ArticleFrontiers in artificial intelligence2022
Recommendations for ethical and responsible use of artificial intelligence in digital agriculture.
Article in Frontiers in artificial intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Harnessing large vision and language models in agriculture: a review.Frontiers in plant science · 2025Pooled it
- The governance of artificial intelligence in agriculture: A review and future research directions.Outlook on agriculture · 2026Article
- AI and IoT in Sugar Beet Systems: A Review of Monitoring, VOC Sensing, and Post-Harvest Applications.Sensors (Basel, Switzerland) · 2026Review
- Reimagining plant science training in the era of generative artificial intelligence: a global perspective.The Plant cell · 2026Review
- Artificial Intelligence Methods in Forest Biotechnology: Current Status and Future Prospects.International journal of molecular sciences · 2026Review
- Strategies for Advanced Production: A Review of the Use of AI in the Dairy Industry.Animals : an open access journal from MDPI · 2026Review
- Traceability and Anti-Counterfeiting in Agri-Food Supply Chains: A Review of RFID, IoT, Blockchain, and AI Technologies.Sensors (Basel, Switzerland) · 2026Review
- Generative AI use and advisory performance among agricultural extension agents in Benin.Frontiers in artificial intelligence · 2026Article
- Scale, trust, and the digital divide: a systematic review of AI and ML for agricultural applications.Frontiers in artificial intelligence · 2026Review
- Bridging agronomic science and context specific farm-level advisory through generative AI for rice systems in India.Frontiers in artificial intelligence · 2026Review
- Improving plant breeding through AI-supported data integration.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- Food's future: sustainability and agricultural robotics.Frontiers in robotics and AI · 2025Review
- AI through the looking glass: an empirical study of structural social and ethical challenges in AI.AI & society · 2025Article
- Two-Way FDI assists agricultural sustainable development: Based on digitalization and greening perspectives.PloS one · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) applications are an integral and emerging component of digital agriculture. AI can help ensure sustainable production in agriculture by enhancing agricultural operations and decision-making. Recommendations about soil condition and pesticides or automatic devices for milking and apple picking are examples of AI applications in digital agriculture. Although AI offers many benefits in farming, AI systems may raise ethical issues and risks that should be assessed and proactively managed. Poor design and configuration of intelligent systems may impose harm and unintended consequences on digital agriculture. Invasion of farmers' privacy, damaging animal welfare due to robotic technologies, and lack of accountability for issues resulting from the use of AI tools are only some examples of ethical challenges in digital agriculture. This paper examines the ethical challenges of the use of AI in agriculture in six categories including fairness, transparency, accountability, sustainability, privacy, and robustness. This study further provides recommendations for agriculture technology providers (ATPs) and policymakers on how to proactively mitigate ethical issues that may arise from the use of AI in farming. These recommendations cover a wide range of ethical considerations, such as addressing farmers' privacy concerns, ensuring reliable AI performance, enhancing sustainability in AI systems, and reducing AI bias.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.