- #RISK A.I. London
- …
- #RISK A.I. London
- #RISK A.I. London
- …
- #RISK A.I. London
"There's a tidal wave coming"
— Time Magazine
“Forget artificial intelligence – in the brave new world of big data, it’s artificial idiocy we should be looking out for.”
— Tom Chatfield
“We need to make sure that the benefits of artificial general intelligence accure to as many people as possible... to all of humanity, ideally.”
— Demis Hassabis, Google DeepMind CEO & Co-Founder
#RISK AI Boston will focus on the emerging world of AI Governance as the global trend
towards governing and regulating AI gains momentum.
Join our waiting list to be notified when tickets become available.
"AI’s rapid advance threatens to overwhelm all efforts at regulation. We need our best tech experts competing to rein in AI as fast as companies are competing to build it."
— Eric Schmidt.
It is crucial for Governance, Risk, and Compliance professionals to have a deep understanding of the risks associated with Generative Artificial Intelligence.
While it's not yet clear who will ultimately oversee the Governance, Risk, and Compliance elements of Gen AI in an organisation, it is evident that key leadership figures are taking proactive measures to assume responsibility in this area.
#RISK A.I. Boston will address the pressing issues in a thought leadership environment, seeking a balance between AI innovation and AI governance.
#RISK A.I. Boston:
Navigating the Evolving Regulatory Landscape of AI
AI governance goes beyond the shoulders of executives. While leadership plays a crucial role, effective AI implementation requires collaboration across all levels of an organization.
#RISK A.I. Boston tackles the challenge of siloed AI responsibilities and missed opportunities.
Join us on October 9th to explore:
- Accountability: Understanding who's responsible for AI outcomes.
- Privacy & data protection: Ensuring ethical and compliant data use.
- Safety, security, & reliability: Trustworthy development of AI.
- Transparency: Building trust and understanding through AI decision-making.
- Bias: Mitigating the potential for unfair or discriminatory AI outputs.
- Human agency & oversight: Maintaining control and oversight in AI systems.
Break down the silos and unlock the full potential of AI.