Robotic and Autonomous Agricultural Technologies (RAAT) are increasingly available yet may fail to be adopted. This paper focusses specifically on cognitive factors that affect adoption including: inability to generate trust, loss of farming knowledge and reduced social cognition. It is recommended that agriculture develops its own framework for the performance and safety of RAAT drawing on human factors research in aerospace engineering including human inputs (individual variance in knowledge, skills, abilities, preferences, needs and traits), trust, situational awareness and cognitive load. The kinds of cognitive impacts depend on the RAATs level of autonomy, ie whether it has automatic, partial autonomy and autonomous functionality and stage of adoption, ie adoption, initial use or post-adoptive use. The more autonomous a system is, the less a human needs to know to operate it and the less the cognitive load, but it also means farmers have less situational awareness about on farm activities that in turn may affect strategic decision-making about their enterprise. Some cognitive factors may be hidden when RAAT is first adopted but play a greater role during prolonged or intense post-adoptive use. Systems with partial autonomy need intuitive user interfaces, engaging system information, and clear signaling to be trusted with low level tasks; and to compliment and augment high order decision-making on farm.
翻译:本文特别侧重于影响收养的认知因素,包括:无法产生信任、丧失农业知识和减少社会认知;建议农业根据航空航天工程中的人类因素研究,包括人的投入(知识、技能、能力、偏好、需要和特性方面的个人差异)、信任、情境意识和认知负荷,为RAAT发展自己的性能和安全框架,包括人类投入(在知识、技能、能力、偏好、需要和特性方面的个人差异)、信任、情境认识和认知负荷。认知影响的类型取决于RAAT的自主程度,即它是否具有自动、部分自主和自主功能以及收养、收养、初始使用或收养后使用阶段的功能和阶段。一个系统越是自主,就越不需要人知道操作这种系统,认知负荷也越少,但这意味着农民对农业活动的情况了解越少,这反过来可能影响企业的战略决策。当RAAT首次采用时,一些认知因素可能隐藏在长期或密集的后施用过程中发挥更大的作用。具有部分自主性的系统需要部分自主性需要增加用户的高度互信度和信任度,以便提高系统决策的高度信号和信任性。