# Responsible AI in Farming: A Multi-Criteria Framework for Sustainable Technology Design
## 1 Introduction  
Recent advances in the fields of robotics, the Internet of Things, and above all artificial intelligence (AI) are now providing a new innovation ground for the next era of farming, often called Farming 4.0 (or Farming 5.0 in some cases). This overarching term combines research fields like precision farming, precision livestock farming, or smart farming, which are all driven by the technological advances in the information and communication technology (ICT) sector. It is thought that the broad application of novel technologies supports the achievement of various political declarations and societal goals (e.g., the Green Deal, Paris Agreement, SDGs, and Farm to Fork Strategy) [1; 2; 3], providing critical mitigation and adaptation capacities to tackle global issues such as greenhouse gas emissions, acidification, or eutrophication. This should be achieved by assisting stakeholders in tackling the aforementioned challenges whilst ensuring productivity goals by enabling real-time monitoring, simulation, and automation capabilities through high-fidelity models and bidirectional information flows [3; 4]. Despite the manifold benefits of novel developments in Farming 4.0 [5; 6], technology introduction without consideration for the needs of users may actually hinder sustainability efforts [5; 7], highlighting the importance of responsible technology development within complex social-technological-ecological systems (STES). This is especially the case for AI, as the maturity of the technology and the diverse and scalable application fields will be a critical part of many future farming technologies, witha global compound annual growth rate of 23.1 percent until 2028 [8]. As farmers' new roles, skills, and requirements in such an environment are changing rapidly, frameworks and design requirements are needed to understand the manifold implications of AI and guide responsible implementation to maintain autonomy and limit potentially adverse effects. Specific technological design recommendations only support a fixed set of problems. Therefore, this article focuses on expanding the understanding of multivariate dependencies in technological integration and emphasizes the importance of prioritizing human-coupled environmental actions. It presents the ability to use an STES perspective to define technological requirements for responsible AI development, exemplified by AI's effects and mitigation potential on farmers' autonomy. By following the structure of a \"systematization of knowledge approach\", this article systematizes the threat landscape, exemplifies technological developments to mitigate the risks, provides a high-level framework for technology development, and elaborates on future work in this field.  
In this context, this work aims to explore four specific subtopics in four sections:  
* The concept of autonomy and the introduction of the STES approach;
* The systemic effects of AI and autonomous technologies and systems on the autonomy of farmers and current challenges in AI research for the preservation of farmers' autonomy;
* The principles, techniques, and methodologies for the trustworthy deployment of an AI framework;
* The increase in alignment of AI systems to user needs by design and implementation from an STES perspective.  
To accomplish this, the initial section introduces autonomy and the design principles of STES. The second section is organized from the STES perspective and offers a comprehensive overview of the threat landscape concerning responsible AI development. The third section illustrates the potential of technological design choices to tackle the aforementioned challenges. The fourth section discusses the high-level framework for establishing requirements within a responsible technology design process.