AI is often discussed in the context of incorporating ethics into automation or data analysis. This is different from AI for Good. At the AIBE Summit 2020, Manoj Saxena spoke about AI Global, which he referred to as a ‘do tank’, rather than a think tank. It was interesting to hear a perspective of a professional who grapples with the ethical considerations of AI on a daily basis. AI Global deals with issues of AI implementation discussed in previous AIBE Summit blog posts. It also goes a step further by building technical solutions to the problems posed by AI for a variety of stakeholders, open-source. This introduces another way to think about AI. It is a powerful tool and can have direct applications in creating social good.

 

What is AI for Good

 

AI for Good has a number of applications. A discussion paper by McKinsey Global Institute includes a survey of ‘160 AI social-impact use cases’, which is stated not to be comprehensive. For each case use, a breakdown is given to determine where AI has been deployed or has the potential to be deployed (see Exhibit 2). Some  important applications include health and hunger, or crisis response. Additionally, 12 cases of AI deployment are shown in the context of environment. Indeed, a quick perusal of the Intergovernmental Panel on Climate Change reports show us that the uncertainty and difficulty of creating accurate climate models. These track and predict the smallest changes in weather. According to an article by Yale Environment 360, the ‘Cloud Brain’, can “capture tiny details in a way that is hundreds of times more efficient than traditional computer programming.” This could help us make advances in climate science, and ultimately, climate policy. In the report, McKinsey ultimately breakdown use-cases identified by the UN Sustainable Development Goals.

 

An organisation called AI for Good aims to use AI as a “tool to help address some of the toughest challenges facing society today”. Founded by AI expert Kriti Sharma, this organisation applies AI to social issues. One of its’ projects, rAInbow, is designed to accompany millions who are in an abusive, controlling or unhealthy relationship. This term ‘AI for Good’ is widespread. It is also a summit organised by the UN. This is a testimony to the diversity of AI uses. For further examples, see this Forbes article: applying pesticides precisely in agriculture, identifying human rights violations, fighting Fake news, processing educational statistics for policy-makers, or helping make infrastructure more resilient to extreme weather events…If you’d like to find out more about AI for Good, you can attend regular community meetups.

 

Finally, it is important to note that AI Ethics and AI for Good are intrinsically linked. Indeed, when designing a solution which leverages the potential of AI for social good, ethical considerations come into play once more, for instance on a technical level. In a paper by researchers at Cervest, it is argued that Ethical AI Frameworks should look at systemic risks: ““technology’s impact is affected by the socio-economic and political context” and the AI for Good stakeholders should draw lessons from fields such as the financial sector and medical research. Below is a diagrammatic (non-comprehensive) representation, which shows that even in AI for Good, ethical considerations must be central.

Applying AI for Good

 

Written by Tanya Beck

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