“The World Bank Unveiled” tells the story of an attempt by World Bank researcher David Shaman and some of his colleagues to introduce greater transparency into the deliberations of the World Bank.
In 1999, at a time when the Bank was subject to intense controversy and public demonstrations, Shaman co-created the internet-based B-SPAN, which offered unedited videos of internal Bank discussions and debates. “We began B-SPAN as a way to increase the Bank’s transparency. We believed by doing so we would increase people’s understanding of what the Bank did, increase opportunities for the Bank to be more accountable to its critics, and thereby mute tensions on all sides.”
The 688-page book details the development of this transparency initiative from the author’s perspective, and describes its early success as well as the opposition that it quickly engendered.
“I decided to write The World Bank Unveiled because I believe it will provide an opportunity for those who want a more open and accountable institution to overcome an internal culture wedded to secrecy and a bureaucracy married to the status quo,” said Mr. Shaman. “If this should occur, the ultimate winners will be those millions who currently live in poverty because they will then have a more effective advocate on their behalf.”
See “The World Bank Unveiled: Inside the Revolutionary Struggle for Transparency” by David Ian Shaman, Parkhurst Brothers Inc. Publishers, 2009.
Commercial artificial intelligence tools have recently emerged that are able to produce police reports. If the resulting reports are inaccurate, incomplete or biased, or if the process leaks confidential information, this could undermine the criminal justice system and harm citizens.
Too often, affected patients, clinicians, and regulators cannot see how the system works, why a decision was made, or whether meaningful human oversight occurred.
Existing tools from other domains, such as existing robust public engagement processes in drug development, when applied to AI deployment can help strengthen public trust in these systems and enhance perceptions of their legitimacy and the decisions they produce.
With thoughtful policy action, it is still possible to build systems that are fair, transparent, and accountable, and to earn the public trust that will ultimately determine AI’s future. We hope policymakers are ready to act.