Attracting Commercial Artificial Intelligence Firms to Support National Security through Collaborative Contracts

The United States Department of Defense (‘DoD’) has determined it is not ready to compete in the Artificial Intelligence (‘AI’) era without significant changes to how it acquires AI. Unlike other military technologies driven by national security needs and developed with federal funding, this ubiquitous technology enabler is predominantly funded and advanced by commercial industry for civilian applications. However, there is a lack of understanding of the reasons commercial AI firms decide to work with the DoD or choose to abstain from the defence market. Although there are several challenges to attracting commercial AI firms to support national security, this thesis argues that the DoD’s contract law and procurement framework are among the most significant obstacles. This research indicates that the commercial AI industry actually views the DoD as an attractive customer. However, this attraction is despite the obstacles presented by traditional contract law and procurement practices used to solicit and award contracts. Drawing on social exchange theory, this thesis introduces a theoretical framework – ‘optimal buyer theory’ – to understand the factors that influence a commercial AI firm’s decision to engage with the DoD. It develops evidence-based best practices in contract law that reveal how the DoD can become a more attractive customer to commercial AI firms. This research builds upon research at the nexus of national security and defence contracts as it studies business decision-makers from AI firms through an explanatory sequential mixed methods design. In the study’s first phase, participants are surveyed to discover the perceptions, opinions, and preferences at AI firms of all sizes, maturity, location, and experience within the DoD marketplace. In the second phase of the study, interviews from a sample of the participants explain why the AI industry holds such perceptions, opinions, and preferences about contracts generally and the DoD, specifically, in its role as a customer. This thesis concludes that commercial AI firms are attracted to contracts that are consistent with their business and technology considerations. These considerations align with contractual relationships that are collaborative, flexible, negotiated, iterative, and awarded promptly as opposed to those with fixed requirements and driven by regulations foreign to the commercial market. Additionally, it develops best practices for leveraging existing contract law, primarily other transaction authority, to align the DoD’s contracting practices with commercial preferences and the machine learning development and deployment lifecycle. Armed with this understanding, the DoD can better attract commercial AI firms to support its national security objectives.Thesis (Ph.D.) -- University of Adelaide, Law School, 202

Are ChatGPT and Other Similar Systems the Modern Lernaean Hydras of AI?

The rise of Generative Artificial Intelligence systems (“AI systems”) has created unprecedented social engagement. AI code generation systems provide responses (output) to questions or requests by accessing the vast library of open-source code created by developers over the past few decades. However, they do so by allegedly stealing the open-source code stored in virtual libraries, known as repositories. This Article focuses on how this happens and whether there is a solution that protects innovation and avoids years of litigation. We also touch upon the array of issues raised by the relationship between AI and copyright. Looking ahead, we propose the following: (a) immediate changes to the licenses for open-source code created by developers that will limit access and/or use of any open-source code to humans only; (b) we suggest revisions to the Massachusetts Institute of Technology (“MIT”) license so that AI systems are required to procure appropriate licenses from open-source code developers, which we believe will harmonize standards and build social consensus for the benefit of all of humanity, rather than promote profit-driven centers of innovation; (c) we call for urgent legislative action to protect the future of AI systems while also promoting innovation; and (d) we propose a shift in the burden of proof to AI systems in obfuscation cases

Developing a Series of AI Challenges for the United States Department of the Air Force

Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have influenced organizations such as the United States Department of the Air Force (DAF). The DAF-MIT AI Accelerator is an initiative between the DAF and MIT to bridge the gap between AI researchers and DAF mission requirements. Several projects supported by the DAF-MIT AI Accelerator are developing public challenge problems that address numerous Federal AI research priorities. These challenges target priorities by making large, AI-ready datasets publicly available, incentivizing open-source solutions, and creating a demand signal for dual use technologies that can stimulate further research. In this article, we describe these public challenges being developed and how their application contributes to scientific advances

Are ChatGPT and Other Similar Systems the Modern Lernaean Hydras of AI?

The rise of Generative Artificial Intelligence systems (“AI systems”) has created unprecedented social engagement. AI code generation systems provide responses (output) to questions or requests by accessing the vast library of open-source code created by developers over the past few decades. However, they do so by allegedly stealing the open-source code stored in virtual libraries, known as repositories. This Article focuses on how this happens and whether there is a solution that protects innovation and avoids years of litigation. We also touch upon the array of issues raised by the relationship between AI and copyright. Looking ahead, we propose the following: (a) immediate changes to the licenses for open-source code created by developers that will limit access and/or use of any open-source code to humans only; (b) we suggest revisions to the Massachusetts Institute of Technology (“MIT”) license so that AI systems are required to procure appropriate licenses from open-source code developers, which we believe will harmonize standards and build social consensus for the benefit of all of humanity, rather than promote profit-driven centers of innovation; (c) we call for urgent legislative action to protect the future of AI systems while also promoting innovation; and (d) we propose a shift in the burden of proof to AI systems in obfuscation cases

Are hedgerows effective corridors between fragments of woodland habitat? An evidence-based approach

Anthropogenic modification of the countryside has resulted in much of the landscape consisting of fragments of once continuous habitat. Increasing habitat connectivity at the landscape-scale has a vital role to play in the conservation of species restricted to such remnant patches, especially as species may attempt to track zones of habitat that satisfy their niche requirements as the climate changes. Conservation policies and management strategies frequently advocate corridor creation as one approach to restore connectivity and to facilitate species movements through the landscape. Here we examine the utility of hedgerows as corridors between woodland habitat patches using rigorous systematic review methodology. Systematic searching yielded 26 studies which satisfied the review inclusion criteria. The empirical evidence currently available is insufficient to evaluate the effectiveness of hedgerow corridors as a conservation tool to promote the population viability of woodland fauna. However, the studies did provide anecdotal evidence of positive local population effects and indicated that some species use hedgerows as movement conduits. More replicated and controlled field investigations or long term monitoring are required in order to allow practitioners and policy makers to make better informed decisions about hedgerow corridor creation and preservation. The benefits of such corridors in regard to increasing habitat connectivity remain equivocal, and the role of corridors in mitigating the effects of climate change at the landscape-scale is even less well understood