The More Things Change, the More They Stay the Same for the TSP
In this insightful interview, Kim Weaver, Director of External Affairs at the Federal Retirement Thrift Investment Board, discusses the changes and constants in the Thrift Savings Plan (TSP) for 2024. Kim highlights the new IRS limits for contributions, the unchanged catch-up limits for older participants, and the role of social sciences in enhancing participant engagement and savings strategies. She delves into the effectiveness of different communication strategies to encourage savings and the commitment of TSP to act in the best interests of its participants.
- Updated TSP Contribution Limits for 2024: The IRS has raised the elective deferral limit to $23,000, and the catch-up limit remains at $7,500 for participants aged 50 and above, enabling a maximum contribution of $30,500.
- Role of Social Sciences in TSP: The use of behavioral economics and nudge theory in communication strategies significantly influences participant contributions and behaviors.
- Roth TSP Exclusion from RMDs: The Secure 2.0 Act changed the requirement for Roth TSP, excluding it from required minimum distributions (RMDs), impacting about 7,000 participants.
Federal Agency AI Explodes at the Use Case Level
Kevin Walsh, Director of the IT and Cybersecurity Team at the Government Accountability Office, discusses the expansive implementation of artificial intelligence (AI) across federal agencies. Kevin reveals the existence of nearly 1200 current or planned AI use cases in the federal government, addressing the evolution, effectiveness, and challenges of these AI applications. He emphasizes the assistive role of AI, its potential to enhance government efficiency, and the necessity of clear guidelines and job categorizations for AI-related positions.
- Expansive AI Use in Government: Almost 1200 current or planned AI use cases exist in federal agencies, indicating a significant and growing reliance on AI technologies.
- AI as Assistive Technology: AI is primarily being used to enhance employee efficiency and handle mundane tasks, rather than replacing full-time employees (FTEs).
- Need for Clear AI Guidelines and Training: There is a lack of clarity in AI definitions and use case documentation, highlighting the need for better guidance, occupational categorization, and training for AI-related workers in the government.