Curated by THEOUTPOST
On Fri, 11 Apr, 12:02 AM UTC
2 Sources
[1]
Tools like Apple's photo Clean Up are yet another nail in the coffin for being able to trust our eyes
You may have seen ads by Apple promoting its new Clean Up feature that can be used to remove elements in a photo. When one of these ads caught my eye this weekend, I was intrigued and updated my software to try it out. The feature has been available in Australia since December for Apple customers with certain hardware and software capabilities. It's also available for customers in New Zealand, Canada, Ireland, South Africa, the United Kingdom and the United States. The tool uses generative artificial intelligence (AI) to analyse the scene and suggest elements that might be distracting. You can see those highlighted in the screenshot below. You can then tap the suggested element to remove it or circle elements to delete them. The device then uses generative AI to try to create a logical replacement based on the surrounding area. Easier ways to deceive Smartphone photo editing apps have been around for more than a decade, but now, you don't need to download, pay for, or learn to use a new third-party app. If you have an eligible device, you can use these features directly in your smartphone's default photo app. Apple's Clean Up joins a number of similar tools already offered by various tech companies. Those with Android phones might have used Google's Magic Editor. This lets users move, resize, recolour or delete objects using AI. Users with select Samsung devices can use their built-in photo gallery app to remove elements in photos. There have always been ways - analogue and, more recently, digital - to deceive. But integrating them into existing software in a free, easy-to-use way makes those possibilities so much easier. Using AI to edit photos or create new images entirely raises pressing questions around the trustworthiness of photographs and videos. We rely on the vision these devices produce in everything from police body and traffic cams to insurance claims and verifying the safe delivery of parcels. If advances in tech are eroding our trust in pictures and even video, we have to rethink what it means to trust our eyes. How can these tools be used? The idea of removing distracting or unwanted elements can be attractive. If you've ever been to a crowded tourist hotspot, removing some of the other tourists so you can focus more on the environment might be appealing (check out the slider below for an example). But beyond removing distractions, how else can these tools be used? Some people use them to remove watermarks. Watermarks are typically added by photographers or companies trying to protect their work from unauthorised use. Removing these makes the unauthorised use less obvious but not less legal. Others use them to alter evidence. For example, a seller might edit a photo of a damaged good to allege it was in good condition before shipping. As image editing and generating tools become more widespread and easier to use, the list of uses balloons proportionately. And some of these uses can be unsavoury. AI generators can now make realistic-looking receipts, for example. People could then try to submit these to their employer to get reimbursed for expenses not actually incurred. Read more: Can you spot a financial fake? How AI is raising our risks of billing fraud Can anything we see be trusted anymore? Considering these developments, what does it mean to have "visual proof" of something? If you think a photo might be edited, zooming in can sometimes reveal anomalies where the AI has stuffed up. Here's a zoomed-in version of some of the areas where the Clean Up feature generated new content that doesn't quite match the old. It's usually easier to manipulate one image than to convincingly edit multiple images of the same scene in the same way. For this reason, asking to see multiple outtakes that show the same scene from different angles can be a helpful verification strategy. Seeing something with your own eyes might be the best approach, though this isn't always possible. Doing some additional research might also help. For example, with the case of a fake receipt, does the restaurant even exist? Was it open on the day shown on the receipt? Does the menu offer the items allegedly sold? Does the tax rate match the local area's? Manual verification approaches like the above obviously take time. Trustworthy systems that can automate these mundane tasks are likely to grow in popularity as the risks of AI editing and generation increase. Likewise, there's a role for regulators to play in ensuring people don't misuse AI technology. In the European Union, Apple's plan to roll out its Apple Intelligence features, which include the Clean Up function, was delayed due to "regulatory uncertainties". AI can be used to make our lives easier. Like any technology, it can be used for good or bad. Being aware of what it's capable of and developing your visual and media literacies is essential to being an informed member of our digital world.
[2]
Tools like Apple's photo Clean Up are yet another nail in the coffin for being able to trust our eyes
You may have seen ads by Apple promoting its new Clean Up feature that can be used to remove elements in a photo. When one of these ads caught my eye this weekend, I was intrigued and updated my software to try it out. The feature has been available in Australia since December for Apple customers with certain hardware and software capabilities. It's also available for customers in New Zealand, Canada, Ireland, South Africa, the United Kingdom and the United States. The tool uses generative artificial intelligence (AI) to analyze the scene and suggest elements that might be distracting. You can see those highlighted in the screenshot below. You can then tap the suggested element to remove it or circle elements to delete them. The device then uses generative AI to try to create a logical replacement based on the surrounding area. Easier ways to deceive Smartphone photo editing apps have been around for more than a decade, but now, you don't need to download, pay for, or learn to use a new third-party app. If you have an eligible device, you can use these features directly in your smartphone's default photo app. Apple's Clean Up joins a number of similar tools already offered by various tech companies. Those with Android phones might have used Google's Magic Editor. This lets users move, resize, recolor or delete objects using AI. Users with select Samsung devices can use their built-in photo gallery app to remove elements in photos. There have always been ways -- analog and, more recently, digital -- to deceive. But integrating them into existing software in a free, easy-to-use way makes those possibilities so much easier. Using AI to edit photos or create new images entirely raises pressing questions around the trustworthiness of photographs and videos. We rely on the vision these devices produce in everything from police body and traffic cams to insurance claims and verifying the safe delivery of parcels. If advances in tech are eroding our trust in pictures and even video, we have to rethink what it means to trust our eyes. How can these tools be used? The idea of removing distracting or unwanted elements can be attractive. If you've ever been to a crowded tourist hotspot, removing some of the other tourists so you can focus more on the environment might be appealing (check out the slider below for an example). But beyond removing distractions, how else can these tools be used? Some people use them to remove watermarks. Watermarks are typically added by photographers or companies trying to protect their work from unauthorized use. Removing these makes the unauthorized use less obvious but not less legal. Others use them to alter evidence. For example, a seller might edit a photo of a damaged good to allege it was in good condition before shipping. As image editing and generating tools become more widespread and easier to use, the list of uses balloons proportionately. And some of these uses can be unsavory. AI generators can now make realistic-looking receipts, for example. People could then try to submit these to their employer to get reimbursed for expenses not actually incurred. Can anything we see be trusted anymore? Considering these developments, what does it mean to have "visual proof" of something? If you think a photo might be edited, zooming in can sometimes reveal anomalies where the AI has stuffed up. Here's a zoomed-in version of some of the areas where the Clean Up feature generated new content that doesn't quite match the old. It's usually easier to manipulate one image than to convincingly edit multiple images of the same scene in the same way. For this reason, asking to see multiple outtakes that show the same scene from different angles can be a helpful verification strategy. Seeing something with your own eyes might be the best approach, though this isn't always possible. Doing some additional research might also help. For example, with the case of a fake receipt, does the restaurant even exist? Was it open on the day shown on the receipt? Does the menu offer the items allegedly sold? Does the tax rate match the local area's? Manual verification approaches like the above obviously take time. Trustworthy systems that can automate these mundane tasks are likely to grow in popularity as the risks of AI editing and generation increase. Likewise, there's a role for regulators to play in ensuring people don't misuse AI technology. In the European Union, Apple's plan to roll out its Apple Intelligence features, which include the Clean Up function, was delayed due to "regulatory uncertainties." AI can be used to make our lives easier. Like any technology, it can be used for good or bad. Being aware of what it's capable of and developing your visual and media literacies is essential to being an informed member of our digital world.
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Apple's new Clean Up feature, which uses AI to remove elements from photos, sparks debate about the trustworthiness of digital images and the ethical implications of easy-to-use photo manipulation tools.
Apple has recently launched its new Clean Up feature, an artificial intelligence-powered tool that allows users to remove unwanted elements from photos. This feature, available since December in several countries including Australia, New Zealand, Canada, and the United States, has sparked discussions about the implications of easy-to-use photo manipulation technologies 12.
The Clean Up feature utilizes generative AI to analyze photos and suggest potentially distracting elements for removal. Users can then tap or circle these elements to delete them, after which the AI generates a logical replacement based on the surrounding area. This functionality is now integrated directly into the default photo app of eligible Apple devices, making advanced photo editing more accessible than ever before 12.
Apple's Clean Up is not alone in this space. Google's Magic Editor for Android phones and Samsung's built-in photo gallery app offer similar AI-powered editing capabilities. These tools allow users to move, resize, recolor, or delete objects in photos using artificial intelligence 12.
While the primary intention of these tools is to enhance photos by removing distractions, there are concerns about potential misuse:
Watermark Removal: Some users might exploit these tools to remove watermarks from copyrighted images, facilitating unauthorized use 12.
Evidence Alteration: There's a risk of these tools being used to manipulate evidence, such as editing photos of damaged goods to falsely claim they were in good condition 12.
Fraud: AI generators can now create realistic-looking fake receipts, which could be used for fraudulent expense reimbursements 12.
The proliferation of these AI-powered editing tools raises significant questions about the trustworthiness of digital images and videos. As society relies on visual evidence for various purposes, from law enforcement to insurance claims, the ease of manipulation challenges our ability to trust what we see 12.
To combat potential deception, several verification strategies have been suggested:
Close Inspection: Zooming in on edited photos may reveal anomalies where AI-generated content doesn't perfectly match the original 12.
Multiple Angles: Requesting multiple images of the same scene from different angles can help verify authenticity 12.
Additional Research: For documents like receipts, verifying details such as the existence of the business, operating hours, and local tax rates can help detect forgeries 12.
The rapid advancement of AI-powered photo editing tools has caught the attention of regulators. In the European Union, Apple's rollout of its Apple Intelligence features, including Clean Up, faced delays due to "regulatory uncertainties" 12.
As AI continues to revolutionize image manipulation, developing strong visual and media literacy skills becomes crucial. While AI can make our lives easier, understanding its capabilities and limitations is essential for navigating the increasingly complex digital landscape 12.
Google's upcoming Pixel 9 smartphone introduces an AI-powered Magic Editor feature, allowing users to dramatically alter photos. While innovative, it raises questions about the authenticity of digital images and potential misuse.
3 Sources
3 Sources
Major tech companies are taking different approaches to AI photo editing, with Apple emphasizing accuracy while others explore more extensive manipulations. This raises questions about the nature of photography in the AI era.
6 Sources
6 Sources
Google Photos is implementing a new feature to label AI-edited images, promoting transparency in photo manipulation and addressing concerns about the authenticity of digital content.
19 Sources
19 Sources
Apple's iOS 18.1 introduces an AI-powered 'Clean Up' feature for photo editing, rivaling Google's Magic Editor. The new tool offers intuitive object removal and background blending, sparking comparisons in performance and user experience.
3 Sources
3 Sources
Adobe has unveiled a new AI-powered 'Distraction Removal' tool for Photoshop, promising to simplify the process of removing unwanted elements from images. This feature, along with other AI enhancements, aims to streamline the creative workflow for photographers and designers.
3 Sources
3 Sources
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