| Title |
The Future of Global Poverty |
| ID_Doc |
75421 |
| Authors |
Juech, C; Onike, C |
| Title |
The Future of Global Poverty |
| Year |
2018 |
| Published |
|
| DOI |
10.5117/9789462987241_ch07 |
| Abstract |
To achieve the first of the Sustainable Development Goals - to end poverty in all of its forms everywhere by 2030 - will require more than business as usual. Despite uncertain global economic growth we have the financial resources to end extreme poverty. We know more, can predict more, and ultimately can better target the extreme poor. Social entrepreneurship models, machine learning, and robotics are pushing the envelope of what we can do. Using three scenarios, the chapter illustrates what poverty could look like in 2030. Our success will ultimately depend on the levels of global cooperation around conflicts and climate change, economic growth that benefits all segments of society, and the inclusion of minorities and previously excluded groups. |
| Author Keywords |
extreme poverty; SDGs; poverty scenarios; social exclusion; fragile states; innovative finance; machine learning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Book Citation Index – Social Sciences & Humanities (BKCI-SSH) |
| EID |
WOS:000518680000009 |
| WoS Category |
Social Sciences, Interdisciplinary |
| Research Area |
Social Sciences - Other Topics |
| PDF |
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