The Download: AI hiring biases, and weather data sabotage
Quick Answer
New research reveals that LLMs can develop their own biases, stereotyping job applicants more than humans.
Quick Take
Additionally, the risk of weather data sabotage is increasing as AI-driven forecasting becomes more prevalent, potentially compromising accuracy in critical decision-making sectors.
Key Points
- may stereotype job applicants more than human recruiters.
- AI models are being developed to remember minute user details.
- Weather data manipulation poses risks to forecasting accuracy.
- Prediction markets are increasingly reliant on weather forecasts.
- Experts warn of systemic problems arising from data sabotage.
DeepSignal Analysis
What happened
Recent research indicates that large language models (LLMs) can develop their own biases, leading to increased stereotyping of job applicants compared to human evaluators. Additionally, the rise of AI-driven weather forecasting has heightened concerns about potential manipulation of weather data, particularly in prediction markets where financial stakes are involved.
Key evidence
- LLMs are known to inherit biases from their training data, but new findings suggest they can also create their own biases through experience, resulting in more pronounced stereotyping of job applicants than humans.
- The increasing reliance on AI for weather forecasting has made the accuracy of these predictions vulnerable to sabotage, especially as prediction markets emerge where financial incentives exist to manipulate data.
- Experts warn that the risks associated with weather data manipulation could escalate into larger systemic issues, affecting critical decision-making in various sectors.
Why it matters
The implications of LLMs developing their own biases could undermine fairness in hiring processes, potentially leading to discriminatory practices. Meanwhile, the integrity of weather data is crucial for sectors like aviation and agriculture, where decisions based on inaccurate forecasts can have significant consequences. As AI technology continues to evolve, addressing these biases and safeguarding data integrity will be essential to prevent broader societal impacts.
📖 Reader Mode
~3 min readWe already know that LLMs pick up human biases from their training data. New research suggests they can also develop their own biases from experience—and stereotype job applicants more than humans do.
As AI companies race to build agentic models that remember the tiniest details about users, they may be handing them ammunition for forming those biases.
Read the full story on AI’s alarming potential to stereotype job applicants.
—Michelle Kim
The risk of weather data sabotage is rising
Every morning, airline dispatchers, grid operators, and farmers around the world make decisions based on weather forecasts. More recently, the forecasts have become relevant for another industry: prediction markets, where people bet money on all kinds of real-world events, including the weather.
The temptation to manipulate weather data to get an edge in these markets, combined with a collective move toward data-driven AI weather forecasting, is starting to put the accuracy of weather predictions at risk.
As experts in the field, we can foresee scenarios where the risks snowball into far bigger, more systemic problems.
Find out why the threats to weather data are growing—and how to stay ahead of them.
—Monique Kuglitsch, Jesper Dramsch, Franz G. Kuglitsch, & Andrea Toreti
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 SpaceX is negotiating to sell the Pentagon AI compute
It would provide data center capacity worth billions of dollars. (WSJ $)
+ Deepening ties between Elon Musk’s company and the DoD. (Reuters $)
+ Meanwhile, Anthropic is in talks with Meta to acquire compute. (CNBC)
+ The compute explosion is only just beginning. (MIT Technology Review)
2 Trump Media wants $100,000 a month for early access to Trump’s posts
The premium feed is being pitched to trading firms and banks. (FT $)
+ It aims to monetize Trump's market-moving social media posts. (Reuters $)
+ Critics described the plan as “brazen corruption.” (Guardian)
3 ICE shared Medicaid data it wasn't supposed to have with Palantir
Court filings show the data reached the contractor before being deleted. (NPR)
+ ICE is using data broker tools to identify “unaccompanied minors.” (Wired $)
4 Apple briefly overtook Nvidia as the world's most valuable company
The iPhone maker’s earnings durability has impressed investors. (Reuters $)
+ While Nvidia’s rise has stalled amid shifting AI bets. (CNBC)
5. Politicians are trying to change what chatbots say about them
A new industry has sprung up to help them edit AI outputs. (NYT $)
+ Chatbots can sway voters better than political ads. (MIT Technology Review)
6 Washington is opening the door to armed robots
The Pentagon is accelerating AI weapons development. (WP $)
+ “Humans in the loop” in war is an illusion. (MIT Technology Review)
7 China’s Moonshot has paused new subscriptions amid surging uptake
Demand for the headline-grabbing Kimi K3 has strained capacity. (SCMP)
+ China’s open-source AI is challenging US models. (MIT Technology Review)
8 Lab-grown teeth could soon replace fillings and implants
Scientists believe regenerative medicine could transform dentistry. (BBC)
+ Humanlike “teeth” have been grown in mini pigs. (MIT Technology Review)
9 AI slop on birdwatching forums is putting research at risk
It could contaminate records of species. (Guardian)
10 Heart experts have good news for your coffee habit
Roughly five cups per day is fine—and may even be beneficial. (Gizmodo)
Quote of the day
“The most authoritarian government is producing the most egalitarian models, and what should be the most democratic government is breeding companies that are the most authoritarian.”
—Rayan Krishnan, CEO of Vals AI, a company that evaluates AI performance, gives the New York Times his take on the competition between Chinese and American models.
One More Thing
RICHARD CHANCE
The curious case of the disappearing Lamborghinis
A new wave of theft is rocking the luxury car industry—mixing high tech with old-school chop-shop techniques to snag vehicles while they’re in transport.
— Originally published at technologyreview.com
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