Artificial intelligence is often believed to have a detrimental effect on employment. However, when reviewing employment forecasts from The U.S. Bureau of Labor Statistics, no information could be found indicating whether they considered the potential impact of artificial intelligence on employment. This thesis aims to examine the relationship between the 2022 employment forecasts and the artificial intelligence exposure measure for occupations developed by Felten, Raj and Seamans (2021) in “Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses” to determine if there is a significant correlation between the two. Using a dataset of 669 observations resulting from matching occupations using their standard occupational classification codes (SOC), a strong correlation was observed. Yet, it remains unclear whether this is due to deliberately accounting for artificial intelligence or any other factors. Nor can it be asserted that this correlation accurately depicts the continuously evolving job market.

This study was intended to investigate the nature of child labour, continued causes and effects of child labour on development initiatives, establishing the magnitude of the problem and make recommendations for intervention. It was generally established that child labour is a hindrance to developmental programmes by negatively affecting the targeted next generations. The high rate of child labour was mainly attributed to poverty, HIV/AIDS, low incomes, culture, weak laws, invisible phenomenon, population growth, armed conflict, limited access to education opportunities, employment, gender, social attitudes and ignorance, irresponsible parenthood, agriculture and orphan hood. Solutions suggested to child labour included; stronger government intervention, training and awareness raising, further research and adopting a zero-tolerance for child labour. Facilitation of the Universal Primary Education Programme to be improved and stronger bye-laws should to be adopted. / Development Studies / M. A. (Development Studies)

This study was intended to investigate the nature of child labour, continued causes and effects of child labour on development initiatives, establishing the magnitude of the problem and make recommendations for intervention. It was generally established that child labour is a hindrance to developmental programmes by negatively affecting the targeted next generations. The high rate of child labour was mainly attributed to poverty, HIV/AIDS, low incomes, culture, weak laws, invisible phenomenon, population growth, armed conflict, limited access to education opportunities, employment, gender, social attitudes and ignorance, irresponsible parenthood, agriculture and orphan hood. Solutions suggested to child labour included; stronger government intervention, training and awareness raising, further research and adopting a zero-tolerance for child labour. Facilitation of the Universal Primary Education Programme to be improved and stronger bye-laws should to be adopted. / Development Studies / M. A. (Development Studies)