Machine learning (ML) is a sort of artificial intelligence (AI) that allows software applications to improve their prediction accuracy without being expressly designed to do so
Machine learning is frequently used in recommendation engines. Fraud detection, spam filtering, malware threat detection, business process automation (BPA), and predictive maintenance are all common applications. Development programmes can only be successful if they are precisely targeted at individuals who are in need. However, properly targeting programmes necessitates detailed information on where the biggest needs are and who is most in need within these locations. In many cases, such information is unavailable. As a result of this problem, an increasing number of academics and research-oriented practitioners in the field of development have begun to use machine learning to guide programme targeting.
Machine learning methods have been used to develop “poverty scorecards” that can accurately predict whether a household is poor with just ten questions, measure female empowerment with just five survey questions, and target cash transfers to those in need using mobile phone metadata over the last several years. Family counsellors work with at-risk kids and their immediate families to enhance family cohesion in family-based counselling programmes. These programmes attempt to disrupt dangerous behaviours and replace them with positive and safe activities through enhancing intra-family communication, strengthening family cohesion, and linking families to community activities and after-school programmes.
However, directing these programmes toward kids who are most at risk of criminal conduct is a difficult task. SI’s Data Science team partnered with USAID’s Eastern and Southern Caribbean Mission to develop a risk assessment tool to help the Mission’s partners more accurately target these programmes towards at-risk youth, recognising the potential of machine learning methods to greatly improve strategic planning and programme targeting. Machine learning is significant because it allows businesses to see trends in customer behaviour and business operating patterns while also assisting in the development of new goods. Machine learning is at the heart of many of today’s most successful businesses, like Facebook, Google, and Uber. For many businesses, machine learning has become a crucial competitive differentiation.