The Future of Funding: What are the priorities and directions of Australian grantmakers? copy

The SmartyGrants Innovation Lab evaluated a dignity lens analytic tool released in 2021 by the Centre for Public Impact as an ethics framework. This white paper demonstrates how the tool was applied retrospectively to help the SmartyGrants Innovation Lab audit each decision made in CLASSIEfier’s development.

Summary

SmartyGrants launched the text auto-classification system CLASSIEfier in 2021 to classify grantmaking records on behalf of grantmakers and other social sector supporters, with a view to tracking the flow of money in Australia by sector, location and beneficiary. The algorithm became a pilot for ethical considerations in artificial intelligence (AI) systems.

When building the algorithm, we faced several ethical considerations. For example, what is the correct way to handle grant data without breaching confidentiality and data privacy? What degree of model accuracy is acceptable? How do we overcome human, data and algorithm bias? How involved should data experts and data owners be?

To improve the performance of the algorithm, the Innovation Lab has taken several steps to facilitate transparency, explainability, interpretability, stakeholder engagement, testing and incorporation of feedback. This white paper frames the decisions we made in terms of their impact on dignity, using the dignity lens analytic tool developed by Lorenn Ruster and Thea Snow and published in partnership with the Centre for Public Impact.

This white paper demonstrates how we used the dignity lens retrospectively; that is, after decisions had already been made. In the future, we expect to use it earlier in the AI development process, as a planning and design tool.

How we used the dignity lens analytic tool

During the development of CLASSIEfier, the Innovation Lab made decisions through brainstorming and team consensus. The Dignity lens analytic tool has been valuable for documenting the ethical questions we faced and the resolutions we took. We found that the tool can adapt to auto-classification and artificial intelligence systems as well as other data-driven projects, such as data visualisation, insight reports, survey design and more.

Ethics of automated classification COVER

Furthermore:

  • The dignity lens assists us to achieve a balance between protective and proactive mechanisms
  • The dignity lens helps us address all 10 essential elements of dignity
  • The dignity lens enables us to give adequate consideration to all stages of AI development
  • The dignity lens provides a language for discussion and debate
  • The dignity lens gives us confidence and a way of documenting our decisions so we can continually improve

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