SDG-2

SDG-2 Zero Hunger

Main
SDG-2

Targets of Goal 2

By 2030, it is necessary to achieve the following targets:

End hunger and ensure a healthy, nutritious and sufficient nourishment.
Put an end to all forms of malnutrition
Double farming productivity and the income of small-scale food producers.
Guarantee the sustainability of food production systems and apply resilient agriculture practices that increase productivity.

We can currently advance towards the attainment of this goal:

How does technology contribute to this SDG? See what we propose and tell us what you think

Lessons Learnt

We have analyzed the literature and extracted the following ideas on how technologies are favouring this SDG.
See also what we propose and tell us what you think

L.1

AI and Machine Learning-based based Early Warning Systems could play a very versatile role in various targets linked to this SDG, as they enable: identifying areas/households under risk of famine, detecting problems or anomalies in agricultural processes that may endanger food security, the production of sufficient food, etc.

L.2

The platforms for shared and accessible data, along with transparent governance processes through AI and blockchain are - similarly as in SDG 1 - important driving forces to tackle the challenges related to food access for everyone, as well as the promotion of better agricultural processes guided by big data.

L.3

There are still relatively little advances on the use of AI and digital technologies to propel sustainable, responsible and healthy eating habits among the population.

Recommendations

The proposed actions on which we introduce an opinion poll for this SDG, are described below:

Poll for SDG-2

The analyses of interrelationships between emerging technologies & AI, and the possibilities they offer to pursue the SDGs, led us to propose a series of actions and/or potential projects to develop.
Among these recommendations, which one is more important in your opinion?

Give my opinion

R2.1 - Accessible platforms for data integration in agricultural-food production

Several studies highlight the enormous importance of data, both in their availability and the quality of them, to optimally exploit solutions based on AI that address SDG-related problems about hunger. It is proposed, therefore, that both institutions and public entities must promote the creation of large data integration platforms on agricultural production and processes leading to food access by the whole population.

R2.2 - Equality-aware decisions for food sustenance through governance and Big Data

The availability, quality and infrastuctures with abundant data should play an important role in designing governance systems envisaged towards managing food shortage risk situations and helping make decisions pertaining action plans in cases of famine, problems affecting crops, livestock, food supply chains, etc. Likewise, we recommending deeming other aspects in these AI-based governance systems, e.g.: (1) ensuring a fair share of food resources; (2) minimizing losses of food stocks for human consumption; and (3) fostering equal access to the adoption of digital technology tools by small farmers to reduce the digital breach in this sector.

R2.3 - Traceable food production and supply under Artificial Intelligence and Blockchain

In processes linked to supply chain and food provision, there exist latent problems such as avoiding food waste and losses of food originally aimed at human consumption, ensuring transparency in the aforesaid supply chain, etc. In order to guarantee food safety we propose establishing reliable traceability tools based on blockchain to help monitoring the food lifecycle from its generation upon farming or livestock processes, up to their distribution and sale to end consumers.

R2.4 - Early Warning Systems to anticipate to risks in safe food sustenance

The consequences of not predicting and acting with enough celerity against potential events may pose great food losses and have devastating consequences specially in developing countries and/or vulnerable communities and households. For this reason, we propose positioning early warning systems as a priority tool to join research, development and innovation efforts on through AI and digital technologies.

R2.5 - Promoting sustainable, healthy and responsible eating across the population

Having secured food access does not necessarily guarantee that some individuals or communities benefit from a healthy eating lifestyle for themselves and their environment. Sustainability related to food provision must also address fostering sustainable, healthy and responsible eating habits with the local and global environment. In this sense, there exist AI and data science tools with much to contribute. For instance, by using models based on recommender systems combined with models for learning consumption, preferences and habits, it would be possible to approach the general population by providing them personalized nourishment suggestions that adapt to their preferences and at the same time are aligned with more sustainable eating practices.