Michael Hawes

Senior Statistician for Scientific Communication

FCSM Research and Policy Conference

Session D4: How Can U.S. Professional Guidelines Inform Federal Statistical Policy?

October 25, 2023

The viewpoints expressed in this presentation are the author’s own, and 

not the viewpoints of the U.S. Census Bureau or the federal government.
Background

Developed as part of the 2019 

Federal Data Strategy, with the 

support of the Chief Data 

Officers’ Council, the Federal 

Privacy Council and the 

Interagency Council on 

Statistical Policy
Data Ethics 

Defined

Data Ethics are the norms of 

behavior that promote 

appropriate judgments and 

accountability when 

acquiring, managing, or 

using data, with the goals of 

protecting civil liberties, 

minimizing risks to 

individuals and society, and 

maximizing the public good.
The Framework

• 7 Data Ethics Tenets

• Recommendations

• Useful Resources

https://resources.data.gov/assets/documents/fds-data-ethics-framework.pdf
Uphold Applicable Statutes, Regulations, 

Professional Practices, and Ethical Standards

• Organizational leaders are encouraged to maintain upto-date, comprehensive ethical standards regarding 

data use.

• Staff are responsible for learning and applying agency 

guidance. 

• If a person works in an area with recognized 

professional ethical codes of conduct (such as 

computer science or software engineering) they should 

be aware of those standards and strive to uphold them.
https://www.amstat.org/your-career/ethical-guidelines-for-statistical-practice

(2022 Revision)
Respect the Public, 

Individuals, and 

Communities

• Responsible federal leaders and data 

users should approach data 

activities with promoting the “public 

good” in mind. 

• Responsible use of data begins with 

careful consideration of its potential 

and differential impacts. 

• Data initiatives should include 

considerations for unique 

community and local contexts, such 

as for federally recognized Tribes, 

Alaskan Natives, and local 

governments, and have an identified 

and clear benefit to society.
Respect Privacy and Confidentiality

• Privacy and confidentiality should always be protected in a manner 

that respects the dignity, rights, and freedom of data subjects. 

• In this context, privacy is the state of being free from unwarranted 

intrusion into the private life of individuals; and

• Confidentiality is the state of one’s information being free from 

inappropriate access and use.

• An essential objective of privacy and confidentiality protection is to 

minimize potential negative consequences, such as the mosaic effect
Act with Honesty, Integrity, and 

Humility

• Federal leaders and data users should not perform or 

condone unethical data behaviors. 

• When sharing data and findings, personnel should accurately 

report information and present data limitations, known 

biases, and methods of analysis that apply.

• They should also take care not to overgeneralize based on 

available data and recognize that no dataset can fully 

represent all facets of a person, community, or issue. 

• Federal leaders and data users are expected to exhibit 

humility when presenting data, be open to feedback, and 

invite discussion with the public.

• In addition, federal data users should accurately and honestly 

represent their abilities when working with data. 

• Federal agencies should also support honesty and integrity 

by clearly defining processes for reporting data ethics 

concerns and violations, and federal leaders and staff should 

appropriately implement those processes
Hold Oneself and Others Accountable 

• Anyone acquiring, managing, or using data should be aware of 

stakeholders and responsible to them, as appropriate. 

• Remaining accountable includes the responsible handling of classified 

and controlled information, upholding data use agreements made 

with data providers, minimizing data collection, informing individuals 

and organizations of the potential uses of their data, and allowing for 

public access, amendment, and contestability to data and findings 

when consistent with privacy and national security concerns. 
Promote 

Transparency 

• Individuals, organizations, and communities 

benefit when the ethical decision-making process 

is as transparent as possible to stakeholders.

• Transparency depends on clear communication 

of all aspects of data activities and appropriate 

engagement with data stakeholders.

• Promoting transparency requires engaging 

stakeholders through easily accessible feedback 

channels and providing timely updates on the 

progress and outcomes of data use. 
Stay Informed of 

Developments in the Fields 

of Data Management and 

Data Science 

• Advanced technologies provide 

great benefit to the public 

sector, but should be deployed 

with a commitment to 

accountability and risk 

mitigation. 

• Emerging systems, technologies, 

and techniques require 

additional awareness and 

oversight as they can present 

new—and sometimes hard to 

detect—opportunities for bias
Alignment across frameworks
14

Results: Example of full table (detail – in Appendix): ASA x Data Ethics Tenets (no red)

Source: Park & Tractenberg (2023)
15

Results: Summarized table (in body of paper): ASA x Data Ethics Tenets

Data Ethics 

Tenets are 

strongly and 

clearly aligned 

with ASA Ethical 

Guidelines for 

Statistical 

Practice

Source: Park & Tractenberg (2023)
Navigating tensions between the 

frameworks
Results : 

SPD 1, 2 and 2A and DET

All DET align with SPD 1 

Responsibilities 2 and 4 (credibility and 

trust) and SPD 2.1.4 (instrument function); 

2.3.4 (disclosure avoidance). See also 

2.7.2 (protection), and 2A.5 (transparency).

Areas of Mixed Alignment: SPD 1 (relevance) could conflict with all DET

17 Source: Park & Tractenberg (2023)
Results Summary: 

DET and PNP

Areas of tension: Principle 1 

(relevance) Practice 7 

(collaboration), and Practice 9 

(dissemination of products) must 

be accomplished in balance with 

DET 

18 Source: Park & Tractenberg (2023)
19

Questions?