Date 1st April 2022
Time: 11:00 to 12:30 CEST
Agricultural data flows involve different actors from generation to transformation, enrichment, aggregation and final fruition. These dynamics have ethical, socio-economic, and legal dimensions that affect the way the digitalization of agriculture benefits the various actors, often leaving the least resourced behind.
These issues are very relevant in the context of the GFAR's Collective Action on Inclusive Digital Agriculture.
GFAR is facilitating a session on these topics during the RDA IGAD Annual Meeting, under the title "Ethical and legal issues around agricultural data".
Speakers and Information about the presentations
Moderator: Valeria Pesce (Global Forum on Agricultural Research and Innovation, GFAR)
Foteini Zampati is a legal professional with over 20 years of experience in various areas of private and business law. She holds an LLB in Law and a LLM in European Union and Business Law. She works at Chapman Freeborn Air Marketing GmbH as a Data Protection Advisor and was previously Data Rights Specialist at the Global Open Data for Agriculture and Nutrition (GODAN) initiative and the Kuratorium für Technik und Bauwesen in der Landwirtschaft (KTBL). Her main specialization areas are Open Data and Intellectual Property, ownership issues and data rights,compliance, best practices, and Codes of Conduct, as well as Data Protection Law and Regulations (i.e. GDPR).
Farmers´ethical and legal considerations in digital agriculture
Ethics is about choices, and agricultural ethics is about choices for people engaged in agriculture, from farmers, industries, researchers, governments, policymakers, technology developers to consumers. There is no doubt that data driven agriculture has a lot of potential and benefits. Nevertheless farmers raise concerns about data ownership, intellectual property, privacy and security. Mostly in developing countries smallholder farmers are not harnessing the power of data and many times must overcome challenges and risks to ensure that these investments benefit them. The lack of awareness about farmers ́ rights on how the data is used, will likely lead to the unfair distribution of wealth in the agricultural sector which will increase due to Data-driven knowledge. Farmers need to feel and be engaged in their privacy and control, they seek trust and transparency in their interaction with providers and of course they would also like to receive benefits of their data, and to have access to all data. This topic is a good opportunity to start a conversation with different stakeholders by acknowledging farmers' importance in the data value chain and by exploring how they could actively contribute in the development of a fairer data governance framework.
Caroline Wanjiru Muchiri
Caroline is an intellectual property expert currently working as a Research Fellow at CIPIT- Strathmore University. She is in charge of IP and innovation research and Manager CIPIT IP Clinic. A Member, IP & Commercialisation Board Committee, Young Scientists Kenya (YSK); and Judge, Trainer, Coach and Mentor for entrepreneurs at @iBizAfrica, Kenya.Caroline is a peer reviewed writer; a World Intellectual Property (WIPO) contributor & presenter on IP, AI and data amongst others. Caroline’s research interests in Law include Innovation and Intellectual Property; Agriculture and the Law; African Feminism; Gender, Women and the Law. She is a Mentor. Mentee. A Rotarian. Amateur Farmer.
Nuanced Approach to Data Governance in Agriculture: What must be on the Agenda?
The question of agricultural data especially in Africa continues to be a subject of debate at different levels. This presentation addresses the subject using a two pronged approach: the nature of data in agriculture and gender considerations in handling such data. The presentation first categorizes data in agriculture into three classes capable of being expanded further. These categories are a) the farm data; b) farmer related data and c) the farming related data. This classification is important because it helps bring forth the nuances in the approaches to governing each data category. To govern the first category, the question on ownership of the farm or right to access the farm has to be addressed before addressing the question of data. It is in the second and the third categories the centrality of the natural person (s) undertaking the farming activities either physically or remotely becomes central. In cases of small scale farming, this person is more often than not a woman and the farming is at a subsistence and/or family level. In most cases, these farmers are not the legal owners of the farm where they are undertaking agricultural or farming activities.
The relevance of small scale farmers and farming to the development of economies in developing countries is not debatable. They contribute directly and indirectly to the countries’ GDP, provide employment etc. In most developing countries, 70% agricultural production is at the small scale level, on food crops and is done by women. Use of technology at this level has many barriers including cultural, ownership and control, perceptions and assumptions perpetuated by industry, media and so on. In contrast, commercial agriculture is dominated by men producing horticultural crops and with easy access to technologies. Should the latter dominate the conversation on data in agriculture, the dialogue would organically revolve around ownership and control as dictated by commercial forces in the market. This single-party conversation would successfully lock out the majority of the farmers in small scale farming especially for subsistence.
As the world moves to develop and adopt forth revolution and emerging technologies, the place of data becomes an ever present and pressing issue to address. The place of data has been equated to oil in the industrial revolution. Against the backdrop of 4IR, this presenter considers agricultural data as a productive resource second to if not equal to soil where the actual productivity happens. Therefore the need to have continuous conversations on access, usefulness and equal distribution of agricultural data remains crucial. However, and noting the context raised above, this conversation would be one sided should it not include gender considerations of the natural person (s) generating, using, processing and storing the data. This is especially so for the third classification of data as provided above.
Against this context, this presentation proposes a nuanced approach to the conversation on agricultural data in Africa. The aim is not to provide solutions but to open a conversation on and highlight the existing gaps in agricultural data in Africa. The presenter hopes to propose standing agenda items that would assist in steering the dialogue to achieve inclusivity in governing data in agriculture.
Leanne Wiseman is an Australian Research Council Future Fellow and Professor in Law at Griffith University, Brisbane Australia. Leanne is an interdisciplinary scholar whose research lies at the intersections of law, science and digital technologies She has most recently focused on the legal dimensions of the digitisation of agriculture in national and international contexts, examining issues around ownership control and access of agricultural data. Leanne is also currently investigating the role that IP law can play in responding to the emerging International Right to Repair movement, with a particular focus on ownership of ag data and the repair of agricultural machinery.
The merits of a mandatory data sharing scheme for Agricultural Machinery
Much has been written about the ownership control and access of agricultural data. Data codes of practice have been established and implemented however it remains to be seen how much evidence is being gathered about how these data codes of practice are changing data collection and sharing practices on farm. In 2021, the Australian Consumer and Competition Commission identified significant competition concerns in the agricultural repairs aftermarket. To address these concerns, a mandatory data sharing scheme is being proposed that will mandate the sharing of data by agricultural machinery manufacturers to ensure that farmers are able to access the data that they need to conduct repairs on their agricultural machinery or to give third party repairers access to that data. This paper will discuss the aim and merits of a mandatory as opposed to a voluntary data sharing scheme and how lessons can be learned for the sharing of agricultural data more generally.
Dr. Ivo Hostens is a bio-engineer holding a PhD in Applied Biological Sciences, by the University of Leuven, BE. After several years in technical consultancy, he joined AGORIA the Belgian Federation for the Technological Industry as senior expert in horizontal technical legislation. In this function as of 2008 he also coordinated the technical work in CEMA. Since 2015 he works full time for CEMA as technical director and defends the interests of its 7,000 European agricultural machinery manufacturers. Since 2019 the function of secretary general of EurAgEng, the European Society for Agricultural and Biosystems Engineering is also part of his duties.
Beyond the code of conduct – a tale of open collaboration
It all started with the Code of conduct on agricultural data sharing by contractual agreement. For many, including our industry it is the basis for further discussions. It puts assigning rights on data to farmers high on the agenda. Unfortunately it had no legal value.
Until now! From the legal side there is now a European commission proposal for a DATA ACT, which states to build on recent developments in specific sectors, such as the Code of Conduct on agricultural data sharing by contractual agreement. That act tries to provide more legal certainty to farmers and others, in relation to the data generated on the farm.However, the implementation of the Code of conduct and the future legal provisions will be done through technical design.
There are many aspects to be taken into account for proper data sharing with issues of safety and security, interoperability and smart contracts which would lead within the proper framework and architecture to a common European agricultural data space, a federated data space that connects the existing data platform. An EU project is in development to prepare the way.
There are different initiatives that already try to facilitate data exchange and build trust by design like AgDatahub or in relation to future AI application Agri-GAIA, two use cases linked to GAIA-X. That organization aims to build the next generation of data infrastructure: an open, transparent and secure digital ecosystem, where data and services can be made available, collated and shared in an environment of trust. It aims to ensure that data of sectors like agriculture are connected not only internally but also over other sectors in the search for new functionalities, new services, to bring more added value to the individual sectors.
When it comes to safety and security, linked with connectivity and data exchange, this is most related to mobile agricultural machinery. Also CEMA-AEF made their case with the industry initiative AgIN. With this initiative the agricultural machinery industry wants to contribute to structuring the many ongoing developments/ initiatives/ architectures, maintain legal compliance with connected products, and extend its build-up knowledge and expertise over a period of 15 years from proven concepts to the level of digital platforms.
The overall vision is to provide a sustainable and industry quality matching interoperability structure, to connect the multi coloured online platforms through harmonized technologies. More precisely a coordinated and non discriminatory governed network would be developed ensuring reliability and trust of the services in the network between agricultural software providers. This would enable them to streamline peer–to-peer interfaces to other platforms and enable their customers to use their data in any ag platform of choice.
Besides that, the network ensures trust and reliability through well known AEF security and conformance measures, two other important core elements are considered, being the development of use case solutions and a contract framework offering simplified contracting for the participants in the network.
Such a network should allow in-field data exchange, can facilitate e.g. edge computing, will keep the freedom of innovation and could also link governments systems. Within the network farmers’ rights could be embedded in the specifications for a use case, and the services related to them. We are fully committed to support with this initiative the development of a common agricultural data space. Furthermore the use cases embedded in such trustworthy reliable architecture can facilitate an ‘Agriculture of Data’ within the agricultural production processes allowing policy monitoring and evaluation in relation to the green deal and farm to fork strategies.
Mark is a Digital Ethics Researcher at Wageningen Economic Research, focusing on areas of robotics, AI, and digital developments and responsible innovation. He worked on H2020 projects, among which the SHERPA project, focused on the ethical, social and human rights implications of smart information systems (data analytics and artificial intelligence). He has published on a wide range of digital ethics topics, such as: smart cities, self-driving vehicles, agricultural data analytics, social robotics, and artificial intelligence.
Ethical and Societal Considerations for the Development and Use of Agricultural Robots
This presentation will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, through a thematic analysis of the literature. The thematic analysis will be divided based on the classifications outlined through 11 overarching principles, from an established lexicon (transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity). While research on AI agriculture is still relatively new, this presentation aims to map the debate and illustrate what the literature says in the context of social and ethical impacts. Its aim is to analyze these impacts, based on these 11 principles. This research will contrast which impacts are not being discussed in agricultural AI and which issues are not being discussed in AI ethics guidelines, but which are discussed in relation to agricultural AI. The aim of this is to identify gaps within the agricultural literature, and gaps in AI ethics guidelines, that may need to be addressed.