Join Anthony Habayeb and the team from Torys for a conversation about the use cases for generative AI and how they go hand-in-hand with navigating the risk it presents.
In the last session of this series presented by Torys, Anthony Habayeb will discuss the various risks that generative AI can pose and its impact across several areas, including employee relations, corporate governance, customer services, and privacy. They will also discuss best practices to help mitigate AI risk and create a proactive risk management strategy.
This registration link goes directly to the registration page at Bluejeans events.
Machine learning: What are loss functions?
In one of our previous posts in our series on bias, titled: How does bias happen, technically? we touched on the notion of a loss function and how algorithms are trained. In this blog, we will dive deeper into what exactly loss functions are as well as how machine learning models are constructed and 'trained'.
Get ready for 2024 and a brand new episode! We discuss non-parametric statistics in data analysis and AI modeling. Learn more about applications in user research methods, as well as the importance of key assumptions in statistics and data modeling that must not be overlooked.
Federal regulators are scrambling to create guidelines for the ethical use of AI in a number of industries. Will healthcare collaborate or stake its own claim to governance?
Leaving the development of such a revolutionary technology to a few unregulated mega-corporations is short-sighted at best and dangerous at worst. While AI might be new, the problems that arise from concentration in core technologies are not. To keep Big Tech from becoming an unregulated AI oligopoly, we should turn to the playbook regulators have used to address other industries that offer fundamental services, like electricity, telecommunications, and banking services.
As policymakers and businesses continue discussing possible regulation around AI, 2024 will also be another big year for data privacy. It will be a busy year for anyone tasked with tracking new privacy laws or proposed legislation on an international, national, and state level — compounded by rules related to other issues like AI and antitrust.
Artificial intelligence (AI) will have a serious societal impact globally. So it is more urgent than ever that state leaders cooperate to regulate the technology. The real question is not whether international cooperation on AI is needed, but how can it be realized?
The urgency to regulate powerful AI has increased in recent times, as governments scramble to address the risks it might create. The European Union, for instance, passed landmark AI regulations last month, amid concerns that the powerful tech grabbing everyone's attention needs to be reined in. But strides made in one region may hardly be enough to tackle AI's challenges.
