Meta is introducing a tool to identify AI-generated images shared on its platforms amid a global rise in synthetic content spreading misinformation. Due to several of systems on the web, the Mark Zuckerberg-owned company is aiming to expand labels to others like Google, OpenAI, Microsoft, and Adobe. Meta said it will fully roll out the labeling feature in the coming months and plans to add a feature that lets users flag AI-generated content. However, the US presidential race is in full swing, leaving some to wonder if the labels will be out in time to stop fake content from spreading. The move comes after Meta's Oversight Board urged the company to take steps to label manipulated audio and video that could mislead users. 'The Board's recommendations go further in that it advised the company to expand the Manipulated Media policy to include audio, clearly state the harms it seeks to reduce, and begin labeling these types of posts more broadly than what was announced,' an Oversight Board spokesperson Dan Chaison told Dailymail.com.

Recent advances in generative models such as GPT may be used to fabricate indistinguishable fake customer reviews at a much lower cost, thus posing challenges for social media platforms to detect these machine-generated fake reviews. We propose to leverage the high-quality elite restaurant reviews verified by Yelp to generate fake reviews from the OpenAI GPT review creator and ultimately fine-tune a GPT output detector to predict fake reviews that significantly outperform existing solutions. We further apply the model to predict non-elite reviews and identify the patterns across several dimensions, such as review, user and restaurant characteristics, and writing style. We show that social media platforms are continuously challenged by machine-generated fake reviews, although they may implement detection systems to filter out suspicious reviews.

Artificial Intelligence/Machine Learning have become far more effective and matured in recent years, thanks to rapid advancements in artificial intelligence and cutting-edge technologies. AI/ML systems are amazing learners because they are constantly improving and becoming smarter than humans, allowing them to make predictions with little or no human intervention. With the growing adoption of AI, IDC's latest forecast on AI market's worldwide revenues, which includes software, hardware, and services are estimated to grow 16.4% year over year in 2021 to $327.5 billion. However, nothing in this world is perfect and has unintended consequences. The power of such technologies can be easily abused or exploited.

The practice of science involves trying to find things out about the world by using rigid logic and testing every assumption. Researchers then write up any important findings in papers and submit them for possible publication. After a peer-review process, in which other scientists check that the research is sound, journals publish papers for public consumption. You might therefore reasonably believe that published papers are quite reliable and meet high-quality standards. You might expect small mistakes that got overlooked during peer review, but no major blunders. You'd be wrong in expecting this, though.

Back in 2019, Ben Lorica and I wrote about deepfakes. Ben and I argued (in agreement with The Grugq and others in the infosec community) that the real danger wasn't "Deep Fakes." The real danger is cheap fakes, fakes that can be produced quickly, easily, in bulk, and at virtually no cost. Tactically, it makes little sense to spend money and time on expensive AI when people can be fooled in bulk much more cheaply. I don't know if The Grugq has changed his thinking, but there was an obvious problem with that argument.

Since the dawn of the computer age, humans have viewed the approach of artificial intelligence (AI) with some degree of apprehension. Popular AI depictions often involve killer robots or all-knowing, all-seeing systems bent on destroying the human race. These sentiments have similarly pervaded the news media, which tends to greet breakthroughs in AI with more alarm or hype than measured analysis. In reality, the true concern should be whether these overly-dramatized, dystopian visions pull our attention away from the more nuanced -- yet equally dangerous -- risks posed by the misuse of AI applications that are already available or being developed today. AI permeates our everyday lives, influencing which media we consume, what we buy, where and how we work, and more.

Since the dawn of the computer age, humans have viewed the approach of artificial intelligence (AI) with some degree of apprehension. Popular AI depictions often involve killer robots or all-knowing, all-seeing systems bent on destroying the human race. These sentiments have similarly pervaded the news media, which tends to greet breakthroughs in AI with more alarm or hype than measured analysis. In reality, the true concern should be whether these overly-dramatized, dystopian visions pull our attention away from the more nuanced -- yet equally dangerous -- risks posed by the misuse of AI applications that are already available or being developed today. AI permeates our everyday lives, influencing which media we consume, what we buy, where and how we work, and more. AI technologies are sure to continue disrupting our world, from automating routine office tasks to solving urgent challenges like climate change and hunger.

Yes, these are amazing places. I'm sure you've used one at least once. Yet, while a few types of media are clearly edited, different changes might be harder to spot. You may have heard the term "deepfake videos" recently. It originally came to fruition in 2017 to depict videos and pictures that incorporate deep learning algorithms to create videos and images that look real.

In a few months the United States will elect its 46th President. While some worry about whether campaigning and casting votes can be done safely during the COVID-19 pandemic, another question is just as critical: how many votes will result via the manipulative influence of artificial intelligence? Specifically, the emerging threat of deepfakes could have an unprecedented impact on this election cycle, raising serious questions about the integrity of elections, policy-making and our democratic society at large. AI-powered deepfakes have the potential to bring troubling consequences for the US 2020 elections. The technology that began as little more than a giggle-inducing gimmick for making homebrew mash-up videos has recently been supercharged by advances in AI.

Bias and susceptibility were evident during the 2016 US Presidential election and has plagued much of President Trump's first four years in office. The term "fake news," which years ago would have been considered absurd, is now part of our cultural vernacular. Allegations against foreign-state actors interfering with US elections and conspiracy theories related to COVID-19 has divided a culture, communities, friends, and even families. Social media has become a platform that propagates both real and fake news and has confounded the next generation of fact checkers and truth seekers dedicated to vetting accurate content. "Deep Fake" In recent years, the emergence of fake news has brought the concept deep fake to the public spotlight.