The risks of AI in agriculture

Integration of artificial intelligence (AI) into agriculture has the potential to revolutionise agriculture, but it also presents challenges and risks that must be carefully managed. AI can improve planning, streamline work processes, and improve decision making in crop cultivation and animal husban...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Hampel György
Fabulya Zoltán
Dokumentumtípus: Cikk
Megjelent: University of Szeged, Faculty of Engineering Szeged 2024
Sorozat:Analecta technica Szegedinensia 18 No. 4
Kulcsszavak:Mesterséges intelligencia alkalmazása - mezőgazdaság, Mezőgazdaság - precíciós, Mezőgazdasági informatika
Tárgyszavak:
doi:10.14232/analecta.2024.4.32-44

Online Access:http://acta.bibl.u-szeged.hu/87059
LEADER 02346nab a2200265 i 4500
001 acta87059
005 20250416164716.0
008 250416s2024 hu o 000 eng d
022 |a 2064-7964 
024 7 |a 10.14232/analecta.2024.4.32-44  |2 doi 
040 |a SZTE Egyetemi Kiadványok Repozitórium  |b hun 
041 |a eng 
100 1 |a Hampel György 
245 1 4 |a The risks of AI in agriculture  |h [elektronikus dokumentum] /  |c  Hampel György 
260 |a University of Szeged, Faculty of Engineering  |b Szeged  |c 2024 
300 |a 32-44 
490 0 |a Analecta technica Szegedinensia  |v 18 No. 4 
520 3 |a Integration of artificial intelligence (AI) into agriculture has the potential to revolutionise agriculture, but it also presents challenges and risks that must be carefully managed. AI can improve planning, streamline work processes, and improve decision making in crop cultivation and animal husbandry, ultimately leading to higher returns for farmers. However, lack of training and high implementation costs can make it difficult for some farmers to adopt AI, creating a competitive disadvantage and concentrating agricultural resources. Additionally, AI may contribute to unemployment among those with lower skill levels and poses cybersecurity risks that need continuous monitoring. Legal concerns also arise with respect to data ownership and usage rights, with questions about who can access and utilise collected data. Farmers often have to rely on AI systems as "black boxes", with limited understanding of how they work. If these systems fail and cause damage, accountability becomes an important issue. It is crucial to assess the drawbacks and risks of AI implementation in agriculture and educate farmers about these risks to prevent significant damage. Managing these risks effectively and ensuring data accuracy and security are essential in the global adoption of AI in agriculture. 
650 4 |a Természettudományok 
650 4 |a Számítás- és információtudomány 
650 4 |a Mezőgazdaság-tudományok 
650 4 |a Egyéb mezőgazdaság-tudományok 
695 |a Mesterséges intelligencia alkalmazása - mezőgazdaság, Mezőgazdaság - precíciós, Mezőgazdasági informatika 
700 0 1 |a Fabulya Zoltán  |e aut 
856 4 0 |u http://acta.bibl.u-szeged.hu/87059/1/engineering_2024_004_032-044.pdf  |z Dokumentum-elérés