In recent years, there has been an exponential increase in the collection, aggregation and automated analysis of information by government and private actors. In response to this there has been significant critique regarding what could be termed 'bad' data practices in the globalised digital economy. These include the mass gathering of data about individuals, in opaque, unethical and at times illegal ways, and the increased use of that data in unaccountable and discriminatory forms of algorithmic decision-making. This edited collection has emerged from our frustration and depression over the previous years of our academic and activist careers critiquing these dystopian 'Bad Data' practices. Rather, in this text on 'Good Data' we seek to move our work from critique to imagining and articulating a more optimistic vision of the datafied future. We see many previous considerations of Bad Data practices, including our own, as only providing critiques rather than engaging constructively with a new vision of how digital technologies and data can be used productively and justly to further social, economic, cultural and political goals. The objective of the Good Data project is to start a multi-disciplinary and multi-stakeholder conversation around promoting good and ethical data practices and initiatives, towards a fair and just digital economy and society. In doing so, we combine expertise from various disciplines and sectors, including law, criminology, justice, public health, data science, digital media, and philosophy. The contributors to this text also have expertise in areas such as renewable energy, sociology, social media, digital humanities, and political science.
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