Welcome to the Clearinghouse Project Library, where we highlight seminal and impactful articles focused on AI and its intersection with law, work, and society. Explore our searchable database of legal scholarly articles related to AI.
Featured Topics
- AI and Administrative Work
- AI and Criminal Justice
- AI and Education
- AI and Employment
- AI and Financial systems
- AI and Health
- AI, Immigration, and Human Rights
- AI Regulation and Strategies
- AI and Surveillance
- International/Comparative Regulation
- Al and War
- Al Race Law
- AI and Business
- AI and Creative Work
- Al and ESG
- AI and Medicine
- AI and Police Work
- AI and Managerial Work
- AI and White Collar Work
- AI and Blue Collar Work
We also introduce books, documentary films, and other media that have been created to address legal issues stemming from the use of automated decision-making. We hope that this clearinghouse will serve as a useful resource for a wide array of stakeholders including: legal scholars, practitioners, media, and students of AI and the Law at every level.
Explore Our Collection
Use the search function to discover articles, books, documentary films, and other media related to AI and the Future of Work, exploring the legal challenges and implications in various sectors.
241.
Crootof, Rebecca
The Killer Robots Are Here: Legal and Policy Implications Journal Article
In: Cardozo Law Review, vol. 36, no. 5, pp. 1837–1916, 2014.
Abstract | Links | BibTeX | Tags: AI and War
@article{crootof_killer_2014,
title = {The Killer Robots Are Here: Legal and Policy Implications},
author = {Rebecca Crootof},
url = {https://heinonline.org/HOL/P?h=hein.journals/cdozo36&i=1943},
year = {2014},
date = {2014-01-01},
urldate = {2024-10-22},
journal = {Cardozo Law Review},
volume = {36},
number = {5},
pages = {1837–1916},
abstract = {In little over a year, the possibility of a complete ban on autonomous weapon systems — known colloquially as “killer robots” — has evolved from a proposal in an NGO report to the subject of an international meeting with representatives from over eighty states. However, no one has yet put forward a coherent definition of autonomy in weapon systems from a law of armed conflict perspective, which often results in the conflation of legal, ethical, policy, and political arguments. To address this problem and to assist future treaty negotiators, this Article proposes that an “autonomous weapon system” be defined as “a weapon system that, based on conclusions derived from gathered information and preprogrammed constraints, is capable of independently selecting and engaging targets.”
Applying this definition, and contrary to the nearly universal consensus, it quickly becomes apparent that autonomous weapon systems are not weapons of the future: they exist and have already been integrated into states’ armed forces. The fact that such weaponry is currently being used with little critique has a number of profound implications. First, it undermines pro-ban arguments based on the premise that autonomous weapon systems are inherently unlawful. Second, it significantly reduces the likelihood that a complete ban would be successful, as states will be unwilling to voluntarily relinquish otherwise lawful and uniquely effective weaponry.
But law is not doomed to follow technology: if used proactively, law can channel the development and use of autonomous weapon systems. The Article concludes that intentional international regulation is needed, now, and suggests how such regulation may be designed to incorporate beneficial legal limitations and humanitarian protections.},
keywords = {AI and War},
pubstate = {published},
tppubtype = {article}
}
In little over a year, the possibility of a complete ban on autonomous weapon systems — known colloquially as “killer robots” — has evolved from a proposal in an NGO report to the subject of an international meeting with representatives from over eighty states. However, no one has yet put forward a coherent definition of autonomy in weapon systems from a law of armed conflict perspective, which often results in the conflation of legal, ethical, policy, and political arguments. To address this problem and to assist future treaty negotiators, this Article proposes that an “autonomous weapon system” be defined as “a weapon system that, based on conclusions derived from gathered information and preprogrammed constraints, is capable of independently selecting and engaging targets.”
Applying this definition, and contrary to the nearly universal consensus, it quickly becomes apparent that autonomous weapon systems are not weapons of the future: they exist and have already been integrated into states’ armed forces. The fact that such weaponry is currently being used with little critique has a number of profound implications. First, it undermines pro-ban arguments based on the premise that autonomous weapon systems are inherently unlawful. Second, it significantly reduces the likelihood that a complete ban would be successful, as states will be unwilling to voluntarily relinquish otherwise lawful and uniquely effective weaponry.
But law is not doomed to follow technology: if used proactively, law can channel the development and use of autonomous weapon systems. The Article concludes that intentional international regulation is needed, now, and suggests how such regulation may be designed to incorporate beneficial legal limitations and humanitarian protections.
Applying this definition, and contrary to the nearly universal consensus, it quickly becomes apparent that autonomous weapon systems are not weapons of the future: they exist and have already been integrated into states’ armed forces. The fact that such weaponry is currently being used with little critique has a number of profound implications. First, it undermines pro-ban arguments based on the premise that autonomous weapon systems are inherently unlawful. Second, it significantly reduces the likelihood that a complete ban would be successful, as states will be unwilling to voluntarily relinquish otherwise lawful and uniquely effective weaponry.
But law is not doomed to follow technology: if used proactively, law can channel the development and use of autonomous weapon systems. The Article concludes that intentional international regulation is needed, now, and suggests how such regulation may be designed to incorporate beneficial legal limitations and humanitarian protections.
242.
Crootof, Rebecca
War, Responsibility, and Killer Robots Journal Article
In: North Carolina Journal of International Law and Commercial Regulation, vol. 40, no. 4, pp. 909–932, 2014.
Abstract | Links | BibTeX | Tags: AI and War
@article{crootof_war_2014,
title = {War, Responsibility, and Killer Robots},
author = {Rebecca Crootof},
url = {https://heinonline.org/HOL/P?h=hein.journals/ncjint40&i=941},
year = {2014},
date = {2014-01-01},
urldate = {2024-10-22},
journal = {North Carolina Journal of International Law and Commercial Regulation},
volume = {40},
number = {4},
pages = {909–932},
abstract = {Although many are concerned that autonomous weapon systems may make war “too easy,” no one has addressed how their use may alter the distribution of the constitutional war power. Drones, cyber operations, and other technological advances in weaponry already allow the United States to intervene militarily with minimal boots on the ground, and increased autonomy in weapon systems will further reduce risk to soldiers. As human troops are augmented and supplanted by robotic ones, it will be politically easier to justify using force, especially for short-term military engagements. Accordingly, one of the remaining incentives for Congress to check presidential warmongering — popular outrage at the loss of American lives — will diminish. The integration of autonomous weapon systems into U.S. military forces will therefore contribute to the growing concentration of the war power in the hands of the Executive, with implications for the international doctrine of humanitarian intervention.},
keywords = {AI and War},
pubstate = {published},
tppubtype = {article}
}
Although many are concerned that autonomous weapon systems may make war “too easy,” no one has addressed how their use may alter the distribution of the constitutional war power. Drones, cyber operations, and other technological advances in weaponry already allow the United States to intervene militarily with minimal boots on the ground, and increased autonomy in weapon systems will further reduce risk to soldiers. As human troops are augmented and supplanted by robotic ones, it will be politically easier to justify using force, especially for short-term military engagements. Accordingly, one of the remaining incentives for Congress to check presidential warmongering — popular outrage at the loss of American lives — will diminish. The integration of autonomous weapon systems into U.S. military forces will therefore contribute to the growing concentration of the war power in the hands of the Executive, with implications for the international doctrine of humanitarian intervention.
243.
Crawford, Kate; Schultz, Jason
Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms Journal Article
In: Boston College Law Review, vol. 55, no. 1, pp. 93–128, 2014.
Abstract | Links | BibTeX | Tags: AI Regulation and Strategies
@article{crawford_big_2014,
title = {Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms},
author = {Kate Crawford and Jason Schultz},
url = {https://heinonline.org/HOL/P?h=hein.journals/bclr55&i=93},
year = {2014},
date = {2014-01-01},
urldate = {2024-10-22},
journal = {Boston College Law Review},
volume = {55},
number = {1},
pages = {93–128},
abstract = {The rise of “big data” analytics in the private sector poses new challenges for privacy advocates. Unlike previous computational models that exploit personally identifiable information (PII) directly, such as behavioral targeting, big data has exploded the definition of PII to make many more sources of data personally identifiable. By analyzing primarily metadata, such as a set of predictive or aggregated findings without displaying or distributing the originating data, big data approaches often operate outside of current privacy protections (Rubinstein 2013; Tene and Polonetsky 2012), effectively marginalizing regulatory schema. Big data presents substantial privacy concerns – risks of bias or discrimination based on the inappropriate generation of personal data – a risk we call “predictive privacy harm.” Predictive analysis and categorization can pose a genuine threat to individuals, especially when it is performed without their knowledge or consent. While not necessarily a harm that falls within the conventional “invasion of privacy” boundaries, such harms still center on an individual’s relationship with data about her. Big data approaches need not rely on having a person’s PII directly: a combination of techniques from social network analysis, interpreting online behaviors and predictive modeling can create a detailed, intimate picture with a high degree of accuracy. Furthermore, harms can still result when such techniques are done poorly, rendering an inaccurate picture that nonetheless is used to impact on a person’s life and livelihood.
In considering how to respond to evolving big data practices, we began by examining the existing rights that individuals have to see and review records pertaining to them in areas such as health and credit information. But it is clear that these existing systems are inadequate to meet current big data challenges. Fair Information Privacy Practices and other notice-and-choice regimes fail to protect against predictive privacy risks in part because individuals are rarely aware of how their individual data is being used to their detriment, what determinations are being made about them, and because at various points in big data processes, the relationship between predictive privacy harms and originating PII may be complicated by multiple technical processes and the involvement of third parties. Thus, past privacy regulations and rights are ill equipped to face current and future big data challenges.
We propose a new approach to mitigating predictive privacy harms – that of a right to procedural data due process. In the Anglo-American legal tradition, procedural due process prohibits the government from depriving an individual’s rights to life, liberty, or property without affording her access to certain basic procedural components of the adjudication process – including the rights to review and contest the evidence at issue, the right to appeal any adverse decision, the right to know the allegations presented and be heard on the issues they raise. Procedural due process also serves as an enforcer of separation of powers, prohibiting those who write laws from also adjudicating them.
While some current privacy regimes offer nominal due process-like mechanisms in relation to closely defined types of data, these rarely include all of the necessary components to guarantee fair outcomes and arguably do not apply to many kinds of big data systems (Terry 2012). A more rigorous framework is needed, particularly given the inherent analytical assumptions and methodological biases built into many big data systems (boyd and Crawford 2012). Building on previous thinking about due process for public administrative computer systems (Steinbock 2005; Citron 2010), we argue that individuals who are privately and often secretly “judged” by big data should have similar rights to those judged by the courts with respect to how their personal data has been used in such adjudications. Using procedural due process principles, we analogize a system of regulation that would provide such rights against private big data actors.},
keywords = {AI Regulation and Strategies},
pubstate = {published},
tppubtype = {article}
}
The rise of “big data” analytics in the private sector poses new challenges for privacy advocates. Unlike previous computational models that exploit personally identifiable information (PII) directly, such as behavioral targeting, big data has exploded the definition of PII to make many more sources of data personally identifiable. By analyzing primarily metadata, such as a set of predictive or aggregated findings without displaying or distributing the originating data, big data approaches often operate outside of current privacy protections (Rubinstein 2013; Tene and Polonetsky 2012), effectively marginalizing regulatory schema. Big data presents substantial privacy concerns – risks of bias or discrimination based on the inappropriate generation of personal data – a risk we call “predictive privacy harm.” Predictive analysis and categorization can pose a genuine threat to individuals, especially when it is performed without their knowledge or consent. While not necessarily a harm that falls within the conventional “invasion of privacy” boundaries, such harms still center on an individual’s relationship with data about her. Big data approaches need not rely on having a person’s PII directly: a combination of techniques from social network analysis, interpreting online behaviors and predictive modeling can create a detailed, intimate picture with a high degree of accuracy. Furthermore, harms can still result when such techniques are done poorly, rendering an inaccurate picture that nonetheless is used to impact on a person’s life and livelihood.
In considering how to respond to evolving big data practices, we began by examining the existing rights that individuals have to see and review records pertaining to them in areas such as health and credit information. But it is clear that these existing systems are inadequate to meet current big data challenges. Fair Information Privacy Practices and other notice-and-choice regimes fail to protect against predictive privacy risks in part because individuals are rarely aware of how their individual data is being used to their detriment, what determinations are being made about them, and because at various points in big data processes, the relationship between predictive privacy harms and originating PII may be complicated by multiple technical processes and the involvement of third parties. Thus, past privacy regulations and rights are ill equipped to face current and future big data challenges.
We propose a new approach to mitigating predictive privacy harms – that of a right to procedural data due process. In the Anglo-American legal tradition, procedural due process prohibits the government from depriving an individual’s rights to life, liberty, or property without affording her access to certain basic procedural components of the adjudication process – including the rights to review and contest the evidence at issue, the right to appeal any adverse decision, the right to know the allegations presented and be heard on the issues they raise. Procedural due process also serves as an enforcer of separation of powers, prohibiting those who write laws from also adjudicating them.
While some current privacy regimes offer nominal due process-like mechanisms in relation to closely defined types of data, these rarely include all of the necessary components to guarantee fair outcomes and arguably do not apply to many kinds of big data systems (Terry 2012). A more rigorous framework is needed, particularly given the inherent analytical assumptions and methodological biases built into many big data systems (boyd and Crawford 2012). Building on previous thinking about due process for public administrative computer systems (Steinbock 2005; Citron 2010), we argue that individuals who are privately and often secretly “judged” by big data should have similar rights to those judged by the courts with respect to how their personal data has been used in such adjudications. Using procedural due process principles, we analogize a system of regulation that would provide such rights against private big data actors.
In considering how to respond to evolving big data practices, we began by examining the existing rights that individuals have to see and review records pertaining to them in areas such as health and credit information. But it is clear that these existing systems are inadequate to meet current big data challenges. Fair Information Privacy Practices and other notice-and-choice regimes fail to protect against predictive privacy risks in part because individuals are rarely aware of how their individual data is being used to their detriment, what determinations are being made about them, and because at various points in big data processes, the relationship between predictive privacy harms and originating PII may be complicated by multiple technical processes and the involvement of third parties. Thus, past privacy regulations and rights are ill equipped to face current and future big data challenges.
We propose a new approach to mitigating predictive privacy harms – that of a right to procedural data due process. In the Anglo-American legal tradition, procedural due process prohibits the government from depriving an individual’s rights to life, liberty, or property without affording her access to certain basic procedural components of the adjudication process – including the rights to review and contest the evidence at issue, the right to appeal any adverse decision, the right to know the allegations presented and be heard on the issues they raise. Procedural due process also serves as an enforcer of separation of powers, prohibiting those who write laws from also adjudicating them.
While some current privacy regimes offer nominal due process-like mechanisms in relation to closely defined types of data, these rarely include all of the necessary components to guarantee fair outcomes and arguably do not apply to many kinds of big data systems (Terry 2012). A more rigorous framework is needed, particularly given the inherent analytical assumptions and methodological biases built into many big data systems (boyd and Crawford 2012). Building on previous thinking about due process for public administrative computer systems (Steinbock 2005; Citron 2010), we argue that individuals who are privately and often secretly “judged” by big data should have similar rights to those judged by the courts with respect to how their personal data has been used in such adjudications. Using procedural due process principles, we analogize a system of regulation that would provide such rights against private big data actors.
244.
Hartzog, Woodrow; Solove, Daniel J.
The Scope and Potential of FTC Data Protection Journal Article
In: George Washington Law Review, vol. 83, no. 6, pp. 2230–2300, 2014.
Abstract | Links | BibTeX | Tags: AI Regulation and Strategies
@article{hartzog_scope_2014,
title = {The Scope and Potential of FTC Data Protection},
author = {Woodrow Hartzog and Daniel J. Solove},
url = {https://heinonline.org/HOL/P?h=hein.journals/gwlr83&i=2318},
year = {2014},
date = {2014-01-01},
urldate = {2024-10-22},
journal = {George Washington Law Review},
volume = {83},
number = {6},
pages = {2230–2300},
abstract = {For more than fifteen years, the FTC has regulated privacy and data security through its authority to police deceptive and unfair trade practices as well as through powers conferred by specific statutes and international agreements. Recently, the FTC’s powers for data protection have been challenged by Wyndham Worldwide Corp. and LabMD. These recent cases raise a fundamental issue, and one that has surprisingly not been well explored: How broad are the FTC’s privacy and data security regulatory powers? How broad should they be?
In this Article, we address the issue of the scope of FTC authority in the areas of privacy and data security, which together we will refer to as “data protection.” We argue that the FTC not only has the authority to regulate data protection to the extent it has been doing, but that its granted jurisdiction can expand its reach much more. Normatively, we argue that the FTC’s current scope of data protection authority is essential to the United States data protection regime and should be fully embraced to respond to the privacy harms unaddressed by existing remedies available in tort or contract, or by various statutes. In contrast to the legal theories underlying these other claims of action, the FTC can regulate with a much different and more flexible understanding of harm than one focused on monetary or physical injury.
Thus far, the FTC has been quite modest in its enforcement, focusing on the most egregious offenders and enforcing the most widespread industry norms. Yet the FTC can and should push the development of norms a little more (though not in an extreme or aggressive way). We discuss steps the FTC should take to change the way it exercises its power, such as with greater transparency and more nuanced sanctioning and auditing.},
keywords = {AI Regulation and Strategies},
pubstate = {published},
tppubtype = {article}
}
For more than fifteen years, the FTC has regulated privacy and data security through its authority to police deceptive and unfair trade practices as well as through powers conferred by specific statutes and international agreements. Recently, the FTC’s powers for data protection have been challenged by Wyndham Worldwide Corp. and LabMD. These recent cases raise a fundamental issue, and one that has surprisingly not been well explored: How broad are the FTC’s privacy and data security regulatory powers? How broad should they be?
In this Article, we address the issue of the scope of FTC authority in the areas of privacy and data security, which together we will refer to as “data protection.” We argue that the FTC not only has the authority to regulate data protection to the extent it has been doing, but that its granted jurisdiction can expand its reach much more. Normatively, we argue that the FTC’s current scope of data protection authority is essential to the United States data protection regime and should be fully embraced to respond to the privacy harms unaddressed by existing remedies available in tort or contract, or by various statutes. In contrast to the legal theories underlying these other claims of action, the FTC can regulate with a much different and more flexible understanding of harm than one focused on monetary or physical injury.
Thus far, the FTC has been quite modest in its enforcement, focusing on the most egregious offenders and enforcing the most widespread industry norms. Yet the FTC can and should push the development of norms a little more (though not in an extreme or aggressive way). We discuss steps the FTC should take to change the way it exercises its power, such as with greater transparency and more nuanced sanctioning and auditing.
In this Article, we address the issue of the scope of FTC authority in the areas of privacy and data security, which together we will refer to as “data protection.” We argue that the FTC not only has the authority to regulate data protection to the extent it has been doing, but that its granted jurisdiction can expand its reach much more. Normatively, we argue that the FTC’s current scope of data protection authority is essential to the United States data protection regime and should be fully embraced to respond to the privacy harms unaddressed by existing remedies available in tort or contract, or by various statutes. In contrast to the legal theories underlying these other claims of action, the FTC can regulate with a much different and more flexible understanding of harm than one focused on monetary or physical injury.
Thus far, the FTC has been quite modest in its enforcement, focusing on the most egregious offenders and enforcing the most widespread industry norms. Yet the FTC can and should push the development of norms a little more (though not in an extreme or aggressive way). We discuss steps the FTC should take to change the way it exercises its power, such as with greater transparency and more nuanced sanctioning and auditing.
245.
Pasquale, Frank
Grand Bargains for Big Data: The Emerging Law of Health Information Journal Article
In: Maryland Law Review, vol. 72, no. 3, pp. 682–772, 2012.
Abstract | Links | BibTeX | Tags: AI and Health
@article{pasquale_grand_2012,
title = {Grand Bargains for Big Data: The Emerging Law of Health Information},
author = {Frank Pasquale},
url = {https://heinonline.org/HOL/P?h=hein.journals/mllr72&i=700},
year = {2012},
date = {2012-01-01},
urldate = {2024-10-21},
journal = {Maryland Law Review},
volume = {72},
number = {3},
pages = {682–772},
abstract = {Health information technology can save lives, cut costs, and expand access to care. But its full promise will only be realized if policymakers broker a “grand bargain” between providers, patients, and administrative agencies. In exchange for subsidizing systems designed to protect intellectual property and secure personally identifiable information, health regulators should have full access to key data those systems collect.
Successful data-mining programs at the Centers for Medicare & Medicaid Services (“CMS”) provide one model. By requiring standardized collection of billing data and hiring private contractors to analyze it, CMS pioneered innovative techniques for punishing fraud. Now it must move beyond deterring illegal conduct and move toward data-driven promotion of best practices.
With this aim in mind, CMS is already subsidizing technology, but more than money is needed to optimize the collection, analysis, and use of data. Policymakers need to navigate intellectual property and privacy rights skillfully. They must condition current (and future) government support for providers and insurers on better collection and dissemination of health information. If they succeed, the law of health information might better incorporate public values than information law generally.},
keywords = {AI and Health},
pubstate = {published},
tppubtype = {article}
}
Health information technology can save lives, cut costs, and expand access to care. But its full promise will only be realized if policymakers broker a “grand bargain” between providers, patients, and administrative agencies. In exchange for subsidizing systems designed to protect intellectual property and secure personally identifiable information, health regulators should have full access to key data those systems collect.
Successful data-mining programs at the Centers for Medicare & Medicaid Services (“CMS”) provide one model. By requiring standardized collection of billing data and hiring private contractors to analyze it, CMS pioneered innovative techniques for punishing fraud. Now it must move beyond deterring illegal conduct and move toward data-driven promotion of best practices.
With this aim in mind, CMS is already subsidizing technology, but more than money is needed to optimize the collection, analysis, and use of data. Policymakers need to navigate intellectual property and privacy rights skillfully. They must condition current (and future) government support for providers and insurers on better collection and dissemination of health information. If they succeed, the law of health information might better incorporate public values than information law generally.
Successful data-mining programs at the Centers for Medicare & Medicaid Services (“CMS”) provide one model. By requiring standardized collection of billing data and hiring private contractors to analyze it, CMS pioneered innovative techniques for punishing fraud. Now it must move beyond deterring illegal conduct and move toward data-driven promotion of best practices.
With this aim in mind, CMS is already subsidizing technology, but more than money is needed to optimize the collection, analysis, and use of data. Policymakers need to navigate intellectual property and privacy rights skillfully. They must condition current (and future) government support for providers and insurers on better collection and dissemination of health information. If they succeed, the law of health information might better incorporate public values than information law generally.
246.
Cherry, Miriam A.
The Gamification of Work Ideas Journal Article
In: Hofstra Law Review, vol. 40, no. 4, pp. 851–858, 2011.
Abstract | Links | BibTeX | Tags: AI and Employment
@article{cherry_gamification_2011,
title = {The Gamification of Work Ideas},
author = {Miriam A. Cherry},
url = {https://heinonline.org/HOL/P?h=hein.journals/hoflr40&i=873},
year = {2011},
date = {2011-01-01},
urldate = {2024-10-21},
journal = {Hofstra Law Review},
volume = {40},
number = {4},
pages = {851–858},
abstract = {In the language of cyberspace, introducing elements of fun or game-playing into everyday tasks or through simulations is known as the process of “gamification.” The idea that people could be working while they play a video game – in some instances without even knowing that they are working – is becoming part of our reality. Gamification is an important element of what in previous writing I have termed “virtual work,” that is, work that is taking place wholly online, in crowdsourcing arrangements, or in virtual worlds. The gamification of work is an important trend with important implications for employment law. This short “Idea” essay begins to describe and formulate theories for thinking about these new forms of work.},
keywords = {AI and Employment},
pubstate = {published},
tppubtype = {article}
}
In the language of cyberspace, introducing elements of fun or game-playing into everyday tasks or through simulations is known as the process of “gamification.” The idea that people could be working while they play a video game – in some instances without even knowing that they are working – is becoming part of our reality. Gamification is an important element of what in previous writing I have termed “virtual work,” that is, work that is taking place wholly online, in crowdsourcing arrangements, or in virtual worlds. The gamification of work is an important trend with important implications for employment law. This short “Idea” essay begins to describe and formulate theories for thinking about these new forms of work.
247.
Cohen, Julie E.
Privacy, Visibility, Transparency, and Exposure Symposium: Surveillance Journal Article
In: University of Chicago Law Review, vol. 75, no. 1, pp. 181–202, 2008.
Abstract | Links | BibTeX | Tags: AI Regulation and Strategies
@article{cohen_privacy_2008,
title = {Privacy, Visibility, Transparency, and Exposure Symposium: Surveillance},
author = {Julie E. Cohen},
url = {https://heinonline.org/HOL/P?h=hein.journals/uclr75&i=183},
year = {2008},
date = {2008-01-01},
urldate = {2024-10-22},
journal = {University of Chicago Law Review},
volume = {75},
number = {1},
pages = {181–202},
abstract = {This essay considers the relationship between privacy and visibility in the networked information age. Visibility is an important determinant of harm to privacy, but a persistent tendency to conceptualize privacy harms and expectations in terms of visibility has created two problems. First, focusing on visibility diminishes the salience and obscures the operation of nonvisual mechanisms designed to render individual identity, behavior, and preferences transparent to third parties. The metaphoric mapping to visibility suggests that surveillance is simply passive observation, rather than the active production of categories, narratives, and, norms. Second, even a broader conception of privacy harms as a function of informational transparency is incomplete. Privacy has a spatial dimension as well as an informational dimension. The spatial dimension of the privacy interest, which the author characterizes as an interest in avoiding or selectively limiting exposure, concerns the structure of experienced space. It is not negated by the fact that people in public spaces expect to be visible to others present in those spaces, and it encompasses both the arrangement of physical spaces and the design of networked communications technologies. U.S. privacy law and theory currently do not recognize this interest at all. This essay argues that they should.},
keywords = {AI Regulation and Strategies},
pubstate = {published},
tppubtype = {article}
}
This essay considers the relationship between privacy and visibility in the networked information age. Visibility is an important determinant of harm to privacy, but a persistent tendency to conceptualize privacy harms and expectations in terms of visibility has created two problems. First, focusing on visibility diminishes the salience and obscures the operation of nonvisual mechanisms designed to render individual identity, behavior, and preferences transparent to third parties. The metaphoric mapping to visibility suggests that surveillance is simply passive observation, rather than the active production of categories, narratives, and, norms. Second, even a broader conception of privacy harms as a function of informational transparency is incomplete. Privacy has a spatial dimension as well as an informational dimension. The spatial dimension of the privacy interest, which the author characterizes as an interest in avoiding or selectively limiting exposure, concerns the structure of experienced space. It is not negated by the fact that people in public spaces expect to be visible to others present in those spaces, and it encompasses both the arrangement of physical spaces and the design of networked communications technologies. U.S. privacy law and theory currently do not recognize this interest at all. This essay argues that they should.
248.
Garland, Brent
Dana Press, 2004, ISBN: 978-1-932594-04-1, (Google-Books-ID: yTetQgAACAAJ).
Abstract | Links | BibTeX | Tags: Books on AI and the Law
@book{garland_neuroscience_2004,
title = {Neuroscience and the Law: Brain, Mind, and the Scales of Justice : a Report on an Invitational Meeting Convened by the American Association for the Advancement of Science and the Dana Foundation},
author = {Brent Garland},
url = {https://www.aaas.org/sites/default/files/NeuroLawSummary1.pdf},
isbn = {978-1-932594-04-1},
year = {2004},
date = {2004-01-01},
publisher = {Dana Press},
abstract = {Neuroscience and the Law is a concise, jargon-free work examining how discoveries in neuroscience are influencing criminal and civil legal proceedings and what imminent and longer-term advances may affect the U.S. justice system. Part One of the book summarizes the deliberations at a meeting of 26 top neuroscientists, legal scholars, attorneys, and state and federal judges to sort out the issues. Part Two comprises the four formal commissioned papers that anchored these discussions:
“Free Will in the 21st Century,” by Michael S. Gazzaniga, and Megan S. Steven
“Neuroscience Developments and the Law,” by Laurence Tancredi
“Prediction, Litigation, Privacy and Property,” by Henry T. Greely
“New Neuroscience, Old Problems,” by Stephen J. Morse},
note = {Google-Books-ID: yTetQgAACAAJ},
keywords = {Books on AI and the Law},
pubstate = {published},
tppubtype = {book}
}
Neuroscience and the Law is a concise, jargon-free work examining how discoveries in neuroscience are influencing criminal and civil legal proceedings and what imminent and longer-term advances may affect the U.S. justice system. Part One of the book summarizes the deliberations at a meeting of 26 top neuroscientists, legal scholars, attorneys, and state and federal judges to sort out the issues. Part Two comprises the four formal commissioned papers that anchored these discussions:
“Free Will in the 21st Century,” by Michael S. Gazzaniga, and Megan S. Steven
“Neuroscience Developments and the Law,” by Laurence Tancredi
“Prediction, Litigation, Privacy and Property,” by Henry T. Greely
“New Neuroscience, Old Problems,” by Stephen J. Morse
“Free Will in the 21st Century,” by Michael S. Gazzaniga, and Megan S. Steven
“Neuroscience Developments and the Law,” by Laurence Tancredi
“Prediction, Litigation, Privacy and Property,” by Henry T. Greely
“New Neuroscience, Old Problems,” by Stephen J. Morse
249.
Ashley, Kevin; Branting, Karl; Margolis, Howard; Sunstein, Cass
Legal Reasoning and Artificial Intelligence: How Computers "Think" Like Lawyers Journal Article
In: The University of Chicago Law School Roundtable, vol. 8, no. 1, 2001, ISSN: 1075-9166.
Links | BibTeX | Tags: AI and Administrative Work
@article{ashley_legal_2001,
title = {Legal Reasoning and Artificial Intelligence: How Computers "Think" Like Lawyers},
author = {Kevin Ashley and Karl Branting and Howard Margolis and Cass Sunstein},
url = {https://chicagounbound.uchicago.edu/roundtable/vol8/iss1/2},
issn = {1075-9166},
year = {2001},
date = {2001-01-01},
journal = {The University of Chicago Law School Roundtable},
volume = {8},
number = {1},
keywords = {AI and Administrative Work},
pubstate = {published},
tppubtype = {article}
}