Sydney Machine Learning (Sydney, Australia)


PLEASE NOTE: that RSVPing to this page DOES NOT GRANT YOU ACCESS to this meetup, Spaces are limited! DESCRIPTION How do we design Ai systems that we trust? Algorithmic Bias, Algorithmic Transparency, Technological Unemployment, Data Privacy & Algorithmic Misinformation (fake news) are just some of the issues facing the fair and ethical use of Machine Learning. In collaboration with Microsoft for this DSAi special edition Ethics & Interpretability event - come along to learn from industry leaders how issues such as Algorithmic Bias might affect you & what is being done to address the ethical use of Machine Learning in 2019. 'Ethics for Artificial Intelligence' In this 20 minute presentation, Aurelie will provide a formal introduction as to what ethical and responsible AI is.

Mark Zuckerberg and Elon Musk Battle Over Ethics of AI


In the Facebook livestream heard around the world, Mark Zuckerberg had choice words for Elon Musk and other AI naysayers. The comments spurred an online debate between the two, evoking juicy Twitter beefs that better befit the pop culture industry.

How Tech Giants Are Using AI Ethics Centres To Avoid Future Mishaps


As artificial intelligence and machine learning become the new industry norm, tech giants and service providers across the world are riding the emerging tech wave. However, with its applicability to enhance services, AI and machine learning have become ubiquitous for any technological advancements. As the world acknowledges the inevitability of AI and ML, the conversation has, however, shifted to its ethics, with governments and lawmakers bringing out stringent policies regarding the applicability of the technology. In Europe, countries like the UK and France have put ethics at the core of AI, while laying out stronger compliance rules for tech giants to adhere to. Taking note of the latest developments, tech giants like Google and Facebook, among many other companies, have brought out their ethical policies regarding deployment of AI and ML within their organisations.

FPF Launches AI and Machine Learning Working Group and Releases New AI Resource Guides


The opportunities created by machine learning range across every sector of the economy and will impact every area of daily life. Better health care, safer transportation, greater efficiencies in manufacturing, retail, and online services are all already on the horizon. But concerns about the privacy impact, ethical consequences and real world harms of the technology are real and may lead to dangers large and small if not countered. FPF has convened a leading group of its members to consider priority areas for technologies and companies to address ML privacy and ethics concerns. Our AI and Machine Learning Working Group, composed of FPF member companies with an interest in AI and Machine Learning privacy and data management challenges, meets monthly to discuss various relevant issues regarding new updates, hear from experts regarding AI in the EU and under GDPR, the occurrence and defense against bias, and other timely topics.

Microsoft, IBM Facial Analyses Struggle With Race and Gender


Facial recognition is becoming more pervasive in consumer products and law enforcement, backed by increasingly powerful machine-learning technology. But a test of commercial facial-analysis services from IBM and Microsoft raises concerns that the systems scrutinizing our features are significantly less accurate for people with black skin.