Satya Pandey
Enterprise AI Journey – From Vision to Value
Embark on a journey that explores the core of enterprise AI initiatives, tailored to different stages of maturity. The session will offer insights into formulating a strong AI vision, standing up the right team, measuring progress, and creating value-driven strategies that align with your organization’s unique trajectory.
Key takeaways:
- How should enterprises think about starting and/or scaling the AI journey?
- How do you create strategies around talent, business value, and execution approaches?
- How do you think of the full spectrum of AI from classical ML applications to next-gen generative AI applications?
Kanchana Padmanabhan
Array Insights
Navigating the Ethical Landscape of Large Language Models in Healthcare: Balancing Potential Benefits and Challenges
In this era of digital transformation, Large Language Models (LLMs) are emerging as powerful tools in healthcare. They have the potential to revolutionize patient care and research by processing vast amounts of data to generate insights, predict outcomes, and aid in decision-making. However, along with these promising benefits comes a host of ethical questions surrounding privacy, security, and explainability – the ability to understand and interpret the results produced by these models, which is critical in the sensitive context of healthcare.
In this talk, we will delve into the exciting potential of LLMs in healthcare, exploring how these AI models can enhance patient care, drive research, and foster innovation. From summarizing patient stories and clinical notes, extracting structured insights such as metastasis and cause of death, understanding patient sentiments, and predicting health trends, to identifying patterns in disease progression and treatment responses, LLMs can play a pivotal role in shaping the future of healthcare. Simultaneously, we will confront the ethical dilemmas that these technologies pose to patient privacy. We will end the talk with discussion on how to work through these challenges.
Key takeaways:
- Capabilities of LLMs
- Ethical challenges posed by LLMs
- Avenues that need work both from technical and policy perspective
Kristian Hammond
Managing Transformation: Business and Technology in the Age of Language Models
Artificial intelligence (AI) is reshaping numerous industries, and one of the most impactful developments in this landscape has been the rise of generative AI systems such as ChatGPT. Powered by a unique blend of machine learning and natural language processing capabilities, ChatGPT has emerged as a transformative technology that has redefined the realm of human-computer interaction. This 90-minute session aims to offer functional review of its core functions, potential applications, and its role in empowering users in their personal and professional lives.
We will navigate how language models can be developed and deployed, demonstrating their potential across sectors such as customer service, education, healthcare, and content creation. Participants will gain insights into how this technology can be tailored to meet individual requirements, thereby enhancing efficiency, productivity, and decision-making capabilities.
We will also discuss the concerns to keep in mind when integrating Language Models into workflows and products. We will address ethical considerations, data privacy, and model training limitations to ensure you make informed decisions that align with your specific needs and values.
Designed for business leaders and technical decision-makers, this talk offers a functional understanding of the business uses of LLMs, how to bring them into the enterprise, and how to avoid possible pitfalls. Our goal is to ensure you walk away with a solid grasp of this game-changing technology and a clear vision of how you can leverage it to stay at the forefront of the digital revolution.
Key takeaways:
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Understanding the reality of Language Models
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Use case and approaches to using them
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Mistakes to avoid
Nicholas Soulakis
Pathways to Inclusive Public Health Informatics
This talk will lay a conceptual framework and present simulation results for more inclusive community-based studies and interventions. We will demonstrate how systems that initially conserve anonymity may be architected to provide pathways of trust-building activities and can ultimately lead to full participation. Special cases of peer referral will demonstrate how we might discover clusters of engagement among communities which may otherwise wish to remain in the margins.
Jie Shen
Gulé Sheikh
Ethical AI Considerations
Ethical AI is paramount for the future of artificial intelligence due to the impact on societal implications. As AI becomes more integrated into our lives, addressing the ethical concerns around data validation, transparency and responsible innovation. Biased algorithms, privacy violations and potential for job displacements necessitate the establishment of ethical frameworks and guidelines. As we build our roadmaps for the evolution of AI, we must also consider how we contribute to enhancing societies growth while mitigating unintended consequences.
Derrick Higgins
Health Care Service Corporation (HCSC)
AI in Healthcare
Joe DeCosmo
