The Ethics of Generative AI & Conversational Agents

The Ethics of Generative AI & Conversational Agents

The release of ChatGPT and DALL-E marked the beginning of the widespread use of generative AI. This technology, allowing us to create content such as text or images within seconds, now supports us with a range of tasks: from writing emails to brainstorming gift ideas, or creating art. It can support academics with writing papers, parents with entertaining their children, and it might even be used in psychiatric contexts to provide mental health advice. We also increasingly interact with conversational generative AI in communicating with virtual assistants or chatbots used in customer service.

The increasing reliance on and interaction with conversational agents and generative AI raises a host of ethical issues. In which areas, and to what extent, is it reasonable for us to rely on content provided by AI? Where does our reliance involve too great dangers? Moreover, who deserves the credit for the content created by AIs? And who should be blamed, if the created content is harmful or false?

What are some of the dangers of our increasing interaction with conversational AIs? Can we, in the first place, be truly said to interact with them? If we can’t, then what are some of the potential risks of our believing that we can interact with AIs?

This conference explores these, and other ethical issues posed by generative artificial intelligence and conversational agents. It brings together academic researchers and AI ethics practitioners to examine the ethics of generative AI in general, as well as studying the specific challenges this new technology poses in industrial settings.

Datum & Uhrzeit
Montag, 12. August 2024
Start - 09:00 (Europe/Berlin)
Dienstag, 13. August 2024
Ende - 17:00 (Europe/Berlin)

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LMU / Fakultät für Philosophie, Wissenschaftstheorie und Religionswissenschaft

Geschwister-Scholl-Platz 1
80539 München
--LMU / Fakultät für Philosophie, Wissenschaftstheorie und Religionswissenschaft--



Munich Center for Machine Learning

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