
The "ELSA Scan: Supporting Responsible AI and IoT Development in Agriculture" training webinar introduces the ‘Evaluation of Ethical, Legal, and Social Aspects (ELSA Scan) service’, developed within agrifoodTEF. AI and data-driven technologies hold great promise for agriculture, but they also raise questions about transparency, bias, data privacy, safety, and societal impact. The ELSA Scan helps developers address these issues early in the design process through a structured evaluation based on surveys and interviews. Participants will learn how the service identifies key ELSA aspects and provides high-level recommendations that improve ethical technologies, ensure legal compliance, and increase societal acceptance. The provided materials are the slides presented during the event.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
