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In modern democracies, governmental transparency is thought to have great value. When it comes to addressing administrative corruption and mismanagement, many would agree with Justice Brandeis’s observation that sunlight is the best disinfectant. Beyond this, many credit transparency with enabling meaningful citizen participation. But even though transparency appears highly correlated with successful governance in developed democracies, assumptions about administrative transparency have remained empirically untested. Testing effects of transparency would prove particularly helpful in developing democracies where transparency norms have not taken hold or only have done so slowly. In these contexts, does administrative transparency really create the sorts of benefits attributed to it? Transparency might grease the gears of developed democracies, but what good is grease when many of the gears seem to be broken or missing entirely? This Article presents empirical results from a first-of-its-kind field study that tested two major promises of administrative transparency in a developing democracy: that transparency increases public participation in government affairs and that it increases government accountability. To test these hypotheses, we used two randomized controlled trials. Surprisingly, we found transparency had no significant effect in almost any of our quantitative measurements, although our qualitative results suggested that when transparency interventions exposed corruption, some limited oversight could result. Our findings are particularly significant for developing democracies and show, at least in this context, that Justice Brandeis may have oversold the cleansing effects of transparency. A few rays of transparency shining light on government action do not disinfect the system and cure government corruption and mismanagement. Once corruption and mismanagement are identified, it takes effective government institutions and action from civil society to successfully act as a disinfectant.
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The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization’s Algorithms
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Concerns about the risks and harms posed by artificial intelligence (AI) have resulted in significant study into algorithmic transparency, giving rise to a sub-field known as Explainable AI (XAI). Unfortunately, despite a decade of development in XAI, an existential challenge remains: progress in research has not been fully translated into the actual implementation of algorithmic transparency by organizations. In this work, we test an approach for addressing the challenge by creating transparency advocates, or motivated individuals within organizations who drive a ground-up cultural shift towards improved algorithmic transparency.Over several years, we created an open-source educational workshop on algorithmic transparency and advocacy. We delivered the workshop to professionals across two separate domains to improve their algorithmic transparency literacy and willingness to advocate for change. In the weeks following the workshop, participants applied what they learned, such as speaking up for algorithmic transparency at an organization-wide AI strategy meeting. We also make two broader observations: first, advocacy is not a monolith and can be broken down into different levels. Second, individuals' willingness for advocacy is affected by their professional field. For example, news and media professionals may be more likely to advocate for algorithmic transparency than those working at technology start-ups.more » « less
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Concerns about the risks and harms posed by artificial intelligence (AI) have resulted in significant study into algorithmic transparency, giving rise to a sub-field known as Explainable AI (XAI). Unfortunately, despite a decade of development in XAI, an existential challenge remains: progress in research has not been fully translated into the actual implementation of algorithmic transparency by organizations. In this work, we test an approach for addressing the challenge by creating transparency advocates, or motivated individuals within organizations who drive a ground-up cultural shift towards improved algorithmic transparency. Over several years, we created an open-source educational workshop on algorithmic transparency and advocacy. We delivered the workshop to professionals across two separate domains to improve their algorithmic transparency literacy and willingness to advocate for change. In the weeks following the workshop, participants applied what they learned, such as speaking up for algorithmic transparency at an organization-wide AI strategy meeting. We also make two broader observations: first, advocacy is not a monolith and can be broken down into different levels. Second, individuals' willingness for advocacy is affected by their professional field. For example, news and media professionals may be more likely to advocate for algorithmic transparency than those working at technology start-ups.more » « less
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The paper proposes to study the onset of color transparency in hard exclusive reactions in the backward regime. Guided by the encouraging Jefferson Laboratory (JLab) results on backward π and ω electroproduction data at moderate virtuality Q2, which may be interpreted as the signal of an early scaling regime, where the scattering amplitude factorizes in a hard coefficient function convoluted with nucleon to meson transition distribution amplitudes, the study shows that investigations of these channels on nuclear targets opens a new opportunity to test the appearance of nuclear color transparency for a fast-moving nucleon.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3544549.3574169
