and editing.

Countless articles chronicle rising housing prices. Eye on Ohio wanted to look at the opposite end of the spectrum: What happens to the worst housing? How does that impact people who are struggling?

In Ohio, the county keeps delinquent property lists showing which owners did not pay taxes the previous year - and how much they owe. An auditor's website lets anyone see property value and payment history.

Most delinquent taxpayers eventually pay back their taxes. But Eye on Ohio started here for several reasons.

First, it would be impractical to study every property in a county to see which might be eligible for a land bank. The delinquent-taxpayer list is a public record which represents virtually all decrepit properties in a county.

Second, delinquent property owners are the biggest funders of land banks in the first place. County Treasurers and Prosecutors split 5 percent of delinquent tax revenue between them in a delinquent tax and assessment collection fund (DTAC). When a county establishes a land bank, they use those funds. County commissioners can authorize up to 5 percent more.

Third, one of the stated goals of most land banks is to take perpetually delinquent properties and turn them over to responsible owners who pay their taxes.

When a taxpayer becomes delinquent, the Treasurer usually will set up a payment plan. If that fails, the government will sell their tax lien to a third party. But sometimes not even that is successful, particularly for abandoned properties where it can be difficult to first find an owner's heirs or successors in interest.

Land banks get properties in a variety of ways. Someone can give them a parcel outright or deed property in lieu of foreclosure. But usually, they remediate properties that are way behind on their taxes in the first place.

The thrust of the project is: Of all delinquent properties in a county, which ones go to the land bank? Each has a policy that essentially says, "We try to do the best we can with our limited budget." What exactly does that mean, mathematically?

Land banks are a great but very limited program. How do officials choose which of the relatively small number of properties they will foreclose upon or demolish?

During the height of the mortgage crisis, many counties got federal funds to supplement their budgets. That money is now largely gone. How will land banks treat rusting properties with a smaller budget?

Click here to look at the code for this open source project.

First in the series: How do public officials make Land Bank decisions? Artificial Intelligence may seek patterns

This collaboration is produced in association with Media in the Public Interest and funded in part by the George Gund Foundation.


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Since the passage of the American Rescue Plan Act in 2021, a number of cities and counties in Ohio and around the nation have used ARPA funding to retire medical debt.

Over the summer, Akron became the latest community in Ohio to adopt a plan to retire such debts.

The city council allocated $500,000 to purchase debts through the non-profit RIP Medical Debt. RIP in turn negotiates with hospitals and debt collectors to buy old debts for pennies on the dollar and then forgives them.

Akron Ward 1 City Council Representative Nancy Holland said these debts take a toll on the community.

"Medical debt is one of the leading causes of personal bankruptcy," said Holland. "It's also a leading cause of divorce, of job disruption, of inability to qualify for most major loans like home loans, it can also cause trouble in a rental application, just to rent an apartment. "

Akron joins Lucas County, Toledo, and Cleveland in using ARPA funds to eliminate medical debts. The anticipated value of retired debts from Akron's allocation is up to $50 million.

After entering into a contract with a local government, RIP Medical Debt reviews hospital debt portfolios to determine which ones will be retired.

Residents who qualify must earn less than 400% of the federal poverty level, and their medical debts must be at least 5% of their annual income.

Allison Sesso is the president and CEO of RIP, and says medical debt can be hard to avoid.

"I think medical debt is different than other kinds of debt, because of the fact that it's inherent in the system," said Sesso. "And it's sort of a trap, you can't avoid it. You can have insurance and yet you still have medical debt. You can do all the right things and you still have medical debt. You don't control the pricing. It is not transparent as a system and so it's really hard to avoid. "

Pre-pandemic research found that 23 million Americans have medical debt, with 3 million owing more than $10,000.

While these debts are accumulated in countless ways, and at different types of healthcare organizations, Sesso said RIP will negotiate with anyone to buy qualifying medical debt belonging to those most financially burdened.

"There's often been questions about whether or not we'll work with certain kinds of hospitals, that maybe are seen as bad actors," said Sesso. "And at the end of the day, we really focus on the patient. If you have debt at a bad actor hospital, you shouldn't be punished for that."

Sesso said to date, RIP has retired $10 billion of debt for 7 million people nationally.

A tight labor market with steady growth and historically low unemployment - those are the findings in the new "State of Working Pennsylvania" report.

In July, Pennsylvania's unemployment rate was 3.5%, compared with 4.3% a year ago.

Report co-author Stephen Herzenberg, an economist and executive director of the Keystone Research Center, said the strong economy should benefit workers even more looking forward. When there are more job openings than unemployed workers, he said, it gives workers greater choice and leverage in the job market.

"Because of the tight labor market, even though inflation was high, workers' wages have actually kept up," he said, "and they're beginning to see increases in real wages in their pay packets. And that should continue into the next year."

He said the tight labor market appears to be driven by continued job growth plus long-term demographic factors which are shrinking the growth rate of the working-age population.

The good news now, Herzenberg added, is that inflation is no longer high and has come down in the last 12 months.

"While inflation was coming down - from the 9% to the current 3% - workers kept up because of that tight labor market," he said. "There's some industries - low-wage industries, like restaurants and hospitality, and retail sector - where you've seen robust wage increases."

He noted that Pennsylvania has been a leader in some areas of workforce training, such as growing apprenticeship programs, and said the state should build on that strength and expand training for the kinds of apprenticeships that connect people to well-paid jobs.

The funding gap between the state's poorest and wealthiest school districts is widening, with potentially dire consequences for students and communities, according to new data from the Kentucky Center for Economic Policy.

Jason Bailey, executive director of the Kentucky Center for Economic Policy explains year after year, state budgets passed by lawmakers have eroded the amount of money that goes into the formula to help equalize school funding. He added now, the gap between rich and poor school districts has reached levels not seen since the 1980s, when the state Supreme Court declared it unconstitutional.

"We're not seeing any efforts to reverse that trend yet," he said. "In fact, there are big concerns about actually making it worse, particularly by cutting the income tax, which is the largest source of revenue for state government."

In 2022, the per-student gap between wealthy and poor districts reached more than $3,900, according to the report.

Bailey noted wealthier districts tend to levy a variety of local taxes that are out of reach for lower-income communities. Districts in metro and suburban areas also generate more local revenues from an occupational tax on wages and net profits. He said school districts that have been hit the hardest by the funding gap are also the ones seeing average teacher pay continue to shrink.

"So teachers are facing more workloads, bigger classes, but pay that is just not keeping up, it's harder to attract people to the profession, they're more likely to burn out after a few years," he explained.

The equity gap has also been widening in other areas, including the employer portion of teacher retirement and health and life insurance.