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Transparency And Algorithmic Governance, Cary Coglianese, David Lehr
Transparency And Algorithmic Governance, Cary Coglianese, David Lehr
All Faculty Scholarship
Machine-learning algorithms are improving and automating important functions in medicine, transportation, and business. Government officials have also started to take notice of the accuracy and speed that such algorithms provide, increasingly relying on them to aid with consequential public-sector functions, including tax administration, regulatory oversight, and benefits administration. Despite machine-learning algorithms’ superior predictive power over conventional analytic tools, algorithmic forecasts are difficult to understand and explain. Machine learning’s “black-box” nature has thus raised concern: Can algorithmic governance be squared with legal principles of governmental transparency? We analyze this question and conclude that machine-learning algorithms’ relative inscrutability does not pose a …
The Tax Treatment Of Tokens: What Does It Betoken?, David J. Shakow
The Tax Treatment Of Tokens: What Does It Betoken?, David J. Shakow
All Faculty Scholarship
Digital tokens have been used to raise substantial amounts of money. But little attention has been paid to the tax consequences surrounding their issuance and sale. There are significant potential tax liabilities lurking in the use of digital tokens. But, because of the anonymity inherent in the blockchain structures used for the issuance of tokens and payments for them, there is a significant question as to whether those tax liabilities will ever be collected.