JAIC Seeks Commercial Partners for AI Data Prep
It’s calling for commercial partners to help with AI data prep via its Data Readiness for Artificial Intelligence Development (DRAID) Services acquisition vehicle request for proposal (RFP). The data will be used in the JAIC’s recently launched Joint Common Foundation, a cloud-based platform that enables users to develop AI solutions in a secure environment.
The RFP is notable in that it contains an Accessibility Guide to help startups, small businesses, and non-traditional defense contractors navigate the Pentagon’s proposal process.
The JAIC explained the rationale for its approach in a blog post: “Because AI is a rapidly emerging field, innovative and breakthrough technologies are well distributed across the entire commercial landscape. Innovation is just as likely to be found in the newest startups pioneering breakthrough approaches as it is in the largest traditional companies. In developing the DRAID, we have taken effort to ensure that the best providers— regardless if this is their 1st or 101st time interacting with the Federal government—will be able to participate in the RFP process.”
The scope of work solicited “encompass[es] all tasks needed to create, acquire, curate, prepare, manage, or secure data sets for use in DoD AI models and application development, testing, certification, and operation.” These tasks range from project and program management to data engineering, database development, and data analysis, among others.
While JAIC will serve as the gateway, the services sought are intended to be accessible to all DoD departments and other government users. The potential uses entail DoD-wide support services and warfighting.
The blog post stresses the “cornerstone” of an ethical approach to AI, in accordance with its Ethical Principles for AI. The ethical AI focus follows the Pentagon’s efforts over nearly three years to strengthen trust with the private sector following the fallout over Project Maven.
The blog post notes, “AI systems must be responsible, equitable, traceable, reliable, and governable, apply across the entire product lifecycle and for combat and non-combat application. The DoD recognizes that AI Ethics cannot be ‘bolted on’ to an AI system after it is developed. Successfully embodying these principles in our systems requires integrating prompts, tools, and checkpoints to assess ethical risks across the AI product lifecycle, including directly into our technological processes. AI data preparation is a particularly important focal area in this regard.”
The blog post further explains the program’s focus on “forward-looking areas” to include “AI security, synthetic data generation, and data representativeness.”
To these points, JAIC writes, “AI security must be accounted for early in the process to ensure the data used to train AI systems has not been manipulated or poisoned in a way that will compromise AI system performance once the system is fielded. Synthetic data generation provides alternatives to having to collect, prepare, and label significant amounts of data, promising to substantially accelerate the development process. Checking for data representativeness, such as data bias or excluded entities, both serves to instantiate the DoD AI Ethical Principles as well as ensuring optimal system performance once the AI system is in the hands of the warfighter.”
In September 2020, JAIC then-Acting Director and current CTO Nand Mulchandani laid out a vision and strategy in an interview with Breaking Defense. Mulchandani explained that the JCF will be the technological toolkit for developing AI, and Tradewind will be the contracting toolkit.
Mulchandani mentioned the JAIC’s goal to develop, as part of Tradewind, at least three Multiple Award Contract (MAC) vehicles, including a Data MAC. DRAID appears to be JAIC’s first Data MAC.
Proposals are due to JAIC at 1 p.m. EDT on April 28.