Discussion of the 3 forms of reality at play across our platforms, and the new threats Generative AI present to our platforms and our communities writ large.

The delay in our legal and ethical frameworks’ ability to adapt to Generative AI have created a perfect storm for abuse - one that we must address head on to maintain the integrity and safety of our platforms and the trustworthiness of shared information. 

From there, we will explore a philosophical argument on the interdependencies between Generative AI, Responsible AI and Trust & Safety, drawing on real world examples to highlight threats to the success of Generative AI and Trust & Safety. 

Finally, we’ll walk through 3 main action items for practitioners of Generative AI to apply in their everyday work to help ensure the viability of our platforms in the age of Generative AI. 

Amie White

Founder
ALT Ethics

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In the era of Generative AI, establishing a robust enablement strategy in is paramount. As AI becomes increasingly integrated into healthcare workflows,ensuring ethical, regulatory-compliant, and secure practices is essential for patient safety and trust. Attend to explore how leading enterprises can navigate responsible AI practices in this time of rapid innovation:

• Prioritizing stakeholder engagement to gather diverse perspectives and ensure alignment.

• Establishing clear policies and procedures to guide ethical and regulatory-compliant AI use.

• Investing in AI ethics training to empower healthcare professionals with responsible AI practices.

• Fostering a culture of innovation and calculating GenAI business value and cost drivers.

Joe Siryani

Professor of Data Science & AI
George Washington University

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The operationalization and governance of generative AI demand a meticulous approach. In this session, Alayna will explore crucial considerations and offer practical insights for responsible implementation.

• Integrating AI governance recommendations into operational practices for ethical implementation.
• Establishing robust oversight mechanisms to monitor generative AI applications and ensure compliance.
• Prioritizing practical approaches for effective risk management in AI operationalization.

Alayna Kennedy

AI Governance
Mastercard

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Human-in-the loop and traditional AI standards can only take us so far. In order to ensure large-scale, sustainable production and implementation of Generative AI, we need to be able to rely on our models

to ensure company data is safe & hallucinations are completely avoided. Join this session to understand how business leaders can explore:

• Implementing policies and guardrails for safe scalability from a human-in-the-loop perspective.

• Exploring augmented AI solutions to enhance data protection and ethical decision-making.

• Fostering & preparing for sustained, safe, large scale generative AI through responsible AI practices.

John Rares Almasan

Senior Managing Director | Head of ClienTech and AI
TIAA

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Alayna Kennedy

AI Governance
Mastercard

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In recent years, Retrieval-Augmented Generation (RAG) systems have rapidly commoditized, yet they have not delivered the transformative results the industry anticipated. As we navigate this evolving landscape, Tool-Augmented Generation (TAG) is emerging as a promising alternative, demonstrating impressive outcomes across various applications. This talk will explore the rise of TAG, highlighting its ability to leverage external tools to enhance generative AI capabilities. Furthermore, we will delve into the synergistic potential of combining Agenic systems with TAG, revealing how this integration can yield substantial benefits with relatively modest initial investments. Join us to uncover the future of generative AI and how these advancements are poised to reshape the industry.

Devlin Liles

Chief Consulting Officer and President - Houston and Austin
Improving

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Leading through generative AI adoption requires a unique set of skills. This session explores the critical role of leadership in navigating organizational change.

• Develop change-ready leaders through targeted training programs focused on generative AI.

• Foster transparent communication to align leadership vision with workforce expectations.

• Encourage agile leadership, adapting strategies in response to generative AI developments.

Sami Huovilainen

Managing Director - Head of Next Gen Analytics
Citi

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Best Practices for GenAI Adoption

• How to assess the readiness and maturity of your organization for GenAI

• How to design and implement a GenAI program and strategy

• How to align stakeholders and sponsors

• How to help the enterprise prioritize GenAI use cases

• How to evaluate solution providers and partners

• How to measure and communicate the value and impact of GenAI

Best Practices for GenAI Change Management

• How to manage the cultural and behavioral changes required for GenAI

• How to develop and empower champions, advocates and stakeholders

• How to train and upskill your workforce

• How to address the ethical and social implications of GenAI

• How to foster a culture of innovation and collaboration

Paul Cielinski

Sr. Director Product Management
Syneos Health

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Successfully transitioning from pilot studies to large-scale implementation is a pivotal challenge in realizing the potential of Generative AI.

• Gaining insights into the critical considerations and strategies for scaling Generative AI solutions across organizations.

• Learning how to address infrastructure, data, and compliance challenges when moving from pilot to production.

• Discovering best practices for talent acquisition, training, and collaboration to ensure a smooth transition to large-scale implementation.

James Lin

Head of AI/ML Innovation
Experian

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Kaushal Lahankar

Director - Machine Learning
S&P Global

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Discover strategies to achieve authentic personalization at scale within the creative industries, powered by responsible generative AI. 

• Transitioning from cohort-based to true personalization for enhanced customer experiences.

• Overcoming legal, compliance, and tech limitations to implement personalized services.

• Addressing data privacy concerns and infrastructure limitations while ensuring effective personalization strategies.

Sky Kelley

Former Global Co-GM, Digital Product Innovation
Nike

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Andrew Bloom

Chief Commercial Officer
Bria

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Tina O'Shea

Director, Content Design & Design Tech
Intuit

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One of the primary ways customers shop online, visual shopping refers to any shopping based on visual attributes. Everything from clothes to home décor, visuals and aesthetics are increasingly important to consumers. Join this session to understand how Generative AI can enable meaningful visual shopping experiences, transforming the ways customers find products and make decisions.

• Exploration and visualization of new products helping customers personalize options and dream up their desired products.

• Enabling greater search options by allowing customers to increasingly use visual descriptions to find products.

• Evaluating products to accurately understand how a product will look in their space before purchase to reduce return costs.

• Increasing conversion rates by offering customers more opportunities to shop.

Anuj Bindal

GM and Director, Visual Shopping
Amazon

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In such a dynamic AI landscape, keeping up with the progress & ensuring for strategic implementation is paramount for success. Devlin is leading the Generative AI research within Vanguards applied research group, he will delve into AI Agents & how business leaders can explore:

• Forging partnerships with vendors, academia, and researchers for continuous learning.

• Investing in R&D to anticipate future AI capabilities.

• Understanding & innovating with latest in emerging AI agent technologies.

Devlin McConnell

Senior Manager – Emerging Technology and Generative AI
Vanguard

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Embark on a visionary journey exploring the “Text-to-Spaceship” concept, revolutionizing AI integration across NASA. Discover how AI innovations can transform text-based data into tangible advancements

in spacecraft design, through:

• Fostering interdisciplinary collaboration to integrate AI across all facets of aerospace operations.
• Investing in advanced AI technologies to unlock new possibilities for spacecraft design and development.
• Embracing the “Text-to-Spaceship” vision to propel the aerospace industry into a new era of innovation.

Ryan Mcclelland

Research Engineer
NASA

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In this talk, Sander will discuss the current state of Prompt Engineering drawing from his recent survey paper, The Prompt Report, done in collaboration with OpenAI and Microsoft. The 76 page paper is the largest ever study of prompting, and has gone viral on social media, obtaining millions of views. He will discuss the prompt classification system he developed for prompting techniques, including Zero-Shot, Few-Shot, Decomposition, Thought Generation, Ensembling, and Self-Criticism. Attend this talk to delve into the technical and business implications of prompting and how to get the best results for your teams.

Sander Schulhoff

CEO
Learn Prompting

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Explore the imperative of driving innovation in Generative AI with a multi-modal platform approach. This talk will delve into use cases & strategies for building and leveraging next-generation platforms tailored to industry-specific needs.

• Collaborating with domain experts to develop models tailored to industry requirements.

• Prioritizing applications built atop the platform to address specific industry challenges and opportunities.

• Addressing infrastructure challenges to optimize cost and scalability for multimodal language models.

Abhinav Kohar

SLB
Head of AI Platform (Generative AI)

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AI agents are a fast-developing domain that leverages Large Language Models (LLMs) to autonomously perform and refine tasks, mirroring human-like efficiency and adaptability. Within the AI agent domain, multi-agent collaboration has been promising domain in recent research to solve complex tasks through multiple AI agents collaboration or debating. The talk will cover most recent research conducted in fields like finance, software and medicine and understand how multi-agent frameworks can help complete complex tasks, 

Tina Zhao

Head of Applied AI Modeling
BlackRock

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This session delves into the critical factors that businesses must consider when selecting both the right models and infrastructure for effective Generative AI deployment. It covers key strategic decisions to ensure successful AI operationalization.

• Evaluating the specific requirements and constraints of each application to determine the most suitable model.

• Considering factors such as model complexity, data availability, and computational resources when making choices.

• Continuously monitoring model performance and adapting model selection strategies as AI technologies evolve.

• Assessing organizational needs and stakeholder concerns to determine the optimal infrastructure.

• Establishing clear communication channels between technical and business teams to align priorities.

• Developing a roadmap for implementation, iteratively evaluating progress and adjusting strategies accordingly.

Tina Zhao

Head of Applied AI Modeling
BlackRock

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Matt Lewis

Chief AI Officer
Inizio Medical

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Rama Ryali

Head, Data Platform, Compliance & Operations
McKesson

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