Szabó László István író, költő, az informatika tudományok tanára
Közművelődés, kultúra, oktatás, könyvtár, pedagógia, műszaki informatika, számítástechnika
2026. augusztus 5., szerda
Pemmikán házilag
Lenzangerbach patak
2026. augusztus 4., kedd
The problem of ethical and global regulation of artificial intelligence
The rapid development and widespread adoption of artificial intelligence (AI) raises a number of ethical and legal challenges. This paper aims to provide a comprehensive overview of these challenges, with a particular focus on data protection, privacy, transparency and regulation. I analyze the ethical aspects of AI applications, the “black box” problem and algorithmic bias. I present the current state and future directions of legal regulation, as well as the concept of “ethical AI” and the importance of international cooperation. In my paper, I highlight that addressing these challenges is crucial to protecting individual rights and ensuring responsible technological development. The ethical and global regulatory issues of artificial intelligence (AI) are grouped around discrimination, lack of transparency and the definition of responsibility. The most important challenges are algorithmic bias, the black box problem and the lack of an international legal framework. Main ethical challenges Algorithmic bias: Decisions based on distorted data can adversely affect certain social groups. Lack of transparency: Due to the “black box” operation, the logic of decisions is often incomprehensible and untraceable. Data protection and privacy: The collection of huge amounts of personal data threatens the rights of individuals. Global regulatory issues Establishing responsibility: It is not clear whether the developer, the operator or the AI itself is responsible in the event of an error. International uniformity: Countries regulate the area at different speeds and along different principles, which makes global cooperation difficult. Risk-based restrictions: The creation and enforcement of strict, risk-adjusted legal frameworks, also represented by the European Union, at a global level. The rapid development and spread of artificial intelligence (AI) raises numerous ethical and legal challenges. This paper aims to provide a comprehensive overview of these challenges, with a particular focus on data protection, privacy, transparency and regulation. I analyse the ethical aspects of AI applications, the “black box” problem and algorithmic bias. I present the current state and future directions of legal regulation, as well as the concept of “ethical AI” and the importance of international cooperation. In my paper, I highlight that addressing these challenges is crucial for the protection of individual rights and the responsible development of technology. The development of artificial intelligence is explosive, and although it cannot yet replace certain human qualities, it will soon reach the same level of human capabilities and even surpass them almost immediately, transforming into superintelligence. This could have unforeseeable consequences if humanity loses control and AI becomes fully autonomous. An important element of control is the definition of regulations, i.e. the creation of legislation and the institutional system that oversees the evolving technology. This article is about where we stand in the field of regulation related to artificial intelligence, and in my opinion, what dangers lurk for us and what shortcomings there are in the field of legislation. The rapid rise of artificial intelligence is one of the most exciting and worrying phenomena of our time. While AI is revolutionizing almost every aspect of life from medicine to transportation, it also raises a number of ethical and legal challenges. This study provides a comprehensive picture of these challenges, with a particular focus on data protection, privacy, transparency and regulation. We examine the social impacts of AI applications, the problems of Chinese surveillance systems, the dangers of algorithmic bias, and the current state and future directions of legal regulation. The aim is to help shape a future in which we harness the benefits of AI while preserving our fundamental values and rights. The societal impact of artificial intelligence: Data protection and privacy in the digital age The operation of AI systems requires vast amounts of data, which poses serious challenges to the protection of personal data and respect for privacy. This area is particularly sensitive, as AI-based technologies can deeply penetrate individuals’ private spheres and potentially misuse the information they collect. The tension between the data hunger of AI systems and the right of individuals to privacy is a good example of the ethical dilemmas that accompany the development of technology. The handling of biometric data, especially the spread of facial recognition systems, raises serious privacy concerns. In 2019, it was revealed that Amazon had developed an AI-based recruitment tool that showed gender bias. The algorithm, which learned from the resumes of previous applicants, gave preference to male applicants.This case has sharply highlighted the ability of AI systems to amplify and reproduce social inequalities if we do not pay sufficient attention to the quality and representativeness of the data. Deepfake technology: A new dimension of manipulation The development of deepfake technology has brought new ethical challenges to the fore. The Council of Europe’s Committee on Bioethics also warns: This technology enables identity theft and the manipulation of public opinion, which can have serious consequences. Deepfakes can be used to spread disinformation, which can threaten democratic processes and social stability. In addition, the technology is often used without the consent of the person concerned, which violates the right to privacy and can cause reputational damage to individuals or organisations. Ethical challenges also include the blurring of the line between real and fake content, which can undermine trust in digital media and news sources. In 2018, actor and director Jordan Peele made a video in which former US President Barack Obama makes seemingly offensive statements. The video was intended to raise awareness about the dangers of deepfake technology and the spread of disinformation. This case sharply highlighted how easy it is to manipulate public opinion and undermine trust in digital media. Legal safeguards: GDPR and anti-discrimination rules The General Data Protection Regulation (GDPR) imposes strict requirements on automated decision-making. It requires explainability and guarantees the right of data subjects not to be subject to decisions based solely on automated processing. AI systems must also comply with anti-discrimination legislation, which is particularly relevant in sensitive areas such as housing decisions or financial services. This requirement is consistent with a number of laws, including the Fair Housing Act (housing decisions) and the Equal Credit Opportunity Act (financial services).[6] These laws prohibit discrimination against protected groups, regardless of whether the decision is made by a human or an AI system. As technology advances, legal regulations must continually adapt to new challenges to find a balance between innovation and the protection of fundamental rights. China’s Surveillance Systems: The Conflict between Technology and Human Rights China’s widespread use of facial recognition technologies as a tool for surveillance and state control not only raises ethical concerns, but also paints a picture of the future that evokes George Orwell’s dystopian novel “1984.”[8] The use of the technology not only violates privacy, but also enables a level of social control that was previously unimaginable. The Cyberspace Administration of China (CAC)’s 2023 regulation, the “Regulations on the Security Management of Facial Recognition Technology Applications (Trial Operation),” ostensibly aims to tighten control over the use of the technology and protect privacy. The regulation stipulates that facial recognition technology can only be used for clear purposes and necessity, and that consent from data subjects must be obtained before data collection. Of course, this is unthinkable in China. A 2020 report by Amnesty International highlights the dark side of the technology. According to the organization, the use of facial recognition systems could contribute to the systematic oppression of certain minority groups. This is not just a theoretical concern: concrete examples show that the technology has been used to monitor and control Uyghurs and other ethnic minorities in Xinjiang province. China’s surveillance system demonstrates both the opportunities and dangers of artificial intelligence. While technology can help reduce crime and improve public safety, the same system can easily become a tool for oppression. This duality highlights the importance of establishing appropriate ethical and legal frameworks for the use of AI – not just in China, but around the world. Transparency and Algorithmic Bias: The Ethical Challenges of the “Black Box” of AI Transparency of the decision-making processes of AI systems is one of the most pressing ethical issues of our time. The notorious “black box” problem – which makes it almost impossible to track how AI reaches certain conclusions – raises a number of concerns. This phenomenon not only makes it difficult to identify and correct errors, but also undermines users’ trust in AI systems, while making it almost impossible to hold them accountable for bad decisions. The lack of transparency is closely intertwined with the problem of algorithmic bias.AI systems make decisions based on the data they are fed, and if that data is biased, the system will make biased decisions. This process can create a digital self-perpetuating loop that can amplify and reproduce social inequalities. Imagine, for example, a bank using an AI-based credit assessment system. If the system is fed historical data in which certain groups were underrepresented among successful loan applicants, the AI can “learn” to automatically consider these groups as higher risk. In practice, this could mean that members of certain minority groups may have more difficulty accessing credit simply because the AI system has “learned” from data reflecting historical social inequalities. The dangers of algorithmic bias are well illustrated by the COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) system in the United States. This AI-based system assesses the risk of recidivism of offenders and helps judges determine sentences. However, a 2016 ProPublica investigation revealed a shocking finding: the system showed a pronounced racial bias. It incorrectly classified African-American defendants as high risk twice as often as white defendants. This case sharply highlights the serious consequences that the lack of transparency of AI systems and algorithmic bias can have in critical decision-making processes. It is no exaggeration to say that these problems can fundamentally question the impartiality of justice and the principle of social equality. The issue of transparency and algorithmic bias is therefore not just a technical problem, but a fundamental social and ethical challenge. Solving it is essential for AI systems to truly serve the benefit of humanity and not become a new source of discrimination and inequality in the digital age. Regulation and international cooperation: The global challenges of artificial intelligence The rapid development of AI has triggered a real regulatory race around the world. This technological revolution raises legal and ethical questions that traditional legislation has difficulty keeping up with. The challenge is no less than creating a legal framework that both protects individuals’ rights and encourages innovation in this highly dynamic environment. The EU General Data Protection Regulation (GDPR), the Digital Services Act (DSA) and the Artificial Intelligence Act (AI Act) were born. This difference clearly reflects the different approaches to technology regulation in the two regions. The dialogue between the EU and the US in the framework of the Trade and Technology Council (TTC) is an exciting attempt at transatlantic cooperation. The parties are calling for a risk-based approach that prioritizes transparency and security. The joint roadmap released by the TTC sets ambitious goals, including the development of common AI terminologies, risk benchmarks and standards. This initiative is a promising step towards a global consensus, although the two jurisdictions are still at different stages in the regulatory process. The global picture is further clouded by the different approaches of China and Japan. In 2023, China introduced the “Interim Measures for the Management of Generative Artificial Intelligence Services”, which provides a comprehensive legal framework to address key ethical issues such as discrimination and the protection of intellectual property rights. This move demonstrates China’s proactive approach to AI regulation, although critics say that these regulations are closely aligned with state objectives. Japan, in contrast, is taking a more flexible, “soft regulation” approach. The “AI Guidelines for Enterprises Ver1.0”, released in April 2024, provides non-binding guidance for AI developers and users. Japan’s “agile governance” strategy prioritizes adapting to rapid technological developments and supporting innovation while seeking to minimize risks. This global regulatory mosaic illustrates how complex and culturally sensitive the ethical and legal challenges of AI are. International cooperation will be key to developing a global framework that balances innovation and ethical development while respecting the unique approaches and values of different regions. Conclusions: The path to ethical development of AI Addressing the ethical issues that arise in the use of AI is indeed a complex task that requires ongoing dialogue and cooperation between different sectors of society.Dialogue between technologists, ethicists, legislators and civil society is key to the responsible development and use of AI. Developing innovative solutions that strike a balance between data protection and privacy and harnessing the benefits of AI technologies is essential. This could include: Developing transparent AI systems whose decision-making processes are understandable and traceable Developing robust data protection protocols that comply with the latest legal regulations Continuous monitoring and correction of algorithmic bias Implementing the concept of “ethical AI” in practice at all stages of development Ethical development and use of AI is not a one-time task, but a continuous, iterative process. This approach can ensure that we harness the benefits of AI technologies while preserving and strengthening human rights, privacy and the democratic values of our societies. Ultimately, the ethical development of AI is not only a technological challenge, but also a social one. Only through close cooperation and open dialogue between different sectors can we create a future where AI truly benefits humanity while respecting our fundamental values and rights.
2026. augusztus 1., szombat
Térkép

Almási tanya
Ásvány tó
Bazinok
Báboly,
Berete tó
Bersény tó
Bikás gerincje
Borgácska tó
Borzsovapuszta,
Büdöskanális
Csalános
Dédeli láp
Dinnyés-hegy
Disznós kút
Elizabet telep
Fekete rakottyás
Földvár,
Grófi tag.
Gyűrűs sziget
Hosszú rét
Ida-tanya
Ingje sziget
Irtovány
Jókút
Karkalom tó
Kaszálló
Kéki határ.
Keményítőgyár
Keselyűs
Királytó
Kis tó
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Kolokányos
Körtefás
Kunyhók,
Lakteleke
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Málé sziget
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pap erdeje
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2026. július 31., péntek
Demecseri poémák(válogatás)
2026. július 30., csütörtök
A hátizsákos atombomba
Miért a Python?
2026. július 29., szerda
Yahoo Finance
Yahoo Finance adatbázis amerikai részvényárfolyamai
A 2025-ös hozzávetőleges teljesítmény sorrend:
| Hely | Részvény | Ticker | 2025-ös hozam kb. |
|---|---|---|---|
| 🥇 1. | Alphabet (Google) | GOOGL | +65–66% |
| 🥈 2. | Microsoft | MSFT | +15–16% |
| 🥉 3. | Meta Platforms | META | +13% |
| 4. | Tesla | TSLA | +11–18% (forrástól függően) |
| 5. | Apple | AAPL | +9% |
| 6. | Amazon | AMZN | +5–6% |
Tehát ha például 1 000 000 Ft-ot fektettél volna be 2025 elején:
- GOOGL (+66%) → kb. 1 660 000 Ft
- MSFT (+16%) → kb. 1 160 000 Ft
- META (+13%) → kb. 1 130 000 Ft
- AAPL (+9%) → kb. 1 090 000 Ft
- AMZN (+6%) → kb. 1 060 000 Ft
Miért nyert ennyit a GOOGL?
- mesterséges intelligencia (Gemini) várakozások,
- erős Google Cloud növekedés,
- magas profitabilitás,
- a befektetők újraértékelték az Alphabet AI-potenciálját.
Ha csak ezt a hat részvényt nézzük, akkor a 2025-ös "bajnok" egyértelműen a GOOGL volt.
Készíthetek hozzá egy Python programot is, amely letölti az AAPL, MSFT, AMZN, GOOGL, META, TSLA 2025-ös adatait és grafikusan összehasonlítja a hozamokat.
Vásárlási javaslat;
- Erős negyedéves adatok: A korrigált árbevétel 24%-kal 109,8 milliárd dollárra nőtt, ami meghaladta a várakozásokat.
- Magasabb CapEx (tőkekiadások): A vállalat 195–205 milliárd dollárra emelte a 2026-os éves beruházási előrejelzését.
- Negatív szabad cash flow: A negyedév során a cég 5,9 milliárd dollárt égetett el, ami bizonytalanságot keltett a befektetőkben.
- Árfolyamreakció: A növekvő költségek hírére a részvény eséssel reagált, és a 200 napos mozgóátlaga (322 dollár környéke) felé gyengült.











