Reports & Testimonies
Recommendations Database
GAO’s recommendations database contains report recommendations that still need to be addressed. GAO’s priority recommendations are those that we believe warrant priority attention. We sent letters to the heads of key departments and agencies, urging them to continue focusing on these issues. Below you can search only priority recommendations, or search all recommendations.
Our recommendations help congressional and agency leaders prepare for appropriations and oversight activities, as well as help improve government operations. Moreover, when implemented, some of our priority recommendations can save large amounts of money, help Congress make decisions on major issues, and substantially improve or transform major government programs or agencies, among other benefits.
As of October 25, 2020, there are 4812 open recommendations, of which 473 are priority recommendations. Recommendations remain open until they are designated as Closed-implemented or Closed-not implemented.
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Results:
Subject Term: Automation
GAO-19-161, Mar 7, 2019
Phone: (202) 512-7215
Agency: Department of Labor
Status: Open
Comments: DOL agreed with this recommendation. The agency noted several efforts that it said will help the agency assess and provide information on the potential workforce effects of evolving technologies, such as automated trucking. For example, DOL noted that the agency's employment projections incorporate expert interviews and other information to identify shifts in industry employment. DOL is also currently consulting with DOT to study these workforce effects, and agreed to consider what other information and stakeholder meetings remain necessary after that study-due in March 2019-is completed. Likewise, DOL agreed to share related information as the technology evolves, and the agency noted it currently publishes employment projections and other occupational information. While useful, these efforts alone will not allow DOL to sufficiently anticipate the future workforce effects of automated trucking. For instance, the broad employment projections do not provide estimates specifically for the long-haul truck drivers who could be affected by automated trucking first. Further, DOL's occupational information is based on surveys of current workers, so it does not include the skills future drivers will need as automated trucking evolves. Therefore, we continue to believe that convening stakeholders and sharing information about potential workforce effects in the future will position DOL to better understand and inform key stakeholders of these changes.
Agency: Department of Transportation
Status: Open
Comments: DOT agreed with this recommendation. We will monitor the agency's progress to address it.
Agency: Department of Transportation
Status: Open
Comments: DOT agreed with this recommendation. The agency noted two of its current efforts related to automated trucking technology, namely its October 2018 automated vehicles voluntary guidance, Preparing for the Future of Transportation: Automated Vehicles 3.0, and its Congressionally-directed research on the impact of automated vehicle technologies on the workforce.
Agency: Department of Labor
Status: Open
Comments: DOL agreed with this recommendation. The agency noted several efforts that it said will help the agency assess and provide information on the potential workforce effects of evolving technologies, such as automated trucking. For example, DOL noted that the agency's employment projections incorporate expert interviews and other information to identify shifts in industry employment. DOL is also currently consulting with DOT to study these workforce effects, and agreed to consider what other information and stakeholder meetings remain necessary after that study-due in March 2019-is completed. Likewise, DOL agreed to share related information as the technology evolves, and the agency noted it currently publishes employment projections and other occupational information. While useful, these efforts alone will not allow DOL to sufficiently anticipate the future workforce effects of automated trucking. For instance, the broad employment projections do not provide estimates specifically for the long-haul truck drivers who could be affected by automated trucking first. Further, DOL's occupational information is based on surveys of current workers, so it does not include the skills future drivers will need as automated trucking evolves. Therefore, we continue to believe that convening stakeholders and sharing information about potential workforce effects in the future will position DOL to better understand and inform key stakeholders of these changes.
GAO-19-257, Mar 7, 2019
Phone: (202) 512-7215
including 1 priority recommendation
BLS could expand existing worker or firm surveys to ask respondents whether advanced technologies have resulted in worker displacements, work hour reductions, or substantial adjustments to work tasks.
BLS could expand its employment projections work to regularly identify occupations projected to change over time due to advanced technologies.
ETA could expand the O*NET data system to identify changes to skills, tasks, and tools associated with occupations, as the information is updated on its rotational basis, and consider how this could be used to track the spread of advanced technologies.
(Recommendation 1)
Agency: Department of Labor
Status: Open
Priority recommendation
Comments: DOL agreed with this recommendation. DOL stated that it will continue coordinating with the Census Bureau on research activities in this area, and plans to identify and recommend data collection options to fill gaps in existing information about how the workplace is affected by new technologies, automation, and AI. In February 2020, DOL's Bureau of Labor Statistics (BLS) issued a public report evaluating data gaps and providing recommendations for data collection options. In June 2020, DOL reported that BLS plans to host a seminar to discuss the report findings and potential pilot data collection options. DOL also plans to release its first annual employment projections data in September 2020 (previously released every 2 years). In addition, DOL reported that the Employment and Training Administration has undertaken three research efforts, which are still underway, to test ways to analyze O*NET data elements for their potential to track changes in occupations over time and to flag areas for further study on the workforce effects of automation. This recommendation will be implemented when DOL completes more of its activities.
Phone: (202) 512-2834
including 1 priority recommendation
Agency: Department of Transportation
Status: Open
Priority recommendation
Comments: In July 2018, DOT released an initial plan related to this recommendation in response to congressional direction. This plan outlines DOT's overall approach for managing policy and research issues related to automated vehicles across DOT's modal administrations. In January 2020, DOT and the National Science and Technology Council released Ensuring American Leadership in Automated Vehicle Technologies (AV 4.0), building on prior policies that DOT has identified as actions regarding its implementation of GAO's recommendation. DOT has yet to identify, for example, performance measures to monitor and gauge results. Without a comprehensive plan, it continues to be unclear whether DOT is adequately tackling automated vehicle challenges.
GAO-17-281, Feb 7, 2017
Phone: (202) 512-6304
Agency: Department of Housing and Urban Development
Status: Open
Comments: In April 2017, HUD reported that the department concurred with the recommendation and noted that the Office of the Chief Information Officer (OCIO) intended to establish cost estimation guidance for IT projects within its IT Management Framework Guide, incorporating appropriate best practices from the GAO Cost Estimating and Assessment Guide. In March 2019, HUD reported that, with contractor assistance, the department had begun to develop a standard methodology for investment lifecycle cost estimation; however, the methodology had not been fully institutionalized across all investments, and a policy for cost estimation had not been developed. Lacking an updated IT Management Framework and cost estimation policy, OCIO took additional interim action in the most recent budget cycle to reduce cost estimation risk by having the Chief Technology Officer standardize the cost estimates for IT investments. HUD continues to take action intended to address this recommendation; however, OCIO has not yet finalized a cost estimation methodology or the associated policy for IT investments or established a timeframe for implementing cost estimation practices departmentwide.
GAO-16-336, Mar 30, 2016
Phone: (202) 512-4456
Agency: Department of Defense: Department of the Navy
Status: Open
Comments: DOD concurred with this recommendation and stated in March 2016 that the Navy had corrected the data query issue that caused 11 requirements to be eliminated from the traceability matrix we reviewed. DOD also stated that the Navy had identified the weakness in the traceability process that led to 14 general requirements not being fully traced. However, as of June 2020, DOD had not provided us with documentation that supports that it identified the weakness in the requirements traceability process. It also had not demonstrated that the program office has updated its requirements management guidance to address the weakness it identified.