The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systems
Artificial intelligence (AI) offers potential solutions to optimize agricultural production and sustainability. This study examined American perceptions and attitudes toward AI applications in the food and agriculture systems, assessing both public optimism and concerns. Using a mixed-methods approa...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Future Foods |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666833525000164 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832572992901611520 |
|---|---|
| author | Cheng-Xian Yang Lauri M. Baker Anissa Mattox David Diehl Sydney Honeycutt |
| author_facet | Cheng-Xian Yang Lauri M. Baker Anissa Mattox David Diehl Sydney Honeycutt |
| author_sort | Cheng-Xian Yang |
| collection | DOAJ |
| description | Artificial intelligence (AI) offers potential solutions to optimize agricultural production and sustainability. This study examined American perceptions and attitudes toward AI applications in the food and agriculture systems, assessing both public optimism and concerns. Using a mixed-methods approach grounded in online ethnography and survey analysis, we identified five primary themes influencing public support for AI in agriculture: Knowledge of AI in agriculture, trust in scientific experts in agriculture and food production, concerns about using AI in agriculture, health concerns about agriculture and food production, and general attitudes toward AI technology itself. Findings indicated moderate public knowledge about AI's agricultural applications, with higher support correlating with trust in agricultural scientists and awareness of health benefits linked to AI innovations. Conversely, concerns over privacy, data security, and potential job displacement contribute to hesitancy. Our regression model further highlights the significance of these themes with demographic factors. This study indicated the need for AI stakeholders to address knowledge gaps and ethical considerations, emphasizing transparent data practices and clear communication of AI in enhancing agricultural sustainability. These insights offer valuable directions for future research and policy-making, promoting a balanced approach to integrating AI in agriculture that is responsive to public sentiment and ethical standards. |
| format | Article |
| id | doaj-art-196ba47d504e4a478cb8872379bf5873 |
| institution | Kabale University |
| issn | 2666-8335 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Future Foods |
| spelling | doaj-art-196ba47d504e4a478cb8872379bf58732025-02-02T05:29:27ZengElsevierFuture Foods2666-83352025-06-0111100553The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systemsCheng-Xian Yang0Lauri M. Baker1Anissa Mattox2David Diehl3Sydney Honeycutt4Corresponding author.; University of Florida, FL, United StatesUniversity of Florida, FL, United StatesUniversity of Florida, FL, United StatesUniversity of Florida, FL, United StatesUniversity of Florida, FL, United StatesArtificial intelligence (AI) offers potential solutions to optimize agricultural production and sustainability. This study examined American perceptions and attitudes toward AI applications in the food and agriculture systems, assessing both public optimism and concerns. Using a mixed-methods approach grounded in online ethnography and survey analysis, we identified five primary themes influencing public support for AI in agriculture: Knowledge of AI in agriculture, trust in scientific experts in agriculture and food production, concerns about using AI in agriculture, health concerns about agriculture and food production, and general attitudes toward AI technology itself. Findings indicated moderate public knowledge about AI's agricultural applications, with higher support correlating with trust in agricultural scientists and awareness of health benefits linked to AI innovations. Conversely, concerns over privacy, data security, and potential job displacement contribute to hesitancy. Our regression model further highlights the significance of these themes with demographic factors. This study indicated the need for AI stakeholders to address knowledge gaps and ethical considerations, emphasizing transparent data practices and clear communication of AI in enhancing agricultural sustainability. These insights offer valuable directions for future research and policy-making, promoting a balanced approach to integrating AI in agriculture that is responsive to public sentiment and ethical standards.http://www.sciencedirect.com/science/article/pii/S2666833525000164Agri-food systemArtificial intelligence (AI)Online ethnographyPublic perceptionSustainabilityTechnology acceptance |
| spellingShingle | Cheng-Xian Yang Lauri M. Baker Anissa Mattox David Diehl Sydney Honeycutt The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systems Future Foods Agri-food system Artificial intelligence (AI) Online ethnography Public perception Sustainability Technology acceptance |
| title | The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systems |
| title_full | The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systems |
| title_fullStr | The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systems |
| title_full_unstemmed | The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systems |
| title_short | The forgotten factor: Exploring consumer perceptions of artificial intelligence in the food and agriculture systems |
| title_sort | forgotten factor exploring consumer perceptions of artificial intelligence in the food and agriculture systems |
| topic | Agri-food system Artificial intelligence (AI) Online ethnography Public perception Sustainability Technology acceptance |
| url | http://www.sciencedirect.com/science/article/pii/S2666833525000164 |
| work_keys_str_mv | AT chengxianyang theforgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT laurimbaker theforgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT anissamattox theforgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT daviddiehl theforgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT sydneyhoneycutt theforgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT chengxianyang forgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT laurimbaker forgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT anissamattox forgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT daviddiehl forgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems AT sydneyhoneycutt forgottenfactorexploringconsumerperceptionsofartificialintelligenceinthefoodandagriculturesystems |