Three battles that will form her future

Behind the scenes of two main topics of the World Economic Forum –Trump and Shi—Fa on a snowy background of Davos, a growing wave of claims associated with AI, continues to unfold. Why should we pay attention to these lawsuits? History offers a clear precedent.

In the early era of the Internet, an explosive climb of Napster, free and open music service. But Copyright Lawsuits from Artists and the Music Industry Led To Its Shutdown in 2001. This Accelerated the Shift Town Paid and Centralized Digital Distribution, With Itunes Laic Urchases, Followed by Subscripti-Based Streaming Services Like Spotify in mid-2000s.

Such a struggle for power is now unfolding in AI. This article explores three key categories of claims related to AI, revealing an inevitable trend: Growth of decentralized AI (Deai) as a solution to these legal and ethical problems.

Three Main Legal Fronts in AI War in AI

1. Intellectual property position (IP): Who owns AI content, studies?
2. Case of Privacy and Data Protection: Who controls personal and confidential data in the AI?
3. Ethical and responsibility lawsuits: who is responsible when she is harmful?

These legal battles will significantly shape the future AI events. IP disputes can force AI to license data by increasing data collection. The lawsuit will contribute to the rigid management of data, which makes compliance with a key challenge, facilitating the privacy of AI models. Cases of liability will require clearer accountability, potentially slowing down high -risk sectors and will lead to stringent AI rules.

IP Landings: To whom do AI training data have?

AI models rely on huge data sets – books, articles, images and music – often scraped without permission. Copyright owners claim that AI companies make a profit from their work without compensation, aligning lawsuits about whether AI is a fair use or copyright.

In January 2023, Getty Images filed a lawsuit against AI stability, arguing that the company illegally jumped millions of image from the Ghetty platform to prepare its AI model, stable diffusion without receiving proper licensing. Getty states that this unauthorized use violates its intellectual property rights.

Openai and Meta have also filed a claim and accused of using pirate books to prepare their AI models, allegedly violating the copyright of the authors.

If the courts are in favor of content creators, companies will need to receive proper data licensing that they use to teach their models. This will significantly increase operating costs, as firms would have to agree and pay for the rights to human rights. In addition, the need for licensing can limit access to high -quality training data, especially for smaller AI startups that may not have financial resources for competition with larger technological firms. As a result, innovations in the AI ​​space can slow down, and the competitive landscape may change in favor of well -funded corporations that can afford these licensed fees.

Case of Privacy and Data Protection: Who controls personal data in the AI?

AI Systems processes a huge amount of personal data – cancellation, search history, biometric information and even medical records. Regulators and consumers are repelled, demanding Stronger controls About how this data is collected and used.

Clearview AI, a US face recognition firm, was fined by regulators in the US and the EU for scraping images without consent. In 2024, the Dutch Data Protection Department fined the company for 30.5 million euros, while the US state was objected to the settlement of privacy due to lack of compensation. Italy fined Openai for 15 million euros in 2024 for GDPR violations, citing unauthorized data processing and lack of transparency. The regulator also marked insufficient age check. The Amazon was fined $ 25 million in FTC in 2023 for storage of Alexa’s children’s records for an indefinite period. Google also faced lawsuits for alleged users without consent.

Stronger privacy laws will require AI to obtain clear consent of users before collecting or processing data. This requires transparent policy, stronger security measures and user control over data use. When increasing privacy and trust, it can also increase the cost of compliance and slowed down the development of AI.

Ethical and responsibility lawsuits: who is responsible when she is harmful?

Since AI systems are increasingly affecting the decisions on hiring, medical diagnosis and moderation of content, legal questions arise: who answers when AI makes a harmful mistake? Is it possible to file a lawsuit for misinformation, bias or discrimination?

In February 2024, Gemini AI Google faced criticism of creating historically inaccurate images, such as images of founding parents and Nazi soldiers as color people. This has led to the accusations that AIs have been overly “woke up” and incorrectly presenting historical facts. In response, Google has suspended the Gemini image generation function to solve these problems and increase accuracy.

In April 2023, the Australian mayor looked at Openai after Chatgpt mistakenly argued that he was involved in a scandal with a bribery life, emphasizing anxiety about misinformation and AI. This case emphasized the potential legal challenges that AI developers may face when their models create false or harmful content.

In 2018, Amazon stopped AI set tool after finding it discriminated against his applicants. The system that has been submitted for a decade has preferred man candidates by punishing resumes who included the word “women” or referred to women’s colleges. This incident emphasized the challenges of fairness in the processes of AI hiring.

If stronger AI liability laws are adopted, it will push the company to improve the detection of bias and transparency for the fair and more accountable AI systems. However, poor regulation can increase the risks of misinformation and discrimination controlled by AI, as companies can prioritize rapid development over ethical guarantees. Striving the balance between supervision and innovation will be a delicate call.

How deai provides a reasonable and practical solution

Deai offers a viable way forward against the background of constant legal battles. Based on blockchain and using decentralized networks, DEAI ensures the voluntary submission of global data from participants and participants, guaranteeing that Data collection And the treatment remains transparent and accountable. On blockchain, all the data collected, as well as its processing and use, are invariably recorded. This approach not only minimizes intellectual property conflicts, but also increases the confidentiality of data, allowing users to maintain control over their information, reducing the risk of unauthorized access or abuse.

Unlike centralized AI models, which are often built on limited and potentially biased data sets due to cost limits and resources, DEAI sources from a globally distributed network that provide greater variety. Using the inherent decentralized nature of Blockchain, DEAI works through community -oriented management, where AI models are audited and improved by a decentralized network and not controlled by one corporation.

As the legal challenges around the AI ​​continue to unfold, DEAI is one of the most promising approaches to the construction of open, ethical and AI future.