The Data Pollution & Power (DPP) Initiative is set up at the Bonn University’s Institute for Science and Ethics’ Sustainable AI Lab to explore the power dynamics that shape the data pollution of AI across the UN Sustainable Development Goals. DataEthics.eu is dissemination partner ensuring that the DPP Initiative is anchored in fields of practice.
See more about the initiative here
The DPP Initiative will run from June 2021 to May 2022 and has two components:
The DPP Group
The DPP Group is a cross-disciplinary group with diverse expertise and interests that cut across several of the UN Sustainable Development Goals. The core aim of the group is to debate, scope out, map and explore the interrelation of the data pollution of AI holistically across the goals. See members here.
The DPP White Paper
The DPP white paper will investigate data pollution as the interrelated (big) data adverse effects on the UN sustainable development goals. In particular it will look at the power dynamics and interests in the data of AI that determine how data resources are handled and distributed in data eco systems. To be published in May 2022.
What is Data Pollution about?
Conversation between DataEthics.eu co-founder Gry Hasselbalch, who is also working independently as the Data Pollution & Power Principal Investigator and Professor Aimee van Wynsberghe, founder of the Bonn University’s Institute for Science and Ethics’ Sustainable AI Lab.
I was thinking about the way in which the concept of ‘sustainability’ was articulated in response to the adverse impact on our physical environment in the Industrial Age and how this took form over the last 50 years. This idea of tackling something very concrete like pollution became a driver for entire new legal and policy frameworks, national and international environmental laws; it transformed industries, like the car industry, and drove forward the development of new industries and sciences, like ‘green tech’. We are in a similar process right now when it comes to data pollution.
We have had policy and public debates on the privacy and social implications of big data since the early 2000s, we are having more serious conversations about the carbon foot prints of data storage and processing, and we have also in society started a conversation about the main power actors in this field. However, there is very little awareness about data pollution as an ‘environmental problem’ or as a disturbance of an entire ‘eco system’.
What we need is a new green movement for data pollution, but for this to happen, we need a better understanding of the power dynamics that shape the field across different data pollution issues. Because power struggles and negotiations are core components of sociotechnical change and governance.
There are a lot of interests invested in the data of AI, and also a lot of hype about how AI can transform not only humanity, but the entire planetary eco-system for the better with the development of AI to achieve the UN Sustainable Development Goals. Here, I really like the way you, Aimee, frame the power dynamics of this debate by emphasising the sustainability of AI instead of just for sustainability.
Can you tell me more about this?
I’m happy to tell you more about this Gry. For me, I see a huge increase in the use of AI to solve environmental concerns like energy reduction or predicting natural disasters and this is referred to as AI for sustainability. But it feels as if no one knows (and maybe it’s being hidden from us on purpose) that the creation and application of AI itself creates an environmental impact; training and using AI algorithms creates carbon emissions. In a time when the world should be limiting carbon emissions it seems counterintuitive to me that we would use a technology that is itself unsustainable, to solve problems of sustainability.
My goal is to investigate sustainability as an issue of AI ethics and to explore what happens if we place sustainability as the dominant value in AI development and implementation. Hence, I am interested in the sustainablity of AI; of making and using AI products. Interestingly, to do this we need to know more about the environmental impact of AI. And this is where I think there is an interesting discussion to be had re power dynamics.
First, I don’t think it should be the sole responsibility of the consumer to limit their use of AI products. Of course we, the consumer, should be more aware and should limit ourselves, but it shouldn’t be just up to us. Second, governments need to start demanding that AI companies measure the carbon emissions from training and using AI. At a certain point we may have to think about a carbon cap or limiting the kind of things we use AI for once we know the extent of the damage being done. So who has the power, who should have the power, who should be limited and to what extent? These are the questions we should be asking now in order to re calibrate the asymmetry in power that we currently see when it comes to the collection and use of data.