AI and Digital Rights

Microsoft AI chief Mustafa Suleyman recently sparked controversy by asserting that anything published on the open web becomes "freeware" for AI use. This bold statement challenges established norms and has significant implications for copyright law and AI ethics. In a recent interview, Microsoft AI executive Mustafa Suleyman made a surprising claim about the status of web content, suggesting it is freely available for AI training. This perspective is particularly controversial given the ongoing legal battles faced by Microsoft and OpenAI, which have been accused of using copyrighted material without permission to train their AI models. Understanding the nuances of this issue is critical as it touches on complex copyright laws, fair use interpretations, and the ethical use of online content. ⚖️ Copyright Laws: In the US, any created work is automatically protected by copyright, and publishing it on the web does not waive these rights. 🤖 Fair Use Misconceptions: Fair use is determined by courts based on specific criteria, including the purpose of use, the nature of the work, the amount used, and the effect on the market, not by a "social contract." 📄 Robots.txt: Robots.txt can specify which bots are allowed to scrape content, but it is not legally binding, and compliance is voluntary. 📉 Legal Battles: Microsoft and OpenAI face multiple lawsuits for allegedly using copyrighted content without permission, highlighting the ongoing legal disputes in AI training practices. 🌐 Ethical Considerations: The ethical use of online content by AI companies remains a hotly debated issue, with significant implications for content creators and AI developers. Suleyman's comments underscore the urgent need for clear guidelines and robust legal frameworks to govern the use of online content in AI development. These measures are crucial in ensuring that the rights of content creators are respected and that AI companies operate within the bounds of the law. #AI #Copyright #FairUse #MicrosoftAI #OpenAI #WebContent #DataEthics #LegalIssues #AITraining #TechNews

At first glance, the Studio Ghibli style AI-generated art seems harmless. You upload a photo, the model processes it, and you get a stunning, anime-style transformation. But there's something far more complex beneath the surface—a quiet trade-off of identity, privacy, and control. Today, we casually give away fragments of ourselves: - Our faces to AI art apps - Our health data to wearables - Even our genetic blueprints to direct-to-consumer biotech services All in exchange for a few minutes of novelty or convenience. And while frameworks like India’s Digital Personal Data Protection Act (DPDPA) attempt to address this through “consent,” we must ask: What does consent even mean in an era of opaque AI systems designed to extract value far beyond that initial interaction? Because it’s not about the one image you uploaded. It’s about the aggregated behavioral and biometric insights these platforms derive from millions of us. That data trains models that can infer, profile, and yes—discriminate. Not just individually, but at community and population levels. This is no longer just a personal privacy issue. This is about digital sovereignty. Are we unintentionally allowing global AI systems to construct intimate, predictive bio-digital profiles of Indian citizens—only for that value to flow outward? And this isn’t just India’s challenge. Globally, these concerns resonate, creating complex challenges for cross-border data flows and requiring companies to navigate a patchwork of regulations like GDPR. The real risk isn’t that your selfie becomes a meme. It’s that your data contributes to shaping algorithms that may eventually determine what insurance you're offered, which job you’re filtered out of, or how your community is policed or advertised to, all without your knowledge or say. We need to go beyond checkbox consent. We need: 🔐 Privacy-by-design in every product 🛡️ Stronger enforcement of rights across borders 🧠 Collective awareness about how predictive analytics can influence entire societies Let’s be clear that innovation is critical. But if we don’t anchor it within ethics, rights, and sovereignty, we risk building tools that define and disadvantage us, rather than empower us. #Cybersecurity #PrivacyMatters #AIethics #DPDPA #DigitalSovereignty #DataProtection #AIresponsibility #IndiaTech

A painter’s masterpiece becomes fodder for an AI model, scraped, dissected, and absorbed without the artist’s consent. The UK government is poised to legalize what amounts to wholesale appropriation of creative works. Their proposed copyright legislation explicitly permits AI companies to consume copyrighted material without permission or compensation, a fundamentally different approach than previous digital transformations. The legislation allows AI companies to train models on copyrighted material without permission, forcing creators to opt out rather than opt in. This has triggered opposition from artists, authors, musicians, and creative professionals who reject having their work harvested as "training data" without compensation. When AI ingests thousands of books, songs, or artworks, it learns to mimic styles and generate content that could devalue or replace human-made work. If AI can produce a symphony like Mozart, a novel like Rushdie, or artwork like Banksy, all without attribution or payment, what happens to the economic system sustaining creative professionals? The UK government argues these changes are necessary to secure Britain’s place as a global AI hub, warning that without them, companies might relocate to jurisdictions with looser regulations. Ministers frame it as a pragmatic economic choice. In response to pressure, the government has promised an economic impact assessment and required AI companies to publish transparency reports. Yet critics remain skeptical, seeing these steps as insufficient to address the power imbalance between individual creators and tech giants. This debate is not confined to Britain. In India, where the creative economy and tech sector are both booming, the stakes are just as high. The Copyright Act of 1957, even with its 2012 digital amendments, needs urgent reconsideration to meet AI’s challenges. Without smart intervention, India risks either slowing tech growth or weakening the cultural industries that define its global influence. At this crossroads, the central question is not whether AI should learn from human creativity, but how to ensure the value it generates flows back to sustain the creative work it depends on. In chasing technological progress, are we eroding the very foundations of human creativity? #ai

I'm increasingly convinced that we need to treat "AI privacy" as a distinct field within privacy, separate from but closely related to "data privacy". Just as the digital age required the evolution of data protection laws, AI introduces new risks that challenge existing frameworks, forcing us to rethink how personal data is ingested and embedded into AI systems. Key issues include: 🔹 Mass-scale ingestion – AI models are often trained on huge datasets scraped from online sources, including publicly available and proprietary information, without individuals' consent. 🔹 Personal data embedding – Unlike traditional databases, AI models compress, encode, and entrench personal data within their training, blurring the lines between the data and the model. 🔹 Data exfiltration & exposure – AI models can inadvertently retain and expose sensitive personal data through overfitting, prompt injection attacks, or adversarial exploits. 🔹 Superinference – AI uncovers hidden patterns and makes powerful predictions about our preferences, behaviours, emotions, and opinions, often revealing insights that we ourselves may not even be aware of. 🔹 AI impersonation – Deepfake and generative AI technologies enable identity fraud, social engineering attacks, and unauthorized use of biometric data. 🔹 Autonomy & control – AI may be used to make or influence critical decisions in domains such as hiring, lending, and healthcare, raising fundamental concerns about autonomy and contestability. 🔹 Bias & fairness – AI can amplify biases present in training data, leading to discriminatory outcomes in areas such as employment, financial services, and law enforcement. To date, privacy discussions have focused on data - how it's collected, used, and stored. But AI challenges this paradigm. Data is no longer static. It is abstracted, transformed, and embedded into models in ways that challenge conventional privacy protections. If "AI privacy" is about more than just the data, should privacy rights extend beyond inputs and outputs to the models themselves? If a model learns from us, should we have rights over it? #AI #AIPrivacy #Dataprivacy #Dataprotection #AIrights #Digitalrights

Artificial intelligence (AI) and human rights: Using AI as a weapon of repression and its impact on human rights by Akin Unver (European Parliament) This in-depth analysis (IDA) explores the most prominent actors, cases and techniques of algorithmic authoritarianism together with the legal, regulatory and diplomatic framework related to AI-based biases as well as deliberate misuses. With the world leaning heavily towards digital transformation, AI’s use in policy, economic and social decision-making has introduced alarming trends in repressive and authoritarian agendas. Such misuse grows ever more relevant to the European Parliament, resonating with its commitment to safeguarding human rights in the context of digital transformation. By shedding light on global patterns and rapidly developing technologies of algorithmic authoritarianism, this IDA aims to produce a wider understanding of the complex policy, regulatory and diplomatic challenges at the intersection of technology, democracy and human rights. Insights into AI’s role in bolstering authoritarian tactics offer a foundation for Parliament’s advocacy and policy interventions, underscoring the urgency for a robust international framework to regulate the use of AI, whilst ensuring that technological progress does not weaken fundamental freedoms. Detailed case studies and policy recommendations serve as a strategic resource for Parliament’s initiatives: they highlight the need for vigilance and proactive measures by combining partnerships (technical assistance), industrial thriving (AI Act), influence (regulatory convergence) and strength (sanctions, export controls) to develop strategic policy approaches for countering algorithmic control encroachments. #AI #humanrights #EU

The line between data ownership and exploitation is blurring in a rapidly evolving AI landscape. As generative AI systems hunger for more data to fuel their outputs, content creators are at the epicenter of a legal and economic storm. The recent report from the U.S. Copyright Office highlighted this conflict, challenging the notion that vast data ingestion for AI training can be casually framed as fair use. Yet, just as the report outlined the boundaries of permissible use, its impact was swiftly undercut by the abrupt dismissal of two key figures advocating for enforceable data ownership. For data creators, the stakes have never been higher. Will their work remain protected assets, or will it be reframed as raw material for AI systems with no enforceable rights or compensation? The regulatory landscape is rapidly fragmenting, with the U.S. moving toward broader interpretations of fair use while the UK and EU entrench data provenance as an enforceable economic right. This article examines the strategic maneuvers by AI firms to recast data as a public good, the growing pushback from international frameworks, and the profound implications for data sovereignty in a world where AI-generated content could eclipse human authorship. Data creators now face a stark choice: enforce their rights through embedded controls or risk being erased from the digital economy. #DataSovereignty #AIRegulation #DataProvenance #CopyrightLaw #GenerativeAI #DigitalEconomy

Data Ownership in the Age of AI: Empowerment Over Control By Todd M. Price, MBA, Ph.D.(c) President, Global Counter-Terrorism Institute (GCTI) https://lnkd.in/gDJjaNh ⸻ AI should serve humanity—not shape it behind closed algorithms. We are entering a decisive era where data ownership equals power, and each of us holds the ability to reclaim how artificial intelligence interacts with our identity, privacy, and future. Your clicks, conversations, and content? That’s your intellectual currency. It’s time to stop surrendering our data blindly to platforms that profit from opacity. Instead, we must demand transparency, ownership, and ethical AI design—beginning with how we control our digital presence. Here are proactive strategies to take ownership: • Minimize the data you share. Every unnecessary field filled is potential fuel for AI training. • Encrypt your communication. Use secure tools like ProtonMail, Tutanota, and Signal. • Challenge how your data is used to train AI. Opt out where platforms allow it. • Understand your rights. Define boundaries with contracts, NDAs, and privacy terms. • Educate to liberate. Take control through cyber literacy and security training. As I often say: “You own your narrative, your voice, and your data. Let AI amplify your purpose—not rewrite your identity.” Let’s reshape how AI evolves—by placing human dignity, privacy, and purpose at the core of innovation. ⸻ Sources: ProtonMail | Mozilla Foundation | OpenAI | Google | Signal | Global Counter-Terrorism Institute (GCTI) ⸻ #Hashtags #ArtificialIntelligence #CyberSecurity #DataPrivacy #EthicalAI #Leadership #AIEthics #DigitalRights #CyberResilience #TechForGood #DataSovereignty #FutureOfAI #HumanCenteredAI #Innovation #DigitalTrust #CyberProtection

🚨 Fascinating AI paper alert: "Consent and Compensation: Resolving Generative AI’s Copyright Crisis" by Frank Pasquale & Haochen Sun is a must-read for everyone interested in AI, copyright, and artists' rights. Quotes: "The opacity and scale of AI systems is disrupting the knowledge ecosystem by significantly eroding authors’ proprietary control of their works, well beyond extant digital practices that have already undermined many authors’ well-being. Whereas prior scraping at scale tended to be focused on the non-expressive aspects of works (such as facts), AI is focused by many prompts on their expressive dimensions. Search engines have historically provided links which lead users to works themselves. In contrast, AI tends to provide substitutes for such works, while failing to provide citations to the works in the dataset most similar to the texts, images, and videos it presents as a computed synthesis." (pages 8-9) - "Under the proposed mechanism, copyright owners can first request AI providers to take actions to effectively prevent their systems from generating outputs that appear identical or substantially similar to relevant copyrighted works. A copyright owner would be entitled to send a notice to an AI provider when he or she identifies that an output generated by the provider’s AI system contains either a verbatim or substantially similar copy of his or her work, or a derivative work. In the notice, the copyright owner would be obliged to document the unauthorized reproduction of the work and his or her copyright ownership, along with a digital copy or an online link to the work." (page 21) - "Given the complexity of the AI supply chain, particularly with respect to generative AI, it is not feasible to impose a per-device cost on AI providers. However, other triggers for payment are possible. Levies on the use of particular datasets may be imposed, or on model training, or on some aggregate number of responses provided to users, or on paid subscriptions. Alternatively, the level of the levy could be benchmarked with respect to some percentage of AI providers’ expenditures or revenues" (page 39) ➡ Link to the paper below. #AI #copyright #consent #AIregulation #AIpolicy #AItraining

The U.S. Copyright Office this month released Part 1 of its report on the legal and policy issues related to copyright and artificial intelligence, focusing on digital replicas. For those who don't know, digital replicas are video, image, or audio recordings digitally created or manipulated to realistically but falsely depict an individual. An example includes the April 2023 song "Heart on My Sleeve," featuring AI-generated voices of Drake and The Weeknd. Here is a topline breakdown of what the Copyright Office has shared: 1️⃣ Existing Legal Frameworks and the Need for Federal Legislation: Current state and federal laws are inadequate in addressing digital replicas, revealing significant gaps and inconsistencies. Privacy and publicity rights are insufficient to tackle AI-generated content. Comprehensive federal legislation is urgently needed to protect individuals from substantial harm. 2️⃣ Scope and Protection of New Law: Proposed legislation should target digital replicas indistinguishable from authentic depictions, offering more precise protection than existing 'name, image, and likeness' laws. This law should apply to all individuals, not just celebrities, and extend at least for a lifetime with possible postmortem extensions. 3️⃣ Infringing Acts and Secondary Liability: Liability should focus on the distribution or availability of unauthorized digital replicas, covering both commercial and non-commercial uses. Traditional tort principles of secondary liability should apply, with a safe harbor mechanism for online service providers to remove infringing content upon notice. This approach balances accountability and practicality for intermediaries. 4️⃣ Licensing, Assignment, and Free Speech Concerns: Individuals should have the right to license their digital replica rights but not permanently assign them to others. Additional safeguards are needed to protect minors from exploitation. The legislation should address free speech concerns by balancing protection of individual rights with the need to avoid overly broad restrictions on expression. 5️⃣ Effective Remedies: The report calls for strong legal remedies, including court orders to stop infringement (injunctive relief) and monetary compensation. It emphasizes the importance of statutory damages and covering legal fees to make the law accessible to everyone. In severe cases, criminal penalties are suggested to act as a strong deterrent against violations, ensuring the law's effectiveness and fairness. Check out the full report below ⤵

The work we've done under the editorial guidance and supervision of Nikolay Dmitrik on regulating digital services has been finally signed into law by the President of Kyrgyzstan. The new Digital Code (Codified Digital Regulation) incorporates and updates the existing law and introduces new rules for trusted digital infrastructure, products and services, including artificial intelligence. I had the honour of drafting the chapter on regulating artificial intelligence. The chapter is inspired by the EU AI Act principles, but introduces a set of rules fit for the market of the Kyrgyz Republic: some rules for high-risk AI systems to safeguard for human rights and public interest, transparency of interactions with AI and deepfakes, and a general obligation to reduce risk for any class of systems, no limitations otherwise. https://lnkd.in/gPsaQ8UY