AI Operationalization with Governance and Model Risk Management
AI Operationalization with Governance and Model Risk Management

Abstract: 

In today’s world, the top challenges involved in using AI for real business outcome are managing risks associated with Model’s iterative life cycle, Transparency and Auditability. Enterprise customers struggle to marry the need of being flexible enough to foster a culture that is absolutely necessary for Data Science innovations and at the same time the need for governance involved in AI model creation and operationalization. These challenges lead to lesser number of AI models getting into production and thereby reducing the extent to which the enterprises can leverage the potential of infusing AI in various applications and get huge benefits out of them. The proposed workshop is aimed to show the AI professionals how AI operationalization can be achieved with Governance and Model Risk Management without taking away any flexibility from Data Science innovations. A real life use case would be used to showcase the various phases of AI Operationalization starting from Data Provisioning in a governed but flexible way to the Model Monitoring and feeding back the Model Factsheet for operationalization. Attendees would understand the nuances involved in these steps while developing the use cases themselves.

Bio: 

Sourav Mazumder is a Data Scientist Thought Leader, Open Group Distinguished Data Scientist, responsible for technical thought leadership & strategy, technical vitality, and technical enablement in AI and Data Science area for IBM's clients and also internal people in IBM. Sourav works with enterprise clients from AI strategy development to implementations and productionization particularly focusing on First of a Kind Projects. 

Sourav has consistently driven business innovation and values through Methodologies and Technologies related to Artificial Intelligence, Data Science and Big Data transpired through his knowledge, insights, experience and influencing skills across multiple industries including Manufacturing, Insurance, Telecom, Banking, Media, Health Care and Retail industries in USA, Europe, Australia, Japan and India. In last 10 years he has influenced key decision makers of several fortune 500 companies to adopt Artificial Intelligence, Data Science, and Big Data related technologies to address complex business needs. Sourav has also consistently provided directions to and successfully led numerous challenging Artificial Intelligence, Data Science and Big Data projects, applying various related methodologies ranging from Descriptive statistics, Probabilistic Modeling, Algorithmic Modeling, Natural Language Processing, etc., to solve critical business problems. Sourav has also successfully partnered with academia within North America, India, South Africa to mentor the students and enabling them in this area.  

Sourav has experience and exposure in working in variety of Artificial Intelligence, Data Science and Big Data related technologies like Watson Open Scale, Watson Studio, Watson Natural Language Processing, Watson Machine Learning, IBM Cloud Pak for Data, Spark, Hadoop, BigSQL, HBase, MongoDb, Solr, System ML, Brunel, Cognos, R, Python, Scala/Java, etc., using them in projects involving phases from creation of Minimum Viable Product to Productionization. Sourav is an Open Source enthusiast and contributes to Open Source regularly. 

Sourav consistently publishes papers/blogs/articles in various industry forums. Sourav is co-author, guest editor and chief editor of multiple books in AI, Data Science and Big Data space. Sourav is regularly invited to speak in various Industry conferences, like Spark Summit, IBM Think, Global AI Conference, etc in this subject area.