Algorithmic Accountability... and What That Means from a Human Rights Perspective | 1.15

Damini Satija is a Human Rights and Public Policy Professional, as well as Head of the Algorithmic Accountability Lab and Interim Director at Amnesty Tech. Satija has experience working on data and AI, with a focus on government surveillance, algorithmic discrimination, welfare automation, and tech equity and justice. She has her Master of Public Administration (MPA) from Columbia University, with a specialization in tech policy, and a BA in Economics from the University of California, Berkeley.In this episode, she and Gutu discuss how:Bias and discrimination generally emerge in AI algorithmsHuman rights implications play a big role in data and consequently, in policy and regulationWe need to understand what needs to be addressed to properly mitigate AI harms... is it the model that should be optimized or the data (i.e., model-centric vs data-centric)?Our biases are codifiedWe can go about ensuring more inclusivity, more representation, and less bias in techNet neutrality, encryption laws, copyright, and content moderation effect usAI is playing an increasingly bigger role in Hollywood, art, and media. Is it possible to reclaim our data? Is data ownership a myth? What are the implications of assigning property rights to personal data?The hype of ChatGPT and GenerativeAI are overdone; and how environmentally unsustainable they are. Should ChatGPT be trained on people's writing, such as their books, articles, and/or poetry? How do property rights and copyright law apply?To be more mindful with technology and the ways it uses our data Check out our website, LinkedIn, or Instagram to stay up to date!#AlgorithmicBias #PredatoryTech #TechnicallyBiasedPodcast #Gakovii