Social Science

In an era of relentless information overload and pervasive misinformation—fueled by algorithms that prioritize fleeting engagement over meaningful value—we have the opportunity to reshape our digital spaces. By leveraging AI and more intentional design of social media spaces for epistemic improvement, we can empower users to curate, evaluate, and contextualize content more effectively to create a healthier digital world.

As AI systems become the cornerstone of competitive advantage, they can inadvertently marginalize human roles and decision-making. The drive for efficiency and cost reduction may lead organizations to rely predominantly on AI, sidelining human judgment, creativity, and accountability. This dynamic risks creating environments where economic and social inequities widen, and the intrinsic value of human input is systematically undermined (see examples). The gradual disempowerment of individuals under such competitive pressures poses significant challenges for societal well-being and democratic governance.  See: https://gradual-disempowerment.ai/

Our current systems for democratic participation are hindered by outdated platforms and tools that fail to scale with modern needs. Limited survey infrastructure, insecure voting methods, and under-informative deliberative tools restrict our capacity for informed, collective decision-making. By harnessing AI to facilitate clearer expression of public opinion and leveraging innovative technologies for secure, scalable engagement, we can transform civic participation into a more robust, effective, and inclusive process.

Policy development and evaluation processes today rely heavily on manual human review to ensure accountability. However, as AI systems increasingly support or automate these processes, this human-centered accountability becomes challenging. Human reviewers risk becoming a critical bottleneck, slowing policy implementation. New tools are needed to streamline policy creation and evaluation, and to ensure consistency and compliance before deployment.

The social sciences need new tools to help researchers identify and prioritize important questions that will have an impact, and better infrastructure to collect qualitative data. Qualitative methods are powerful for understanding the how and why behind social outcomes, yet even the most comprehensive surveys don’t capture all the factors that contribute to social outcomes. AI-enabled qualitative methods could super-charge the social sciences, but there is much work to be done. Similarly, many archaeological methods remain manual and lack the technological revolution seen in other fields, limiting discovery and analysis.

Current education systems face structural inefficiencies such as excessive administrative workloads on educators, overcrowded classrooms, and inequitable resource distribution. Innovative technologies have the potential to significantly reduce these burdens by providing tools that assist teachers with scheduling, grading, and creating personalized, adaptive lesson plans. Digital platforms could dynamically tailor learning experiences to individual student progress, complementing classroom teaching. Additionally, technology-driven improvements in administrative efficiency could free valuable resources, enhancing educational equity and overall student experiences. “US K-12 teachers are 30% more likely to face burnout than U.S. soldiers, whose lives are defined by relentless duty, perpetual war and low wages.” - Adrienne Williams  “Given recent improvements in the quality, affordability, and usability of technologies like AI, computer vision, and AR/VR, we can reimagine a more personali...

Current economic models are often too simplistic to capture the intricate dynamics of our global economy, limiting effective policy-making and forecasting. Experimentation with innovative economic models—such as those incorporating universal basic income or alternative market systems—is rare, leaving us unprepared for emerging trends. The inherent complexity of global systems further complicates accurate forecasting, underscoring the urgent need for more sophisticated, adaptive tools that can better predict and navigate the economic landscape of tomorrow.

There exists a disconnect between academic research and the practical implementation of development economics, hampering the conversion of theoretical insights into effective real-world interventions. Current mechanisms for delivering public goods and fostering collective cooperation are inefficient, limiting our capacity to coordinate resources and drive meaningful change. Innovative approaches are needed to bridge this gap, ensuring that cutting-edge economic theories can be transformed into actionable policies and scalable interventions that truly improve development outcomes.

Much critical data is stored on proprietary platforms and is at risk of disappearing, hindering long-term research and reproducibility.