Generative AI Models: Opportunities and Risks for Industry and Authorities

Tobias Alt, Andrea Ibisch, Clemens Meiser, Anna Wilhelm, Raphael Zimmer +13 more
6/7/2024
cs.AIcs.CLcs.CR

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Abstract

Generative AI models are capable of performing a wide variety of tasks that have traditionally required creativity and human understanding. During training, they learn patterns from existing data and can subsequently generate new content such as texts, images, audio, and videos that align with these patterns. Due to their versatility and generally high-quality results, they represent, on the one hand, an opportunity for digitalisation. On the other hand, the use of generative AI models introduces novel IT security risks that must be considered as part of a comprehensive analysis of the IT security threat landscape. In response to this risk potential, companies or authorities intending to use generative AI should conduct an individual risk analysis before integrating it into their workflows. The same applies to developers and operators, as many risks associated with generative AI must be addressed during development or can only be influenced by the operating organisation. Based on this, existing security measures can be adapted, and additional measures implemented.

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@article{alt2024generative,
  title  = {Generative AI Models: Opportunities and Risks for Industry and Authorities},
  author = {Tobias Alt and Andrea Ibisch and Clemens Meiser and Anna Wilhelm and Raphael Zimmer and Jonas Ditz and Dominique Dresen and Christoph Droste and Jens Karschau and Friederike Laus and Oliver Müller and Matthias Neu and Rainer Plaga and Carola Plesch and Britta Sennewald and Thomas Thaeren and Kristina Unverricht and Steffen Waurick},
  year   = {2024},
  eprint = {2406.04734},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.04734v2}
}

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