AI bias

when-“no”-means-“yes”:-why-ai-chatbots-can’t-process-persian-social-etiquette

When “no” means “yes”: Why AI chatbots can’t process Persian social etiquette

If an Iranian taxi driver waves away your payment, saying, “Be my guest this time,” accepting their offer would be a cultural disaster. They expect you to insist on paying—probably three times—before they’ll take your money. This dance of refusal and counter-refusal, called taarof, governs countless daily interactions in Persian culture. And AI models are terrible at it.

New research released earlier this month titled “We Politely Insist: Your LLM Must Learn the Persian Art of Taarof” shows that mainstream AI language models from OpenAI, Anthropic, and Meta fail to absorb these Persian social rituals, correctly navigating taarof situations only 34 to 42 percent of the time. Native Persian speakers, by contrast, get it right 82 percent of the time. This performance gap persists across large language models such as GPT-4o, Claude 3.5 Haiku, Llama 3, DeepSeek V3, and Dorna, a Persian-tuned variant of Llama 3.

A study led by Nikta Gohari Sadr of Brock University, along with researchers from Emory University and other institutions, introduces “TAAROFBENCH,” the first benchmark for measuring how well AI systems reproduce this intricate cultural practice. The researchers’ findings show how recent AI models default to Western-style directness, completely missing the cultural cues that govern everyday interactions for millions of Persian speakers worldwide.

“Cultural missteps in high-consequence settings can derail negotiations, damage relationships, and reinforce stereotypes,” the researchers write. For AI systems increasingly used in global contexts, that cultural blindness could represent a limitation that few in the West realize exists.

A taarof scenario diagram from TAAROFBENCH, devised by the researchers. Each scenario defines the environment, location, roles, context, and user utterance.

A taarof scenario diagram from TAAROFBENCH, devised by the researchers. Each scenario defines the environment, location, roles, context, and user utterance. Credit: Sadr et al.

“Taarof, a core element of Persian etiquette, is a system of ritual politeness where what is said often differs from what is meant,” the researchers write. “It takes the form of ritualized exchanges: offering repeatedly despite initial refusals, declining gifts while the giver insists, and deflecting compliments while the other party reaffirms them. This ‘polite verbal wrestling’ (Rafiee, 1991) involves a delicate dance of offer and refusal, insistence and resistance, which shapes everyday interactions in Iranian culture, creating implicit rules for how generosity, gratitude, and requests are expressed.”

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AI ruling on jobless claims could make mistakes courts can’t undo, experts warn

AI ruling on jobless claims could make mistakes courts can’t undo, experts warn

Nevada will soon become the first state to use AI to help speed up the decision-making process when ruling on appeals that impact people’s unemployment benefits.

The state’s Department of Employment, Training, and Rehabilitation (DETR) agreed to pay Google $1,383,838 for the AI technology, a 2024 budget document shows, and it will be launched within the “next several months,” Nevada officials told Gizmodo.

Nevada’s first-of-its-kind AI will rely on a Google cloud service called Vertex AI Studio. Connecting to Google’s servers, the state will fine-tune the AI system to only reference information from DETR’s database, which officials think will ensure its decisions are “more tailored” and the system provides “more accurate results,” Gizmodo reported.

Under the contract, DETR will essentially transfer data from transcripts of unemployment appeals hearings and rulings, after which Google’s AI system will process that data, upload it to the cloud, and then compare the information to previous cases.

In as little as five minutes, the AI will issue a ruling that would’ve taken a state employee about three hours to reach without using AI, DETR’s information technology administrator, Carl Stanfield, told The Nevada Independent. That’s highly valuable to Nevada, which has a backlog of more than 40,000 appeals stemming from a pandemic-related spike in unemployment claims while dealing with “unforeseen staffing shortages” that DETR reported in July.

“The time saving is pretty phenomenal,” Stanfield said.

As a safeguard, the AI’s determination is then reviewed by a state employee to hopefully catch any mistakes, biases, or perhaps worse, hallucinations where the AI could possibly make up facts that could impact the outcome of their case.

Google’s spokesperson Ashley Simms told Gizmodo that the tech giant will work with the state to “identify and address any potential bias” and to “help them comply with federal and state requirements.” According to the state’s AI guidelines, the agency must prioritize ethical use of the AI system, “avoiding biases and ensuring fairness and transparency in decision-making processes.”

If the reviewer accepts the AI ruling, they’ll sign off on it and issue the decision. Otherwise, the reviewer will edit the decision and submit feedback so that DETR can investigate what went wrong.

Gizmodo noted that this novel use of AI “represents a significant experiment by state officials and Google in allowing generative AI to influence a high-stakes government decision—one that could put thousands of dollars in unemployed Nevadans’ pockets or take it away.”

Google declined to comment on whether more states are considering using AI to weigh jobless claims.

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Biden orders every US agency to appoint a chief AI officer

Mission control —

Federal agencies rush to appoint chief AI officers with “significant expertise.”

Biden orders every US agency to appoint a chief AI officer

The White House has announced the “first government-wide policy to mitigate risks of artificial intelligence (AI) and harness its benefits.” To coordinate these efforts, every federal agency must appoint a chief AI officer with “significant expertise in AI.”

Some agencies have already appointed chief AI officers, but any agency that has not must appoint a senior official over the next 60 days. If an official already appointed as a chief AI officer does not have the necessary authority to coordinate AI use in the agency, they must be granted additional authority or else a new chief AI officer must be named.

Ideal candidates, the White House recommended, might include chief information officers, chief data officers, or chief technology officers, the Office of Management and Budget (OMB) policy said.

As chief AI officers, appointees will serve as senior advisers on AI initiatives, monitoring and inventorying all agency uses of AI. They must conduct risk assessments to consider whether any AI uses are impacting “safety, security, civil rights, civil liberties, privacy, democratic values, human rights, equal opportunities, worker well-being, access to critical resources and services, agency trust and credibility, and market competition,” OMB said.

Perhaps most urgently, by December 1, the officers must correct all non-compliant AI uses in government, unless an extension of up to one year is granted.

The chief AI officers will seemingly enjoy a lot of power and oversight over how the government uses AI. It’s up to the chief AI officers to develop a plan to comply with minimum safety standards and to work with chief financial and human resource officers to develop the necessary budgets and workforces to use AI to further each agency’s mission and ensure “equitable outcomes,” OMB said. Here’s a brief summary of OMB’s ideals:

Agencies are encouraged to prioritize AI development and adoption for the public good and where the technology can be helpful in understanding and tackling large societal challenges, such as using AI to improve the accessibility of government services, reduce food insecurity, address the climate crisis, improve public health, advance equitable outcomes, protect democracy and human rights, and grow economic competitiveness in a way that benefits people across the United States.

Among the chief AI officer’s primary responsibilities is determining what AI uses might impact the safety or rights of US citizens. They’ll do this by assessing AI impacts, conducting real-world tests, independently evaluating AI, regularly evaluating risks, properly training staff, providing additional human oversight where necessary, and giving public notice of any AI use that could have a “significant impact on rights or safety,” OMB said.

OMB breaks down several AI uses that could impact safety, including controlling “safety-critical functions” within everything from emergency services to food-safety mechanisms to systems controlling nuclear reactors. Using AI to maintain election integrity could be safety-impacting, too, as could using AI to move industrial waste, control health insurance costs, or detect the “presence of dangerous weapons.”

Uses of AI presumed to be rights-impacting include censoring protected speech and a wide range of law enforcement efforts, such as predicting crimes, sketching faces, or using license plate readers to track personal vehicles in public spaces. Other rights-impacting AI uses include “risk assessments related to immigration,” “replicating a person’s likeness or voice without express consent,” or detecting students cheating.

Chief AI officers will ultimately decide if any AI use is safety- or rights-impacting and must adhere to OMB’s minimum standards for responsible AI use. Once a determination is made, the officers will “centrally track” the determinations, informing OMB of any major changes to “conditions or context in which the AI is used.” The officers will also regularly convene “a new Chief AI Officer Council to coordinate” efforts and share innovations government-wide.

As agencies advance AI uses—which the White House says is critical to “strengthen AI safety and security, protect Americans’ privacy, advance equity and civil rights, stand up for consumers and workers, promote innovation and competition, advance American leadership around the world, and more”—chief AI officers will become the public-facing figures accountable for decisions made. In that role, the officer must consult with the public and incorporate “feedback from affected communities,” notify “negatively affected individuals” of new AI uses, and maintain options to opt-out of “AI-enabled decisions,” OMB said.

However, OMB noted that chief AI officers also have the power to waive opt-out options “if they can demonstrate that a human alternative would result in a service that is less fair (e.g., produces a disparate impact on protected classes) or if an opt-out would impose undue hardship on the agency.”

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