Actionable Principles for Artificial Intelligence Policy: Three Pathways

Abstract

In the development of governmental policy for artificial intelligence (AI) that is informed by ethics, one avenue currently pursued is that of drawing on “AI Ethics Principles”. However, these AI Ethics Principles often fail to be actioned in governmental policy. This paper proposes a novel framework for the development of ‘Actionable Principles for AI’. The approach acknowledges the relevance of AI Ethics Principles and homes in on methodological elements to increase their practical implementability in policy processes. As a case study, elements are extracted from the development process of the Ethics Guidelines for Trustworthy AI of the European Commission’s “High Level Expert Group on AI”. Subsequently, these elements are expanded on and evaluated in light of their ability to contribute to a prototype framework for the development of 'Actionable Principles for AI'. The paper proposes the following three propositions for the formation of such a prototype framework: (1) preliminary landscape assessments; (2) multi-stakeholder participation and cross-sectoral feedback; and, (3) mechanisms to support implementation and operationalizability.

Public and Stakeholder Engagement in Developing Human Heritable Genome Editing Policies: What Does it Mean and What Should it Mean?

“…Many scholars have defended the need for PSE and discussed methods for effective PSE (Adashi et al, 2020;Burgess, 2014;Guston, 2014;Jasanoff, 2003 andJones, 2014;Kouper, 2010;Kyle and Dodds, 2009;Neuhaus, 2018;Nisbet, 2009;Norheim et al, 2021;Pham, 2016;Pieczka and Escobar, 2013;Selin et al, 2017;Stilgoe et al, 2014;Stix, 2021;Trench, 2006;Varner, 2014; Wilsdon and Willis, 2014). Our analysis of the literature revealed five ideals for effective PSE that should guide committees when conducting assessments and making policy recommendations or decisions regarding emerging, and especially controversial, areas of science research.…”

“…Sources: Adashi et al, 2020;Barbosa et al, 2020;Burgess, 2014;Cormick, 2009;Fisher, 2011;Guston, 2014;Haywood and Besley, 2014;Heidari et al, 2016;Irwin, 2014;Jones, 2014;Jasanoff, 2003;Jasanoff, 2004;Kyle and Dodds, 2009;Kaner et al, 2014;Kouper, 2010;Lezaun and Soneryd, 2007;Longstaff and Secko, 2016;NASEM, 2017 (p 110, 182) Pham, 2016;Posner et al, 2016;Reed et al, 2018;Scheufele et al, 2021;Selin et al, 2017;Smith et al, 2021;Stilgoe et al, 2014;Stix, 2021;Stirling, 2008;Stirling, 2012;Stix, 2021;Sturgis, 2014;van Est, 2011;Varner, 2014;Warnock, 1984;Weller et al, 2021;Wilsdon and Willis, 2014. to guide the research (Baltimore et al, 2015a;Landphier et al, 2015;Lander et al, 2019).…”

“…The ideal of comprehensiveness applies both at a broad level (when and how decision-makers call for PSE) as well as the scope of PSE efforts committees are tasked with (Fisher, 2011;Kyle and Dodds, 2009;Scheufele et al, 2021;Smith et al, 2021;Stix, 2021;van Est, 2011). One measure of the former is how far along research has progressed before PSE begins.…”

“…PSE should seek a broad range of sometimes divergent views and opinions on subjects, including people with different backgrounds, expertise or experiences (Adashi et al, 2020;Barbosa et al, 2020;Cormick, 2009;Fisher, 2011;Heidari et al, 2016;Kyle and Dodds, 2009;Neuhaus, 2018;Scheufele et al, 2021;Smith et al, 2021;Stirling, 2012;Stix, 2021;Sturgis, 2014). Each committee attempted to be inclusive.…”

Four investment areas for ethical AI: Transdisciplinary opportunities to close the publication-to-practice gap

“…There is wide consensus that AI needs some kind of government regulation, even among leaders of well-resourced AI-heavy organizations like Microsoft, Google, and IBM (Kharpal, 2020). Nonetheless, like AI product teams, policymakers report that Ethical AI principles have had disappointingly little impact on the creation of policy in practice (Stix, 2021). Enforced Ethical AI public policy could reduce the Publication-to-Practice gap in at least three important ways.…”