Embedding gender in the development of digital agriculture technology to achieve sustainable global development goals

The promise of data-driven and digital agriculture

Data-driven and digital agriculture is seen as a set of disruptive technologies with wide-ranging potential to transform food systems and affect the lives of billions. Mechanization, apps, and artificial intelligence promise better harvests and food production through self-driving tractors, drones, and big data analytics, while making agriculture climate resilient and more sustainable across political and cultural boundaries.

Advances in sensors, connectivity, technology use and analytical capabilities are seen as solutions how technology can improve food systems. Digitization can therefore increase productivity and reduce waste in agriculture and food systems by overcoming technical barriers and providing transparent information. Looking at reality, however, we see an ever increasing (digital) divide in the agricultural sector between rural and urban areas as well as the Global North and Global South. It is becoming increasingly aware that the political, social, and cultural implications of technological advancement are as important as the creation of technology itself. Unintended consequences of technologies are real but often not adequately accounted for.

Gender for development: More than just a data point

As one preeminent example, gender and digital agriculture innovation are closely connected. Gender roles and norms can shape how individuals engage with technology and how they benefit or are excluded from an innovation through various ways:

1. Access to digital technologies: Women farmers, especially in developing countries, often have limited access to digital technologies due to factors such as social norms, lack of digital skills, and limited access to finance. Even though significant improvements were achieved over the last decades, the remaining gap still limits their ability to benefit from digital agriculture innovation.

2. Unequal distribution of benefits: Women farmers also face challenges in accessing farming resources, educational services, and markets, which limits their ability to benefit from digital agriculture innovation. This can perpetuate gender inequalities in agriculture.

3. Role in decision-making: Gender roles and norms can influence women’s participation in decision-making processes related to agricultural production and digital innovation. Women may have less decision-making power within households or communities, which can limit their ability to adopt new technologies or participate in digital agriculture programs.

Besides these challenges, digital innovation can also help to bridge existing gender divides and realize benefits for women farmers by enabling needs-specific capabilities, mentoring and communication approaches.

Policy Options/Recommendations

Gender-sensitive approaches to agriculture technology can help to ensure that women farmers benefit equally from these by considering the specific needs and constraints of women farmers, when designing, implementing, and evaluating digital agriculture technology programs. Gender should therefore be embedded in the policy and development environment for digital agriculture technology to achieve sustainable global development goals both in the US and globally through various options:

1. Increase equitable access to resources and information: Policies are needed to increase women’s access to agricultural technologies, including credit, extension services, and information and communication technologies (ICTs). Governments could invest in providing information and training on the use of agriculture technologies to women farmers. This could include training on how to operate equipment, use mobile apps, and access information through online platforms.

2. Promote gender-sensitive research and development: Social and cultural norms can limit women’s access to and use of technology. Governments could work to address these barriers by promoting gender equality and empowerment through education campaigns and policy changes. Governments could encourage research and development of gender-inclusive agriculture technologies by funding projects that consider the different needs and constraints of women and men in the agricultural sector.

3. Provide financial support and encourage private sector engagement: Women farmers often face more significant financial constraints than men due to gender-based discrimination. Governments could provide financial support for women to invest in agriculture technologies, such as through subsidies, grants, or loans with favorable terms. Governments could work with the private sector to develop and distribute gender-inclusive agriculture technologies. This should include promoting public-private partnerships and providing incentives for companies to develop technologies that benefit women farmers.

Conclusion

There is a net benefit to these measures, as current non-inclusive technologies have vast indirect cost to societies, for example an estimated reduction of USD 1 trillion in GDP in the overall digital economy of low- and middle-income countries.

Overall, gender-inclusive agriculture technology requires a multifaceted approach that addresses social, cultural, economic, and political factors that contribute to gender-based disparities in the agricultural sector. By implementing these policy changes, governments can help to promote gender equity and improve the productivity and livelihoods of women farmers. With climate change, a growing world population and still people suffering from hunger, there is an urgent need for improvements in our food system.

This agricultural example highlights the general importance of sound policy and development frameworks, even for seemingly straight-forward and clear-defined engineering innovations. Policies must be advanced to support systemic changes, global data streams, system integration and a holistic consideration of both culture and context in designing and implementing the new tools, technologies, and business models. Interdisciplinary work and cross-sector collaboration will be driving this transformation and must be mandated in the policy design process.