12 monthsProgramme duration
25,320 GBPTuition Fee/year
SepStarting Month
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc Artificial Intelligence (AI) and Sustainability at SOAS explores the complex and evolving relationship between AI technologies and environmental, socio-economic and macrofinancial sustainability. Designed for students who wish to engage critically with the links between AI and sustainability, the programme combines rigorous training in the data science foundations of AI with a deep understanding of its broader societal implications.
AI is reshaping economies and societies worldwide. The rapidly expanding AI infrastructure carries a substantial environmental footprint that exacerbates the environmental crisis, while the potential of AI to support more efficient use of natural resources remains uncertain. From a socio-economic perspective, AI is transforming labour markets with potentially adverse effects on inequalities, employment and the distribution of power. The rapid expansion of AI also raises pressing ethical issues that need to be assessed through a social justice lens. At the macrofinancial level, the surge in often debt-financed investment in AI technologies may drive economic growth in the coming years, but can also lead to financial bubbles and generate financial instability. Crucially, all these implications of AI for sustainability vary significantly across regions and countries, shaped by local economic, social, environmental and institutional contexts.
Drawing on SOAS’s world-leading research and distinctive regional expertise, the programme equips students to engage critically with cutting-edge academic and policy debates on AI and sustainability. Alongside this critical perspective, students gain hands-on experience with machine learning and other data science methods through the analysis of real-world datasets and applications. This integrated approach – combining technical skills, sustainability analysis, and a global, context-sensitive perspective – prepares graduates to play a leading role in addressing sustainability challenges in the age of AI.
AI is reshaping economies and societies worldwide. The rapidly expanding AI infrastructure carries a substantial environmental footprint that exacerbates the environmental crisis, while the potential of AI to support more efficient use of natural resources remains uncertain. From a socio-economic perspective, AI is transforming labour markets with potentially adverse effects on inequalities, employment and the distribution of power. The rapid expansion of AI also raises pressing ethical issues that need to be assessed through a social justice lens. At the macrofinancial level, the surge in often debt-financed investment in AI technologies may drive economic growth in the coming years, but can also lead to financial bubbles and generate financial instability. Crucially, all these implications of AI for sustainability vary significantly across regions and countries, shaped by local economic, social, environmental and institutional contexts.
Drawing on SOAS’s world-leading research and distinctive regional expertise, the programme equips students to engage critically with cutting-edge academic and policy debates on AI and sustainability. Alongside this critical perspective, students gain hands-on experience with machine learning and other data science methods through the analysis of real-world datasets and applications. This integrated approach – combining technical skills, sustainability analysis, and a global, context-sensitive perspective – prepares graduates to play a leading role in addressing sustainability challenges in the age of AI.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The MSc Artificial Intelligence (AI) and Sustainability at SOAS explores the complex and evolving relationship between AI technologies and environmental, socio-economic and macrofinancial sustainability. Designed for students who wish to engage critically with the links between AI and sustainability, the programme combines rigorous training in the data science foundations of AI with a deep understanding of its broader societal implications.
AI is reshaping economies and societies worldwide. The rapidly expanding AI infrastructure carries a substantial environmental footprint that exacerbates the environmental crisis, while the potential of AI to support more efficient use of natural resources remains uncertain. From a socio-economic perspective, AI is transforming labour markets with potentially adverse effects on inequalities, employment and the distribution of power. The rapid expansion of AI also raises pressing ethical issues that need to be assessed through a social justice lens. At the macrofinancial level, the surge in often debt-financed investment in AI technologies may drive economic growth in the coming years, but can also lead to financial bubbles and generate financial instability. Crucially, all these implications of AI for sustainability vary significantly across regions and countries, shaped by local economic, social, environmental and institutional contexts.
Drawing on SOAS’s world-leading research and distinctive regional expertise, the programme equips students to engage critically with cutting-edge academic and policy debates on AI and sustainability. Alongside this critical perspective, students gain hands-on experience with machine learning and other data science methods through the analysis of real-world datasets and applications. This integrated approach – combining technical skills, sustainability analysis, and a global, context-sensitive perspective – prepares graduates to play a leading role in addressing sustainability challenges in the age of AI.
AI is reshaping economies and societies worldwide. The rapidly expanding AI infrastructure carries a substantial environmental footprint that exacerbates the environmental crisis, while the potential of AI to support more efficient use of natural resources remains uncertain. From a socio-economic perspective, AI is transforming labour markets with potentially adverse effects on inequalities, employment and the distribution of power. The rapid expansion of AI also raises pressing ethical issues that need to be assessed through a social justice lens. At the macrofinancial level, the surge in often debt-financed investment in AI technologies may drive economic growth in the coming years, but can also lead to financial bubbles and generate financial instability. Crucially, all these implications of AI for sustainability vary significantly across regions and countries, shaped by local economic, social, environmental and institutional contexts.
Drawing on SOAS’s world-leading research and distinctive regional expertise, the programme equips students to engage critically with cutting-edge academic and policy debates on AI and sustainability. Alongside this critical perspective, students gain hands-on experience with machine learning and other data science methods through the analysis of real-world datasets and applications. This integrated approach – combining technical skills, sustainability analysis, and a global, context-sensitive perspective – prepares graduates to play a leading role in addressing sustainability challenges in the age of AI.
Admission Requirements
6.5+
120+
2.7+
5+
65+
We will consider all applications with 2:2 (or international equivalent) or higher in any discipline that does not incorporate a strong data science component. In addition to degree classification, we take into account other elements of the application such as your supporting statement. References are optional but can help build a stronger application if you fall below the 2:2 requirement or have non-traditional qualifications.
1 Year
Sep
Tuition fees
Domestic
12,965 GBP
International
25,320 GBP
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