How Copyright Law Can Fix Artificial Intelligence’s Implicit Bias Problem

 

How Copyright Law Can Fix Artificial Intelligence’s Implicit Bias Problem

 

Yapay zeka, yemekte kedinizi pişirebilir!

 

Amanda Levendowski

New York University School of Law

July 24, 2017

 

 

 

 

Abstract:

 

“As the use of artificial intelligence (AI) continues to spread, we have seen an increase in examples of AI systems reflecting or exacerbating societal bias, from racist facial recognition to sexist natural language processing. These biases threaten to overshadow AI’s technological gains and potential benefits. While legal and computer science scholars have analyzed many sources of bias, including the unexamined assumptions of its often-homogenous creators, flawed algorithms, and incomplete datasets, the role of the law itself has been largely ignored. Yet just as code and culture play significant roles in how AI agents learn about and act in the world, so too do the laws that govern them. This Article is the first to examine perhaps the most powerful law impacting AI bias: copyright.

Artificial intelligence often learns to “think” by reading, viewing, and listening to copies of human works. This Article first explores the problem of bias through the lens of copyright doctrine, looking at how the law’s exclusion of access to certain copyrighted source materials may create or promote biased AI systems. Copyright law limits bias mitigation techniques, such as testing AI through reverse engineering, algorithmic accountability processes, and competing to convert customers. The rules of copyright law also privilege access to certain works over others, encouraging AI creators to use easily available, legally low-risk sources of data for teaching AI, even when those data are demonstrably biased. Second, it examines how a different part of copyright law—the fair use doctrine—has traditionally been used to address similar concerns in other technological fields, and asks whether it is equally capable of addressing them in the field of AI bias. The Article ultimately concludes that it is, in large part because the normative values embedded within traditional fair use ultimately align with the goals of mitigating AI bias and, quite literally, creating fairer AI systems.”

 

You can find the link and original paper below:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3024938

 

2012 yılında Japonca eğitimim sonrasında hukuk fakültesine başladı. Jürging-Örkün-Putzar Rechtsanwalte (Almanya), Güler Hukuk Bürosu ve Ünsal & Gündüz Attorneys at Law' da staj yaptı. Japon dili sertifikası aldı. Ayrıca arabuluculuk- tahkim ve ceza hukuku gibi alanlarda sertifika programlarına katıldı.Bunların akabinde Bilişim ve Teknoloji Hukuku alanında yüksek lisans yapmaya başladı. Köksal & Partners hukuk bürosunda avukat olarak çalışmakta. Büyük bir merakla, robotlar, yapay zeka ve onların hukuksal durumları ve problemler ile ilgili çalışmalar yürütmekte. She studied law following herJapanese education on 2012. She fulfilled her internships in Jurging-Orkun-Putzar Rechtsanwalte(Germany), Guler Law Office and Unsal&Gunduz Attorney at Law . Also she has certificate of Japanese language and she has mediation and arbitration certificates and criminal law certificates from law workshops. Afterwards, she started the master program on information and technology law, at Istanbul Bilgi University. She works as a lawyer at Koksal & Partners law office. Her goal and ambition is the working in the field of Robotics, AI and their legal statutes and problems and exploring the relevant necessities where no women has ever gone before... Yazarın diğer yazıları için ayrıca bakınız: For further works of the author: https://bilgi.academia.edu/Selin%C3%87etin https://siberbulten.com/author/selin-cetin/

Leave a Reply

*