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AI Facilitates Cash Relief Payments for Some Households

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Nearly 1,000 households affected by hurricanes in North Carolina and Florida will benefit from a new disaster aid initiative this week, which utilizes a model not commonly used by philanthropy in the United States: providing rapid, direct cash payments.

The nonprofit organization GiveDirectly is set to send $1,000 payments on Friday to some households impacted by Hurricanes Helene and Milton. Utilizing a Google-developed artificial intelligence tool, the group identifies areas with high levels of poverty and storm damage. On Tuesday, residents in these areas were invited to enroll in the program via a smartphone app used to manage SNAP and other government benefits, with donations deposited directly through the app’s debit card.

This method aims to deliver aid in a streamlined and dignified manner, according to Laura Keen, a senior program manager at GiveDirectly. It simplifies the application process and enables recipients to address their most urgent needs according to their discretion.

Though the program may not reach every individual in need, GiveDirectly hopes it can serve as a model for more efficient disaster aid. Keen emphasized their intent to increase the share of disaster response delivered as cash, whether through FEMA or private entities.

In contrast to traditional aid comprising clothing, blankets, and food, cash offers flexibility in situations where immediate cash expenditures, such as securing hotel accommodation during evacuation or covering childcare when schools are closed, are necessary.

Keen highlighted the advantages of cash, noting that it empowers individuals to address their unique needs, which can differ significantly from those of their neighbors. Rapid access to funds can also shield recipients from predatory lending practices and reduce credit card debt.

GiveDirectly has employed direct payments for poverty relief globally, initially experimenting with cash disaster payments in the U.S. in 2017 during Hurricane Harvey in Texas and Hurricane Maria in Puerto Rico. At that time, enrollments were conducted in person, and debit cards were distributed, a process that took several weeks. Currently, the process has been expedited to days and is conducted remotely.

A Google team employs its SKAI machine learning tool to identify the most severely affected areas by comparing aerial imagery taken before and after disasters. GiveDirectly then cross-references these findings with poverty data using another Google-developed tool. Targeted areas are sent to Propel, an app for electronic benefits transfers, which invites residents to enroll.

Beneficiaries do not need to provide extensive documentation to establish eligibility, according to Keen, as eligibility is already established through the program’s targeting system.

However, this model may not include all low-income households devastated by disasters, as not all eligible individuals are enrolled in government benefits, and undocumented residents are not eligible. Those without smartphones cannot access the application. Propel reaches 5 million of the 22 million households enrolled in SNAP benefits.

In North Carolina, where electricity remains unavailable in some areas following Hurricane Helene, smartphones are ineffective without power or connectivity.

GiveDirectly acknowledges the model’s limitations, Keen stated, noting that a hybrid model combining remote and in-person enrollment could mitigate some challenges. Funding constraints are also a factor. Currently, $1.2 million has been raised for this campaign, including a $300,000 contribution from the Conrad N. Hilton Foundation.

Despite these challenges, GiveDirectly hopes its model will inspire other direct payment programs.

FEMA revised its cash relief program, Serious Needs Assistance, in January, raising payments from $500 to $750 and removing the stipulation that states must request aid first. As of October 24, more than 693,000 households across states affected by Hurricanes Helene and Milton have received assistance, amounting to over $522 million.

However, the program still requires applications, which proved challenging when misinformation spread about it. In high-cost living areas, the $750 aid may not suffice.

Chris Smith, who managed FEMA’s Individual Assistance program from 2015 to 2022, suggests that technology could help FEMA enhance its system. He acknowledges that public programs do not have the same liberty to experiment as philanthropic ones, underscoring the importance of accountability in government assistance provision.

The government has tested other forms of unconditional cash assistance, such as the temporary expansion of the child tax credit in 2021, which nearly halved the child poverty rate before expiring.

Research on guaranteed income programs indicates that recipients allocate funds to their basic needs, according to Stacia West, founding director at the University of Pennsylvania’s Center for Guaranteed Income Research. West noted that no one can manage a budget better than individuals living in poverty.

A study tracking spending among over 9,000 participants in more than 30 guaranteed income programs in the U.S. found that most funds are spent on retail goods, food, groceries, and transportation.

West stated that one-time cash payments considerably assist families recovering from disasters. Yet, sustained cash support could offer more profound benefits.

Similar sustained programs have been implemented during previous U.S. disasters. In 2016, Dolly Parton funded a program providing $1,000 monthly for six months to individuals in Tennessee who lost homes in the Great Smoky Mountains wildfires. The People’s Fund of Maui, supported by Oprah Winfrey and Dwayne Johnson, provided $1,200 monthly for six months in 2023 to adults affected by the Maui wildfires.

Keen expressed that GiveDirectly would be eager to implement a long-term assistance program if funding were available, as sustained help can foster resilience for future challenges by enabling not just repairs but fortifications against future threats.

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