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2. Anthropic researchers wear down AI ethics with repeated questions

   techcrunch.com/2024/04/02/anthropic-researchers...

   The vulnerability is a new one, resulting from the increased “context window” of the latest generation of LLMs. This is the amount of data they can hold in what you might call short-term ...

3. Anthropic thinks 'constitutional AI' is the best way to train ...

   techcrunch.com/2023/05/09/anthropic-thinks...

   Dubbed “constitutional AI,” Anthropic argues its technique, which aims to imbue systems with “values” defined by a “constitution,” makes the behavior of systems both easier to ...

4. Anthropic researchers find that AI models can be trained to ...

   techcrunch.com/2024/01/13/anthropic-researchers...

   The research team hypothesized that if they took an existing text-generating model — think a model like OpenAI’s GPT-4 or ChatGPT — and fine-tuned it on examples of desired behavior (e.g ...

5. Ethics of artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Ethics_of_artificial...

   The Centre for Digital Governance at the Hertie School in Berlin was co-founded by Joanna Bryson to research questions of ethics and technology. The AI Now Institute at NYU is a research institute studying the social implications of artificial intelligence. Its interdisciplinary research focuses on the themes bias and inclusion, labour and ...

6. AI alignment - Wikipedia

   en.wikipedia.org/wiki/AI_alignment

   Artificial intelligence. In the field of artificial intelligence (AI), AI alignment research aims to steer AI systems toward a person's or group's intended goals, preferences, and ethical principles. An AI system is considered aligned if it advances its intended objectives. A misaligned AI system may pursue some objectives, but not the intended ...

7. Existential risk from artificial general intelligence - Wikipedia

   en.wikipedia.org/wiki/Existential_risk_from...

   Duplicability: unlike human brains, AI software and models can be easily copied. Editability: the parameters and internal workings of an AI model can easily be modified, unlike the connections in a human brain. Memory sharing and learning: AIs may be able to learn from the experiences of other AIs in a manner more efficient than human learning.