Playlist: 5 videos
Algorithm Design, Law, and Policy Virtual Kick-Off
1:3:55
Ron Rivest (MIT)
https://simons.berkeley.edu/talks/perspectives-digital-contact-tracing
Algorithm Design, Law, and Policy
Visit talk page
https://simons.berkeley.edu/talks/perspectives-digital-contact-tracing
Algorithm Design, Law, and Policy
0:22:16
https://simons.berkeley.edu/talks/tracing-apps-challenges
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.
Visit talk page
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.
1:1:52
Hal Varian (Google)
https://simons.berkeley.edu/talks/nowcasting-covid-19
Algorithm Design, Law, and Policy
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.
Visit talk page
https://simons.berkeley.edu/talks/nowcasting-covid-19
Algorithm Design, Law, and Policy
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.
1:0:39
Rediet Abebe (Harvard)
https://simons.berkeley.edu/talks/roles-computing-social-justice
Algorithm Design; Law and Policy Virtual Kick-Off
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.
Visit talk page
https://simons.berkeley.edu/talks/roles-computing-social-justice
Algorithm Design; Law and Policy Virtual Kick-Off
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.
1:8:40
Jennifer Chayes (UC Berkeley)
https://simons.berkeley.edu/talks/computing-and-data-science-human-welfare-and-social-justice
Algorithm Design, Law, and Policy Virtual Kick-Off
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.
Visit talk page
https://simons.berkeley.edu/talks/computing-and-data-science-human-welfare-and-social-justice
Algorithm Design, Law, and Policy Virtual Kick-Off
https://simons.berkeley.edu/workshops/algorithm-design-and-law
Two decades ago, Lawrence Lessig famously coined the term “code is law,” speaking to the importance of computer code as a central regulating force in the digital era. Today, as the usage of algorithms in society is exploding, it is becoming increasingly clear that algorithms are regulating human behavior in a variety of different manners. Algorithms have been infiltrating — and increasingly governing — every aspect of our lives as individuals and as a society. Governance by algorithms raises a whole new set of technical, social, ethical, and legal challenges, to ensure accountability, fairness, and equality, as well as fundamental rights such as privacy and free speech. Furthermore, this development reflects the rise of unmonitored private power, which may escape traditional checks and balances.
Tackling these challenges requires an interdisciplinary effort aimed at bridging the gap between ethical, legal and social norms and the performance of algorithmic systems. For instance, notions like privacy or fairness, which are formulated as ethical norms and legal doctrines, are increasingly defined as mathematical theorems in computer science. Are these formulations compatible? How does one reconcile legal and ethical standards with algorithmic performance? Could algorithms be sufficiently transparent to be subjected to public and legal oversight? How does one design checks and balances for algorithmic governance? These questions are highly relevant to a diverse range of topics including privacy in data analysis, fairness in algorithmic decision-making, duty of care in autonomous driving, free speech in algorithmic content moderation, and competition in algorithmic pricing.
This workshop will bring together researchers and scholars from diverse disciplines, including: computer science, law, ethics, social science, and data science. Our short-term goal is to identify concrete research problems of joint interest, which will benefit from a collaborative interdisciplinary approach over the next few years, and to form the necessary connections to tackle them as a community. Our long-term goal is to enable decades of legal and ethical thought to inform algorithm design, and the mathematical rigor and power of computer science theory to inform lawmaking.