• Improving mission effectiveness is the end goal
• Understanding your sector scope and interdependencies
• Maintain vigilance of emerging concepts and technologies impacting your sector
• Trust – how to show it and earn it?
• Have a solid organizational foundation to build on

Even before the pandemic, governments around the world face more challenges than ever: Providing citizens with better benefits and services at lower cost, while combating fraud and improper payments; improving public safety and national security in the face of new threats; delivering better health care while controlling skyrocketing health care costs; and the list goes on.

At the same time, government entities produce, collect and store an unprecedented amount of increasingly diverse data that could be used to help solve these problems. However, traditional approaches to gleaning insights from data are no longer sufficient given the volume, velocity and variety that modern governments must manage. It is becoming increasingly critical for governments to find new ways to transform data into actionable information – new ways that include techniques like artificial intelligence (AI) and machine learning.

In this session, we will briefly review government domain areas with the largest potential for benefit from AI, and then spend most of our time talking about stories from around the world in which these techniques have made a difference in the public sector.  We’ll also highlight the many ways AI has helped the public sector on the front lines of the fight against COVID-19.

• Problems, opportunities and strategies for data and analytics capabilities
• Data and analytics program transformation
• Building a modern Enterprise Data and Analytics Ecosystem forEnabling AI and big data
• Use Case Analytics & prioritization
• POCs and Use cases of AI

• What is really new about analytics and AI
• Aspects to consider when establishing  a new data science team
• How to select the right use cases and demonstrate value early on
• Challenges (technical, analytical, political, ethical and data-related) involved in conducting advanced analytics and AI in a government or military setting
• Lessons learned

• Human to machine interactions
• What does future leadership look like?
• AI that is trusted and interpretable
• Preparing yourself and your team for human to machine interactions
• AI systems built to scale

• Fostering global cooperation in AI: What does it take?
• Examine the intersection between the public and private sector
• Shaping marketplace rules and policy-oriented standards that govern our data and AI applications