{"id":843450,"date":"2026-08-04T17:30:11","date_gmt":"2026-08-04T17:30:11","guid":{"rendered":"https:\/\/www.newsbeep.com\/au\/843450\/"},"modified":"2026-08-04T17:30:11","modified_gmt":"2026-08-04T17:30:11","slug":"google-earths-potential-disinformation-nightmare-technology","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/au\/843450\/","title":{"rendered":"Google Earth\u2019s potential disinformation nightmare | Technology"},"content":{"rendered":"

Hello, and welcome to TechScape. This week we\u2019ll be discussing a regrettable decision by Google Earth, the dramatic fall of the \u201cNostradamus of AI\u201d, and what happens when AI<\/a> agents go rogue.<\/p>\n

Google Earth pauses new AI feature for satellite images<\/p>\n

Last Thursday, Google announced that users of its satellite-imagery software, Google Earth, could create AI-generated images to overlay on any location they looked up. The tool could be used to \u201chelp students visualize the past\u201d, \u201ccreate professional real estate plans\u201d to envision the final result, or \u201cgive your favorite place a makeover\u201d, Google suggested in its announcement. Nearly immediately, users began testing the limits of the feature. Turns out there weren\u2019t many.<\/p>\n

Henk van Ess, an AI researcher and investigator, posted images he created showing refugees near the Mexican border. He also said he \u201cplanted a nuclear plant in Iran\u201d. \u201cWhat on earth is Google doing?\u201d Van Ess posted on X<\/a>. Another image he generated showed a crater from a bomb near a fake hospital he created in Gaza. We tested the feature too. The process just required choosing a location, clicking \u201ccreate image\u201d and entering a prompt. We chose to show \u201crefugees swarming New York\u201d. The image it created was not ultra-realistic, but it was still troubling.<\/p>\n

Google Maps screengrab with AI overlay. Illustration: Google Maps<\/p>\n

Satellite imagery has become widely used by journalists, researchers and investigators to shed light on the breadth and realities of global crises, especially in places that are otherwise inaccessible. The utility of satellite images first became apparent in 2020, after BuzzFeed News won a Pulitzer for a series that exposed the location and expansion of China\u2019s Uyghur detention camps. The imagery captured, for the first time, factories within the walls of the camp. The journalists worked with satellite firm Planet Labs, which is backed by Google and acquired satellite startup Terra Bella from the tech giant in 2017.<\/p>\n

The use of satellite imagery to better understand and uncover global crises really took off in the last two years as reporters and the world sought to better understand the mass destruction Israel has wrought on Gaza. Satellite imagery of Gaza before and after Israel\u2019s years-long rampage on the 365 sq km strip shows cities completely leveled.<\/a> Satellite imagery was also used to expose the human toll of the crisis in Sudan. Images captured from space in November 2025<\/a> showed stains that resembled blood and what researchers believed were human bodies scattered near the besieged city of El Fasher, Sudan, which was under siege by paramilitary fighters from the Rapid Support Forces.<\/p>\n

So a feature that allows you to \u201ctransform\u201d satellite imagery, as Google described it, is a potential disinformation nightmare. Satellite imagery lends a degree of authority, authenticity and veracity to claims and has been used as a mechanism to better understand inaccessible global events. It feels more indisputable than images captured by humans on the ground, which face more public skepticism \u2013 even when they\u2019re real \u2013 as AI-generated images proliferate. Enabling anyone to create any image overlaid on satellite photos of real places may make it impossible to suss out the truth.<\/p>\n

Unsurprisingly, Google rolled back the feature so it can create more guardrails, meaning they may bring the feature back. \u201cWe know that people uniquely trust Google Earth for a reliable view of the world,\u201d the company wrote. \u201cWe\u2019ve seen geospatial professionals using this feature for a range of useful purposes, however we\u2019ve also seen people sharing screenshots of generated imagery that appear to violate our policies.\u201d<\/p>\n

\u2018Nostradamus of AI\u2019 sees $45bn hedge fund unravel practically overnightLeopold Aschenbrenner, once hailed as \u201cthe Nostradamus of AI\u201d, saw his multibillion-dollar hedge fund decimated last week as many of its investments withered. Illustration: Guardian Design<\/p>\n

The popular podcaster Tim Ferriss once called Leopold Aschenbrenner \u201cthe Nostradamus of AI\u201d, saying that the 24-year-old investor and his theories on the future of artificial intelligence were \u201cas close to clairvoyant as you could possibly be\u201d. But that lore hasn\u2019t been borne out.<\/p>\n

Last week, Aschenbrenner saw his multibillion-dollar hedge fund decimated as his many investments withered. By Thursday, the fund had no choice but to sell the majority of its public holdings to a rival.<\/p>\n

Aschenbrenner isn\u2019t a household name, but he is well-known in Silicon Valley circles. When he graduated college, in 2021, he started working for the now defamed crypto exchange FTX. When the exchange collapsed, he joined OpenAI. Aschenbrenner was later fired from OpenAI for reportedly leaking sensitive information to the husband of an Anthropic executive, according to the Wall Street Journal<\/a>. At that point, in 2024, Aschenbrenner wrote a 165-page essay called \u201cSituational Awareness: the Decade Ahead\u201d, which catapulted him toward fame in the tech world.<\/p>\n

The essay laid out his theories on AI, saying that the technology had set in motion \u201cextraordinary techno-capital acceleration\u201d and that \u201cbefore long, the world will wake up\u201d. As his essay gained momentum, Aschenbrenner collected prominent Silicon Valley investors for his hedge fund, also called Situational Awareness. The fund grew exorbitantly.<\/p>\n

Situational Awareness didn\u2019t adhere to the usual cautions of Wall Street, however. Instead, it took the gamble of borrowing money to buy stocks, a strategy that doesn\u2019t have a safety net when stocks go south. And, as AI stocks took a downturn this past month \u2013 with doubts of the technology\u2019s potential swirling \u2013 the hedge fund was forced to pay back skittish lenders. Situational Awareness sold off its investments in a fire sale<\/a> with its billions now dissipated.<\/p>\n

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AI models go on hacking spreesThe Claude AI app on a smartphone. Photograph: Anthropic<\/p>\n

Over the past several weeks, Anthropic<\/a> and OpenAI have revealed that their artificial intelligence models carried out unauthorized hacking operations against outside organizations. The hacks took place during their tests of yet-to-be released AI models, which were supposed to happen within isolated, controlled environments.<\/p>\n

In OpenAI\u2019s case, an autonomous AI agent carried out a days-long hack in early July against Hugging Face, a developer platform which hosts AI models. It also hacked a customer of AI startup Modal Labs. Anthropic similarly revealed last week that its AI models had hacked into three undisclosed organizations<\/a> during a cybersecurity test, in part because human error gave it access to the public internet during the test.<\/p>\n

The reports of rogue AI agents breaking out of their testing sandboxes to carry out attacks have, unsurprisingly, drawn huge amounts of tech and media attention amid heightened cybersecurity concerns and distrust of the industry. They have also divided tech experts over whether these hacks are as consequential as they seem and how to stop them in the future.<\/p>\n

One of the longstanding problems of AI development is that models can act in unpredictable ways when directed to complete a task. An AI instructed to win a racing game may not solely try to drive fast to succeed, for instance. It may also look for loopholes in the game or shortcuts in the course. This is a well-known phenomenon that is usually described as models \u201ccheating\u201d or \u201clying\u201d during testing.<\/p>\n

OpenAI\u2019s hack of Hugging Face was an extreme example of this type of behavior and one that highlights how advancements in AI have exacerbated these unsolved problems. Models that go rogue to achieve their goals are now powerful enough that the unintended consequences can be much more damaging and far-reaching than finding a glitch in a video game.<\/p>\n

While cybersecurity experts agree that AI has become incredibly capable at finding security vulnerabilities, some also cautioned that OpenAI\u2019s hacking incident<\/a> fit into one of the company\u2019s well-worn marketing narratives \u2013 that its technology was scarily powerful and therefore exceedingly valuable. Others, meanwhile, described it as a wake-up call<\/a> about the threat of AI as a cybersecurity nightmare, with the technology rapidly gaining new capabilities.<\/p>\n

Regardless of whether the hacking incidents mark a new frontier or merely play into industry talking points, they highlight the lack of coherent policy and industry standards surrounding the technology. As AI experts Bruce Schneier and Barath Raghavan argued for the Guardian<\/a>, the industry has been focused on whether AI can reach a goal without enough scrutiny of how it gets there:<\/p>\n

Dozens of benchmarks and leaderboards tell us how well these AI models write code, perform logical reasoning, and pass standardized legal and medical exams. But there is nothing that scores whether a system does what you actually meant. We need to develop a measure for this, test it regularly, and push for improvement. We\u2019re not going to have trustworthy AI agents without it.<\/p>\n

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