The Imperative of Good Data in AI Ethics

Author: Alain Álvarez

Date: 08-02-2024

Introduction to Good Data

In the digital age, the ethical implications of artificial intelligence (AI) are a topic of intense debate and concern. Angela Daly, S. Kate Devitt, and Monique Mann's seminal work, "AI Ethics Needs Good Data," propels this conversation forward, highlighting the often overlooked aspect of data quality in AI systems. The authors argue for a paradigm shift towards 'Good Data'—a concept that ensures data used in AI is not only accurate and relevant but also ethically sourced and utilized.

The Shortcomings of Current AI Ethics Frameworks

The chapter begins with a critical evaluation of existing AI ethics frameworks. Daly, Devitt, and Mann assert that these frameworks are too narrow, focusing mainly on immediate ethical dilemmas without considering the broader socio-political and environmental ramifications of AI. They point out the lack of enforceability of these frameworks and call for a more inclusive approach that addresses the power imbalances and privileges inherent in AI development.

A Call for Social and Environmental Justice

The heart of their argument lies in the integration of social and environmental justice into AI ethics. The authors propose that Good Data practices must prioritize the empowerment of marginalized communities and the minimization of environmental impact. This approach requires acknowledging and acting upon the complex web of relationships between data, technology, and society, ensuring that AI serves as a tool for positive societal change rather than exacerbating existing inequalities.

Implementing Good Data Practices

To move towards a more ethical use of AI, Daly, Devitt, and Mann suggest practical steps for integrating Good Data practices. This includes fostering community engagement in AI development, ensuring the usability of AI systems for diverse populations, and advocating for political action to regulate and guide AI technologies towards equitable outcomes. The authors emphasize the importance of a collective effort among technologists, policymakers, and communities to redefine the ethical landscape of AI.

Conclusion: Towards a Future of Ethical AI

"AI Ethics Needs Good Data" is a clarion call to reevaluate the foundations upon which AI ethics stand. By centering the conversation around Good Data, Daly, Devitt, and Mann invite us to envision a future where AI technologies are developed with a deep commitment to justice, inclusivity, and sustainability. This chapter is a must-read for anyone involved in AI development, offering a comprehensive framework for navigating the ethical challenges of the digital future.

Through their insightful analysis and actionable recommendations, the authors provide a roadmap for constructing an AI ecosystem that respects human dignity, promotes social equity, and safeguards our planet. As we continue to advance in our technological capabilities, let us take these lessons to heart and commit to building a world where AI serves all of humanity, guided by the principles of Good Data.

Source: Daly, A et al. 2021. AI Ethics Needs Good Data. In: Verdegem, P (ed.), AI for Everyone?. London: University of Westminster Press. DOI:

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