Artificial Intelligence and Federal Agencies

Artificial intelligence stands to revolutionize government agencies — as long as they understand how to procure, implement and use it, according to a new report.

The Administrative Conference of the United States commissioned the report, titled “Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies,” from researchers at Stanford and New York Universities. Released in February, it found that 45% of federal agencies have experimented with AI and related machine learning tools and that those agencies are already improving operations in myriad ways, such as monitoring risks to public health and safety and enforcing regulations on environmental protection.

“The growing sophistication of and interest in artificial intelligence (AI) and machine learning (ML) is among the most important contextual changes for federal agencies during the past few decades,” the report stated.

The Department of Justice’s Office of Justice Programs had 12 AI use cases — the most of the responding agencies. The Securities and Exchange Commission and NASA follow with 10 and 9, respectively. In total, the researchers documented 157 use cases across 64 agencies after studying 142 federal departments, agencies and subagencies.

More broadly, the top three policy areas where AI is used were law enforcement, health and financial regulation. In terms of government tasks, regulatory research, analysis and monitoring clocked in at about 80 use cases, while enforcement had about 55, and public services and engagement had about 35.

The report also found that agencies were at different stages of AI and ML use. Fifty-three use cases, or 33%, were fully deployed, whereas roughly 60 were in the planning phase and about 45 were piloting or have partially deployed. More than half — 53% — of the AI and ML use cases were developed in-house, while roughly a third were built by commercial contractors and about 13% involved collaboration with non-commercial entities such as an academic lab.

One agency that uses AI for enforcement is SEC, which has a suite of algorithmic tools to identify violators of securities laws. For example, to detect fraud in accounting and financial reporting, the agency developed the Corporate Issuer Risk Assessment, which has a dashboard of about 200 metrics that can find anomalies in the financial reporting of more than 7,000 corporate issuers of securities. An ML tool identifies filers who might be engaging in suspicious activities by using historical data to predict possible misconduct.

Two other tools — the Advanced Relational Trading Enforcement Metrics Investigation System and the Abnormal Trading and Link Analysis System — look for suspicious trading. ARTEMIS hunts for potential serial insider trading offenders by using an electronic database of more than 6 billion electronic equities and options trading records to study patterns and relationships among traders. ATLAS analyzes for first-time offenders.

Lastly, the Form ADV Fraud Predictor helps predict which financial services professionals who manage more than $25 million in assets annually may be violating federal securities laws. The tool parses Form ADVs, which those professionals must submit to the SEC annually. Ultimately, it flags people as high, medium or low priority for further SEC investigation.

Despite the ways these tools help SEC employees, there are challenges. For instance, many of the documents powering the tools are not in machine-readable formats, the agency struggles to find accurate ground truth for algorithm training data, and it must stay up-to-date on what constitutes wrongdoing.

The report identified a common lack of sophistication across the use cases. Researchers ranked only 12% as highly sophisticated. “This is concerning because agencies will find it harder to realize gains in accuracy and efficiency with less sophisticated tools,” the report stated. “This result also underscores AI’s potential to widen, not narrow, the public-private technology gap.”

More understanding about how agencies use and acquire AI and ML tools is necessary to further adoption, the report said.

“Rapid developments in AI have the potential to reduce the cost of core governance functions, improve the quality of decisions, and unleash the power of administrative data, thereby making government performance more efficient and effective,” the report stated. “Agencies that use AI to realize these gains will also confront important questions about the proper design of algorithms and user interfaces, the respective scope of human and machine decision-making, the boundaries between public actions and private contracting, their own capacity to learn over time using AI, and whether the use of AI is even permitted. These are important issues for public debate and academic inquiry.”

Author: Prasanna Haresh Patil

References: https://fcw.com/articles/2020/04/30/comment-covid-data-management.aspx

https://washingtontechnology.com/articles/2020/04/29/insights-palmer-ai-governance.aspx?m=1

https://gcn.com/articles/2020/03/03/ai-use-cases-federal-agencies.aspx

IG Report: GSA Missed out on $1.1 Billion in Potential Savings

The General Services Administrations inspector general issued its annual review this month of 130 pre-award audits of new or renewed schedule contracts. The report outlines several adjustments to price and discounts that amount to an alarming $1.1 billion in potential savings that the agency has missed out on.

“By not effectively using all of the negotiation tools available, contracting officers are failing to leverage the government’s purchasing power,” the report states. “While we recognize that negotiations may not always yield the full amount of cost savings identified in our pre-award audit reports, FAS’ general disregard of pre-award audit results wasted our audit resources and forfeited opportunities to save over $900 million in taxpayer dollars.”

The report is a huge hit to the GSA, as a potential loss of this magnitude could cause a great deal of trouble for those responsible. This $1.1 billion figure may not be entirely accurate. These pre-award audits arise from an analysis of a single data point, and does not take negotiations and other administrative costs into account.

Experts maintain that, while pre-award audits are helpful, they may not accurately depict the actual price paid by the agency. To make a more accurate report, the inspector general’s audits would need to wait to review post-award information. While this may result in more accurate information, the delay could wind up allowing agencies to overpay for years before the issue is identified.

GSA and the IG have been working together to make improvements to schedule contracts. A GSA official said the Federal Acquisition Service and the IG formed a working group in 2018 to improve the value of pre-award audits. The working group helped develop new policies, established performance metrics that are reviewed quarterly, which led to a 22% improvement in audit timeliness, and more than 2,100 hours of training for the acquisition workforce.

Author: Paul McVeigh

Source: https://federalnewsnetwork.com/reporters-notebook-jason-miller/2020/04/ig-says-gsa-missed-out-on-potentially-1-1b-in-savings-but-is-that-really-the-case/

Navy Contract Spending: 30% Increase Despite COVID-19

For many across the country, across the world for that matter, the effects of COVID-19 have had a significant impact on everyday businesses. For most, this impact is negative, costing tens of millions of Americans their jobs and forcing small businesses to hang on for dear life. Within Federal contracting, contractors have had the fortunate of performing the needs required by the country maintain the status quo in the ability to perform daily task, showing improved results from previous years.

Even with trillions of dollars being allocated for stimulus and small business relief, the Navy reported a 30% increase in contract spending as compared to last years figures. As of Tuesday, April 28, 2020, the Department of the Navy obligated $96.9 billion towards contracts in April, compared to $74.7 billion in April of 2019, even though more than 95% of its contracting workforce is working remotely. During the same month, those acquisition professionals also increased their use of distance learning for ongoing workforce development by more than 65%.

This increase is undoubtedly a result of the Navy’s efforts to combat this virus, spending more dollars-on-contract to ensure our country’s safety and supply chain efficiency. The increase also shows that the Navy has seen research and development efforts, as well as acquisition efficiencies pay off. “I’m seeing some remarkable efficiencies,” said James Geurts, the assistant secretary of the Navy for research, development and acquisition, on a conference call Tuesday. “I think a lot of that is getting rid of layers of bureaucracy that weren’t needed. Some of it is also creating better partnerships with industry so that we can leverage cost and pricing data we already have, and we don’t have to send out an RFP and get a proposal back just to confirm that data. And some of it is just a continued sense of urgency and mission focus.”

The Navy’s efforts, along with the contractors who continue to fulfill critical contract obligations, are paying off in fighting this unprecedented virus. It is encouraging that we are seeing an increase in spending, especially since it illuminates improvements in reaction time and efficiency, areas that are integral in keeping our country safe.

Author: Paul McVeigh

Source: https://federalnewsnetwork.com/defense-main/2020/04/navy-contract-spending-jumps-30-in-april-amid-covid-pandemic/