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Full-Text Articles in Engineering
Administrative Law In The Automated State, Cary Coglianese
Administrative Law In The Automated State, Cary Coglianese
All Faculty Scholarship
In the future, administrative agencies will rely increasingly on digital automation powered by machine learning algorithms. Can U.S. administrative law accommodate such a future? Not only might a highly automated state readily meet longstanding administrative law principles, but the responsible use of machine learning algorithms might perform even better than the status quo in terms of fulfilling administrative law’s core values of expert decision-making and democratic accountability. Algorithmic governance clearly promises more accurate, data-driven decisions. Moreover, due to their mathematical properties, algorithms might well prove to be more faithful agents of democratic institutions. Yet even if an automated state were …
Paper Prototyping Comfortable Vr Play For Diverse Sensory Needs, Louanne E. Boyd, Kendra Day, Ben Wasserman, Kaitlyn Abdo, Gillian Hayes, Erik J. Linstead
Paper Prototyping Comfortable Vr Play For Diverse Sensory Needs, Louanne E. Boyd, Kendra Day, Ben Wasserman, Kaitlyn Abdo, Gillian Hayes, Erik J. Linstead
Engineering Faculty Articles and Research
We co-designed paper prototype dashboards for virtual environments for three children with diverse sensory needs. Our goal was to determine individual interaction styles in order to enable comfortable and inclusive play. As a first step towards an inclusive virtual world, we began with designing for three sensory-diverse children who have labels of neurotypical, ADHD, and autism respectively. We focused on their leisure interests and their individual sensory profiles. We present the results of co-design with family members and paper prototyping sessions conducted by family members with the children. The results contribute preliminary empirical findings for accommodating different levels of engagement …
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 …
Toward A Closer Integration Of Law And Computer Science, Christopher S. Yoo
Toward A Closer Integration Of Law And Computer Science, Christopher S. Yoo
All Faculty Scholarship
Legal issues increasingly arise in increasingly complex technological contexts. Prominent recent examples include the Stop Online Piracy Act (SOPA) and the Protect Intellectual Property Act (PIPA), network neutrality, the increasing availability of location information, and the NSA’s surveillance program. Other emerging issues include data privacy, online video distribution, patent policy, and spectrum policy. In short, the rapid rate of technological change has increasingly shown that law and engineering can no longer remain compartmentalized into separate spheres. The logical response would be to embed the interaction between law and policy deeper into the fabric of both fields. An essential step would …