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A Data Ethics Framework for Agriculture

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  • Full or part time
    Dr K Shields
    Dr Jonathan Hillier
    Dr L Boden
    Mr Graham Mullier
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

This PhD project will develop a framework for the ethical regulation of agricultural data based on legal and ethical grounds, focussing on power asymmetries between different actors in the food and agriculture ecosystem: farmers, food supply chain companies, large agribusinesses and governments and large pan-national NGOs.

With the onset of new data technologies, the agricultural data sector is growing at an accelerating speed. With the encroaching use of machine learning algorithms to process such data we are moving towards an interconnected and automated farming and food data ecosystem. Much of this data is sensitive proprietary data and public data, which may be exploited for public and private gain.

Whilst some businesses are collecting enormous volumes of agricultural data to provide “precision” solutions to support efficient agricultural production, others in the horizontal and vertical supply chains are collecting data from farmers to assess environmental impacts and to identify farming practices and use of agricultural inputs which are more sustainable and resilient to future climates and resultant threats from new and emerging diseases and pests.

Behind the data, farmers and agricultural livelihoods are often invisible, potentially vulnerable to exploitation and often excluded from the benefits of improved data metrics; of farmers and others exclude themselves from benefits through uncertainty about how their data may be used. A comprehensive data ethics framework for agriculture applicable across regional jurisdictions is therefore urgently needed to ensure that the agricultural data ecosystem develops in an equitable and sustainable manner.

Research Questions may include

1. Should agricultural data be viewed as a public good?

2. How can the benefits of data in agriculture be shared amongst all stakeholders including farmers, consumers, food distributers and others in the value chain, plus academia and society as a whole?

3. How might risk and responsibility for agriculture data ecosystems be managed?

4. What constitutes good practice for managing data activities when they have the potential to impact individual people and wider society?

5. How might an ethical framework for the governance of data in agriculture be created?

Methodology:

Research will begin by identifying the risks of increased power asymmetries between different actors in the food and agriculture ecosystem: farmers, food supply chain companies, large agribusinesses and governments and large pan-national NGOs.

Research methodology will be structured as follows:
• Year 1: Desk-based survey of systems, practices and trends in agricultural data; development of legal and ethical grounds for the establishment of an ethical framework in the sector; review of existing initiatives including their aims and objectives, successes and failure in the agricultural data sector and in adjacent sectors such as consumer data, land use data.
• Year 2: Field work including surveys and interviews of key stakeholders; integration of field work findings into a variety of ethical framework models; review and refinement of proposed frameworks with stakeholders.
• Year 3: Identification of pathways for adoption of the proposed ethical framework into national, regional and international policy frameworks.

Comprehensive training programme comprising both specialist scientific training and generic transferable and professional skills and on ethics assessment will be provided. Mixed methods research training, reference management, especially on qualitative data collection and analysis with be provided. The student will have the opportunity to present their research at national and international conferences and will be supported in writing first author publications during the PhD. S/he will be more widely supported through networks within and beyond the University of Edinburgh, such as the postgrad cohort at the Global Academy of Agriculture and Food Security and the Edinburgh Futures Institute.

We seek a student with:

• A good first degree (at least 2:1), and a Masters or equivalent experience in a subject area cognate to the project (law, policy, politics or related social science subject).
• An interest in, and some knowledge of data privacy and ethics, and relevant data policies
• Prior study, experience, or demonstration of interest in normative ethics, preferably in the context of agriculture although training can be providing if necessary
• A strong interest in multidisciplinary research, teaching, and collaboration with partners within and beyond academia
• Ability to work with people in different roles and organisations
• Ability to manage self and workload within competing deadlines.
• Ability to communicate effectively orally, in writing and through social media for various audiences (e.g. academic publications, practitioners and policy-makers, users of services).
• Study or experience in data science, digital methods, and/or innovative research methods is desirable although training can be provided.



Funding Notes

Queries regarding project-specific eligibility should be directed to relevant project lead supervisors. General enquiries can be directed to [Email Address Removed] (University of Edinburgh)

Email applications to [Email Address Removed]

Required documentation:
- Personal statement
- CV
- 2 references (at least 1 academic reference)
- Degree transcripts (translations should be provided if the originals are not in English)
- Evidence of English Language Proficiency (if relevant).

Documentation to be combined as a PDF document.

Applicants must meet the English Language requirements of the University of Edinburgh

References

Ryan, M. Agricultural Big Data Analytics and the Ethics of Power. J Agric Environ Ethics 33, 49–69 (2020).

Ryan, M. (2019). Ethics of Using AI and Big Data in Agriculture: The Case of a Large Agriculture Multinational. ORBIT Journal, 2(2).

Sung, Jehoon (2018). The Fourth Industrial Revolution and Precision Agriculture, Automation in Agriculture - Securing Food Supplies for Future Generations, IntechOpen, 10.5772/intechopen.71582. https://www.intechopen.com/books/automation-in-agriculture-securing-food-supplies-for-future-generations/the-fourth-industrial-revolution-and-precision-agriculture

UN OHCHR (2018). A Human Rights Based Approach to Data - Leaving No One Behind in the 2030 Agenda for Sustainable Development. UN OHCHR publications. https://www.ohchr.org/Documents/Issues/HRIndicators/GuidanceNoteonApproachtoData.pdf


Key facts
· Open to home, EU and international students
· Tuition Fee and 4 years stipend at UKRI rates (estimated to be in the region of £15,245 for 2020/21)
· Annual research support budget of £2,000
· Deadline: noon, 15th May 2020

While the selected student will be supervised within the School, they will also take part in collaborative cohort activities as one of five Ph.D. students in the Edinburgh Futures Institute’s Baillie Gifford programme in the Ethics of Data and Artificial Intelligence. Headed by Shannon Vallor, the first Baillie Gifford Chair in the Ethics of Data and Artificial Intelligence (EFI), the aim of this programme is to cultivate multi-disciplinary skills and knowledge in the application of ethical values to data-driven technologies. More broadly, the goal is to develop the shared vocabulary and methodologies needed to support new models of education and research into the complex challenges and opportunities that data and AI present.

Please note: We are aware that circumstances surrounding COVID-19 may require arrangements for remote interviews by videoconference; the Edinburgh Futures Institute will adapt our recruitment procedures for these positions as necessary to remain in observance of current public health guidance.

Information for prospective students who have applied to study at the University of Edinburgh can be found on the following link:

https://www.ed.ac.uk/news/covid-19/prospective-students


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