CHAIR: David Snyder, Chairperson: President, 42TEK LLC

Omar Santos, Distinguished Engineer, Cisco
Cybersecurity for Agentic AI
Many AI deployments have been narrow in scope, focusing on augmenting specific tasks rather than radically reimagining work, but now we are seeing the early signs of true agentic workflows. In this presentation, we’ll explore the cybersecurity risks of agentic AI—intelligent systems capable of autonomous action. As AI agents become more integrated into critical infrastructure and decision-making processes, they pose unique threats. We’ll examine how their autonomy can be exploited for malicious purposes, leading to potential data breaches, service disruptions, and even physical damage. The focus will be on understanding the attack vectors specific to agentic AI, including compromised algorithms, data poisoning, and adversarial attacks. We’ll also discuss mitigation strategies to safeguard against these vulnerabilities, emphasizing the need for robust security protocols, continuous monitoring, and ethical AI design. This talk aims to raise awareness and prepare for the cybersecurity challenges of increasingly autonomous AI systems.  

Jaya Baloo, CSO, Rapid7
Our Secure Quantum Future
This talk will dive into the transformative world of quantum computing and its impact on digital security, specifically the enormous impact to cybersecurity. This session will introduce the fundamentals of quantum technology, examine the potential risks it poses to today’s encryption standards, and discuss the evolution towards quantum-resistant cryptography. Participants will leave with a solid understanding of how to safeguard digital communications against the impending quantum advancements, ensuring a secure future in the quantum age.  

Wally Rhines, CEO, Cornami, Inc.
Secure Sharing of GenAI/LLMs with Post Quantum Encryption
Combining proprietary corporate data with LLMs is driving revolutionary change.  But the fine-tuning data that corporations are building on top of foundation models is so sensitive that most organizations are reluctant to host the resulting LLMs in the cloud or other publicly accessible platforms.  The evolving solution is the use of fully homomorphic encryption (FHE) to provide quantum proof protection so that all queries and computation are limited to data that remains encrypted at all times.  It is not practical to encrypt multi-terabyte foundation models so techniques have been developed to encrypt only the fine tuning data.  This evolution of technology provides the ability to share proprietary models and data without exposing the actual data and, ultimately, the ability to charge users for queries made to the protected model. Dr. Rhines will discuss how the challenges of FHE encrypted model processing have been overcome and what capabilities will be available in the future.  

Richard Tong, Chair, IEEE Artificial Intelligence Standards Committee
Developing and Deploying Industry Standards for Artificial Intelligence: Challenges, Strategies, and Future Directions
The IEEE Computer Society’s Artificial Intelligence Standards Committee (C/AISC) is one of the leading international organizations for the development of industry standards for AI. Established in 2020, C/AISC oversees more than 50 standard working groups covering various aspects of AI standardization, including foundations, governance, horizontal and vertical interoperability, evaluation, security, and domain applications. These standards aim to provide guidelines for the responsible development and deployment of AI across industries. 

This talk will focus on the standard development efforts and strategies to meet the current challenges, such as the rapid pace of AI advancement and the need for international cooperation and collaboration between industry, government, and international bodies to shape the future of AI standards and ensuring the effective, efficient, enabling, safe, secure, and trustworthy development and deployment of AI technologies.  

David Sanker, Patent Attorney, SankerIP
AI and Intellectual Property
The U.S. Constitution provides the basis for intellectual property rights in the United States, and the specific laws relating to IP rights have adapted over the past 235 years due to advances in technology and other geopolitical changes.  AI creates new challenges for IP rights, as expressed in the U.S. Executive Order on AI and the AU AI Act.  Important considerations include: (i) can you patent AI algorithms or inventions that use AI (and if so, how); (ii) can you get intellectual property protection for inventions or creative works that were fully or partially created by AI (and if so, how); (iii) with respect to patents, how does AI affect what is considered “obvious” (and is therefore not patentable); and (iv) how is AI affecting the work of IP attorneys (e.g., drafting new patent applications or drafting responses to office actions).  While AI is evolving quickly, laws relating to AI are moving much more slowly.  People involved in AI and IP need to understand how to work within the existing laws right now while preparing for how the laws are changing.  

Brandie Nonnecke, Founding Director, CITRIS Policy Lab
The Laws, Policies & Regulations Shaping the Future of AI
As AI technologies continue to advance at an unprecedented pace, governments and organizations worldwide are grappling with how to effectively govern their development and deployment. This presentation will delve into key legislative frameworks, regulatory initiatives, and policy trends shaping the future of AI. Learn about the impact of landmark laws and governance strategies, such as the EU AI Act, the NIST AI Risk Management Framework, and recent executive orders from the White House and the State of California. Additionally, this presentation will address the challenges and opportunities in aligning international standards, fostering public-private collaborations, and safeguarding human rights in the age of AI, providing attendees with key insights into the critical legal and regulatory considerations that will define AI’s trajectory in the coming years.