Published: November, 2020 DOI: https://doi.org/10.1016/S2542-5196(20)30254-0
The world is transitioning into a data-driven era, where algorithms can influence anything from our health-care services, consumer behaviour, and even national and international environmental decisions. Fears around the embedded bias and discrimination seen in algorithms has motivated an Environmental Data Justice movement of citizens, researchers, and technical practitioners who aim to make data more equitable.
Growth of data
As we navigate the climate crisis, we find that the scale of the challenges we face, like the ecosystems they threaten, are vast. One way researchers aim to deal with this scale and complexity is through the development and application of powerful computational techniques that can tap into underutilised and highly diverse environmental data sets. From finding better ways to manage resources, forecasting future crises, and tracking progress against the Sustainable Development Goals, a growing proportion of “the next generation of environmental scientists are data scientists”. With big corporations advocating for the continued growth of such data, energised by the prospect of conquering a greater percentage of “untapped” sources such as imagery, social media feeds, emails, journals, and videos, the echoes of our Western history of “exploration”, “discovery”, and empire should not be ignored. With a growing abundance of data, the real task is often knowing how best to use it. But as many, emboldened by notions like innovation and breakthrough, focus on efficiency, is there enough thought spared for equality?
As data becomes ever more pervasive in our lives and instances of prejudice and discrimination as a result of technology become more frequent, there is growing pressure from a community of researchers, activists, and artificial intelligence (AI) practitioners to make Environmental Data Justice (EDJ) a top priority. Motivated by the capacity for data, much of which is generated by companies and governments, to perpetuate social norms and status quo that often share roots in oppression, researchers in the EDJ field aim to create future technologies that enable greater wellbeing, with the goal of beneficence and justice for all. One overarching and fundamental concern in the data justice field is the ability of data and AI practitioners to decide what and whose knowledge and data is counted as valid, and what goes ignored and unquestioned, identifying it as a form of power that should not continue to operate without critique.
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