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Articles 1 - 13 of 13
Full-Text Articles in Computer Law
Submission To The Province Of Nova Scotia On Its Review Of The Intimate Images And Cyber-Protection Act - Leaf, Suzie Dunn, Rosel Kim
Submission To The Province Of Nova Scotia On Its Review Of The Intimate Images And Cyber-Protection Act - Leaf, Suzie Dunn, Rosel Kim
Reports & Public Policy Documents
The Women’s Legal Education and Action Fund (LEAF) commends the Nova Scotia government for reviewing its Intimate Images and Cyber-protection Act (the Act) and seeking public input for this review. Nova Scotia has been, and continues to be, a leader in Canada for its role in advancing innovative laws and supports for people targeted by technology-facilitated violence (TFV), digital abuse, and the non-consensual distribution of intimate images (NCDII). As these forms of harmful behaviour evolve and become better understood, it is important to revisit this legislation to assess whether it is providing meaningful and accessible responses to such serious social …
Models, Race, And The Law, Moon Duchin, Douglas M. Spencer
Models, Race, And The Law, Moon Duchin, Douglas M. Spencer
Publications
Capitalizing on recent advances in algorithmic sampling, The Race-Blind Future of Voting Rights explores the implications of the long-standing conservative dream of certified race neutrality in redistricting. Computers seem promising because they are excellent at not taking race into account—but computers only do what you tell them to do, and the rest of the authors’ apparatus for measuring minority electoral opportunity failed every check of robustness and numerical stability that we applied. How many opportunity districts are there in the current Texas state House plan? Their methods can give any answer from thirty-four to fifty-one, depending on invisible settings. But …
Artificial Intelligence And The Challenges Of Workplace Discrimination And Privacy, Pauline Kim, Matthew T. Bodie
Artificial Intelligence And The Challenges Of Workplace Discrimination And Privacy, Pauline Kim, Matthew T. Bodie
Scholarship@WashULaw
Employers are increasingly relying on artificially intelligent (AI) systems to recruit, select, and manage their workforces, raising fears that these systems may subject workers to discriminatory, invasive, or otherwise unfair treatment. This article reviews those concerns and provides an overview of how current laws may apply, focusing on two particular problems: discrimination on the basis of protected characteristics like race, sex, or disability, and the invasion of workers’ privacy engendered by workplace AI systems. It discusses the ways in which relying on AI to make personnel decisions can produce discriminatory outcomes and how current law might apply. It then explores …
Accessible Websites And Mobile Applications Under The Ada: The Lack Of Legal Guidelines And What This Means For Businesses And Their Customers, Josephine Meyer
Accessible Websites And Mobile Applications Under The Ada: The Lack Of Legal Guidelines And What This Means For Businesses And Their Customers, Josephine Meyer
Seattle University Law Review SUpra
No abstract provided.
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. …
Big Data And Artificial Intelligence: New Challenges For Workplace Equality, Pauline Kim
Big Data And Artificial Intelligence: New Challenges For Workplace Equality, Pauline Kim
Scholarship@WashULaw
This essay contains remarks delivered in a keynote speech at the University of Louisville Brandeis School of Law’s 35th Annual Carl A. Warns and Edwin R. Render Labor and Employment Law Institute. Big data and artificial intelligence are increasingly being used by employers in their human resources processes in ways that control access to employment opportunities. This essay describes some of those developments and explains how practices like targeted online recruitment strategies and the use of hiring algorithms to screen applicants raise a significant risk of discriminating against protected groups such as women and racial minorities. It then considers some …
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
Regulating By Robot: Administrative Decision Making In The Machine-Learning Era, Cary Coglianese, David Lehr
All Faculty Scholarship
Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others …
Ancient Worries And Modern Fears: Different Roots And Common Effects Of U.S. And Eu Privacy Regulation, David Thaw, Pierluigi Perri
Ancient Worries And Modern Fears: Different Roots And Common Effects Of U.S. And Eu Privacy Regulation, David Thaw, Pierluigi Perri
Articles
Much legal and technical scholarship discusses the differing views of the United States and European Union toward privacy concepts and regulation. A substantial amount of effort in recent years, in both research and policy, focuses on attempting to reconcile these viewpoints searching for a common framework with a common level of protection for citizens from both sides of Atlantic. Reconciliation, we argue, misunderstands the nature of the challenge facing effective cross-border data flows. No such reconciliation can occur without abdication of some sovereign authority of nations, that would require the adoption of an international agreement with typical tools of international …
Data-Driven Discrimination At Work, Pauline Kim
Data-Driven Discrimination At Work, Pauline Kim
Scholarship@WashULaw
A data revolution is transforming the workplace. Employers are increasingly relying on algorithms to decide who gets interviewed, hired, or promoted. Although data algorithms can help to avoid biased human decision-making, they also risk introducing new sources of bias. Algorithms built on inaccurate, biased, or unrepresentative data can produce outcomes biased along lines of race, sex, or other protected characteristics. Data mining techniques may cause employment decisions to be based on correlations rather than causal relationships; they may obscure the basis on which employment decisions are made; and they may further exacerbate inequality because error detection is limited and feedback …
Auditing Algorithms For Discrimination, Pauline Kim
Auditing Algorithms For Discrimination, Pauline Kim
Scholarship@WashULaw
This Essay responds to the argument by Joshua Kroll, et al., in Accountable Algorithms, 165 U.PA.L.REV. 633 (2017), that technical tools can be more effective in ensuring the fairness of algorithms than insisting on transparency. When it comes to combating discrimination, technical tools alone will not be able to prevent discriminatory outcomes. Because the causes of bias often lie, not in the code, but in broader social processes, techniques like randomization or predefining constraints on the decision-process cannot guarantee the absence of bias. Even the most carefully designed systems may inadvertently encode preexisting prejudices or reflect structural bias. For this …
Electronic Communications Privacy Act And The Revolution In Cloud Computing : Hearing Before The Subcomm. On The Constitution, Civil Rights, And Civil Liberties Of The H. Comm. On The Judiciary, 111th Cong., Sept. 23, 2010 (Statement By Adjunct Professor Marc J. Zwillinger, Geo. U. L. Center), Marc J. Zwillinger
Testimony Before Congress
ECPA has functioned fairly well during its first 20 years in striking the right balance between law enforcement needs and the privacy expectation of U.S. citizens. But when it was initially passed in 1986, Congress recognized that the “law must advance with the technology to ensure the continued vitality of the fourth amendment.” Based on my experience as an ECPA practitioner for the past 13 years, I believe the time is ripe for another advancement. I hope you will consider these perspectives in crafting legislation that balances law enforcement needs and user privacy in a manner that reflects the reality …
Student Comprehension Of Privacy Issues In Sns, Collaborative Project
Student Comprehension Of Privacy Issues In Sns, Collaborative Project
Dyson College- Seidenberg School of CSIS : Collaborative Projects and Presentations
This entry adheres to the use of the quad chart template to provide for a succint description only of the current research project undertaken by the participants. It provides for the following information:
1. Participant/s
2. Overall project goals
3. Illustrative picture/s
4.Specific research/artistic/pedagogic foci