As artificial intelligence rapidly advances toward potentially surpassing human capabilities across most domains, fundamental questions emerge about human purpose and meaning in a post-TAI world. This research proposal explores how traditional sources of meaning like work and achievement might transform when AI handles most complex tasks, and what new frameworks could sustain human flourishing in such conditions.

Understanding the Meaning Gap

The core challenge stems from how humans derive meaning from activities that AI may soon dominate: creative work, skilled professions, scientific discovery, and technological innovation. These domains currently provide structure, challenge, and identity for many people. Historical transitions like the industrial revolution caused similar disruptions, but TAI presents qualitatively different challenges because it could potentially outperform humans in nearly all intellectual domains rather than just physical labor.

Some key questions this research would investigate:

• Which components of meaning (purpose, significance, coherence) are most vulnerable to disruption?
• How have societies adapted meaning systems after major technological shifts?
• What new social structures or practices could emerge in a world where traditional productivity becomes largely unnecessary?

Research Approaches and Applications

One way to approach this would be through interdisciplinary methods combining philosophy's conceptual rigor with psychology's empirical tools. This might involve:

1. Analyzing historical cases where technology disrupted meaning systems
2. Surveying current attitudes about AI's impact on personal purpose
3. Developing and testing prototype interventions for meaning preservation

The findings could inform policymakers designing future social systems, AI developers considering societal impacts, and philosophers studying human purpose. While primarily academic, the research might attract funding from tech company responsibility initiatives or government future studies programs, given its relevance to social stability in potential post-work scenarios.

Execution Strategy

A minimal viable approach could begin with a comprehensive literature review establishing the research framework, followed by pilot studies measuring how people currently imagine their sources of meaning might change with advanced AI. This foundation could then support more speculative work exploring novel meaning systems for post-TAI conditions, using scenario-based thought experiments with diverse participant groups.

The ultimate goal wouldn't be to predict the future, but to identify robust principles of human meaning-making that could inform societal adaptation regardless of how exactly TAI develops. This could complement existing work on AI safety and economic transitions by focusing specifically on the psychological dimensions of a radically transformed world.