4 Best Practices for Responsible Data in Agriculture
July 18, 2017 Editor 0
The agriculture sector is creating increasing amounts of data, from many different sources. From tractors equipped with GPS tracking, to open data released by government ministries, data is becoming ever more valuable, as agricultural business development and global food policy decisions are being made based upon data.
But the sector is also home to severe resource inequality. The largest agricultural companies make billions of dollars per year, in comparison with subsistence farmers growing just enough to feed themselves, or smallholder farmers who grow enough to sell on a year-by-year basis.
When it comes to data and technology, these differences in resources translate to stark power imbalances in data access and use. The most well resourced actors are able to delve into new technologies and make the most of those insights, whereas others are unable to take any such risks or divert any of their limited resources.
Access to and use of data has radically changed the business models and behaviour of some of those well resourced actors, but in contrast, those with fewer resources are re- ceiving the same, limited access to information that they always have.
In Responsible Data in Agriculture, Lindsay Ferris and Zara Rahman for The Engine Room have approached these issues from a responsible data perspective, drawing upon the experience of the Responsible Data community who over the past three years have created tools, questions and resources to deal with the ethical, legal, privacy and security challenges that come from new uses of data in various sectors.
Through their interviews and desk research, there were four best practices suggested as ways to mitigate the responsible data challenges mentioned above. Many of these are not unique to the agriculture sector, but rather speak to broad responsible data best practices writ large.
Education and awareness
One of the biggest differences between people we spoke to was how they perceived the effects of publishing data. Broadly speaking, those coming from the open data perspective were keen to publish everything apart from personally identifiable information.
Others, especially those working with small- holder farmers, or indigenous populations, were much more aware that publishing data would benefit only the better-resourced actors in the agriculture sector, and expressed serious concerns about the potential unintended consequences of publishing data about, for example, indigenous populations.
They were keen to emphasise that much more needs to happen in addition to making data available as online open data for farmers to make use of it – including educating farmers on their rights to data and information, and strengthening their capacity to make use of information to inform their practices.
Establishing and regularly reviewing policies
Proactive recognition of the inequalities at play when it comes to data use in the agriculture sector is a prerequisite to ensuring that new data uses are sure to mitigate, rather than strengthen, these inequalities.
Some organisations are doing this via focused policies, such as CGIAR’s Open Access and Data Management Policy. In the international development sector, Oxfam has developed a Responsible Data policy, which looks at their internal management and use of data to ensure they are working in a responsible and ethical way. There is a lot of potential for re-use of items within these policies to reduce the burden of developing a new policy from scratch.
Given the quickly moving field and fast-changing technologies available, it is essential to regularly review these policies to ensure they are still valid. For example, as the cost of satellite imagery drops, access will undoubtedly increase and so the considerations around actors using satellite imagery will need to be re-evaluated.
Strengthening and enabling rights of vulnerable people
Within the sector, vulnerable communities are most at risk of being put at a further disadvantage as a result of the increased use and influx of data. One way of countering this is by focusing on strengthening rights of those groups, such as farmers’ rights.
The Privacy and Security Principles for Farm data, a declaration signed by 37 ATPs as of March 2016, marks the beginning of integrating actionable practices into data collection and use by companies. However, unless farmers have the awareness and resources to defend their rights, there can be no accountability for principles like these. International organizations need to recognise this, and train their members on how to advocate for their rights as well as better understand the use of their information.
Prioritising contextual considerations
In many of the responsible data challenges and tensions outlined above, the importance of context in making appropriate and responsible decisions cannot be underestimated. Even when a certain dataset is deemed publishable in one context, the same information in another context might have very different consequences.
In many cases, choices around how best to disseminate information are being made based upon existing information systems and cultural under- standings of various technologies. In some cases, radio remains the best way to communicate with farmers working in rural situations. In others, with high levels of mobile penetration, SMS or IVR is best.
In order to make these kinds of decisions in a responsible way, sharing the decision-making responsibility with people from the communities themselves seems to be the best way of ensuring no harm or negative unintended consequences. Co-design methods and collaboration early on in the data sharing process is also recommended as a way of getting solid buy-in from relevant communities.
Go to SourceReprinted from ICTWorks
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Tags: Data in Agriculture
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