Short abstract:

AI systems such as ChatGPT, Gemini and Copilot are widely conceptualized as agents. As we witness the explosive multiplication of such agents the paper aims to map this dynamically evolving field in order to raise the question what differences between AI agents make a difference.

Long abstract:

Following the release of ChatGPT in November 2022, generative AI quickly moved to the center of technical imaginaries worldwide. Developments and news in this field are rapidly evolving in a competition among global technology companies to create increasingly powerful language models, integrate them into specific practical contexts, and explore ways to commodify them. Interactions with language models are conceived as dialogs with AI agents, which can be fine-tuned in various ways and operate semi-autonomously through different interfaces in digital environments. AI researchers working on large language models argue that “agenticness” (Shavit et al. 2023) is what’s specific and new about applications such as ChatGPT, Gemini, Copilot etc. With the introduction of GPTs and a dedicated GPT Store by OpenAI, we are currently experiencing an explosive proliferation of AI agents, raising the question of which differences among AI agents make a difference and how these differences manifest in media practices. Against this backdrop, the paper attempts to map the dynamically evolving field of AI agents. Opposing the rhetoric of the radically new, it first recalls the recurring idea of software agents in the history of AI. Secondly, drawing on approaches from digital methods it explores experimental approaches of engaging with the multiplicity of AI agents and their agentic capacities in situ.