Rethinc. Labs is a consortium of globally prominent thought leaders and researchers examining how businesses can best mitigate challenges and leverage opportunities amid today’s rapid digital transformation.

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On Quantum Ambiguity and Potential Exponential Computational Speed-Ups to Solving Dynamic Asset Pricing Models

Quantum | May 7, 2024
We formulate quantum computing solutions to a large class of dynamic nonlinear asset pricing models using algorithms, in theory exponentially more efficient than classical ones, which leverage the quantum properties of superposition and entanglement. The equilibrium asset pricing solution is a quantum state. We introduce quantum decision-theoretic foundations of ambiguity and model/parameter uncertainty to deal with model selection.

2024 Future of Digital Assets Symposium

Decentralized Finance | February 28, 2024
In March 2023 the story of crypto hinged on FTX, but crypto has turned a page in a new chapter and that was clearly the case this year. There was an upbeat mood among industry participants, which included some of the creators of the recent SEC approved spot Bitcoin ETFs. Capital inflow into crypto funds has surpassed their two-year highs. However, regulatory uncertainty around the digital assets industry remains.

Pandemic Highlights Differences in European and American Data Privacy Laws

Data Privacy | May 28, 2020
Traditional contact tracing, where workers query patients about their interactions to see who else might have been infected — and perhaps to find out where they got the infection — is being widely used. But for the first time, many public health authorities are considering, or have implemented, smart phone apps to partially automate and scale contact tracing.

Artificial Intelligence: A Strategy to Harness its Power Through Organizational Learning

AI & Machine Learning | March 16, 2022
Although artificial intelligence (AI) has become a crucial component of digital transformation efforts tied to organizational strategy, many firms struggle to articulate the strategic value of emerging AI systems. In this article we argue that the power of AI as a strategic resource lies in its self-learning capabilities. Such learning capabilities are only realized in partnership with humans through mutual learning. By building on a learning-centered framework, we elaborate on how AI can contribute to organizational learning to create a competitive advantage. We formulate the concept of artificial capital and the ways artificial and human capital can together drive routinization and strategic learning processes that connect internal and external environments of the organization. Finally, we use this conception to formulate practical recommendations for managing and developing AI to meet strategic business goals.