ArchiveDisruptive TechnologyOODA Original

DHS Science and Technology Directorate (S&T) releases Artificial Intelligence (AI) and Machine Learning (ML) Strategic Plan Amidst Flurry of USG-wide AI/ML RFIs

An artificial intelligence security strategy (see “Securing AI – Four Areas to Focus on Right Now”) should be the cornerstone of any AI and machine learning (ML) efforts within your enterprise.  We also recently outlined the need for enterprises to further operationalize the logging and analysis of artificial intelligence (AI) related accidents and incidents based on an “AI Accidents” framework from the Georgetown University CSET.    As a next step, we have taken the time to sort out the signal from the noise in the vast amount of solid research and not so great media coverage (or ‘think pieces’) AI and ML have garnered in the last five years.  The best analysis is a sophisticated body of work on AI-related issues of morality, ethics, fairness, explainable and interpretable AI, bias, privacy, adversarial behaviors, trust, fairness, evaluation, testing and compliance. 

As far as governmental contributions, what should be encouraging to industry players is the fact that AI/ML strategy is now very actionable at the policy, research and development and strategic partnership level across the USG.  Not to be too Pollyanna, but current agency efforts really do deserve praise for the sophistication, open collaboration and interdisciplinary research approach of their initial strategic initiatives, proposals and documents to date.  The ICT infrastructure of the USG intelligence agencies notwithstanding, within government agencies AI and ML strategic plans have not reached an implementation phase – nor are they in any way operational.  

To start, we have evaluated the efforts within the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) based on the August 2021 release of  the DHS S&T Artificial Intelligence (AI) and Machine Learning (ML) Strategic Plan.


Using the classification of the three types of “AI Accidents” provided by the Georgetown CSET,
we charted the DHS S&T AI and ML strategies to the CSET AI Accidents framework 


Case studies and primary source documents are linked throughout the flow chart in the PDF version (link opens in new tab). 

Please feel free to reach out directly ( if you would like to receive the pptx source file. 

The DHS S&T document is found here:  Artificial Intelligence (AI) and Machine Learning (ML) Strategic Plan  (August 2021)

Depending on the priorities for your enterprise, this chart should be helpful for AI/ML strategic planning within your organization.  In short, now is the time for the AI enterprise to plug into the research, development, test, and evaluation activities within the DHS S&T which will grow out of this strategic document. 

The DHS S&T Strategic Plan was released as part of a flurry of recent activity from the USG regarding AI and ML strategy and implementation, all of which we plan to analyze and coverage in the weeks ahead.

Further USG AI and ML initiatives announced recently:

AI.GOV  National Artificial Intelligence Initiative – Overseeing and Implementing the US National AI Strategy (launched May 2021)

The Biden Administration Launches Aimed at Broadening Access to Federal Artificial Intelligence Innovation Efforts, Encouraging Innovators of Tomorrow | The White House

Request for Information (RFI) on an Implementation Plan for a National AI Research Resource (deadline for comments extended to 10/01/2021)

Request for Information (RFI): Department of Commerce NIST Artificial Intelligence Risk Management Framework (comments due 08/19/2021)

(GAO) Artificial Intelligence: An Accountability Framework for Federal Agencies and Other Entities  06/30/2021

Further OODA Resources: 

OODA Loop – Pentagon Experiments with Self-Driving Shuttles at San Diego Military Base 

OODA Loop – NIST Prioritizes External Input in Development of AI Risk Management Framework 

Special Series on Artificial Intelligence

AI, machine learning, and data science will be used to create some of the most compelling technological advancements of the next decade.  The OODA team will continue to expand our reporting on AI issues.  Please check out the AI reports listed below.

A Decision-Maker’s Guide to Artificial Intelligence –  This plain english overview will give you the insights you need to drive corporate decisions

When Artificial Intelligence Goes Wrong – By studying issues we can help mitigate them

Artificial Intelligence for Business Advantage – The reason we use AI in business is to accomplish goals. Here are best practices for doing just that

The Future of AI Policy is Largely Unwritten – Congressman Will Hurd provides insight on the emerging technologies of AI and Machine Learning.

Artificial Intelligence Sensemaking: Bringing together our special reports, daily AI news and references to AI from the most reliable sources we know. 

Daniel Pereira

Daniel Pereira

Daniel Pereira is research director at OODA. He is a foresight strategist, creative technologist, and an information communication technology (ICT) and digital media researcher with 20+ years of experience directing public/private partnerships and strategic innovation initiatives.