Generative artificial intelligence : the impact on intellectual property crimes
Artificial intelligence (AI) has recently gained significant popularity. News stories about self-driving cars, creative robots and learning algorithms have raised awareness among academics, policymakers and consumers about the benefits and necessity of artificial intelligence. Computer programs known as 'generative AI' can generate new images, messages and other content (or 'outputs') in response to a user's textual requests (or 'inputs'). Examples include OpenAI's DALL-E 2 and ChatGPT programs, Stability AI's Stable Diffusion program, and Midjourney's program. These generative AI programs are trained to produce such results in part by exposing them to a huge number of existing works, such as essays, pictures, paintings and other artworks. While generative AI has a wide range of potential uses for both businesses and people, unfortunately, the promise of more effective automation and autonomy is intrinsically related to criminal activity. Increasing awareness of the potential use of AI by criminals will improve the ability of law enforcement agencies and the judiciary to anticipate potential malicious and criminal activities, as well as to prevent, respond to and mitigate the effects of malicious use of AI in a proactive manner. This would allow for the rapid identification of developing patterns, as well as the use of generative AI's broad capabilities in identifying criminal activity. Although there have been some efforts to regulate generative AI in the EU, the legal framework remains unestablished.
Year of publication: |
[2023]
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Institutions: | European Union Agency for Criminal Justice Cooperation (issuing body) |
Publisher: |
The Hague : EUJUST_2 |
Subject: | Künstliche Intelligenz | Artificial intelligence | Immaterialgüterrechte | Intellectual property rights | Kriminalität | Crime | Welt | World |
Saved in:
Extent: | 1 Online-Ressource (39 p.) Illustrationen (farbig) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | November 2023. - Bibl. : p. 38-39 |
ISBN: | 978-92-9404-161-6 |
Other identifiers: | 10.2812/1651 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015322996
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