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Articles 1 - 8 of 8
Full-Text Articles in Computer Law
The Failure Of Market Efficiency, William Magnuson
The Failure Of Market Efficiency, William Magnuson
Faculty Scholarship
Recent years have witnessed the near total triumph of market efficiency as a regulatory goal. Policymakers regularly proclaim their devotion to ensuring efficient capital markets. Courts use market efficiency as a guiding light for crafting legal doctrine. And scholars have explored in great depth the mechanisms of market efficiency and the role of law in promoting it. There is strong evidence that, at least on some metrics, our capital markets are indeed more efficient than they have ever been. But the pursuit of efficiency has come at a cost. By focusing our attention narrowly on economic efficiency concerns—such as competition, …
Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba
Algorithmic Governance From The Bottom Up, Hannah Bloch-Wehba
Faculty Scholarship
Artificial intelligence and machine learning are both a blessing and a curse for governance. In theory, algorithmic governance makes government more efficient, more accurate, and more fair. But the emergence of automation in governance also rests on public-private collaborations that expand both public and private power, aggravate transparency and accountability gaps, and create significant obstacles for those seeking algorithmic justice. In response, a nascent body of law proposes technocratic policy changes to foster algorithmic accountability, ethics, and transparency.
This Article examines an alternative vision of algorithmic governance, one advanced primarily by social and labor movements instead of technocrats and firms. …
Transparency's Ai Problem, Hannah Bloch-Wehba
Transparency's Ai Problem, Hannah Bloch-Wehba
Faculty Scholarship
A consensus seems to be emerging that algorithmic governance is too opaque and ought to be made more accountable and transparent. But algorithmic governance underscores the limited capacity of transparency law—the Freedom of Information Act and its state equivalents—to promote accountability. Drawing on the critical literature on “open government,” this Essay shows that algorithmic governance reflects and amplifies systemic weaknesses in the transparency regime, including privatization, secrecy, private sector cooptation, and reactive disclosure. These deficiencies highlight the urgent need to reorient transparency and accountability law toward meaningful public engagement in ongoing oversight. This shift requires rethinking FOIA’s core commitment to …
A Unified Theory Of Data, William Magnuson
A Unified Theory Of Data, William Magnuson
Faculty Scholarship
How does the proliferation of data in our modern economy affect our legal system? Scholars that have addressed the question have nearly universally agreed that the dramatic increases in the amount of data available to companies, as well as the new uses to which that data is being put, raise fundamental problems for our regulatory structures. But just what those problems might be remains an area of deep disagreement. Some argue that the problem with data is that current uses lead to discriminatory results that harm minority groups. Some argue that the problem with data is that it impinges on …
Beyond Transparency And Accountability: Three Additional Features Algorithm Designers Should Build Into Intelligent Platforms, Peter K. Yu
Faculty Scholarship
In the age of artificial intelligence, innovative businesses are eager to deploy intelligent platforms to detect and recognize patterns, predict customer choices and shape user preferences. Yet such deployment has brought along the widely documented problems of automated systems, including coding errors, corrupt data, algorithmic biases, accountability deficits and dehumanizing tendencies. In response to these problems, policymakers, commentators and consumer advocates have increasingly called on businesses seeking to ride the artificial intelligence wave to build transparency and accountability into algorithmic designs.
While acknowledging these calls for action and appreciating the benefits and urgency of building transparency and accountability into algorithmic …
Beyond Algorithms: Toward A Normative Theory Of Automated Regulation, Felix Mormann
Beyond Algorithms: Toward A Normative Theory Of Automated Regulation, Felix Mormann
Faculty Scholarship
The proliferation of artificial intelligence in our daily lives has spawned a burgeoning literature on the dawn of dehumanized, algorithmic governance. Remarkably, the scholarly discourse overwhelmingly fails to acknowledge that automated, non-human governance has long been a reality. For more than a century, policymakers have relied on regulations that automatically adjust to changing circumstances, without the need for human intervention. This article surveys the track record of self-adjusting governance mechanisms to propose a normative theory of automated regulation.
Effective policymaking frequently requires anticipation of future developments, from technology innovation to geopolitical change. Self-adjusting regulation offers an insurance policy against the …
Artificial Financial Intelligence, William Magnuson
Artificial Financial Intelligence, William Magnuson
Faculty Scholarship
Recent advances in the field of artificial intelligence have revived long-standing debates about what happens when robots become smarter than humans. Will they destroy us? Will they put us all out of work? Will they lead to a world of techno-savvy haves and techno-ignorant have-nots? These debates have found particular resonance in finance, where computers already play a dominant role. High-frequency traders, quant hedge funds, and robo-advisors all represent, to a greater or lesser degree, real-world instantiations of the impact that artificial intelligence is having on the field. This Article will argue that the primary danger of artificial intelligence in …
The Algorithmic Divide And Equality In The Age Of Artificial Intelligence, Peter K. Yu
The Algorithmic Divide And Equality In The Age Of Artificial Intelligence, Peter K. Yu
Faculty Scholarship
In the age of artificial intelligence, highly sophisticated algorithms have been deployed to provide analysis, detect patterns, optimize solutions, accelerate operations, facilitate self-learning, minimize human errors and biases and foster improvements in technological products and services. Notwithstanding these tremendous benefits, algorithms and intelligent machines do not provide equal benefits to all. Just as the digital divide has separated those with access to the Internet, information technology and digital content from those without, an emerging and ever-widening algorithmic divide now threatens to take away the many political, social, economic, cultural, educational and career opportunities provided by machine learning and artificial intelligence. …