Cognitive factors that affect the adoption of autonomous agriculture

TL;DR

This paper examines how cognitive factors like trust, knowledge loss, and social cognition influence the adoption of autonomous agricultural technologies, emphasizing the need for tailored human factors frameworks.

Contribution

It introduces a framework based on aerospace human factors research to address cognitive challenges in adopting autonomous agricultural systems.

Findings

Higher autonomy reduces cognitive load but may decrease situational awareness.

Trust and intuitive interfaces are crucial for partial autonomy adoption.

Cognitive impacts evolve during different stages of adoption and use.

Abstract

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.