How should the advent of large language models affect the practice of science?

Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the advent of large language models affect the practice of science? For this opinion piece, we have invited four diverse groups of scientists to reflect on this query, sharing their perspectives and engaging in debate. Schulz et al. make the argument that working with LLMs is not fundamentally different from working with human collaborators, while Bender et al. argue that LLMs are often misused and over-hyped, and that their limitations warrant a focus on more specialized, easily interpretable tools. Marelli et al. emphasize the importance of transparent attribution and responsible use of LLMs. Finally, Botvinick and Gershman advocate that humans should retain responsibility for determining the scientific roadmap. To facilitate the discussion, the four perspectives are complemented with a response from each group. By putting these different perspectives in conversation, we aim to bring attention to important considerations within the academic community regarding the adoption of LLMs and their impact on both current and future scientific practices

Stabilising selection on immune response in male black grouse Lyrurus tetrix

Illnesses caused by a variety of micro- and macro- organisms can negatively affect individuals’ fitness, leading to the expectation that immunity is under positive selection. However, immune responses are costly and individuals must trade-off their immune response with other fitness components (e.g. survival or reproductive success) meaning that individuals with intermediate response may have the greatest overall fitness. Such a process might be particularly acute in species with strong sexual selection because the condition-dependence of male secondary sexual-traits might lead to striking phenotypic differences amongst males of different immune response levels. We tested whether there is selection on immune response by survival and reproduction in yearling and adult male black grouse (Lyrurus tetrix) following an immune challenge with a novel antigen and tested the hypothesis that sexual signals and body mass are honest signals of the immune response. We show that yearling males with highest immune response to these challenges had higher survival, but the reverse was true for adults. Adults with higher responses had highest mass loss and adult males with intermediate immune response had highest mating success. Tail length was related to baseline response in adults and more weakly in yearlings. Our findings reveal the complex fitness consequences of mounting an immune response across age classes. Such major differences in the direction and magnitude of selection in multiple fitness components is an alternative route underpinning the stabilizing selection of immune responses with an intermediate immune response being optimal

How should the advent of large language models affect the practice of science?

Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the advent of large language models affect the practice of science? For this opinion piece, we have invited four diverse groups of scientists to reflect on this query, sharing their perspectives and engaging in debate. Schulz et al. make the argument that working with LLMs is not fundamentally different from working with human collaborators, while Bender et al. argue that LLMs are often misused and over-hyped, and that their limitations warrant a focus on more specialized, easily interpretable tools. Marelli et al. emphasize the importance of transparent attribution and responsible use of LLMs. Finally, Botvinick and Gershman advocate that humans should retain responsibility for determining the scientific roadmap. To facilitate the discussion, the four perspectives are complemented with a response from each group. By putting these different perspectives in conversation, we aim to bring attention to important considerations within the academic community regarding the adoption of LLMs and their impact on both current and future scientific practices