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Behavioural analysis and state-of-the-art language models turn talk to action

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Collective and artificial intelligence

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Our Natural Language Processing (NLP) model helps transform voice-led discussions into parsable data, while our collective intelligence human behaviour model surfaces the innovative solutions that exist within the wisdom of crowds.

PSi is also designed to collect a robust data set by reducing the impact of social biases such as herding or “loud voices,” so that analysis accurately represents the true landscape of opinions and insights.

  1. Pescetelli, N., Rutherford, A., & Rahwan, I. (2021). Modularity and composite diversity affect the collective gathering of information online. Nature Communications, 12(1), 3195. https://doi.org/10.1038/s41467-021-23424-1

  2. Navajas, J., Niella, T., Garbulsky, G., Bahrami, B., & Sigman, M. (2018). Aggregated knowledge from a small number of debates outperforms the wisdom of large crowds. In Nature Human Behaviour (Vol. 2, Issue 2, pp. 126–132). https://doi.org/10.1038/s41562-017-0273-4

  3. Kao, A. B., & Couzin, I. D. (2014). Decision accuracy in complex environments is often maximized by small group sizes. Proceedings. Biological Sciences / The Royal Society, 281(1784), 20133305. https://doi.org/10.1098/rspb.2013.3305

  4. Kao, A. B., & Couzin, I. D. (2019). Modular structure within groups causes information loss but can improve decision accuracy. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 374(1774), 20180378. https://doi.org/10.1098/rstb.2018.0378

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