Virtual Library

Our virtual library is an online repository of all of the reports, papers, and briefings that IST has produced, as well as works that have influenced our thinking.

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Op-ed

ROOST Reminds Us Why Open Source Tools Matter

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Reports

Navigating AI Compliance, Part 2: Risk Mitigation Strategies for Safeguarding Against Future Failures

Mariami Tkeshelashvili and Tiffany Saade

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Reports

Deterring the Abuse of U.S. IaaS Products: Recommendations for a Consortium Approach

Steve Kelly, Tiffany Saade

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Podcasts

TechnologIST Talks: Looking Back and Looking Ahead: Deep Dive on the New Cybersecurity Executive Order

Carole House, Megan Stifel, and Steve Kelly

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Podcasts

TechnologIST Talks: The Offense-Defense Balance

Philip Reiner and Heather Adkins

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Reports

The Generative Identity Initiative: Exploring Generative AI’s Impact on Cognition, Society, and the Future

Gabrielle Tran, Eric Davis

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Podcasts

TechnologIST Talks: A Transatlantic Perspective on Quantum Tech

Megan Stifel and Markus Pflitsch

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Contribute to our Library!

We also welcome additional suggestions from readers, and will consider adding further resources as so much of our work has come through crowd-sourced collaboration already. If, for any chance you are an author whose work is listed here and you do not wish it to be listed in our repository, please, let us know.

SUBMIT CONTENT

AI and Human Decision Making: AI and the Battlefield

Institute for Security and Technology, Center for Global Security Research

SUMMARY

As the 21st-century geopolitical balance shifts in uncertain ways, there is an increasing eagerness to deploy AI technologies into both the physical and digital battlefields to gain both tactical and strategic advantage over adversaries. However, the nature of increasingly powerful and unpredictable AI demands a measured and balanced approach to deploying these tools before the limitations, risks, and vulnerabilities are fully understood and addressed. Indeed, these technologies may not currently be “ready for primetime”, on a number of levels. We begin this discussion – meant to be a series of posts on this domain of issues – focused on the following. This initial paper is based off of numerous small-group workshops and ongoing engagement with the AI research community in the San Francisco Bay Area. This initial paper is based off numerous small-group workshops and ongoing engagement with the AI research community in the San Francisco Bay Area: Current AI capabilities remain limited to narrow, well-defined domains. ​ The “black box” nature of state-of-the-art AI/ML algorithms gives limited insight as to their decision-making processes – and conclusions Deploying AI’s could preempt ethical considerations that have yet to be fully understood, identified, or agreed upon, and is in the potential context of an industry-driven race to the bottom

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