38 episodes
ATGO AI | Accountability, Trust, Governance and Oversight of Artificial Intelligence | ForHumanity Center
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- Business
ATGO AI is podcast channel from ForHumanity. This podcast will bring multiple series of insights on topics of pressing importance specifically in the space of Ethics and Accountability of emerging technology. You will hear from game changers in this field who have spearheaded accountability, transparency, governance and oversight in developing and deploying emerging technology (including Artificial Intelligence).
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#OpenBox The Data Brokers & Emerging Governance with Heidi Part 2
OPENBOX aims at bringing an easier understanding of open problems that helps in finding solutions for such problems. For the said purpose, I interview researchers and practitioners who have published works on open problems in a variety of areas of Artificial Intelligence and Machine Learning to collect a simplified understanding of these open problems. These are published as podcast series.
I spoke with Heidi Saas
Heidi is a Data Privacy and Technology Attorney. She regularly advise SMEs and start ups working in a wide variety of industries, on data privacy and ethical AI strategies. She is also a ForHumanity Contributor and algorithmic auditor.
This is part 2. She is speaking about how enterprises can manage the challenges by good governance practices .
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Send in a voice message: https://podcasters.spotify.com/pod/show/ryan-carrier3/message -
#OpenBox The Data Brokers & Emerging Governance with Heidi
OPENBOX aims at bringing an easier understanding of open problems that helps in finding solutions for such problems. For the said purpose, I interview researchers and practitioners who have published works on open problems in a variety of areas of Artificial Intelligence and Machine Learning to collect a simplified understanding of these open problems. These are published as podcast series.
I spoke with Heidi Saas
Heidi is a Data Privacy and Technology Attorney. She regularly advise SMEs and start ups working in a wide variety of industries, on data privacy and ethical AI strategies. She is also a ForHumanity Contributor and algorithmic auditor.
This is part 1. She is speaking about how regulations are emerging in the context of data brokers and how enterprises need to adopt to the changing compliance environment in managing data.
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Send in a voice message: https://podcasters.spotify.com/pod/show/ryan-carrier3/message -
#openbox - Open issues and problems in dealing with dark patterns
OPENBOX aims to bring an easier understanding of open problems that helps in finding solutions for such problems. For the said purpose, I interview researchers and practitioners who have published works on open problems in a variety of areas of Artificial Intelligence and Machine Learning to collect a simplified understanding of these open problems. These are published as podcast series
Today, we have with us Marie. Marie Potel-Saville is the founder and CEO of amurabi, a legal innovation by design agency. She was a lawyer for over 10 years at Magic Circle law firms such as Freshfields and Allen & Overy in London, Brussels and Paris. She is also the founder of Fair-Patterns, a SAAS platform to fight against dark patterns. She is spearheading efforts towards addressing the challenging problem of deceptive designs in applications using innovative technology. We are going to be discussing some nuances with her on this.
In this episode, Marie speaks about the enterprise approaches in working on fair patterns and the emerging regulatory interests in addressing the gap.
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Send in a voice message: https://podcasters.spotify.com/pod/show/ryan-carrier3/message -
#OpenBox - Open issues in dealing with dark patterns and/ or deceptive designs
OPENBOX aims to bring an easier understanding of open problems that helps in finding solutions for such problems. For the said purpose, I interview researchers and practitioners who have published works on open problems in a variety of areas of Artificial Intelligence and Machine Learning to collect a simplified understanding of these open problems. These are published as podcast series
Today, we have with us Marie. Marie Potel-Saville is the founder and CEO of amurabi, a legal innovation by design agency. She was a lawyer for over 10 years at Magic Circle law firms such as Freshfields and Allen & Overy in London, Brussels and Paris. She is also the founder of Fair-Patterns, a SAAS platform to fight against dark patterns. She is spearheading efforts towards addressing the challenging problem of deceptive designs in applications using innovative technology. We are going to be discussing some nuances with her on this.
In this episode, Marie speaks about the key considerations in dealing with the deceptive designs and how fair patterns enable a better business proposition
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Send in a voice message: https://podcasters.spotify.com/pod/show/ryan-carrier3/message -
#openbox Bias identification and mitigation with Patrick Hall - Part 2
OPENBOX aims at bringing an easier understanding of open problems that helps in finding solutions for such problems. For the said purpose, I interview researchers and practitioners who have published works on open problems in a variety of areas of Artificial Intelligence and Machine Learning to collect a simplified understanding of these open problems. These are published as podcast series.
Today, we have with us Patrick Hall. Patrick is a Assistant Professor at George Washington University. He is conducting research in support of the NIST AI Risk Management Framework and a contributor to NIST work on building a Standard for Identifying and Managing Bias in Artificial Intelligence. He is also the collaborator running the open-source initiative called “Awesome Machine Learning Interpretability” which maintains and curates a list of practical and awesome responsible machine learning resources. He is also one of the authors of Machine Learning for High Risk Applications released by O’reilly. He is also managing the AI incident Database.
This is part 2 of the episode
He spoke about key approaches for bias mitigation and the limitations therein. He also discusses the open problems in this area.
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Send in a voice message: https://podcasters.spotify.com/pod/show/ryan-carrier3/message -
#Openbox - bias discussion with Patrick Hall part 1
OPENBOX aims at bringing an easier understanding of open problems that helps in finding solutions for such problems. For the said purpose, I interview researchers and practitioners who have published works on open problems in a variety of areas of Artificial Intelligence and Machine Learning to collect a simplified understanding of these open problems. These are published as podcast series.
Today, we have with us Patrick Hall. Patrick is a Assistant Professor at George Washington University. He is conducting research in support of the NIST AI Risk Management Framework and a contributor to NIST work on building a Standard for Identifying and Managing Bias in Artificial Intelligence. He is also the collaborator running the open-source initiative called “Awesome Machine Learning Interpretability” which maintains and curates a list of practical and awesome responsible machine learning resources. He is also one of the authors of Machine Learning for High Risk Applications released by O’reilly. He is also managing the AI incident Database.
He spoke about key considerations for metrics regarding bias for varied types of data. He also discusses the open problems in this area.
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Send in a voice message: https://podcasters.spotify.com/pod/show/ryan-carrier3/message