#Deepfake Detection Tools

[mehmetyildizmelbourne-blog]

The Scary Effects of Deep Fakes in Our Lives

Dear Subscribers, In this post we want to share an interactive podcast and an insightful article which we curated on Medium and Substack for your information. The story is titled Why Deep Fakes Stop Thought Leaders Like Me from Creating YouTube Videos Here is the link to the interactive podcast about deep fakes: Why Deepfakes Are So Dangerous and What We Can Do to Lower Risks Here is the…

[olivergisttv]

How to Use AI to Detect Deepfake Videos

Deepfake videos, where artificial intelligence (AI) is used to manipulate videos to make people appear as if they are saying or doing things they never did, have become increasingly sophisticated. As these videos pose risks in various areas such as misinformation, fraud, and personal privacy, detecting deepfakes has become critical. Here’s how you can use AI to identify and protect yourself from…

[mariacallous]

These days, when Nicole Yelland receives a meeting request from someone she doesn’t already know, she conducts a multi-step background check before deciding whether to accept. Yelland, who works in public relations for a Detroit-based non-profit, says she’ll run the person’s information through Spokeo, a personal data aggregator that she pays a monthly subscription fee to use. If the contact claims to speak Spanish, Yelland says, she will casually test their ability to understand and translate trickier phrases. If something doesn’t quite seem right, she’ll ask the person to join a Microsoft Teams call—with their camera on.

If Yelland sounds paranoid, that’s because she is. In January, before she started her current non-profit role, Yelland says she got roped into an elaborate scam targeting job seekers. “Now, I do the whole verification rigamarole any time someone reaches out to me,” she tells WIRED.

Digital imposter scams aren’t new; messaging platforms, social media sites, and dating apps have long been rife with fakery. In a time when remote work and distributed teams have become commonplace, professional communications channels are no longer safe, either. The same artificial intelligence tools that tech companies promise will boost worker productivity are also making it easier for criminals and fraudsters to construct fake personas in seconds.

On LinkedIn, it can be hard to distinguish a slightly touched-up headshot of a real person from a too-polished, AI-generated facsimile. Deepfake videos are getting so good that longtime email scammers are pivoting to impersonating people on live video calls. According to the US Federal Trade Commission, reports of job and employment related scams nearly tripled from 2020 to 2024, and actual losses from those scams have increased from $90 million to $500 million.

Yelland says the scammers that approached her back in January were impersonating a real company, one with a legitimate product. The “hiring manager” she corresponded with over email also seemed legit, even sharing a slide deck outlining the responsibilities of the role they were advertising. But during the first video interview, Yelland says, the scammers refused to turn their cameras on during a Microsoft Teams meeting and made unusual requests for detailed personal information, including her driver’s license number. Realizing she’d been duped, Yelland slammed her laptop shut.

These kinds of schemes have become so widespread that AI startups have emerged promising to detect other AI-enabled deepfakes, including GetReal Labs, and Reality Defender. OpenAI CEO Sam Altman also runs an identity-verification startup called Tools for Humanity, which makes eye-scanning devices that capture a person’s biometric data, create a unique identifier for their identity, and store that information on the blockchain. The whole idea behind it is proving “personhood,” or that someone is a real human. (Lots of people working on blockchain technology say that blockchain is the solution for identity verification.)

But some corporate professionals are turning instead to old-fashioned social engineering techniques to verify every fishy-seeming interaction they have. Welcome to the Age of Paranoia, when someone might ask you to send them an email while you’re mid-conversation on the phone, slide into your Instagram DMs to ensure the LinkedIn message you sent was really from you, or request you text a selfie with a timestamp, proving you are who you claim to be. Some colleagues say they even share code words with each other, so they have a way to ensure they’re not being misled if an encounter feels off.

“What’s funny is, the low-fi approach works,” says Daniel Goldman, a blockchain software engineer and former startup founder. Goldman says he began changing his own behavior after he heard a prominent figure in the crypto world had been convincingly deepfaked on a video call. “It put the fear of god in me,” he says. Afterwards, he warned his family and friends that even if they hear what they believe is his voice or see him on a video call asking for something concrete—like money or an internet password—they should hang up and email him first before doing anything.

Ken Schumacher, founder of the recruitment verification service Ropes, says he’s worked with hiring managers who ask job candidates rapid-fire questions about the city where they claim to live on their resume, such as their favorite coffee shops and places to hang out. If the applicant is actually based in that geographic region, Schumacher says, they should be able to respond quickly with accurate details.

Another verification tactic some people use, Schumacher says, is what he calls the “phone camera trick.” If someone suspects the person they’re talking to over video chat is being deceitful, they can ask them to hold up their phone camera to their laptop. The idea is to verify whether the individual may be running deepfake technology on their computer, obscuring their true identity or surroundings. But it’s safe to say this approach can also be off-putting: Honest job candidates may be hesitant to show off the inside of their homes or offices, or worry a hiring manager is trying to learn details about their personal lives.

“Everyone is on edge and wary of each other now,” Schumacher says.

While turning yourself into a human captcha may be a fairly effective approach to operational security, even the most paranoid admit these checks create an atmosphere of distrust before two parties have even had the chance to really connect. They can also be a huge time suck. “I feel like something’s gotta give,” Yelland says. “I’m wasting so much time at work just trying to figure out if people are real.”

Jessica Eise, an assistant professor studying climate change and social behavior at Indiana University-Bloomington, says that her research team has been forced to essentially become digital forensics experts, due to the amount of fraudsters who respond to ads for paid virtual surveys. (Scammers aren’t as interested in the unpaid surveys, unsurprisingly.) If the research project is federally funded, all of the online participants have to be over the age of 18 and living in the US.

“My team would check time stamps for when participants answered emails, and if the timing was suspicious, we could guess they might be in a different time zone,” Eise says. “Then we’d look for other clues we came to recognize, like certain formats of email address or incoherent demographic data.”

Eise says the amount of time her team spent screening people was “exorbitant,” and that they’ve now shrunk the size of the cohort for each study and have turned to “snowball sampling” or having recruiting people they know personally to join their studies. The researchers are also handing out more physical flyers to solicit participants in person. “We care a lot about making sure that our data has integrity, that we’re studying who we say we’re trying to study,” she says. “I don’t think there’s an easy solution to this.”

Barring any widespread technical solution, a little common sense can go a long way in spotting bad actors. Yelland shared with me the slide deck that she received as part of the fake job pitch. At first glance, it seemed like legit pitch, but when she looked at it again, a few details stood out. The job promised to pay substantially more than the average salary for a similar role in her location, and offered unlimited vacation time, generous paid parental leave, and fully-covered health care benefits. In today’s job environment, that might have been the biggest tipoff of all that it was a scam.

[reasonsforhope]

"Major technology companies signed a pact on Friday to voluntarily adopt "reasonable precautions" to prevent artificial intelligence (AI) tools from being used to disrupt democratic elections around the world.

Executives from Adobe, Amazon, Google, IBM, Meta, Microsoft, OpenAI, and TikTok gathered at the Munich Security Conference to announce a new framework for how they respond to AI-generated deepfakes that deliberately trick voters. 

Twelve other companies - including Elon Musk's X - are also signing on to the accord...

The accord is largely symbolic, but targets increasingly realistic AI-generated images, audio, and video "that deceptively fake or alter the appearance, voice, or actions of political candidates, election officials, and other key stakeholders in a democratic election, or that provide false information to voters about when, where, and how they can lawfully vote".

The companies aren't committing to ban or remove deepfakes. Instead, the accord outlines methods they will use to try to detect and label deceptive AI content when it is created or distributed on their platforms. 

It notes the companies will share best practices and provide "swift and proportionate responses" when that content starts to spread.

Lack of binding requirements

The vagueness of the commitments and lack of any binding requirements likely helped win over a diverse swath of companies, but disappointed advocates were looking for stronger assurances.

"The language isn't quite as strong as one might have expected," said Rachel Orey, senior associate director of the Elections Project at the Bipartisan Policy Center. 

"I think we should give credit where credit is due, and acknowledge that the companies do have a vested interest in their tools not being used to undermine free and fair elections. That said, it is voluntary, and we'll be keeping an eye on whether they follow through." ...

Several political leaders from Europe and the US also joined Friday’s announcement. European Commission Vice President Vera Jourova said while such an agreement can’t be comprehensive, "it contains very impactful and positive elements".  ...

[The Accord and Where We're At]

The accord calls on platforms to "pay attention to context and in particular to safeguarding educational, documentary, artistic, satirical, and political expression".

It said the companies will focus on transparency to users about their policies and work to educate the public about how they can avoid falling for AI fakes.

Most companies have previously said they’re putting safeguards on their own generative AI tools that can manipulate images and sound, while also working to identify and label AI-generated content so that social media users know if what they’re seeing is real. But most of those proposed solutions haven't yet rolled out and the companies have faced pressure to do more.

That pressure is heightened in the US, where Congress has yet to pass laws regulating AI in politics, leaving companies to largely govern themselves.

The Federal Communications Commission recently confirmed AI-generated audio clips in robocalls are against the law [in the US], but that doesn't cover audio deepfakes when they circulate on social media or in campaign advertisements.

Many social media companies already have policies in place to deter deceptive posts about electoral processes - AI-generated or not... 

[Signatories Include]

In addition to the companies that helped broker Friday's agreement, other signatories include chatbot developers Anthropic and Inflection AI; voice-clone startup ElevenLabs; chip designer Arm Holdings; security companies McAfee and TrendMicro; and Stability AI, known for making the image-generator Stable Diffusion.

Notably absent is another popular AI image-generator, Midjourney. The San Francisco-based startup didn't immediately respond to a request for comment on Friday.

The inclusion of X - not mentioned in an earlier announcement about the pending accord - was one of the surprises of Friday's agreement."

-via EuroNews, February 17, 2024

--

Note: No idea whether this will actually do much of anything (would love to hear from people with experience in this area on significant this is), but I'll definitely take it. Some of these companies may even mean it! (X/Twitter almost definitely doesn't, though).

Still, like I said, I'll take it. Any significant move toward tech companies self-regulating AI is a good sign, as far as I'm concerned, especially a large-scale and international effort. Even if it's a "mostly symbolic" accord, the scale and prominence of this accord is encouraging, and it sets a precedent for further regulation to build on.

[qualitybreadfestival]

Taylor endorses Trump?

During the 2024 election, Trump responded to a tweet of photos showing singer, songwriter Taylor Swift and all her fans (Swifties) supporting him.

THIS IS FAKE NEWS!

Defined by Chu et al (2012), fake news is "fabricated news with the purpose of misleading people"

There are two types of misleading information. The first, misinformation, refers to using unintentionally misleading information. The second, disinformation, is the intentional use of misleading information.

Fake news can lead us to a "post-truth" world. According to Higgins (2016) post post-truth refers to "blatant lies being routine across society... politicians can lie without condemnation". We can call these photos a "blatant lie"

Vamanu (2019) and Mabia (2021) deciphered the linguistic practices in (online) fake news

Photo or video as an introduction to capture attention

Emotional and persuasive language

Repetition

.Colloquial and expressive syntax

Involvement of social groups

Indifference to logical reasoning

One sided argumentation, often polarizing and devilizing

Using these practices we can see that this fake news has used photos, the involvement of social groups and the repetition of what is said on the AI-generated t-shirts.

Bell 1984 said that speakers "design their style for their audience". In Trump's case, the audience was clearly Swifties.

Those who are Swifties know that in her 'Miss Americana' documentary on Netflix Taylor made it very clear that she did not support Trump or his values. This included speaking about the former House of Representatives (Marsha Blackburn) run in the senate calling her "Trump in a wig" (https://www.elitedaily.com/p/taylor-swifts-quotes-about-trump-in-miss-americana-are-brutal-21762677)

Bell also wrote that the "differences within the speech of a single speaker are accountable as the influence of the second person and some third persons".

The second person is the addressee or main character in the audience. we can assume in this case that it is Taylor.

The third person are the auditors or those who are present but not directly addressed, their presence is known and they are therefore ratified. In this instance, the third person is the Swifties.

Jaster and Lanius (2018) also aid to the deciphering of fake news with their own ways to identify whether or not something is fake news

Its truth value

Its content

Its distribution channels

The way in which they are presented

Most Swifties will immediately know, based on Taylors previous comments about Trump and his views, that this is fake news. We also can see that the photos included are AI-generated. In addition to this, the photos were first shared through X (formally 'Twitter) which is most definitely not a reliable news source.

The use of AI to generate the images can be called deepfake. By definition, a deepfake is "an image or recording that has been convincingly altered and manipulated to misrepresent someone as doing or saying something that was not actually done or said" (Brotha and Pieterse, 2020)

The images made and responded to by Trump can be classed as deepfakes and as Botha and Pieterse said, deepfakes can act as a "tool to conduct political or psychological operations"

References

Botha, J. and Pieterse, H., (2020). Fake news and deepfakes: A dangerous threat for 21st century information security. In ICCWS 2020 15th International Conference on Cyber Warfare and Security. Academic Conferences and publishing limited

Chu, S.K.W., Xie, R. and Wang, Y., (2021). Cross‐language fake news detection. Data and Information Management, 5(1), pp.100‐109.

iggins, K., (2016). Post‐truth: a guide for the perplexed. Nature, 540(7631), pp.9‐9.

Jaster, R. and Lanius, D., (2018). What is fake news?. Versus, 47(2), pp.207-224.

Vamanu, I. 2019. Fake News and Propaganda: A Critical Discourse Research Perspective. Open Information Science, 3(1), pp. 197-208.

[darkmaga-returns]

Federal Reserve Governor Michael Barr is urging banks to begin collecting behavioral and biometric data from customers to combat deepfake digital content created through ID. These deepfakes are capable of replicating a person’s identity, which “has the potential to supercharge identity fraud,” Barr warned.

“In the past, a skilled forger could pass a bad check by replicating a person’s signature. Now, advances in AI can do much more damage by replicating a person’s entire identity,” Barr said of deepfakes, which have the “potential to supercharge identity fraud.”

“[We] should take steps to lessen the impact of attacks by making successful breaches less likely, while making each attack more resource-intensive for the attacker,” Barr insists, believing that regulators should implement their own AI tools to “enhance our ability to monitor and detect patterns of fraudulent activity at regulated institutions in real time,” he said. This could help provide early warnings to affected institutions and broader industry participants, as well as to protect our own systems.”

Enabling multi-factor authentication and monitoring abnormal payments is a first step, but Barr and others believe that banks must begin to collect their customer’s biometric data. “To the extent deepfakes increase, bank identity verification processes should evolve in kind to include AI-powered advances such as facial recognition, voice analysis, and behavioral biometrics to detect potential deepfakes,” Barr noted.

Barr would like banks to begin sharing data to combat fraud. Deepfake attacks have been on the rise, with one in 10 companies reporting an attack according to a 2024 Business.com survey. Yet, will our data be safer in the hands of regulators?

[tieflingkisser]

The Pentagon Wants to Use AI to Create Deepfake Internet Users

The Department of Defense wants technology so it can fabricate online personas that are indistinguishable from real people.

The United States’ secretive Special Operations Command is looking for companies to help create deepfake internet users so convincing that neither humans nor computers will be able to detect they are fake, according to a procurement document reviewed by The Intercept. The plan, mentioned in a new 76-page wish list by the Department of Defense’s Joint Special Operations Command, or JSOC, outlines advanced technologies desired for country’s most elite, clandestine military efforts. “Special Operations Forces (SOF) are interested in technologies that can generate convincing online personas for use on social media platforms, social networking sites, and other online content,” the entry reads. The document specifies that JSOC wants the ability to create online user profiles that “appear to be a unique individual that is recognizable as human but does not exist in the real world,” with each featuring “multiple expressions” and “Government Identification quality photos.”

[...]

The Pentagon has already been caught using phony social media users to further its interests in recent years. In 2022, Meta and Twitter removed a propaganda network using faked accounts operated by U.S. Central Command, including some with profile pictures generated with methods similar to those outlined by JSOC. A 2024 Reuters investigation revealed a Special Operations Command campaign using fake social media users aimed at undermining foreign confidence in China’s Covid vaccine.

[...]

This more detailed procurement listing shows that the United States pursues the exact same technologies and techniques it condemns in the hands of geopolitical foes. National security officials have long described the state-backed use of deepfakes as an urgent threat — that is, if they are being done by another country.

[...]

The offensive use of this technology by the U.S. would, naturally, spur its proliferation and normalize it as a tool for all governments. “What’s notable about this technology is that it is purely of a deceptive nature,” said Heidy Khlaaf, chief AI scientist at the AI Now Institute. “There are no legitimate use cases besides deception, and it is concerning to see the U.S. military lean into a use of a technology they have themselves warned against. This will only embolden other militaries or adversaries to do the same, leading to a society where it is increasingly difficult to ascertain truth from fiction and muddling the geopolitical sphere.” 

[cassiachloe]

Deepfake and AI video recreation is in the public mind a lot. This is a legitimate concern for the public on multiple levels, and one of the more important aspects is not focused upon – that is the way in which AI can be used to enforce Orwell’s dictum.

PRISM (as leaked by Snoden) has demonstrated partially a degree to which the existing state-capitalist institutions of control embed in to internet and other media platforms (primarily focusing on how your data is harvested). What is not considered is the multi-directional control of media platforms, not merely through algorithm manipulation, but by direct interference.

Something I have witnessed personally (as a tortured and trafficked slave it appears I am used as a guinea pig for a variety of novel tech and methods) is the live manipulation of videos already loaded on to Youtube by AI. Whilst I have witnessed targeted posts designed to influence me specifically based on my personal data (this includes using targeted ads or pages controlled by propaganda and mind control factions), I have now witnessed the modification of videos for mind control on YouTube and other platforms.

This does not only include the creation of New AI videos to specifically influence me or the public, BUT also the modification on past videos on the platform. Theoretically, this could be achieved in a targeted way to myself by direct end devices hacking on my laptop (which is achievable due to entrance in my home which I have documented), but also it may now be possible to modify past videos already uploaded to these platforms to entirely rewrite history.

The rewriting of history has never been easier; The mere modification of pixels on a screen can change the entire narrative. Entire sentences never spoken by an individual could be placed in to their mouths with AI. No longer would we have to hunt trough libraries and rip out pages not agreeable to the current regime, but worse. What does this mean? The real truth of the near past may exist only in the living memory of a few, but when they pass, this too will be gone.

Now, theoretically, AI falsification can also be detected with AI tools, and what we could see is a continued spiralling of development; AI becomes better at video falsification, then AI powered AI fake detection becomes more accurate, and this could go on and on (totally throwing the possibility of human detection way out the window). But, I question if there is enough of an incentive for power to (permit or) develop AI fake detection tools as they have the most to gain from AI fakes. Meaning a further power imbalance.

Moving away from public mind control, the manipulation of the past and the propaganda narrative, I would like to focus on an even more dangerous, disturbing and harmful use of the tool of video falsification: that is the tampering of security footage.

This becomes especially concerning when we recognise the edge state-capitalist institutions have to create less-detectable fakes, combined with the knowledge of institutional violence. A poignant example is the fact of sex traffick and rape infiltrating powers, including paedophilia and slavery (look to the Epstein case or Kincora boys). Rape, abuse and paedophilia is hugely profitable, and states have control over (and directly profit form) this cruel, degrading and inhuman black market.

My ultimate fear is that alongside other advancements in technology, such as neural interfaces, we could see entire schools rendered temporarily unconscious or amnesiac, to be mass raped for profit by ‘elites’. And then, due to the hacking capacities of the institutions and AI fake development, all security footage will be undermined, and it will appear as if such crimes did not occur.

And remember, many do not hold security footage for longer than 3 months, and presuming that the state-capitalist rapists have at least a 3 month technological edge, meaning their AI-fake will not be detectable by AI-powered AI-fake detection within that period, the footage will then be deleted.

Tom Keenan Photography

Taken at Hanna & Guy's Wedding

Cassia Chloe Fire Dancer, Pyro Show & Circus Performer

[govindhtech]

How To Reduce 5G Cybersecurity Risks Surface Vulnerabilities

5G Cybersecurity Risks

There are new 5G Cybersecurity Risks technology. Because each 5G device has the potential to be a gateway for unauthorized access if it is not adequately protected, the vast network of connected devices provides additional entry points for hackers and increases the attack surface of an enterprise. Network slicing, which divides a single physical 5G network into many virtual networks, is also a security risk since security lapses in one slice might result in breaches in other slices.

Employing safe 5G Cybersecurity Risks enabled devices with robust security features like multi-factor authentication, end-to-end encryption, frequent security audits, firewall protection, and biometric access restrictions may help organizations reduce these threats. Regular security audits may also assist in spotting any network vulnerabilities and taking proactive measures to fix them.

Lastly, it’s preferable to deal with reputable 5G service providers that put security first.

Take On New Cybersecurity Threats

Cybercriminals often aim their biggest intrusions at PCs. Learn the characteristics of trustworthy devices and improve your cybersecurity plan. In the current digital environment, there is reason for worry over the growing complexity and frequency of cyber attacks. Cybercriminals are seriously harming businesses’ reputations and finances by breaking into security systems using sophisticated tools and tactics. Being able to recognize and address these new issues is critical for both users and businesses.

Threats Driven by GenAI

Malicious actors find it simpler to produce material that resembles other individuals or entities more authentically with generative AI. Because of this, it may be used to trick individuals or groups into doing harmful things like handing over login information or even sending money.

Here are two instances of these attacks:

Sophisticated phishing: Emails and other communications may sound much more human since GenAI can combine a large quantity of data, which increases their credibility.

Deepfake: With the use of online speech samples, GenAI is able to produce audio and maybe even video files that are flawless replicas of the original speaker. These kinds of files have been used, among other things, to coerce people into doing harmful things like sending money to online fraudsters.

The mitigation approach should concentrate on making sure that sound cybersecurity practices, such as minimizing the attack surface, detection and response methods, and recovery, are in place, along with thorough staff training and continual education, even if both threats are meant to be challenging to discover. Individuals must be the last line of defense as they are the targeted targets.

Apart from these two, new hazards that GenAI models themselves encounter include prompt injection, manipulation of results, and model theft. Although certain hazards are worth a separate discussion, the general approach is very much the same as safeguarding any other important task. Utilizing Zero Trust principles, lowering the attack surface, protecting data, and upholding an incident recovery strategy have to be the major priorities.Image Credit To Dell

Ransomware as a Service (RaaS)

Ransomware as a Service (RaaS) lets attackers rent ransomware tools and equipment or pay someone to attack via its subscription-based architecture. This marks a departure from typical ransomware assaults. Because of this professional approach, fraudsters now have a reduced entrance barrier and can carry out complex assaults even with less technical expertise. There has been a notable rise in the number and effect of RaaS events in recent times, as shown by many high-profile occurrences.

Businesses are encouraged to strengthen their ransomware attack defenses in order to counter this threat:

Hardware-assisted security and Zero Trust concepts, such as network segmentation and identity management, may help to reduce the attack surface.

Update and patch systems and software on a regular basis.

Continue to follow a thorough incident recovery strategy.

Put in place strong data protection measures

IoT vulnerabilities

Insufficient security makes IoT devices susceptible to data breaches and illicit access. The potential of distributed denial-of-service (DDoS) attacks is increased by the large number of networked devices, and poorly managed device identification and authentication may also result in unauthorized control. Renowned cybersecurity researcher Theresa Payton has even conjured up scenarios in which hackers may use Internet of Things (IoT) devices to target smart buildings, perhaps “creating hazmat scenarios, locking people in buildings and holding people for ransom.”

Frequent software upgrades are lacking in many IoT devices, which exposes them. Furthermore, the deployment of more comprehensive security measures may be hindered by their low computational capacity.

Several defensive measures, such assuring safe setup and frequent updates and implementing IoT-specific security protocols, may be put into place to mitigate these problems. These protocols include enforcing secure boot to guarantee that devices only run trusted software, utilizing network segmentation to separate IoT devices from other areas of the network, implementing end-to-end encryption to protect data transmission, and using device authentication to confirm the identity of connected devices.

Furthermore, Zero Trust principles are essential for Internet of Things devices since they will continuously authenticate each user and device, lowering the possibility of security breaches and unwanted access.

Overarching Techniques for Fighting Cybersecurity Risks

Regardless of the threat type, businesses may strengthen their security posture by taking proactive measures, even while there are unique tactics designed to counter certain threats.

Since they provide people the skills and information they need to tackle cybersecurity risks, training and education are essential. Frequent cybersecurity awareness training sessions are crucial for fostering these abilities. Different delivery modalities, such as interactive simulations, online courses, and workshops, each have their own advantages. It’s critical to maintain training sessions interesting and current while also customizing the material to fit the various positions within the company to guarantee its efficacy.

Read more on govindhtech.com

[mariacallous]

Former president Donald Trump has shared AI-generated images that falsely claim Taylor Swift fans are supporting his campaign.

In a post on Truth Social, Trump shared screenshots of four posts on X that purport to show a number of young women all wearing “Swifties for Trump” T-shirts in a variety of styles. One of the screenshots claimed that Swifties are supporting Trump now after Taylor Swift canceled her concert in Vienna due to security concerns. Another image included the phrase “Taylor wants you to vote for Donald Trump.”

“I accept!” Trump captioned his post.

However, Trump’s post appears to contain a mixture of real and AI-generated images that falsely suggest a widespread and coordinated movement of Swifties for Trump. Using a tool created by nonprofit True Media to detect the spread of election-related deepfakes, WIRED found that many of the images shared by Trump show “substantial evidence of manipulation.”

One of the screenshots Trump shared was from an anonymous pro-Trump account with over 300,000 followers that regularly posts AI-generated images. Following its post about Swifties for Trump, this account shared a follow-up post that said the original Swifties for Trump post was “satire.”

While there doesn’t appear to be an active Swifties for Trump campaign initiative, there is an active Swifties4Kamala group. “We do not represent every Swiftie, but I think there is a reason we don’t need AI to show our support for Kamala,” Irene Kim, cofounder of Swifties4Harris, tells WIRED.

There is at least one public Swiftie for Trump. Among the images shared by Trump on Sunday on Truth Social was a real picture of Jenna Piwowarczyk, who wore a homemade T-shirt to a Racine, Wisconsin, Trump rally in June, emblazoned with the words “Swifties for Trump.” Piwowarczyk is now selling her homemade T-shirts on Etsy.

Trump has consistently shared AI-generated images. Last week, Trump falsely claimed that the Harris campaign was using AI to artificially inflate crowd sizes at her rallies. Over the weekend, Trump also posted an AI-generated image on X of Harris speaking at the Democratic National Convention in Chicago with a Soviet Union flag hanging over the crowd.

Disinformation experts have warned about the threat posed to the integrity of elections by generative AI tools. Already this year, WIRED has tracked dozens of examples of content created using generative AI in elections across the globe.

Swift has not publicly endorsed any candidate for president, but she did endorse President Joe Biden in 2020. She has also strongly criticized Trump: After Trump made his infamous “when the looting starts, the shooting starts” comment in 2020 following Black Lives Matter protests in support of George Floyd, the pop superstar slammed the then-president for having “the nerve to feign moral superiority” after “stoking the fires of white supremacy and racism your entire presidency.”

[grounddeepfake]

Deepfakes and the Future of Media: Implications and Challenges

The rise of��deepfake technology has fueled concerns about the future of media, as the line between reality and fabrication becomes increasingly blurred. Deepfakes have profound implications for media authenticity, credibility, and public trust. As the technology advances, it is essential to navigate the challenges it presents and find effective solutions to mitigate potential harm.

One of the most pressing challenges is the detection and verification of deepfakes. With the increasing sophistication of deepfake algorithms, traditional methods of visual analysis and forensics are becoming less reliable. Research is underway to develop advanced detection tools, leveraging artificial intelligence to identify signs of manipulation. Robust methods for verification, such as digital watermarking or blockchain technology, need to be explored to ensure the authenticity of media content.

Educating the public about deepfake technology and its potential misuses is another crucial aspect in combating its harmful impacts. By increasing media literacy and critical thinking skills, individuals can be equipped to identify potentially deceptive content and take appropriate actions 아이돌 딥페이크. Educators and policymakers should integrate media literacy programs into educational curricula at all levels to empower citizens to navigate the complexities of the digital age.

Collaboration between industry, academia, and government is paramount in addressing the challenges posed by deepfake technology. Together, they can develop comprehensive regulations, standards, and guidelines that strike a balance between the responsible use of deepfakes and safeguarding the integrity of media. Close cooperation and knowledge sharing are vital to stay ahead of potential threats and to build a more secure and trustworthy media landscape.

In conclusion, while deepfake technology offers vast creative potential, it also gives rise to significant ethical, legal, and societal concerns. Detecting and preventing the malicious use of deepfakes, while preserving their positive applications, requires a comprehensive approach involving technology, legislation, education, and collaboration.

[generative-ai-kroop]

Unleashing Gen AI: A Revolution in the Audio-Visual Landscape

Artificial Intelligence (AI) has consistently pushed the boundaries of what is possible in various industries, but now, we stand at the brink of a transformative leap: Generative AI, or Gen AI. Gen AI promises to reshape the audio-visual space in profound ways, and its impact extends to a plethora of industries. In this blog, we will delve into the essence of Gen AI and explore how it can bring about a sea change in numerous sectors.

Decoding Generative AI (Gen AI)

Generative AI is the frontier of AI where machines are capable of creating content that is remarkably human-like. Harnessing neural networks, particularly Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), Gen AI can generate content that is not just contextually accurate but also creatively ingenious.

The Mechanics of Gen AI

Gen AI operates by dissecting and imitating patterns, styles, and structures from colossal datasets. These learned insights then fuel the creation of content, whether it be music, videos, images, or even deepfake simulations. The realm of audio-visual content is undergoing a monumental transformation courtesy of Gen AI.

Revolutionizing the Audio-Visual Realm

The influence of Generative AI in the audio-visual sphere is profound, impacting several dimensions of content creation and consumption:

1. Musical Masterpieces:

Gen AI algorithms have unlocked the potential to compose music that rivals the creations of human composers. They can effortlessly dabble in diverse musical genres, offering a treasure trove of opportunities for musicians, film score composers, and the gaming industry. Automated music composition opens the doors to boundless creative possibilities.

2. Cinematic Magic:

In the world of film production, Gen AI can conjure up realistic animations, special effects, and entirely synthetic characters. It simplifies video editing, making it more efficient and cost-effective. Content creators, filmmakers, and advertisers are poised to benefit significantly from these capabilities.

3. Artistic Expression:

Gen AI is the artist's secret tool, generating lifelike images and artworks. It can transform rudimentary sketches into professional-grade illustrations and graphics. Industries like fashion, advertising, and graphic design are harnessing this power to streamline their creative processes.

4. Immersive Reality:

Gen AI plays a pivotal role in crafting immersive experiences in virtual and augmented reality. It crafts realistic 3D models, environments, and textures, elevating the quality of VR and AR applications. This technological marvel has applications in gaming, architecture, education, and beyond.

Industries Set to Reap the Rewards

The versatile applications of Generative AI are a boon to numerous sectors:

1. Entertainment Industry:

Entertainment stands as a vanguard in adopting Gen AI. Film production, music composition, video game development, and theme park attractions are embracing Gen AI to elevate their offerings.

2. Marketing and Advertising:

Gen AI streamlines content creation for marketing campaigns. It generates ad copies, designs visual materials, and crafts personalized content, thereby saving time and delivering more engaging and relevant messages.

3. Healthcare and Medical Imaging:

In the realm of healthcare, Gen AI enhances medical imaging, aids in early disease detection, and generates 3D models for surgical planning and training.

4. Education:

Gen AI facilitates the creation of interactive learning materials, custom tutoring content, and immersive language learning experiences with its natural-sounding speech synthesis.

5. Design and Architecture:

Architects and designers benefit from Gen AI by generating detailed blueprints, 3D models, and interior design concepts based on precise user specifications.

The Future of Gen AI

The journey of Generative AI is far from over, and the future holds promise for even more groundbreaking innovations. However, it is imperative to navigate the ethical and societal implications thoughtfully. Concerns related to misuse, privacy, and authenticity should be addressed, and the responsible development and application of Gen AI must be prioritized.

In conclusion, Generative AI is on the cusp of redefining the audio-visual space, promising an abundance of creative and pragmatic solutions across diverse industries. Embracing and responsibly harnessing the power of Gen AI is the key to ushering these industries into a new era of ingenuity and innovation.

[xylophonetangerine]

“Made me think that if they are doing this for trivial crap, then what is being done to surveillance video or other facial recognition images by others with better tools,” one FBI official wrote in January 2018. William McKinsey, section chief of the information technology section at FBI, replied “I googled face swapping and learned a lot.” “Pls follow [redacted by FBI] closely. It could put us out of business,” he added. In another later email he wrote “This could require urgent action [on] our part if it is real.” [...] The ecosystem of deepfake-detection has evolved greatly since 2018. Intel, for instance, has been running ads for its own such capability on the Bloomberg Businessweek podcast recently. In those, Intel claims to be 96 percent accurate. Those claims, as are many in the deepfake detection industry, are difficult to verify.

7 July 2023

[gook54-blog]

As a tester of AI for military and other purposes

(Deepfake Detection & Generation

Use: Identifies manipulated content or, conversely, generates synthetic personas or decoy videos.

Agencies Concerned: FBI, CIA, GCHQ, Mossad.

Tools: Sensity AI, Deepware Scanner, internally developed neural nets.) I asked them to ID this and other crackpot similar pictures

Reply :

The image circulating online that appears to show JD Vance with the phrase "I KILLED THE POPE" tattooed across his knuckles is a digitally altered deepfake. There is no credible evidence that Vice President Vance has such a tattoo. This image is part of a broader wave of internet memes and satire that emerged after Pope Francis's death on Easter Monday, 2025, which occurred shortly after a meeting with Vance.

The meme gained traction through social media posts and satirical content, including a segment on "Saturday Night Live" where Vance was humorously depicted as the Grim Reaper. Despite the humorous intent, some individuals have mistaken these satirical images for real photographs.

Fact-checking organizations have confirmed that these images are not authentic and that the claims about Vance's involvement in the Pope's death are unfounded.

In summary, the knuckle tattoo image is a digitally manipulated creation intended for satire and should not be considered a genuine photograph of JD Vance.

Seems legit

[airnetmarketing]

Analyzing the Role of AI Agents in Modern Espionage Operations

The landscape of espionage has undergone a monumental transformation in recent years, marked by the advent of artificial intelligence (AI) agents. As global conflicts and security threats evolve, so too do the tactics employed by intelligence agencies to gather information and conduct covert operations. AI agents have emerged as valuable assets, capable of processing vast amounts of data, employing sophisticated algorithms, and enhancing decision-making processes. This article delves into the integration of AI agents into contemporary espionage tactics and evaluates the profound impact these technologies have had on intelligence collection strategies.

The Integration of AI Agents in Contemporary Espionage Tactics

The integration of AI agents into modern espionage is reshaping how intelligence is gathered and analyzed. Traditional methods, often reliant on human operatives and manual data processing, are being augmented by AI-driven tools that can analyze complex datasets at unprecedented speeds. For instance, AI algorithms can sift through millions of communications, social media interactions, and satellite images, identifying patterns and anomalies that would take human analysts weeks or months to uncover. This not only enhances the efficiency of data collection but also allows for real-time intelligence gathering, giving agencies a significant tactical advantage. AI agents also play a pivotal role in surveillance operations. With advancements in machine learning and computer vision, AI technologies can improve the accuracy of facial recognition systems and automate the monitoring of multiple feeds from surveillance cameras. This capability is particularly useful in urban environments where human operatives may struggle to maintain situational awareness. Additionally, AI can detect subtle behavioral cues that indicate suspicious activity, allowing intelligence agencies to respond swiftly to potential threats. The automation of these processes reduces the risk of human error and provides a more comprehensive overview of the operational landscape. Moreover, the integration of AI in espionage is not limited to data collection and surveillance; it extends to psychological operations and misinformation campaigns. AI agents can generate realistic fake content—be it text, audio, or video—that can be used to mislead adversaries or influence public opinion. By leveraging natural language processing and deepfake technology, agencies can create convincing narratives that can sway political discourse or create discord among enemy factions. This strategic use of AI for psychological operations highlights its multifaceted role in modern espionage, emphasizing the need for ethical considerations and regulatory frameworks to manage its deployment.

Evaluating the Impact of AI on Intelligence Collection Strategies

The impact of AI on intelligence collection strategies is profound, fundamentally altering how agencies approach data gathering and analysis. One of the most significant advantages is the ability to handle and interpret massive datasets, commonly referred to as "big data." AI algorithms excel at identifying correlations and trends within these datasets, enabling intelligence agencies to make informed predictions and decisions. The predictive analytics capabilities of AI can enhance threat assessment processes, allowing agencies to prioritize resources toward potential risks before they escalate. Furthermore, AI's ability to learn and adapt over time means that intelligence collection strategies can become increasingly sophisticated. Machine learning models can refine their algorithms based on new data and past outcomes, improving their accuracy and reliability. This adaptability allows intelligence agencies to remain agile in a rapidly changing security environment, responding effectively to new types of threats and evolving geopolitical dynamics. The shift from reactive to proactive intelligence collection signifies a major evolution in how agencies safeguard national security. However, the reliance on AI in intelligence collection also raises significant ethical and operational concerns. Issues related to data privacy, surveillance overreach, and algorithmic bias must be addressed to ensure the responsible use of AI in espionage. Furthermore, the potential for adversaries to exploit similar technologies necessitates an ongoing assessment of the effectiveness and security of AI systems. As intelligence agencies increasingly adopt AI-driven strategies, the balance between leveraging technology for national security and upholding civil liberties will remain a critical challenge for policymakers and practitioners alike. The role of AI agents in modern espionage operations is both transformative and complex. As intelligence agencies integrate AI into their tactics, they gain enhanced capabilities for data collection, analysis, and operational execution. However, this technological evolution also brings forth ethical dilemmas and operational challenges that must be navigated carefully. The future of espionage will undoubtedly continue to be shaped by advancements in AI, requiring a thoughtful approach to ensure that these powerful tools are used responsibly in the pursuit of national security. Balancing innovation with ethical considerations will be essential for harnessing the full potential of AI in the intelligence domain. Read the full article