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

• The need for data officers to adopt strong security and governance processes
• How innovative technologies such as AI and Machine Learning can be leveraged to modernize government data architectures?
• Prioritize building an efficient organization by establishing clear data governance polices to promote data driven decisions at all levels

• How are you raising data quality awareness within your agency?
• How are you coordinating the people, processes, and culture necessary for success?
• Identifying tools & technology needed for creating & maintaining high quality data

• 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

Participants:

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

• Communicating the purpose of data collection to citizens
• Assessing potential privacy risks and identify mitigation measures
• Avoiding unnecessary or excessive data collection

Participants:

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

• 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

Participants:

Nathan Manzotti, Director, Data Analytics & AI Centers of Excellence / Co-Manager AI Community of Practice, GSA - TECHNOLOGY TRANSFORMATION SERVICES

Marcus Thornton, Deputy Chief Data Officer, COMMONWEALTH OF VIRGINIA

• 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

Participants:

LaShonda Henderson, Data Evangelist, Branch Chief Data Quality, UNITED STATES CITIZEN AND IMMIGRATION SERVICES

• Communicating the purpose of data collection to citizens
• Assessing potential privacy risks and identify mitigation measures
• Avoiding unnecessary or excessive data collection

Participants:

Shravan Kotha, Chief Data and Analytics Officer, OHIO ATTORNEY GENERAL'S OFFICE

• 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

Participants:

CAPT Kathleen Powell, RESFOR Force Data & AI Officer, U.S. NAVY RESERVE

Richard Patterson, CGFS Chief Data and AI Officer, U.S. DEPARTMENT OF STATE

• 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

Participants:

COL Kristin Saling, Chief of Staff, Innovation Directorate, US ARMY RECRUITING COMMAND

• Communicating the purpose of data collection to citizens
• Assessing potential privacy risks and identify mitigation measures
• Avoiding unnecessary or excessive data collection

Participants:

Julia Cherashore, Deputy Superintendent, Data Governance and Management, NEW YORK STATE DEPARTMENT OF FINANCIAL SERVICES

• 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

Participants:

Anil ‘Neil’ Chaudhry, Senior Advisor, Artificial Intelligence, US DEPARTMENT OF TRANSPORTATION  

• 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

• Communicating the purpose of data collection to citizens
• Assessing potential privacy risks and identify mitigation measures
• Avoiding unnecessary or excessive data collection

• 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

Participants:

Dr. Delester Brown Jr., Chief Data & AI Officer, NATIONAL GUARD BUREAU

• 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