Table of Links Abstract and 1. Introduction 2. Related Work 3. Theoretical Lenses 3.1. Handoff Model 3.2. Boundary objects 4. Applying the Theoretical Lenses and 4.1 Handoff Triggers: New tech, new threats, new hype 4.2. Handoff Components: Shifting experts, techniques, and data 4.3. Handoff Modes: Abstraction and constrained expertise 4.4 Handoff Function: Interrogating the how and 4.5. Transparency artifacts at the boundaries: Spaghetti at the wall 5. Uncovering the Stakes of the Handoff 5.1. Confidentiality is the tip of the iceberg 5.2. Data Utility 5.3. Formalism 5.4. Transparency 5.5. Participation 6. Beyond the Census: Lessons for Transparency and Participation and 6.1 Lesson 1: The handoff lens is a critical tool for surfacing values 6.2 Lesson 2: Beware objects without experts 6.3 Lesson 3: Transparency and participation should center values and policy 7. Conclusion 8. Research Ethics and Social Impact 8.1. Ethical concerns 8.2. Positionality 8.3. Adverse impact statement Acknowledgments and References 8 RESEARCH ETHICS AND SOCIAL IMPACT 8.1 Ethical concerns 8.1.1 Methods. To the best of our understanding, there are no significant ethical concerns inherent to this work, as it is based in analysis of only publicly available documents. No interviews or sensitive data were collected for this paper. As such, no IRB approval was sought, as this work does not interface with human subjects. 8.1.2 Fairness. As we undertook our analysis, we took care to consider and portray the opinions of the various communities involved as fairly and equitably as possible, while understanding that some of these communities have been in active disagreement around the specifics of the 2020 DAS for years. Due to representation in the public archive and space limitations, we acknowledge that we were not able to represent every stakeholder viewpoint nor every notable event in the history of the Bureau’s DP implementation. 8.2 Positionality All four authors are U.S. citizens. While we are all thus implicated in matters of American legislative representation and voting rights, we all also reside in well-resourced regions which are not threatened by census undercounts or exclusion, nor by active infringements upon voting rights. One author participated in processes around the 2020 DAS in real time; the other three became involved the project post-2020, and do not belong to any of the primary stakeholder groups that were most active in the census debate. One author is trained in computer science, two in the mathematical and physical sciences, and one as a lawyer; these backgrounds informed our comprehension of and perspectives on the legal and technical processes at play. 8.3 Adverse impact statement The primary adverse impact that this work could have would be playing into the hands of those who would weaponize the census for political gain. Given the heavily politicized nature of the census in general, and of the DP debate in particular, we cannot anticipate how or whether this work could be used to undermine the legitimacy of the census. Further, given the importance of the census for essential societal processes such as redistricting and resource allocation (which we address in our paper), we cannot dismiss the potential for such weaponization as inconsequential. Unfortunately, there is indeed precedent for such adverse impact. During the DAS development process, the Bureau faced direct political threats to its data products, the most serious of which arose in March 2021 when the state of Alabama sued the Department of Commerce and the Census Bureau in federal district court, alleging that by adopting DP the Bureau had “manipulated” and “intentionally skewed” the redistricting data that they provided to states [1]. Furthermore, the coincidence of the decennial count with the 2020 presidential election, as well as the uncertainty around the Trump administration’s proposal to include a citizenship question on the census, drew political attention to the count. In a time when political actors were searching for any chinks in governmental armor, a Federal agency which was public about internal sources of error became an easy target. Indeed, the Bureau has faced bipartisan scrutiny for the troubles made evident by the implementation of DP – including allegations that DP was a Trump administration tactic attempting to ‘game’ federal funding allocations, and directly contradictory allegations that DP was a Democratic tactic to destabilize the Trump administration [18, p. 32]. Of course, such critiques undermine the ultimate role of the Bureau - to produce representative population counts - and further muddy the already-cloudy waters when it comes to identifying an appropriate implementation of DP. Ultimately, we believe that the benefits that publishing our analysis might provide - hopefully, insights for both more effective algorithmic governance and more critical algorithmic scholarship - outweigh any potential risks for further weaponization. Authors:
(1) AMINA A. ABDU, University of Michigan, USA;
(2) LAUREN M. CHAMBERS, University of California, Berkeley, USA;
(3) DEIRDRE K. MULLIGAN, University of California, Berkeley, USA;
(4) ABIGAIL Z. JACOBS, University of Michigan, USA. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Related Work 2. Related Work 3. Theoretical Lenses 3.1. Handoff Model 3.1. Handoff Model 3.2. Boundary objects 3.2. Boundary objects 4. Applying the Theoretical Lenses and 4.1 Handoff Triggers: New tech, new threats, new hype 4. Applying the Theoretical Lenses and 4.1 Handoff Triggers: New tech, new threats, new hype 4.2. Handoff Components: Shifting experts, techniques, and data 4.2. Handoff Components: Shifting experts, techniques, and data 4.3. Handoff Modes: Abstraction and constrained expertise 4.3. Handoff Modes: Abstraction and constrained expertise 4.4 Handoff Function: Interrogating the how and 4.5. Transparency artifacts at the boundaries: Spaghetti at the wall 4.4 Handoff Function: Interrogating the how and 4.5. Transparency artifacts at the boundaries: Spaghetti at the wall 5. Uncovering the Stakes of the Handoff 5. Uncovering the Stakes of the Handoff 5.1. Confidentiality is the tip of the iceberg 5.1. Confidentiality is the tip of the iceberg 5.2. Data Utility 5.2. Data Utility 5.3. Formalism 5.3. Formalism 5.4. Transparency 5.4. Transparency 5.5. Participation 5.5. Participation 6. Beyond the Census: Lessons for Transparency and Participation and 6.1 Lesson 1: The handoff lens is a critical tool for surfacing values 6. Beyond the Census: Lessons for Transparency and Participation and 6.1 Lesson 1: The handoff lens is a critical tool for surfacing values 6.2 Lesson 2: Beware objects without experts 6.2 Lesson 2: Beware objects without experts 6.3 Lesson 3: Transparency and participation should center values and policy 6.3 Lesson 3: Transparency and participation should center values and policy 7. Conclusion 7. Conclusion 8. Research Ethics and Social Impact 8.1. Ethical concerns 8.1. Ethical concerns 8.2. Positionality 8.2. Positionality 8.3. Adverse impact statement 8.3. Adverse impact statement Acknowledgments and References Acknowledgments and References 8 RESEARCH ETHICS AND SOCIAL IMPACT 8.1 Ethical concerns 8.1.1 Methods. To the best of our understanding, there are no significant ethical concerns inherent to this work, as it is based in analysis of only publicly available documents. No interviews or sensitive data were collected for this paper. As such, no IRB approval was sought, as this work does not interface with human subjects. 8.1.1 Methods. 8.1.2 Fairness. As we undertook our analysis, we took care to consider and portray the opinions of the various communities involved as fairly and equitably as possible, while understanding that some of these communities have been in active disagreement around the specifics of the 2020 DAS for years. Due to representation in the public archive and space limitations, we acknowledge that we were not able to represent every stakeholder viewpoint nor every notable event in the history of the Bureau’s DP implementation. 8.1.2 Fairness. 8.2 Positionality All four authors are U.S. citizens. While we are all thus implicated in matters of American legislative representation and voting rights, we all also reside in well-resourced regions which are not threatened by census undercounts or exclusion, nor by active infringements upon voting rights. One author participated in processes around the 2020 DAS in real time; the other three became involved the project post-2020, and do not belong to any of the primary stakeholder groups that were most active in the census debate. One author is trained in computer science, two in the mathematical and physical sciences, and one as a lawyer; these backgrounds informed our comprehension of and perspectives on the legal and technical processes at play. 8.3 Adverse impact statement The primary adverse impact that this work could have would be playing into the hands of those who would weaponize the census for political gain. Given the heavily politicized nature of the census in general, and of the DP debate in particular, we cannot anticipate how or whether this work could be used to undermine the legitimacy of the census. Further, given the importance of the census for essential societal processes such as redistricting and resource allocation (which we address in our paper), we cannot dismiss the potential for such weaponization as inconsequential. Unfortunately, there is indeed precedent for such adverse impact. During the DAS development process, the Bureau faced direct political threats to its data products, the most serious of which arose in March 2021 when the state of Alabama sued the Department of Commerce and the Census Bureau in federal district court, alleging that by adopting DP the Bureau had “manipulated” and “intentionally skewed” the redistricting data that they provided to states [1]. Furthermore, the coincidence of the decennial count with the 2020 presidential election, as well as the uncertainty around the Trump administration’s proposal to include a citizenship question on the census, drew political attention to the count. In a time when political actors were searching for any chinks in governmental armor, a Federal agency which was public about internal sources of error became an easy target. Indeed, the Bureau has faced bipartisan scrutiny for the troubles made evident by the implementation of DP – including allegations that DP was a Trump administration tactic attempting to ‘game’ federal funding allocations, and directly contradictory allegations that DP was a Democratic tactic to destabilize the Trump administration [18, p. 32]. Of course, such critiques undermine the ultimate role of the Bureau - to produce representative population counts - and further muddy the already-cloudy waters when it comes to identifying an appropriate implementation of DP. Ultimately, we believe that the benefits that publishing our analysis might provide - hopefully, insights for both more effective algorithmic governance and more critical algorithmic scholarship - outweigh any potential risks for further weaponization. Authors: (1) AMINA A. ABDU, University of Michigan, USA; (2) LAUREN M. CHAMBERS, University of California, Berkeley, USA; (3) DEIRDRE K. MULLIGAN, University of California, Berkeley, USA; (4) ABIGAIL Z. JACOBS, University of Michigan, USA. Authors: Authors: (1) AMINA A. ABDU, University of Michigan, USA; (2) LAUREN M. CHAMBERS, University of California, Berkeley, USA; (3) DEIRDRE K. MULLIGAN, University of California, Berkeley, USA; (4) ABIGAIL Z. JACOBS, University of Michigan, USA. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv available on arxiv

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