CDAO Fed Ready Summit schedule

• Fostering innovation and increased efficiency by leveraging data-driven and AI insights
• Enhancing business operations through data-driven process improvement
• Transparency: Building trust and accountability between government and residents

• Aligning data initiatives with business goals and driving innovation through AI adoption
• Understanding their roles and responsibilities in the context of AI
• Addressing security and privacy concerns

• Discuss when CDOs and CIOs in Federal Agencies must publicly report a data inventory used in AI systems
• Examine what details Federal Agencies must disclose for transparency and accountability under the law
• Analyze the potential positive and negative implications of sharing data used for AI generated analytics

• Enhancing the effectiveness and efficiency of each stage of policymaking
• Establishing robust governance structures from the outset of the AI/CX journey
• Building consistent CX standards across government agencies and services

• Why ethical factors can no longer be an afterthought of AI initiatives
• Why ethics, transparency, and explainability are necessary for successful, scalable AI programs
• How are you navigating privacy, trust, and security concerns around the use of AI?

• Aligning your data & analytics strategy with cross-government & organization level priorities and goals
• Balancing strategic approaches to data analytics with the changing priorities of the wider organization
• How innovative technologies such as AI and Machine Learning can be leveraged to modernize government data architectures?

Contributors:

Natalie Evans Harris, MD State Chief Data Officer, STATE OF MARYLAND

• Defining the state of the possible – how mature are AI technologies currently, what are the realistic use cases, and what is hype?
• Getting beyond the buzzword to identify what opportunities does AI present to Governmental organizations seeking to improve their delivery of services?
• Avoiding bias in data sets, algorithms, and machine learning models to ensure citizens are treated fairly & equitably

Contributors:

Richard Patterson, Chief Data and AI Officer, Bureau of the Comptroller and Global Financial Services, U.S. DEPARTMENT OF STATE

• Enabling transformation and decision making with trusted data
• Ensuring data quality, consistency, and integration
• Improving the quality and speed of government decision-making at scale by automating administrative tasks

Contributors:

LaShonda C. Henderson, Data Evangelist

• Why ethical factors can no longer be an afterthought of AI initiatives
• Why ethics, transparency, and explainability are necessary for successful, scalable AI programs
• How are you navigating privacy, trust, and security concerns around the use of AI?

• Aligning your data & analytics strategy with cross-government & organization level priorities and goals
• Balancing strategic approaches to data analytics with the changing priorities of the wider organization
• How innovative technologies such as AI and Machine Learning can be leveraged to modernize government data architectures?

• Defining the state of the possible – how mature are AI technologies currently, what are the realistic use cases, and what is hype?
• Getting beyond the buzzword to identify what opportunities does AI present to Governmental organizations seeking to improve their delivery of services?
• Avoiding bias in data sets, algorithms, and machine learning models to ensure citizens are treated fairly & equitably

Contributors:

Hengyi Hu, Ph.D., Chief Data Analytics Officer, U.S. CONSUMER PRODUCT SAFETY COMMISSION

• Enabling transformation and decision making with trusted data
• Ensuring data quality, consistency, and integration
• Improving the quality and speed of government decision-making at scale by automating administrative tasks

Contributors:

Patrick McLoughlin, Executive Director, MD THINK, STATE OF MARYLAND

• Why ethical factors can no longer be an afterthought of AI initiatives
• Why ethics, transparency, and explainability are necessary for successful, scalable AI programs
• How are you navigating privacy, trust, and security concerns around the use of AI?

• Aligning your data & analytics strategy with cross-government & organization level priorities and goals
• Balancing strategic approaches to data analytics with the changing priorities of the wider organization
• How innovative technologies such as AI and Machine Learning can be leveraged to modernize government data architectures?

• Defining the state of the possible – how mature are AI technologies currently, what are the realistic use cases, and what is hype?
• Getting beyond the buzzword to identify what opportunities does AI present to Governmental organizations seeking to improve their delivery of services?
• Avoiding bias in data sets, algorithms, and machine learning models to ensure citizens are treated fairly & equitably

• Enabling transformation and decision making with trusted data
• Ensuring data quality, consistency, and integration
• Improving the quality and speed of government decision-making at scale by automating administrative tasks

• Why ethical factors can no longer be an afterthought of AI initiatives
• Why ethics, transparency, and explainability are necessary for successful, scalable AI programs
• How are you navigating privacy, trust, and security concerns around the use of AI?

• Aligning your data & analytics strategy with cross-government & organization level priorities and goals
• Balancing strategic approaches to data analytics with the changing priorities of the wider organization
• How innovative technologies such as AI and Machine Learning can be leveraged to modernize government data architectures?

• Defining the state of the possible – how mature are AI technologies currently, what are the realistic use cases, and what is hype?
• Getting beyond the buzzword to identify what opportunities does AI present to Governmental organizations seeking to improve their delivery of services?
• Avoiding bias in data sets, algorithms, and machine learning models to ensure citizens are treated fairly & equitably

• Enabling transformation and decision making with trusted data
• Ensuring data quality, consistency, and integration
• Improving the quality and speed of government decision-making at scale by automating administrative tasks