Tuesday, August 30, 2022
Understanding Distributional Effects of Services and Promoting Inclusion and Diversity in Operations

With the IBM Center for The Business of Government’s next due date for new research report proposals approaching on September 6th, we are publishing additional perspectives on our research topics over the next week in the form of blog posts focused on each topic.   The insights in these posts draw from dialogue that helped to frame the research agenda, as well as subsequent content relevant to each research topic area.  We hope that these posts provide potential research applicants and authors of upcoming reports with additional context to help frame final proposals and draft reports that follow.

We lead today with our seventh topic, Addressing Equity (authored by Center Fellow Mark Newsome). ~

As noted in the Center’s Research Agenda, effective implementation of government programs carries a pressing and growing imperative to address racial, ethnic, gender and similar social equity issues. Connected to challenges facing government programs, equity has long been important to the field of public administration; the National Academy of Public Administration has written that “Social equity is often named as the fourth pillar of public administration … which addresses fairness, justice and equity for all.” 

This essential principle matters because effective and efficient government must also include equitable government.  This includes ensuring the government agency staffs reflect the diversity of the people who they served.  Moreover, the Federal government workforce has benefitted for decades from significant contributions by leaders from diverse communities, who have served the Nation in defense and civilian roles as heads of agencies and programs and who have led talented teams of entry-, mid- and senior level staff.  Research is needed on strengthening leadership in government from communities of color, including practical, actionable recommendations to achieve this goal, especially in light of data that show diminishing relative presence as civil servants rise in the civil service system and move into the Senior Executive Service.  As noted by the Partnership for Public Service:

As of March 2021, people of color represent 47% of all full-time, entry-level employees but only 33% of senior-level positions. And within the Senior Executive Service—the elite corps of experienced civil servants responsible for leading the federal workforce—the disparity is even wider. Only 23% of all career SES members are people of color.

Developing and delivering sound leadership and management that leads to effective government must also involve an inclusive and diverse government.  Research that addresses important social equity issues and represents points of view from across racial and ethnic groups will broaden our understanding of how to bring social equity considerations to the fore in the work of government. Research into government programs can include practices that have inequitable effects

Additionally, the impacts of equity on governance are not separable from other elements of policy design and program delivery.  Equity considerations cross-cut with multiple functions of government and with multiple elements of the IBM Center Research Agenda, including development of an effective workforce and workplace for the future with rewarding career paths, building resiliency across communities, and trust in government.  Specific questions for further exploration include:

  • Research into differential impacts on digital technology.  For example, how can large human services systems be delivered in more equitable ways to provide benefits across diverse communities; how can more efficient gov can allow government case workers to focus on serving a broad range of clients and not spend inordinate time addressing bureaucratic process requirements, resulting in better distribution of benefits to diverse communities in service areas like education, housing, food, and unemployment insurance.
  • What measurements and benchmarks can help leaders understand the current state and future progress in delivering government in a more equitable way?And what different methodologies or partner organizations provide a pathway toward using practical and actionable metrics effectively?

Research on the interconnections of equity and these other critical areas of governance will add to government’s understanding of how best to serve a nation that continues to grow more diverse over time.

Using data and AI to understand and improve equity

Another element where research can inform practice around supporting goals of equity involves how government uses data, which can be key to understanding challenges in social equity and recommending response strategies.  The Center for Open Data Enterprise (CODE) has identified several areas where research and insights can inform more equitable solutions.  Research in each of these areas can help inform government leaders and stakeholders on benchmark and forward-leaning data resources and methods to guide policy and practice, including fair housing, health care access, and the government workforce.  A recent report for our Center authored by several CODE experts did a deep exploration on the use of open data to drive greater equity in health care.

This report found that as the COVID-19 pandemic has evolved, multiple studies and reports have documented that people of color are at higher risk of adverse health outcomes. Existing health disparities in the U.S. are heavily influenced by the conditions in which people are born, grow, live, work, and age, known as the social determinants of health (SDOH). Health outcomes can also be influenced by differential applications of emerging technology and differential effects of climate change.

Governments can use open data about the impact of the SDOH, technology, and climate change to manage health care programs and services in ways that drive more equitable outcomes for patients and their families. Moreover, better and more available data, combined with the use of emerging technologies, can help illuminate the problem and support new solutions to address health risk and access in a way that reduces the potential for bias.

The report identified several themes for future research on how to bring the power of data to bear on the existing inequities in areas beyond health care: trust and data collection, use, privacy, and security; equitable data governance, data sovereignty and data ownership, access to data, data quality and gaps, data standards, and interoperability and data sharing;.  Some of the report’s specific recommendations also focused on enhancing research capacity for around equity, including:

  • Expanded access to geocoded data at the sub-Census tract/ZIP code level.
  • Expand access to racially/ethnically disaggregated data.
  • Invest in data and technical capacity through grants and other financial support mechanisms.

Additionally, research on differential effects of artificial intelligence and intelligent automation in government programs and services – how can government ensure access by communities where outdated technology may limit their participation, or how can government build systems that reduce risk from biased data or algorithms?  As IBM’s CEO Arvind Krishna has noted, “users of Al systems have a shared responsibility to ensure that Al is tested for bias … and that such bias testing is audited and reported.”

Indeed, AI can drive greater social equity to improve service.  Research can promote understanding and implementation of best practice, in areas including:

  • security and privacy for sensitive data
  • human review of algorithms to ensure the data and autonomous decisions in such systems represent the diversity of the state of the world
  • explainability and transparency of data, to build confidence across communities that they contribute to decisionmaking with reduced bias
  • how best to collective diverse user feedback so that AI developers can program with an eye to how recipients of government programs experience such actions.
  • auditing for fairness and building in risk management, building on models such as the government of Canada’s algorithmic impact assessment.
  • How best to apply ethical AI principles like those of the Organization for Economic Cooperation and Development (OECD) in a way that also promotes social equity.