engels 1'

aid when they are working, or a

housing subsidy for living alone when

they are living with several others.

The Ministry of Social Affairs and

Employment that runs the program

said the data could include income,

debt, education, property, not car

ownership, home address and the

welfare benefits received for children,

housing and health care.

The algorithm produces "risk

reports" on individuals who should

be questioned by investigators.

In Rotterdam, where the system

was used, 1,353 risk reports were

produced in just two neighbourhoods.

"You're putting me in a system that

I didn't even know existed," said

Mr. Bouchkhachakhe, who works

for a logistics company. "Whole

neighbourhoods are considered suspect

and are especially checked. It's like

digital fraud inspectors knocking on

every door in a certain area," he said.

"Those living in better-off areas are

not being looked into like that."

In Rotterdam, opposition built after

word about the techniques spread.

Privacy rights groups, civil rights

lawyers and the largest national labour

union got citizens to stand up and fight

all this. "They will not tell you if you --- OCR Start ---

are on the list," said Tijmen Wisman,

an assistant professor of privacy law

who runs a Dutch privacy group.

The district court that agreed with

the opponents ordered an immediate

halt to the risk algorithm's use. In

the closely watched case, which is

seen as setting an example in Europe

about government use of predictive

algorithms, the court said that the

welfare program lacked privacy

safeguards and that the government

was not transparent enough about

how it worked.

"Now, you must allow the

government's algorithms to watch

and check you if you want to get

any social security money," said

Christiaan van Veen, a lawyer who is

a special advisor on new technology

and human rights for the United

Nations.

Dr. Berk, the Penn professor who

made the algorithm that is now used

by governments around the world,

said there will be less argument

against it once more algorithms are

used. He compared algorithms to the

automatic pilot systems in airliners.

"Automatic pilot is an algorithm," he

said. "We have learned that automatic

pilot is reliable, more reliable than an

individual human pilot. The same is

going to happen here." But people like Mr. Gates and

many others, whose future hangs in

the balance, will take some strong

convincing.

Sitting in the Philadelphia public

defender's office, Mr. Gates said he

was an easy person to add painting

the tattoos on his arms, which were

meant to look like the bones under his

skin. He understands machines. From

a young age, he enjoyed pulling apart

computers and smartphones before

putting them back together.

But Mr. Gates believed that a person

could read him better than a machine.

"Does a computer know I might

have to go to a doctor's appointment

next Friday at 2 o'clock?" he asked.

Visiting the probation office so often

can prevent him from getting the rest

of his life on track. "How is it going to understand me when it is telling

me everything that I have to do?" Mr.

Gates asked.

Several weeks after his interview, he

was allowed to make a short trip to

Puerto Rico after a personal

judge. He always felt comfortable

in front of his judge. The experience

showed him the importance of the

human touch.

I can't explain my situation to a

computer," Mr. Gates said. "But I can

sit here and interact with you, and

you can see my expressions and what

I am going through.

Darnell Gates sat at a long table in a downtown Philadelphia office building. He wore a black T-shirt with "California" in bright yellow letters 5 on the chest. He had never been to the state, but he hoped to visit family there after finishing his probation. When Mr. Gates was released from jail in 2018, he had to visit 10 a probation office once a week because he was considered "high risk." Eventually, his visits went to every two weeks. Later, it became a month. Mr. Gates wasn't told why. He 15 complained that conversations with his probation officers were cold and impersonal. They rarely took the time to understand his rehabilitation. He didn't realize that an algorithm 20 had marked him high risk until he was told about it during an interview with The New York Times. "What do you mean?" Mr. Gates, 30, asked. "You mean to tell me I'm dealing with all 25 this because of a computer?" In Philadelphia, an algorithm created by Dr. Berk, a professor at the University of Pennsylvania, has been used for at least five years to 30 help decide how to evaluate people's behavior on probation. The algorithm is one of many making decisions about people's lives both in the United States and in Europe. 35 Local authorities use so-called predictive algorithms to decide on police patrols, prison sentences, probation rules. In the Netherlands, an algorithm even flagged welfare 40 fraud risks. In Bristol, a British city, an algorithm rates which teenagers are most likely to become criminals. Nearly every state in America has turned to this new sort of checking 45 algorithm, according to the Electronic Privacy Information Center, a digital rights movement. Algorithm Watch, a watchdog in Berlin, has found similar programs in at least 16 European 50 countries. As its use has been spreading into new places and new parts of government, United Nations investigators, civil rights lawyers, labor unions and 55 community organizers have been fighting back. They are angered by a growing dependence on automated systems that are taking humans and transparency out of the process. It is often unclear how the systems are making their decisions. Is gender a factor? Age? ZIP code? It's hard to say, since many countries have few rules for getting algorithm-makers to check their formulas. Other opponents say governments haven't shown much interest in learning what it means to take humans out of the decision-making. "Where is my human interaction?" Mr. Ganes asked, sitting next to his lawyer in the meeting room of the Philadelphia public defender's office. "How do you win against a computer that is built to stop you? How do you stop something that predetermines your fate?" Last year, Idaho passed a law saying that the methods and data used in algorithms must be publicly available so the general public can understand how they work. In the Netherlands, a district court ruled that the country's welfare-fraud software violated European human rights law, one of the first rulings against a government's use of predictive algorithms. For it was in Rotterdam, the Netherlands, a few years ago, that a rumour spread in two mostly low- income and immigrant neighbourhoods that claimed that the city government had begun using an experimental predictive algorithm to help catch citizens who were committing welfare and tax fraud. Mohamed Saidi learned about it from a WhatsApp message that he at first thought was a joke. Mohamed Bouchchachakhe first heard from his mother, who had been told by a friend Driss Tahghi got word from a local union official. The rumour turned out to be true. The Dutch program, System Risk Indication, scans data from different government authorities to flag people who may be claiming unemployment aid when they are working, or a housing subsidy for living alone when they are living with several others. The Ministry of Social Affairs and Employment that runs the program said the data could include income, debt, education, property, not car ownership, home address and the welfare benefits received for children, housing and health care. The algorithm produces "risk reports" on individuals who should be questioned by investigators. In Rotterdam, where the system was used, 1,353 risk reports were produced in just two neighbourhoods. "You're putting me in a system that I didn't even know existed," said Mr. Bouchkhachakhe, who works for a logistics company. "Whole neighbourhoods are considered suspect and are especially checked. It's like digital fraud inspectors knocking on every door in a certain area," he said. "Those living in better-off areas are not being looked into like that." In Rotterdam, opposition built after word about the techniques spread. Privacy rights groups, civil rights lawyers and the largest national labour union got citizens to stand up and fight all this. "They will not tell you if you --- OCR Start --- are on the list," said Tijmen Wisman, an assistant professor of privacy law who runs a Dutch privacy group. The district court that agreed with the opponents ordered an immediate halt to the risk algorithm's use. In the closely watched case, which is seen as setting an example in Europe about government use of predictive algorithms, the court said that the welfare program lacked privacy safeguards and that the government was not transparent enough about how it worked. "Now, you must allow the government's algorithms to watch and check you if you want to get any social security money," said Christiaan van Veen, a lawyer who is a special advisor on new technology and human rights for the United Nations. Dr. Berk, the Penn professor who made the algorithm that is now used by governments around the world, said there will be less argument against it once more algorithms are used. He compared algorithms to the automatic pilot systems in airliners. "Automatic pilot is an algorithm," he said. "We have learned that automatic pilot is reliable, more reliable than an individual human pilot. The same is going to happen here." But people like Mr. Gates and many others, whose future hangs in the balance, will take some strong convincing. Sitting in the Philadelphia public defender's office, Mr. Gates said he was an easy person to add painting the tattoos on his arms, which were meant to look like the bones under his skin. He understands machines. From a young age, he enjoyed pulling apart computers and smartphones before putting them back together. But Mr. Gates believed that a person could read him better than a machine. "Does a computer know I might have to go to a doctor's appointment next Friday at 2 o'clock?" he asked. Visiting the probation office so often can prevent him from getting the rest of his life on track. "How is it going to understand me when it is telling me everything that I have to do?" Mr. Gates asked. Several weeks after his interview, he was allowed to make a short trip to Puerto Rico after a personal judge. He always felt comfortable in front of his judge. The experience showed him the importance of the human touch. I can't explain my situation to a computer," Mr. Gates said. "But I can sit here and interact with you, and you can see my expressions and what I am going through.

ARGUMENT 1

Improves Efficiency:
Why?
Governments and organizations often deal with thousands or even millions of cases. Processing this manually can be overwhelming, leading to delays, errors, or cases being ignored. Algorithms streamline these processes, quickly sorting through data and prioritizing tasks based on risk or urgency.
Example:
A welfare fraud detection system uses algorithms to flag suspicious claims, allowing investigators to focus on cases most likely to involve fraud. This helps avoid wasting time on legitimate claims and speeds up the process for those in need.

The welfare fraud system in the Netherlands analyzed large amounts of data, such as income, debt, and housing subsidies, generating 1,353 "risk reports" in just two neighborhoods. While controversial, this level of efficiency would be impossible for human investigators to achieve on their own.

WEERLEGGING:

Algorithms can process data quickly, but they often prioritize speed over fairness or accuracy. This can lead to problems, especially if the data is biased. For example, you mentioned that the welfare fraud system in the Netherlands flagged 1,353 cases in low-income neighborhoods. While this was efficient and faster than humans could manage, it raised concerns that the algorithm unfairly targeted poorer communities, while wealthier areas weren't checked as closely. Additionally, if people rely too much on algorithms, they might miss mistakes. Investigators could focus only on the cases flagged by the algorithm, potentially delaying help for legitimate claims.

ARGUMENT 2