The rankings and accompanying data provide a means of holding federal leaders accountable for the health of their organizations, shining the spotlight on agencies that are successfully engaging employees as well as on those that are falling short. All in-person sessions will take place at the Partnership for Public Service offices in Washington, D.C. and applicants who live in the D.C. metro area are highly encouraged to join the in-person program. Different agencies and levels of government have widely varying experience with using artificial intelligence in public service delivery. All in-person sessions will take place at the Partnership for Public Service offices in Washington, D.C. and applicants who live in the D.C. metro area are highly encouraged to join the in-person program. Theinformationalsoprovideshistorical comparisons to the previous administrationandillustrations of thedatathat revealkey confirmation and nomination trends. Biased tendencies can also affect our professional lives. Sep 20, 2022. Positive numbers indicate how many more times a given adjective was used than expected. Work with ODEP to provide expertise on key industry issues as they pertain to the employment of people with disabilities. Partnership for Public Service and Accenture Federal Services, "Government for the People: Designing for Equitable and Trusted Customer Experiences," Nov. 16, 2021. Although they highlight many of the same principles, each of these frameworks addresses specific considerations for how to achieve responsible artificial intelligence in a particular contextfor example, in the medical or legal fields. There are many different types of biases, both unconscious and conscious. Listen in, Our Best Places to Work in the Federal Government Rankings are the authoritative rating of employee engagement in government. Agencies also should consider how to establish governance processes that facilitate agility, so that they can adapt as circumstances change and continue to adhere to responsible AI principles. Richardson, Agnes, and Cynthia Loubier. Our previous research highlighted differences between how men and women leaders in the federal government scored on the Public Service Leadership Model. .paragraph--type--html-table .ts-cell-content {max-width: 100%;} While not in the list of top three adjectives, we include warm here for comparison since it has been used in the literature to describe a characteristic that women leaders are more often expected to display than leaders who are men. Partnership for Public Service. Graduation from Partnership programs is contingent upon full attendance and participation in our training sessions. Phase 1 of the project ran from 2016 to 2019, and Phase 2 of the project will run until December 2024. How can government leaders ensure their use of AI is responsible? When DEI is optimized, everyone is encouraged and feels safe in bringing their . Washington, DC 20005. Our Center for Presidential Transition is the nations premier nonpartisan resource for presidential candidates and their teams as they prepare for a new administration or a presidents second term. Similarly, we found significant differences in the top adjectives used to describe the federal leaders in our sample based on race and gender. Partnership for Public Service; Best Places to Work; Center for Presidential Transition; Go Government; Service to America Medals; Home; Frequently Asked Questions; Media Highlights; Resources; Contact Us Of those, 1,123 were self-ratings, and 14,007 were ratings completed by othersfor example, managers, direct reports, friends or family, or colleagues. Focusing on the common reference point of the problem an AI tool is intended to solve can help technical and non-technical leaders communicate more effectively. print and electronic media, electronic assistance tools and ODEP's and the PPS's Web sites) to employers. $60,711 to $91,067 Yearly. Portillo, Shannon, Nicole Humphrey, and Domonic A. Bearfield. The adjective intelligent was used statistically significantly less for men of diverse racial and ethnic backgrounds than for any other group. Women are often perceived as warm and communal, whereas leaders are often viewed as more assertive and competent.4, In addition to these implicit biases, how we define and imagine leadership has historically been grounded in specific notions of gender and racespecifically ones that elevate white men and other societal norms.24567 This implicit bias leads to systemic bias against women and other leaders with diverse racial or ethnic backgrounds. Whether agencies are building their own AI systems or acquiring them from outside vendors, they should ensure they have sufficient expertise to evaluate and operate artificial intelligence tools. "The trials of women leaders in the workforce: How a need for cognitive closure can influence acceptance of harmful gender stereotypes." Leadership programsas well as agency efforts to implement President Joe Bidens executive order on supporting diversity, equity, inclusion and accessibility in the federal workforceshould focus on helping federal organizations address these issues. Washington, DC 202101-866-4-USA-DOL, Financial Capability, Asset Development, and Work and Tax Incentives, National Disability Employment Awareness Month, National Expansion of Employment Opportunities Network, Americans with Disabilities Act 30th Anniversary. Updates. Before sharing sensitive information, make sure youre on a federal government site. Partnership for Public Service Federal Employee Morale is Falling, and One Group Thinks the Slow Appointments Process Is to Blame, Federal employees less satisfied under Biden: report, Partnership for Public Service (202) 775-9111. Inclusion: Intent or Impact? The difference between the observed and expected values is statistically significant. These race and ethnicity categories predate the authors work on this project. Exploring other ways that implicit bias may affect perceptions of federal leaders. Promote ODEP-funded technical assistance services, such as the Job Accommodation Network and the Employer Assistance and Resource Network on Disability Inclusion. From . Without robust attention to representativeness, an AI model in this situation could fail to perform correctly and could even worsen service delivery. Loren DeJonge Schulman It is also older. The existing resources on standards for responsibly using artificial intelligence often focus on technical and data specifications.5 These are fundamental considerations, but such recommendations are often difficult to understand for those without deep technical knowledge. The experts we interviewed highlighted key recommendations for how technical and non-technical leaders can productively collaborate to ensure responsible AI use: Focus on the problem and intended outcomes. Many experts have created frameworks that aim to provide guardrails to help organizations take advantage of AIs capabilities while avoiding its potential risks. Retrieved from bit.ly/3fEn7AW. Impact bonds, outcomes funds, and other partnerships for public purpose (new PPPs) have the potential to support COVID-19 recovery while strengthening social service delivery. . Furthermore, using qualitative data, we also found that gender bias persists in the federal workplace against both diverse groups of women and white women. The same is also true for diverse racial or ethnic groups, who make up about 40% of the U.S. population, but roughly 23% of the Senior Executive Service, about 47% of entry-level jobs and more than 50% of the clerical roles in our federal government.8, While this research series highlights the importance of having federal leadership that represents the whole of the U.S. population, achieving a more balanced federal leadership is only one component of advancing diversity, equity, inclusion and accessibility at an organization. The intersection of race bias and public policy resonates deeply with Western values. AI tools use data to learn a task, and they continue to improve at functions such as transferring information from paper into computers, recognizing images, answering questions by quickly finding relevant information in databases or documents, detecting patterns in data, making decisions about simple queries and predicting someones behavior based on past conduct. Learn more about these solutions below. 2023 Summer Leadership Development Internship. For more than 20 years, we have helped make this . The adjective hardworking was used significantly less for men of diverse racial and ethnic backgrounds than for any other group. Our findingsand others from this assessment toolcan help shape and inform organizational performance and public policy. The chart below highlights the percentage of respondents that used a given term to describe the federal leader. The .gov means its official. 27. There are limitations to this analysis, and researchers should interpret these results with caution. X2 (6, N = 12,792) =24.76, p = .05.22. Collaborate with other Alliance participants on employer issues that are identified through the Alliance Program. For more than 20 years, we have helped make this . Our findings indicate that the racial and gender disparities within federal leadership reflect broader stereotypes and biases that have historically resulted in barriers for women and diverse racial and ethnic groups in the workplace. Considering questions such as how will frontline employees interpret model outputs and what are the privacy implications of using this system will help technical and non-technical leaders find concrete points of collaboration and ensure the AI tool is well-integrated into the broader system. Honoree Archive. This field is for validation purposes and should be left unchanged. "Beyond a Numbers Game? Responsibly evaluating, implementing and using artificial intelligence tools requires successful collaboration between technical and non-technical leaders. These differences were statistically significant for all subcompetencies except embracing risk and uncertaintypart of the leading change competencyand for three of the four achieving results subcompetenciesevidence-based decision-making, systems thinking and tech savviness, where the scores were still higher, but not statistically significant. 30. p.usa-alert__text {margin-bottom:0!important;} Both employees with diverse racial and ethnic backgrounds and white employees scored similarly on the two core values: stewardship of public trust and commitment to public good. For more than 20 years, we have helped make this . "Redeeming leadership: An anti-racist feminist intervention." The Partnership for Public Service (PPS) is a nonprofit, nonpartisan organization that works to revitalize the federal government by inspiring a new generation to serve and by transforming the way government works. 2. Please see ourFAQsandGlossary of Federal Termsfor more information. This Program explores the many barriers to inclusion in the AI space as . Full-Time. Technical and non-technical leaders each bring important expertise to conversations around responsible AI, but this expertise is sometimes difficult to communicate across different frames of reference. To explore how leaders with different racial or ethnic identities scored on these competencies and values, we used a statistical test called an independent samples t-test, to compare their average scores. Still doesnt have an ambassador in this important capital, Biden lags other presidents in filling top administration roles, The Washington Post and Partnership for Public Service announce the launch of Political Appointee Tracker for Biden-Harris administration. This interactive GPS map will help guide you through your career path journey, starting at GS 7-9 entry level, and spanning through the GS 12-13 level. Suite 600 "Intersectionality, leadership, and inclusion: How do racially underrepresented women fare in the federal government?." Also, scores on the four key competenciesbecoming self-aware, engaging others, leading change and achieving resultsand 20 subcompetencies. Current Directions in Psychological Science 19.1 (2010): 14-18. 22. Stier has been married twice. However, public service leaders should focus on providing transparency in a way that is meaningful for the public, rather than providing technical information that is likely to create more confusion. "A nonpartisan model for developing public-service leaders." Participants will choose to participate in the full program either virtually or in-person. 21. The Sammies honorees represent the many exceptional career public servants who are breaking down barriers, overcoming huge challenges and getting results. Public Administration Review 82.3 (2022): 594-597. Algorithmic bias refers to the ways in which algorithms might perform more poorly for certain demographic groups or produce disparate outcomes across such groups. About Us. Suite 600 .dol-alert-status-error .alert-status-container {display:inline;font-size:1.4em;color:#e31c3d;} 31. Launched in 2016, the political appointee trackerhas been followingroughly800 ofthe 1,200political appointedpositions that require Senate confirmation,including Cabinet secretaries, chief financial officers, general counselsandambassadors. .h1 {font-family:'Merriweather';font-weight:700;} This program is designed to: The Partnership has extensive experience delivering leadership development programs that support federal employees at all levels. The Partnership for Public Service is the place where you learn how to manage competing priorities and also build the network of support that will help you further your career., -Gwen Keyes Fleming, former chief of staff at the EPA, Partnership for Public Service These agencies are especially troubled. Retrieved from, 3. The digital resources here on Go Government can help you better understand the federal hiring process and launch your government career. 5. Effective transparency requires agencies to as much as possible, explain how the algorithm was evaluated, so that people understandthis is the standard it met, Dorie said. Note:We are unable to provide individual counseling about the federal application process. The reasons for these gender differences could be due to both employment and wage prospects in the public sector . As stated in the 1996 report of the Task Force on Public Service Values and Ethics: Footnote 2 Overall, white women received the least positively framed feedback on opportunities to improve. Edward Elgar Publishing, 2022. Henne, Kathryn. Galton, Francis. Summer 2023 application open through November 27, 2022. Tho' tenacious in seeking buy-in her sometimes aggressive approach with peers could be more assertive and less aggressive, was coded as negative. Table 1. The Partnership for Public Service's Center for Presidential Transition is the nation's premier nonpartisan source of information and resources designed to help presidential candidates and their teams lay the groundwork for a new administration or for a president's second term. Participants in our interviews and focus groups mentioned this consistently as one additional helpful tool, however, barriers can exist in those mentoring relationships32 and it may not address all the structural inequities that exist. A key facet of responsible AI is understanding when AI is or is not well-suited to address a specific problem. Learn more, The Public Service Leadership Institute brings together our many efforts to strengthen public service leadership. The Partnership for Public Service is committed to building a culture of inclusion. Livingston, Robert W., Ashleigh Shelby Rosette, and Ella F. Washington. Across our 13 interviews and one focus group, women repeatedly mentioned that they felt others in the workplace were holding them to different standards due to their gender. This finding suggests that gender continues to affect the type of feedback leaders receive, which may hinder leadership development opportunities for women and help explain why they remain underrepresented in certain senior government roleseven while the number of white women in these roles has grown in recent years.3. Although these agencies represent a small fraction of those that improved, others can apply these successes to create a better employee experience. Before beginning AI initiatives, organizations should be sure they have in place processes that enable collaborative decision-making that takes into account the many perspectives needed for truly responsible AI use. We will evaluate applications based on numerous criteria to ensure that individuals selected for the program are interested in developing a vision for AI and leading change at their agencies. Highlight best practices for how to make the case for and develop AI solutions. We also found that, while there is not a consistent statistically significant difference in how individuals are rated based on their race, ethnicity and gender, women with diverse racial and ethnic backgrounds scored higher than white women on all core values and competencies. Individuals with diverse racial and ethnic backgrounds scored higher than their white colleagues on all four core competencies and all 20 subcompetencies. The strategy for revitalizing public service is pursued through three strategic goals: securing the right talent, fueling innovation and efficiency, and building public support for the nation's civil service. Retrieved from, 4. The top three most used adjectives to describe leaders in our sample were intelligent, trustworthy and hardworking. An official website of the United States government. Stan. Below are some of the specific considerations and questions non-technical leaders should address at each stage of the process. . Legal name of organization: PARTNERSHIP FOR PUBLIC SERVICE INC. Close. Employing inclusive leadership practices, which directly impacts an employees experience and perception of organizational fairness, is a more crucial factor.9, Additionally, even within the field of study of women in leadership it is only recently that the focus has shifted from one of white women to also including Black womens experiences to understand how the intersection of racism and sexism compound systems of oppression.10, This idea, termed intersectionality by Kimberl Crenshaw, highlights the ways in which different social identities overlap to reinforce discrimination and is an important lens to understand womens experiences in the federal government, especially when it comes to race and gender.11 Using intersectionality to explore leadership is an evolving field of study1213 and necessitates caution in interpreting or generalizing results across diverse groupings of people.14151617 Our brief uses findings from our 360 assessment to build new knowledge in this area and add much-needed data analysis to studies of systemic racism, gender identity and whiteness.18. We believe that our future and our democracy depend on our ability to solve big problemsand that we need an effective federal government to do so. Suite 600 Because our previous analyses identified significant differences in how men and women were rated by others, such as supervisors, direct reports, colleagues, or friends and family, we also ran an additional statistical test, a two-way analysis of variance (ANOVA), to explore any trends in how others rated women based on their race and ethnicity. ActionAid International (AAI), Eastern and Southern Africa Small Scale Farmers' Forum (ESAFF), SAfAIDS, and Public Service Accountability Monitor (PSAM) of Rhodes University. When we closely examined the data, we uncovered several important trends about these differences. Bearfield, Domonic A. Technical and non-technical leaders can improve their coordination by recognizing from the beginning that AI tools do not operate independently, but rather as part of a larger context.