AI attacks

AI for Good

Artificial Intelligence (AI) has grown exponentially in recent decades, becoming a tool with great potential for positive impact in fighting loneliness, curbing the food crisis, improving the diagnosis and treatment of diseases or predicting natural disasters, among many other areas.

The convergence of powerful algorithms, advanced computing capacity and the availability of large volumes of data has allowed AI to solve complex problems in sustainability and humanitarian aid with an effectiveness and scalability that are hard to match.

Despite its potential, AI faces various challenges. Although another AI winter seems unlikely, unequal access to technology and distrust could leave various sections of the population out of its benefits. Made worse by the fact that the third sector, traditionally the leader of initiatives for social good, tends to lag behind in technological innovation.

To address these challenges, it is necessary to encourage collaboration between governments, NGOs, companies and academia to promote inclusive AI, ensuring that technologies reach every community and adapt to their needs. Some keys:

1. From hype to reality: not every problem has its ideal solution in AI. In AI for social good, the first steps could be in the following areas. a) There is no AI without data: a prior analysis of the quantity and quality of the information to be analysed is essential to assess the reliability and impact of the results returned by AI. The third sector must ensure the efficient collection and handling of data in order to benefit from the advantages of AI now and in the future. b) Internal agility and efficiency: applying AI to administration and internal processes can have a greater positive impact on optimising resources than applying it directly to the causes that different organisations champion.

2. Protecting rights: it is essential to establish solid regulatory frameworks that protect people’s privacy and rights and that consider ethical issues related to automated decision-making and algorithmic bias. In humanitarian aid, where the work is with especially vulnerable populations, it is key to promote transparency and accountability in the development and use of AI algorithms.

3. Training and talent: investing in training programmes and promoting collaboration between AI experts and specialists in climate change, conservation, education and so on is key to developing effective and ethical solutions. Initiatives for the common good cannot and must not be left out of technological development.

AI can play a fundamental role in building a more sustainable and fairer future for everyone, as long as we keep in mind that this is its purpose and work to achieve it.