#data protection and artificial intelligence

[merchantservices444]

Safeguarding Success: The Crucial Role of Data Protection in E-Commerce Business

[allthebrazilianpolitics]

Meta ordered to stop training its AI on Brazilian personal data

Following similar pushback in the EU, Meta now faces daily fines if it uses Brazilian Facebook and Instagram data for AI training.

Brazil’s data protection authority (ANPD) has banned Meta from training its artificial intelligence models on Brazilian personal data, citing the “risks of serious damage and difficulty to users.” The decision follows an update to Meta’s privacy policy in May in which the social media giant granted itself permission to use public Facebook, Messenger, and Instagram data from Brazil — including posts, images, and captions — for AI training.

The decision follows a report published by Human Rights Watch last month which found that LAION-5B — one of the largest image-caption datasets used to train AI models — contains personal, identifiable photos of Brazilian children, placing them at risk of deepfakes and other exploitation.

As reported by The Associated Press, ANPD told the country’s official gazette that the policy carries “imminent risk of serious and irreparable or difficult-to-repair damage to the fundamental rights” of Brazilian users. The region is one of Meta’s largest markets, with 102 million Brazilian user accounts found on Facebook alone according to the ANPD. The notification published by the agency on Tuesday gives Meta five working days to comply with the order, or risk facing daily fines of 50,000 reais (around $8,808).

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[melyzard]

Time for a new edition of my ongoing vendetta against Google fuckery!

Hey friends, did you know that Google is now using Google docs to train it's AI, whether you like it or not? (link goes to: zdnet.com, July 5, 2023). Oh and on Monday, Google updated it's privacy policy to say that it can train it's two AI (Bard and Cloud AI) on any data it scrapes from it's users, period. (link goes to: The Verge, 5 July 2023). Here is Digital Trends also mentioning this new policy change (link goes to: Digital Trends, 5 July 2023). There are a lot more, these are just the most succinct articles that might explain what's happening.

FURTHER REASONS GOOGLE AND GOOGLE CHROME SUCK TODAY:

Stop using Google Analytics, warns Sweden’s privacy watchdog, as it issues over $1M in fines (link goes to: TechCrunch, 3 July 2023) [TLDR: google got caught exporting european users' data to the US to be 'processed' by 'US government surveillance,' which is HELLA ILLEGAL. I'm not going into the Five Eyes, Fourteen Eyes, etc agreements, but you should read up on those to understand why the 'US government surveillance' people might ask Google to do this for countries that are not apart of the various Eyes agreements - and before anyone jumps in with "the US sucks!" YES but they are 100% not the only government buying foreign citizens' data, this is just the one the Swedes caught. Today.]

PwC Australia ties Google to tax leak scandal (link goes to: Reuters, 5 July 2023). [TLDR: a Russian accounting firm slipped Google "confidential information about the start date of a new tax law leaked from Australian government tax briefings." Gosh, why would Google want to spy on governments about tax laws? Can't think of any reason they would want to be able to clean house/change policy/update their user agreement to get around new restrictions before those restrictions or fines hit. Can you?

SO - here is a very detailed list of browsers, updated on 28 June, 2023 on slant.com, that are NOT based on Google Chrome (note: any browser that says 'Chromium-based' is just Google wearing a party mask. It means that Google AND that other party has access to all your data). This is an excellent list that shows pros and cons for each browser, including who the creator is and what kinds of policies they have (for example, one con for Pale Moon is that the creator doesn't like and thinks all websites should be hostile to Tor).

[frank-olivier]

The Future of Justice: Navigating the Intersection of AI, Judges, and Human Oversight

One of the main benefits of AI in the justice system is its ability to analyze vast amounts of data and identify patterns that human judges may not notice. For example, the use of AI in the U.S. justice system has led to a significant reduction in the number of misjudgments, as AI-powered tools were able to identify potential biases in the data and make more accurate recommendations.

However, the use of AI in the justice system also raises significant concerns about the role of human judges and the need for oversight. As AI takes on an increasingly important role in decision-making, judges must find the balance between trusting AI and exercising their own judgement. This requires a deep understanding of the technology and its limitations, as well as the ability to critically evaluate the recommendations provided by AI.

The European Union's approach to AI in justice provides a valuable framework for other countries to follow. The EU's framework emphasizes the need for human oversight and accountability and recognizes that AI is a tool that should support judges, not replace them. This approach is reflected in the EU's General Data Protection Regulation (GDPR), which requires AI systems to be transparent, explainable and accountable.

The use of AI in the justice system also comes with its pitfalls. One of the biggest concerns is the possibility of bias in AI-generated recommendations. When AI is trained with skewed data, it can perpetuate and even reinforce existing biases, leading to unfair outcomes. For example, a study by the American Civil Liberties Union found that AI-powered facial recognition systems are more likely to misidentify people of color than white people.

To address these concerns, it is essential to develop and implement robust oversight mechanisms to ensure that AI systems are transparent, explainable and accountable. This includes conducting regular audits and testing of AI systems and providing clear guidelines and regulations for the use of AI in the justice system.

In addition to oversight mechanisms, it is also important to develop and implement education and training programs for judges and other justice professionals. This will enable them to understand the capabilities and limitations of AI, as well as the potential risks and challenges associated with its use. By providing judges with the necessary skills and knowledge, we can ensure that AI is used in a way that supports judges and enhances the fairness and accountability of the justice system.

Human Centric AI - Ethics, Regulation. and Safety (Vilnius University Faculty of Law, October 2024)

Friday, November 1, 2024

[mister-forest]

Chiques fíjense de activar la opción de no compartir datos en el apartado "Visibilidad" en Ajustes ‼️‼️

[jcmarchi]

Deepfake misuse & deepfake detection (before it’s too late) - CyberTalk

New Post has been published on https://thedigitalinsider.com/deepfake-misuse-deepfake-detection-before-its-too-late-cybertalk/

Deepfake misuse & deepfake detection (before it’s too late) - CyberTalk

Micki Boland is a global cyber security warrior and evangelist with Check Point’s Office of the CTO. Micki has over 20 years in ICT, cyber security, emerging technology, and innovation. Micki’s focus is helping customers, system integrators, and service providers reduce risk through the adoption of emerging cyber security technologies. Micki is an ISC2 CISSP and holds a Master of Science in Technology Commercialization from the University of Texas at Austin, and an MBA with a global security concentration from East Carolina University.

In this dynamic and insightful interview, Check Point expert Micki Boland discusses how deepfakes are evolving, why that matters for organizations, and how organizations can take action to protect themselves. Discover on-point analyses that could reshape your decisions, improving cyber security and business outcomes. Don’t miss this.

Can you explain how deepfake technology works? 

Deepfakes involve simulated video, audio, and images to be delivered as content via online news, mobile applications, and through social media platforms. Deepfake videos are created with Generative Adversarial Networks (GAN), a type of Artificial Neural Network that uses Deep Learning to create synthetic content.

GANs sound cool, but technical. Could you break down how they operate?

GAN are a class of machine learning systems that have two neural network models; a generator and discriminator which game each other. Training data in the form of video, still images, and audio is fed to the generator, which then seeks to recreate it. The discriminator then tries to discern the training data from the recreated data produced by the generator.

The two artificial intelligence engines repeatedly game each other, getting iteratively better. The result is convincing, high quality synthetic video, images, or audio. A good example of GAN at work is NVIDIA GAN. Navigate to the website https://thispersondoesnotexist.com/ and you will see a composite image of a human face that was created by the NVIDIA GAN using faces on the internet. Refreshing the internet browser yields a new synthetic image of a human that does not exist.

What are some notable examples of deepfake tech’s misuse?

Most people are not even aware of deepfake technologies, although these have now been infamously utilized to conduct major financial fraud. Politicians have also used the technology against their political adversaries. Early in the war between Russia and Ukraine, Russia created and disseminated a deepfake video of Ukrainian President Volodymyr Zelenskyy advising Ukrainian soldiers to “lay down their arms” and surrender to Russia.

How was the crisis involving the Zelenskyy deepfake video managed?

The deepfake quality was poor and it was immediately identified as a deepfake video attributable to Russia. However, the technology is becoming so convincing and so real that soon it will be impossible for the regular human being to discern GenAI at work. And detection technologies, while have a tremendous amount of funding and support by big technology corporations, are lagging way behind.

What are some lesser-known uses of deepfake technology and what risks do they pose to organizations, if any?

Hollywood is using deepfake technologies in motion picture creation to recreate actor personas. One such example is Bruce Willis, who sold his persona to be used in movies without his acting due to his debilitating health issues. Voicefake technology (another type of deepfake) enabled an autistic college valedictorian to address her class at her graduation.

Yet, deepfakes pose a significant threat. Deepfakes are used to lure people to “click bait” for launching malware (bots, ransomware, malware), and to conduct financial fraud through CEO and CFO impersonation. More recently, deepfakes have been used by nation-state adversaries to infiltrate organizations via impersonation or fake jobs interviews over Zoom.

How are law enforcement agencies addressing the challenges posed by deepfake technology?

Europol has really been a leader in identifying GenAI and deepfake as a major issue. Europol supports the global law enforcement community in the Europol Innovation Lab, which aims to develop innovative solutions for EU Member States’ operational work. Already in Europe, there are laws against deepfake usage for non-consensual pornography and cyber criminal gangs’ use of deepfakes in financial fraud.

What should organizations consider when adopting Generative AI technologies, as these technologies have such incredible power and potential?

Every organization is seeking to adopt GenAI to help improve customer satisfaction, deliver new and innovative services, reduce administrative overhead and costs, scale rapidly, do more with less and do it more efficiently. In consideration of adopting GenAI, organizations should first understand the risks, rewards, and tradeoffs associated with adopting this technology. Additionally, organizations must be concerned with privacy and data protection, as well as potential copyright challenges.

What role do frameworks and guidelines, such as those from NIST and OWASP, play in the responsible adoption of AI technologies?

On January 26th, 2023, NIST released its forty-two page Artificial Intelligence Risk Management Framework (AI RMF 1.0) and AI Risk Management Playbook (NIST 2023). For any organization, this is a good place to start.

The primary goal of the NIST AI Risk Management Framework is to help organizations create AI-focused risk management programs, leading to the responsible development and adoption of AI platforms and systems.

The NIST AI Risk Management Framework will help any organization align organizational goals for and use cases for AI. Most importantly, this risk management framework is human centered. It includes social responsibility information, sustainability information and helps organizations closely focus on the potential or unintended consequences and impact of AI use.

Another immense help for organizations that wish to further understand risk associated with GenAI Large Language Model adoption is the OWASP Top 10 LLM Risks list. OWASP released version 1.1 on October 16th, 2023. Through this list, organizations can better understand risks such as inject and data poisoning. These risks are especially critical to know about when bringing an LLM in house.

As organizations adopt GenAI, they need a solid framework through which to assess, monitor, and identify GenAI-centric attacks. MITRE has recently introduced ATLAS, a robust framework developed specifically for artificial intelligence and aligned to the MITRE ATT&CK framework.

For more of Check Point expert Micki Boland’s insights into deepfakes, please see CyberTalk.org’s past coverage. Lastly, to receive cyber security thought leadership articles, groundbreaking research and emerging threat analyses each week, subscribe to the CyberTalk.org newsletter.

[open-era]

Top Social Media Trends in 2023: What to Watch For

Stay ahead of the game with top social media trends in 2023! From user-generated content to AI and privacy, unlock the keys to success in the ever-evolving digital landscape. #SocialMediaTrends #2023Trends

The social media landscape is a dynamic and ever-changing space, and as we enter 2023, it is crucial for brands to stay ahead of the curve. With new advancements and shifts in user behaviour, understanding the latest trends will empower brands to leverage social media effectively, connect with their target audiences, and achieve their business goals. In this article, we explore the top social…

[midnightwind]

latest generative algo scrape has me sitting here like "my work isn't good enough to warrant going all out to prevent anyone from seeing it" and "quality of my work doesn't matter, I still deserve to not have it stolen and should do whatever I can to prevent that"

hope every tech bro touting this shit as AI while breaking every law possible in the process has something horrifying happen to them every day they continue to shill it either way!!

[utsav-c]

New Website Launched for Digital Personal Data Protection Act 2023 & Draft DPDP Rules 2025

New Website Launched for Digital Personal Data Protection Act 2023 & Draft DPDP Rules 2025

[alyfoxxxen]

Elon Musk says xAI acquired X | TechCrunch

[sweetbread282]

I am 100 percent sure that AI is storing info about me and I cannot order it to forget. OH MAN DO I FEEL UNCOMFORTABLE RIGHT NOW

Honestly! Who says yes to my opinion who says no? Poll here, people

BTW coming from a person who uses AI chatbots almost every day, ugh the little facts that the AI remembers without me being able to delete it is... concernninggg

[coookie-banner]

[allthebrazilianpolitics]

Google Launches AI Anti-Theft Feature for Android Phones in Brazil

Alphabet’s Google will launch a new AI-powered anti-theft feature for Android phones in Brazil, the first country to test this technology, aiming to reduce phone theft rates in a country where nearly one million phones were stolen last year.

Google, the tech giant under Alphabet Inc., made a groundbreaking announcement. Brazil, a country plagued by high phone theft rates, will be the first to test a new anti-theft feature for Android phones using artificial intelligence (AI). This innovative technology, a significant step in the fight against phone theft, automatically locks the device’s screen when a phone has been stolen, thereby enhancing security for users.

The initiative is part of Google’s broader strategy to leverage AI to address real-world problems. Starting in July, the anti-theft feature will initially be available to Brazilian users of Android phones running version 10 or higher. According to the company, this phased rollout will eventually extend to other countries over the year.

The new anti-theft feature, powered by AI, operates through three types of locks. The first lock utilizes AI to identify movements typically associated with theft, such as sudden, rapid movements that suggest snatching or running. Once these movements are detected, the feature automatically locks the screen, rendering the phone unusable to the thief. The AI model has been trained to recognize specific patterns that indicate a theft, enabling it to provide an immediate response to protect the user’s data.

Continue reading.

[diagnozabam]

Google îmbunătățește protecția Chrome cu inteligență artificială

Google a anunțat îmbunătățiri semnificative pentru funcționalitatea Enhanced Protection din browser-ul Chrome, aducând un nivel superior de securitate utilizatorilor. Noile actualizări promit protecție în timp real împotriva site-urilor periculoase, extensiilor malițioase și descărcărilor infectate, utilizând tehnologii avansate bazate pe inteligență artificială (AI) și procesare în…

[thetech-dictionary]

Use this guide to the newest trends and best practices to safeguard your company from new cyberthreats in 2025.

[dimitrisxenos]

Data protection obligations in recruitment involving artificial intelligence.

In their recent report, ICO have set out findings and recommendations.