The AI Lab has the mission to analyze and compare how emerging transformative technologies, such as artificial intelligence, genomics and genome-editing, raise new opportunities and challenges for health, security, economics and governance in different geo-political contexts.

Technological advances in artificial intelligence (AI), automation, genomics, additive manufacturing and nanotechnology are increasingly converging and enabling each other, with significant ramifications in health, economics, security, and governance. This transformative power reminds us of: the continued presence of a diverse array of threats to our country; lingering vulnerabilities in our defenses; the consequences of not adequately addressing these vulnerabilities; and the centrality that technological convergence will continue to play in our society.

The new twist to the science policy game is the sheer complexity of the socio-technical systems that surround us. In the past, policymakers and funders could often ignore complexity, and it did not have much of an impact on their results. People were less connected, markets were less integrated, disciplines existed in siloes, and the flow of knowledge was severely limited. Part of the growing complexity challenge involves technological convergence, the increasing interaction of multiple fields, such as AI, genomics and nanotechnology, which rapidly expands the range of possible impacts that need to be considered in any science policy exercise. Ten years ago, nanotechnology was celebrated largely for its impacts on chemistry and material sciences, but the ability to precision engineer matter at genetically relevant scale has resulted in significant advances in neurosciences, such as creating the ability to interrogate networks of neurons.

As “outsiders” to the AI design processes, it is extremely complex for policymakers to assess AI development because of a human trend to overestimate technologies in the short term, a lack of comprehension of how the technology functions, applying traditional outdated regulatory models that are not adequate for AI, and playing a catch-up game to decode the terms of reference used by researchers. There will be significant systems’ transformations through AI and converging technologies over the next few decades, but perhaps it will be more incremental than we fear or imagine.

An ethos of responsible AI innovation would bring technologists, scholars, and policymakers together in an effort to ensure that society reaps all of the benefits and avoids potential harms. This is the goal and mission The AI Lab aims to foster.