Speaker "Ali Arsanjani" Details Back



Responsible use of Generative AI in the Enterprise


The responsible use of generative AI in the enterprise requires a new set of provisions for the AI life cycle, with specific phases, steps, and considerations that may differ from traditional AI development.
One important consideration is the need to carefully plan and design the data inputs and training data for generative AI models, since these systems are designed to create new content based on existing patterns. This may require additional steps in the data preparation and cleansing phase, as well as careful consideration of the potential biases and ethical concerns that may arise from using certain types of data.
Another key consideration is the need for transparency and explainability in generative AI models, particularly in industries where decisions made by AI systems can have significant impacts on people's lives. This may require additional steps in the model development and testing phase to ensure that the model is interpretable and can be audited for fairness and bias.
In addition, the deployment and monitoring phases of generative AI systems may require additional considerations, such as monitoring for unintended outputs or impacts on user privacy, and developing processes for handling any ethical or legal concerns that arise.
The development and deployment of generative AI systems in the enterprise requires a thoughtful and comprehensive approach that takes into account the unique challenges and considerations of this emerging technology. This may require new phases, steps, and considerations in the AI life cycle, and a proactive approach to addressing potential risks and ethical concerns.


Dr. Ali Arsanjani is the Director of Cloud Partner Engineering at Google Cloud, and Head of AI Center of Excellence, where he leads the development of strategic co-innovation partnerships in the fields of Generative AI, Data/Analytics & Predictive AI/ML. His team specializes in co-innovation with ISV and GSI partners as they run, integrate and build on GCP across the ML Lifecycle. Ali also works closely with product management to shape the direction of Google's AI and analytics offerings from a cloud perspective.
In addition to his role at Google Cloud, Ali is an Adjunct Professor at San Jose State University and the University of California, San Diego, where he teaches and advises students in the Masters in Data program and the Data Science Institute, respectively.