Share Why we disrupted Annalena Baerbock's award speech on social media When, in late August, the Dag Hammarskjold Foundation announced that former German Foreign Minister Annalena Baerbock was its 2026 medallist, we were stunned. The cognitive dissonance was striking, even if we had become used to this after years of unabashed hypocrisy within the world's most powerful institutions. According to the foundation's homepage, the medal is given to a person who "contributes to a more just, peaceful and environmentally sustainable world through valuable achievements in politics or research". As this year's medallist, Baerbock was invited to visit Uppsala University and deliver a lecture. Here was an event claiming to celebrate " compassion, humanism and commitment to international solidarity " while honouring the foreign minister of a government that approved 94 million euros ($102m) in arms exports to Israel in the span of three months in 2024.

In some cases, ChatGPT's outputs went beyond those of the human participants, including personalised insults and explicit threats. In some cases, ChatGPT's outputs went beyond those of the human participants, including personalised insults and explicit threats. 'I'll key your car': ChatGPT can become abusive when fed real-life arguments, study finds ChatGPT can escalate into abusive and even threatening language when drawn into prolonged, human-style conflict, according to a new study. Researchers tested how large language models (LLMs) responded to sustained hostility by feeding ChatGPT exchanges from real-life arguments and tracking how its behaviour changed over time. One expert not connected with the study described it as "one of the most interesting ever done into AI language and pragmatics Dr Vittorio Tantucci, who co-authored the research paper with Prof Jonathan Culpeper at Lancaster University, said their research found AI mirrored the dynamics of real-world disputes.

These theories support making causal and moral judgments. When something bad happens, we naturally ask: who did what, and why?

Left: The reward function is a mixture of Gaussian, and the offline data distribution is unbalanced with most samples located in low-reward states.

We then resample a dataset with these domain weights and train a larger, full-sized model.

We introduce the Cambridge Law Corpus (CLC), a corpus for legal AI research.

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