科学还是科幻?用 ChatGPT 预测水产饲料行业的未来

IF 8.8 1区 农林科学 Q1 FISHERIES
Sara M. Pinho, Giovanni M. Turchini
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Whereas other AI tools are freely available to the public and most of them engage with users in natural language conversations, that is, chatbots. Examples of such open-source AIs include Gemini (Google-based), Meta.ai (developed by Meta and integrated with their social media platforms), and ChatGPT (OpenAI). While each platform offers distinct features and functionalities, ChatGPT has notably revolutionised how the general public perceives and utilises AI tools.<span><sup>2</sup></span> Since its release in November 2022, ChatGPT has been adopted for conversational interactions and widely used for knowledge searches, marking a significant shift in the accessibility and usability of AI for everyday users.</p><p>In the context of aquaculture, AI has the potential to help us drive the activity towards more sustainable practices.<span><sup>3</sup></span> ChatGPT, for example, has surely been a source of information for many aquaculture students and farmers, and an additional tool for writing and researching for scientists. Most of us have probably used ChatGPT at least once for fun and curiosity, but possibly also to summarise information, provide definitions, interpret or translate a text, revise a code, or for searching an explanation on an unfamiliar concept related to aquaculture. These are general functionalities offered by ChatGPT, and other chatbots, and are mostly based on information available online. In this editorial of <i>Reviews in Aquaculture</i>, we wanted to go beyond the search for solely past information and, in a mix of scientific curiosity and trying to add extra fun in our daily research tasks, we asked ChatGPT to predict the future. We specifically explored its potential in predicting future trends in the aquafeed industry, inspired by the 6 out of 20 papers published in the current issue that directly focused on aquafeed or fish nutrition.<span><sup>4-9</sup></span> For that, we asked two questions on future prediction and research guidance, and limited the output to 250 words. Prompts and responses are presented below:</p><p><b>Q1. What will the aquafeed industry look like by the end of the century?</b></p><p>ChatGPT: “<i>By the end of the century, the aquafeed industry is likely to have undergone significant transformations. With increasing demand for seafood due to population growth and dwindling wild fish stocks, aquaculture will have become a dominant source of seafood production. Aquafeed will evolve to be more sustainable and efficient, incorporating innovative ingredients such as algae, insects, and single-cell proteins to reduce reliance on traditional fishmeal and fish oil derived from wild-caught fish. Advancements in biotechnology may enable the production of feed tailored to specific species, improving growth rates and health outcomes while minimising environmental impacts. Precision feeding systems, driven by artificial intelligence and IoT technologies, will optimise feeding regimes, reducing waste and improving feed conversion ratios. Sustainability will be paramount, with aquafeed production striving for minimal environmental impact through the use of renewable energy sources, closed-loop systems, and efficient resource utilisation. Vertical integration and consolidation within the aquafeed industry may lead to the emergence of large multinational corporations dominating the market, driving standardisation and quality control. Furthermore, consumer preferences for ethically and sustainably sourced seafood will drive transparency and traceability throughout the aquaculture supply chain, influencing the formulation and marketing of aquafeed products. Overall, the aquafeed industry in 2100 will likely be characterised by innovation, sustainability, and technological integration to meet the growing global demand for seafood while safeguarding the health of the planet</i>.”</p><p><b>Q2. As a researcher in aquaculture sustainability aiming to drive the aquafeed industry towards minimal environmental impact by the end of the century, I'm seeking guidance on the most impactful research topics to focus on. What are the top three key areas I should prioritise to ensure a sustainable future for aquafeed by 2100?</b></p><p>ChatGPT: “<i>Alternative Protein Sources: Investigate and develop alternative protein sources such as insect meal, single-cell proteins, and algae to reduce dependency on traditional fishmeal and soy-based ingredients. Optimise production methods to ensure scalability, nutritional quality, and cost-effectiveness while minimising environmental footprint</i>.</p><p><i>Circular Economy Approaches: Explore circular economy models within the aquafeed industry, including recycling and upcycling of by-products and waste streams from aquaculture and other industries. Research innovative technologies for converting organic waste into high-quality feed ingredients, thus reducing reliance on virgin resources and mitigating environmental pollution</i>.</p><p><i>Nutritional Optimisation and Precision Feeding: Focus on fine-tuning aquafeed formulations through precision feeding techniques, leveraging advances in nutritional science and feed additives. Develop personalised feeding strategies tailored to specific species, life stages, and environmental conditions to optimise feed conversion efficiency, minimise nutrient loss, and reduce overall environmental impact.”</i></p><p>By analysing the first prediction, we felt that ChatGPT presented a future of innovation and sustainability, in an optimistic and somewhat idealised, if not utopian, sci-fi perspective, where technology-driven solutions will fix all the problems. While it highlights ambitious industry goals reflected in recent research, such predictions seem to be overlooking important factors that could affect feasibility. For instance, several studies have focused on innovative protein ingredients, and the trend of less usage of wild fish-based ingredients in the aquafeed industry is already taking place. However, the complexities of incorporating such new ingredients need to be highlighted, mainly for scaling up production, ensuring nutritional adequacy, understanding their rheological and organoleptic properties and interactions with other raw materials during feed manufacturing, and addressing potential ecological ramifications of large-scale cultivation or production of such materials. Additionally, the AI output reflected an assumption perpetuated in the scientific community that circular approaches always guarantee environmental sustainability, even though there is not enough scientific, nor quantitative, evidence to support that. Another critical concern is the emphasis on vertical integration, which might well become a reality and thus it will require further considerations as it might lead to monopolistic control and lack of diversity, hiding rather than promoting local socio-economic sustainability.</p><p>Reading then the recommended top three research topics, we were somewhat disappointed, as we were, possibly a bit naively, expecting truly innovative and out-of-the-box suggestions. But here, we could see very little imagination and no sci-fiction like suggestions, which is reassuring evidence that human imagination and creativity are likely yet not at risk of being replaced by a computer, at least for now. ChatGPT summarised three well-known, hot topics targeted by aquaculture nutrition researchers in recent years. Investigations on “Alternative protein sources,” “Circular economy approaches,” and “Nutritional optimisation and Precision feeding” are relevant and very much welcomed, as they indeed can contribute to improving the sustainability of aquafeed. Yet, ChatGPT seems to have lacked the fundamental understanding that advancing aquafeed sustainability primarily depends on the integration of ecological, social, and economic perspectives, to potentially develop context-specific solutions tailored to diverse environmental settings and stakeholder needs. One of the insights that we can gain from this exercise is that AI is a very useful tool, that is, and will increasingly be, utilised in science as well as in R&amp;D. Not differently from the abacus, the calculator, the personal computer, and the writing and spreadsheet programs, it will make no sense not using it. It is also worth noting that the outputs of AI will always depend on the users and how the prompts are formulated, as seen in our exercise where we limited the output to a few words, potentially constraining the depth of the explanation. This constraint becomes evident when comparing the two predictions, as scalability was not mentioned in the first but addressed in the second. Thus, we feel like a caveat should be reported to all researchers who also happen to be ChatGPT enthusiasts: the possible misunderstanding and misuse of this tool, and for example, its utilisation for interpreting findings and conceptualising research, are unlikely to produce any impactful or novel research.</p><p>For this, we believe that reading scientific papers, written by experts who have intimate knowledge and direct expertise of the sector, is fundamental to expand our scientific reasonings, and ultimately to help moving current science and technologies towards a better future. Thus, we hope you will enjoy this new issue of <i>Reviews in Aquaculture</i>.</p>","PeriodicalId":227,"journal":{"name":"Reviews in Aquaculture","volume":"16 3","pages":"995-996"},"PeriodicalIF":8.8000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/raq.12935","citationCount":"0","resultStr":"{\"title\":\"Science or science-fiction? Playing with ChatGPT to predict the future of the aquafeed industry\",\"authors\":\"Sara M. Pinho,&nbsp;Giovanni M. Turchini\",\"doi\":\"10.1111/raq.12935\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Technology continually reshapes our interactions with others and the broader society, with the environment, with the way we work and play, and possibly even the way we think. This continuous change seems to have recently accelerated by the widespread introduction of artificial intelligence (AI) tools. For those like us who are not AI experts, a simpler way to understand AI might be as a combination of algorithms and technologies that enable machines to mimic human-like cognitive functions, including problem-solving, learning from experience, and recognising patterns, all guided by human commands.<span><sup>1</sup></span> Advanced AI capabilities, including complex machine learning algorithms and specialised decision-making processes, are predominantly found in paid platforms, tailored for industrial and collaborative use. Whereas other AI tools are freely available to the public and most of them engage with users in natural language conversations, that is, chatbots. Examples of such open-source AIs include Gemini (Google-based), Meta.ai (developed by Meta and integrated with their social media platforms), and ChatGPT (OpenAI). While each platform offers distinct features and functionalities, ChatGPT has notably revolutionised how the general public perceives and utilises AI tools.<span><sup>2</sup></span> Since its release in November 2022, ChatGPT has been adopted for conversational interactions and widely used for knowledge searches, marking a significant shift in the accessibility and usability of AI for everyday users.</p><p>In the context of aquaculture, AI has the potential to help us drive the activity towards more sustainable practices.<span><sup>3</sup></span> ChatGPT, for example, has surely been a source of information for many aquaculture students and farmers, and an additional tool for writing and researching for scientists. Most of us have probably used ChatGPT at least once for fun and curiosity, but possibly also to summarise information, provide definitions, interpret or translate a text, revise a code, or for searching an explanation on an unfamiliar concept related to aquaculture. These are general functionalities offered by ChatGPT, and other chatbots, and are mostly based on information available online. In this editorial of <i>Reviews in Aquaculture</i>, we wanted to go beyond the search for solely past information and, in a mix of scientific curiosity and trying to add extra fun in our daily research tasks, we asked ChatGPT to predict the future. We specifically explored its potential in predicting future trends in the aquafeed industry, inspired by the 6 out of 20 papers published in the current issue that directly focused on aquafeed or fish nutrition.<span><sup>4-9</sup></span> For that, we asked two questions on future prediction and research guidance, and limited the output to 250 words. Prompts and responses are presented below:</p><p><b>Q1. What will the aquafeed industry look like by the end of the century?</b></p><p>ChatGPT: “<i>By the end of the century, the aquafeed industry is likely to have undergone significant transformations. With increasing demand for seafood due to population growth and dwindling wild fish stocks, aquaculture will have become a dominant source of seafood production. Aquafeed will evolve to be more sustainable and efficient, incorporating innovative ingredients such as algae, insects, and single-cell proteins to reduce reliance on traditional fishmeal and fish oil derived from wild-caught fish. Advancements in biotechnology may enable the production of feed tailored to specific species, improving growth rates and health outcomes while minimising environmental impacts. Precision feeding systems, driven by artificial intelligence and IoT technologies, will optimise feeding regimes, reducing waste and improving feed conversion ratios. Sustainability will be paramount, with aquafeed production striving for minimal environmental impact through the use of renewable energy sources, closed-loop systems, and efficient resource utilisation. Vertical integration and consolidation within the aquafeed industry may lead to the emergence of large multinational corporations dominating the market, driving standardisation and quality control. Furthermore, consumer preferences for ethically and sustainably sourced seafood will drive transparency and traceability throughout the aquaculture supply chain, influencing the formulation and marketing of aquafeed products. Overall, the aquafeed industry in 2100 will likely be characterised by innovation, sustainability, and technological integration to meet the growing global demand for seafood while safeguarding the health of the planet</i>.”</p><p><b>Q2. As a researcher in aquaculture sustainability aiming to drive the aquafeed industry towards minimal environmental impact by the end of the century, I'm seeking guidance on the most impactful research topics to focus on. What are the top three key areas I should prioritise to ensure a sustainable future for aquafeed by 2100?</b></p><p>ChatGPT: “<i>Alternative Protein Sources: Investigate and develop alternative protein sources such as insect meal, single-cell proteins, and algae to reduce dependency on traditional fishmeal and soy-based ingredients. Optimise production methods to ensure scalability, nutritional quality, and cost-effectiveness while minimising environmental footprint</i>.</p><p><i>Circular Economy Approaches: Explore circular economy models within the aquafeed industry, including recycling and upcycling of by-products and waste streams from aquaculture and other industries. Research innovative technologies for converting organic waste into high-quality feed ingredients, thus reducing reliance on virgin resources and mitigating environmental pollution</i>.</p><p><i>Nutritional Optimisation and Precision Feeding: Focus on fine-tuning aquafeed formulations through precision feeding techniques, leveraging advances in nutritional science and feed additives. Develop personalised feeding strategies tailored to specific species, life stages, and environmental conditions to optimise feed conversion efficiency, minimise nutrient loss, and reduce overall environmental impact.”</i></p><p>By analysing the first prediction, we felt that ChatGPT presented a future of innovation and sustainability, in an optimistic and somewhat idealised, if not utopian, sci-fi perspective, where technology-driven solutions will fix all the problems. While it highlights ambitious industry goals reflected in recent research, such predictions seem to be overlooking important factors that could affect feasibility. For instance, several studies have focused on innovative protein ingredients, and the trend of less usage of wild fish-based ingredients in the aquafeed industry is already taking place. However, the complexities of incorporating such new ingredients need to be highlighted, mainly for scaling up production, ensuring nutritional adequacy, understanding their rheological and organoleptic properties and interactions with other raw materials during feed manufacturing, and addressing potential ecological ramifications of large-scale cultivation or production of such materials. Additionally, the AI output reflected an assumption perpetuated in the scientific community that circular approaches always guarantee environmental sustainability, even though there is not enough scientific, nor quantitative, evidence to support that. Another critical concern is the emphasis on vertical integration, which might well become a reality and thus it will require further considerations as it might lead to monopolistic control and lack of diversity, hiding rather than promoting local socio-economic sustainability.</p><p>Reading then the recommended top three research topics, we were somewhat disappointed, as we were, possibly a bit naively, expecting truly innovative and out-of-the-box suggestions. But here, we could see very little imagination and no sci-fiction like suggestions, which is reassuring evidence that human imagination and creativity are likely yet not at risk of being replaced by a computer, at least for now. ChatGPT summarised three well-known, hot topics targeted by aquaculture nutrition researchers in recent years. Investigations on “Alternative protein sources,” “Circular economy approaches,” and “Nutritional optimisation and Precision feeding” are relevant and very much welcomed, as they indeed can contribute to improving the sustainability of aquafeed. Yet, ChatGPT seems to have lacked the fundamental understanding that advancing aquafeed sustainability primarily depends on the integration of ecological, social, and economic perspectives, to potentially develop context-specific solutions tailored to diverse environmental settings and stakeholder needs. One of the insights that we can gain from this exercise is that AI is a very useful tool, that is, and will increasingly be, utilised in science as well as in R&amp;D. Not differently from the abacus, the calculator, the personal computer, and the writing and spreadsheet programs, it will make no sense not using it. It is also worth noting that the outputs of AI will always depend on the users and how the prompts are formulated, as seen in our exercise where we limited the output to a few words, potentially constraining the depth of the explanation. This constraint becomes evident when comparing the two predictions, as scalability was not mentioned in the first but addressed in the second. Thus, we feel like a caveat should be reported to all researchers who also happen to be ChatGPT enthusiasts: the possible misunderstanding and misuse of this tool, and for example, its utilisation for interpreting findings and conceptualising research, are unlikely to produce any impactful or novel research.</p><p>For this, we believe that reading scientific papers, written by experts who have intimate knowledge and direct expertise of the sector, is fundamental to expand our scientific reasonings, and ultimately to help moving current science and technologies towards a better future. 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引用次数: 0

摘要

为确保水产饲料在 2100 年前实现可持续发展,我应优先考虑的三大关键领域是什么?调查和开发替代蛋白质来源,如昆虫粉、单细胞蛋白和藻类,以减少对传统鱼粉和大豆配料的依赖。优化生产方法,确保可扩展性、营养质量和成本效益,同时最大限度地减少对环境的影响:探索水产饲料行业的循环经济模式,包括水产养殖和其他行业副产品和废物流的回收和再循环。研究将有机废物转化为优质饲料原料的创新技术,从而减少对原始资源的依赖,减轻环境污染:利用营养科学和饲料添加剂方面的进步,重点通过精准投喂技术对水产饲料配方进行微调。开发针对特定物种、生命阶段和环境条件的个性化投喂策略,以优化饲料转化效率,最大限度地减少营养流失,并降低对环境的总体影响。"通过分析第一份预测,我们认为 ChatGPT 以一种乐观和有点理想化的科幻视角(如果不是乌托邦式的)展示了创新和可持续发展的未来,技术驱动的解决方案将解决所有问题。虽然它强调了近期研究中反映出的雄心勃勃的行业目标,但这种预测似乎忽略了可能影响可行性的重要因素。例如,一些研究重点关注创新蛋白质配料,水产饲料行业已经出现减少使用野生鱼类配料的趋势。然而,需要强调纳入这些新配料的复杂性,主要是为了扩大生产规模、确保营养充足、了解其流变和感官特性以及在饲料生产过程中与其他原料的相互作用,并解决大规模养殖或生产这些原料的潜在生态影响。此外,人工智能产出反映了科学界长期存在的一种假设,即循环方法总是能保证环境的可持续性,尽管没有足够的科学或定量证据支持这种假设。另一个关键问题是对纵向一体化的强调,这很可能成为现实,因此需要进一步考虑,因为这可能导致垄断控制和缺乏多样性,掩盖而不是促进当地社会经济的可持续性。但在这里,我们几乎看不到想象力,也看不到类似科幻小说的建议,这令人欣慰地证明,人类的想象力和创造力很可能还没有被计算机取代的风险,至少目前是这样。ChatGPT 总结了近年来水产养殖营养研究人员瞄准的三个众所周知的热门话题。关于 "替代蛋白质来源"、"循环经济方法 "和 "营养优化与精准投喂 "的研究都很有意义,也很受欢迎,因为它们确实有助于提高水产饲料的可持续性。然而,ChatGPT似乎没有从根本上认识到,推进水产饲料可持续性主要取决于生态、社会和经济视角的整合,从而有可能开发出针对不同环境和利益相关者需求的具体解决方案。我们可以从这项工作中获得的启示之一是,人工智能是一个非常有用的工具,现在和将来都会越来越多地用于科学和研发领域。与算盘、计算器、个人电脑、写作和电子表格程序一样,不使用它将毫无意义。同样值得注意的是,人工智能的输出结果将始终取决于用户和提示的制定方式,正如我们在练习中看到的那样,我们将输出结果限制为几个字,这可能会限制解释的深度。在比较两个预测时,这种限制就变得很明显了,因为第一个预测没有提到可扩展性,而第二个预测却提到了。因此,我们认为应该向所有同时也是 ChatGPT 发烧友的研究人员提出警告:对这一工具可能存在的误解和误用,例如,将其用于解释研究结果和概念化研究,不太可能产生任何有影响力或新颖的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Science or science-fiction? Playing with ChatGPT to predict the future of the aquafeed industry

Technology continually reshapes our interactions with others and the broader society, with the environment, with the way we work and play, and possibly even the way we think. This continuous change seems to have recently accelerated by the widespread introduction of artificial intelligence (AI) tools. For those like us who are not AI experts, a simpler way to understand AI might be as a combination of algorithms and technologies that enable machines to mimic human-like cognitive functions, including problem-solving, learning from experience, and recognising patterns, all guided by human commands.1 Advanced AI capabilities, including complex machine learning algorithms and specialised decision-making processes, are predominantly found in paid platforms, tailored for industrial and collaborative use. Whereas other AI tools are freely available to the public and most of them engage with users in natural language conversations, that is, chatbots. Examples of such open-source AIs include Gemini (Google-based), Meta.ai (developed by Meta and integrated with their social media platforms), and ChatGPT (OpenAI). While each platform offers distinct features and functionalities, ChatGPT has notably revolutionised how the general public perceives and utilises AI tools.2 Since its release in November 2022, ChatGPT has been adopted for conversational interactions and widely used for knowledge searches, marking a significant shift in the accessibility and usability of AI for everyday users.

In the context of aquaculture, AI has the potential to help us drive the activity towards more sustainable practices.3 ChatGPT, for example, has surely been a source of information for many aquaculture students and farmers, and an additional tool for writing and researching for scientists. Most of us have probably used ChatGPT at least once for fun and curiosity, but possibly also to summarise information, provide definitions, interpret or translate a text, revise a code, or for searching an explanation on an unfamiliar concept related to aquaculture. These are general functionalities offered by ChatGPT, and other chatbots, and are mostly based on information available online. In this editorial of Reviews in Aquaculture, we wanted to go beyond the search for solely past information and, in a mix of scientific curiosity and trying to add extra fun in our daily research tasks, we asked ChatGPT to predict the future. We specifically explored its potential in predicting future trends in the aquafeed industry, inspired by the 6 out of 20 papers published in the current issue that directly focused on aquafeed or fish nutrition.4-9 For that, we asked two questions on future prediction and research guidance, and limited the output to 250 words. Prompts and responses are presented below:

Q1. What will the aquafeed industry look like by the end of the century?

ChatGPT: “By the end of the century, the aquafeed industry is likely to have undergone significant transformations. With increasing demand for seafood due to population growth and dwindling wild fish stocks, aquaculture will have become a dominant source of seafood production. Aquafeed will evolve to be more sustainable and efficient, incorporating innovative ingredients such as algae, insects, and single-cell proteins to reduce reliance on traditional fishmeal and fish oil derived from wild-caught fish. Advancements in biotechnology may enable the production of feed tailored to specific species, improving growth rates and health outcomes while minimising environmental impacts. Precision feeding systems, driven by artificial intelligence and IoT technologies, will optimise feeding regimes, reducing waste and improving feed conversion ratios. Sustainability will be paramount, with aquafeed production striving for minimal environmental impact through the use of renewable energy sources, closed-loop systems, and efficient resource utilisation. Vertical integration and consolidation within the aquafeed industry may lead to the emergence of large multinational corporations dominating the market, driving standardisation and quality control. Furthermore, consumer preferences for ethically and sustainably sourced seafood will drive transparency and traceability throughout the aquaculture supply chain, influencing the formulation and marketing of aquafeed products. Overall, the aquafeed industry in 2100 will likely be characterised by innovation, sustainability, and technological integration to meet the growing global demand for seafood while safeguarding the health of the planet.”

Q2. As a researcher in aquaculture sustainability aiming to drive the aquafeed industry towards minimal environmental impact by the end of the century, I'm seeking guidance on the most impactful research topics to focus on. What are the top three key areas I should prioritise to ensure a sustainable future for aquafeed by 2100?

ChatGPT: “Alternative Protein Sources: Investigate and develop alternative protein sources such as insect meal, single-cell proteins, and algae to reduce dependency on traditional fishmeal and soy-based ingredients. Optimise production methods to ensure scalability, nutritional quality, and cost-effectiveness while minimising environmental footprint.

Circular Economy Approaches: Explore circular economy models within the aquafeed industry, including recycling and upcycling of by-products and waste streams from aquaculture and other industries. Research innovative technologies for converting organic waste into high-quality feed ingredients, thus reducing reliance on virgin resources and mitigating environmental pollution.

Nutritional Optimisation and Precision Feeding: Focus on fine-tuning aquafeed formulations through precision feeding techniques, leveraging advances in nutritional science and feed additives. Develop personalised feeding strategies tailored to specific species, life stages, and environmental conditions to optimise feed conversion efficiency, minimise nutrient loss, and reduce overall environmental impact.”

By analysing the first prediction, we felt that ChatGPT presented a future of innovation and sustainability, in an optimistic and somewhat idealised, if not utopian, sci-fi perspective, where technology-driven solutions will fix all the problems. While it highlights ambitious industry goals reflected in recent research, such predictions seem to be overlooking important factors that could affect feasibility. For instance, several studies have focused on innovative protein ingredients, and the trend of less usage of wild fish-based ingredients in the aquafeed industry is already taking place. However, the complexities of incorporating such new ingredients need to be highlighted, mainly for scaling up production, ensuring nutritional adequacy, understanding their rheological and organoleptic properties and interactions with other raw materials during feed manufacturing, and addressing potential ecological ramifications of large-scale cultivation or production of such materials. Additionally, the AI output reflected an assumption perpetuated in the scientific community that circular approaches always guarantee environmental sustainability, even though there is not enough scientific, nor quantitative, evidence to support that. Another critical concern is the emphasis on vertical integration, which might well become a reality and thus it will require further considerations as it might lead to monopolistic control and lack of diversity, hiding rather than promoting local socio-economic sustainability.

Reading then the recommended top three research topics, we were somewhat disappointed, as we were, possibly a bit naively, expecting truly innovative and out-of-the-box suggestions. But here, we could see very little imagination and no sci-fiction like suggestions, which is reassuring evidence that human imagination and creativity are likely yet not at risk of being replaced by a computer, at least for now. ChatGPT summarised three well-known, hot topics targeted by aquaculture nutrition researchers in recent years. Investigations on “Alternative protein sources,” “Circular economy approaches,” and “Nutritional optimisation and Precision feeding” are relevant and very much welcomed, as they indeed can contribute to improving the sustainability of aquafeed. Yet, ChatGPT seems to have lacked the fundamental understanding that advancing aquafeed sustainability primarily depends on the integration of ecological, social, and economic perspectives, to potentially develop context-specific solutions tailored to diverse environmental settings and stakeholder needs. One of the insights that we can gain from this exercise is that AI is a very useful tool, that is, and will increasingly be, utilised in science as well as in R&D. Not differently from the abacus, the calculator, the personal computer, and the writing and spreadsheet programs, it will make no sense not using it. It is also worth noting that the outputs of AI will always depend on the users and how the prompts are formulated, as seen in our exercise where we limited the output to a few words, potentially constraining the depth of the explanation. This constraint becomes evident when comparing the two predictions, as scalability was not mentioned in the first but addressed in the second. Thus, we feel like a caveat should be reported to all researchers who also happen to be ChatGPT enthusiasts: the possible misunderstanding and misuse of this tool, and for example, its utilisation for interpreting findings and conceptualising research, are unlikely to produce any impactful or novel research.

For this, we believe that reading scientific papers, written by experts who have intimate knowledge and direct expertise of the sector, is fundamental to expand our scientific reasonings, and ultimately to help moving current science and technologies towards a better future. Thus, we hope you will enjoy this new issue of Reviews in Aquaculture.

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来源期刊
CiteScore
24.80
自引率
5.80%
发文量
109
审稿时长
>12 weeks
期刊介绍: Reviews in Aquaculture is a journal that aims to provide a platform for reviews on various aspects of aquaculture science, techniques, policies, and planning. The journal publishes fully peer-reviewed review articles on topics including global, regional, and national production and market trends in aquaculture, advancements in aquaculture practices and technology, interactions between aquaculture and the environment, indigenous and alien species in aquaculture, genetics and its relation to aquaculture, as well as aquaculture product quality and traceability. The journal is indexed and abstracted in several databases including AgBiotech News & Information (CABI), AgBiotechNet, Agricultural Engineering Abstracts, Environment Index (EBSCO Publishing), SCOPUS (Elsevier), and Web of Science (Clarivate Analytics) among others.
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