Bill Overview
Title: Digital Civil and Human Rights Act of 2022
Description: This bill establishes prohibitions on the use of automated systems in a discriminatory manner. Specifically, the bill prohibits (1) a federal agency, U.S. court, or state, local, or tribal government from using any automated decision system that has a disparate impact on the basis of race, national origin, color, religion, disability, or sex; or (2) the use of automated systems with bias by the Department of Defense. Each federal agency must maintain on its public website a bias data sheet for each automated decision system used by such agency with the potential for a disparate impact on such bases. The bill prohibits a respondent, in connection with the selection or referral of applicants or candidates for employment or promotion, from using any automated decision system that has a disparate impact on the basis of race, color, religion, sex, or national origin. The bill prohibits places of public accommodation from using in their operations that affect commerce any decision system that has a disparate impact on the basis of race, color, religion, sex, or national origin. The bill requires (1) the Office of the Director of National Intelligence to submit to Congress a report on the use within the intelligence community of automated decision systems with an adverse distinction based on race, religion, sex, health, age, or any other similar criteria; and (2) the National Institute of Standards and Technology to develop, publish, and maintain standards for reporting bias in an automated decision system.
Sponsors: Rep. Brown, Anthony G. [D-MD-4]
Target Audience
Population: People subject to discriminatory practices by automated decision systems
Estimated Size: 331000000
- The bill targets the use of automated decision systems, which are widespread in both public and private sectors globally.
- Automated systems impact a plethora of decisions related to employment, legal, governmental, military, and commercial services.
- Any population demographic that could be subjected to discriminatory practices by automated systems, such as those defined by race, color, religion, sex, national origin, age, and disability, is impacted.
- The protections and standards proposed by the bill will potentially affect people worldwide as many countries observe legislation originating from the US for policy development.
- The scope of the bill implies changes for organizations and institutions using or adapting US technologies for automated decision making globally.
Reasoning
- The policy targets the widespread use of automated systems and aims to prevent discriminatory impacts, which suggests it will affect a wide demographic across various sectors.
- Given the budget constraints, the policy's reach will be limited initially, likely focusing on major systems within government and large organizations.
- The policy will predominantly impact individuals who interact with automated systems related to employment, public accommodations, and governmental services.
- The policy will positively impact marginalized communities by reducing the likelihood of discrimination in automated decision-making.
- Not everyone will feel the effects immediately due to the gradual implementation and resource allocations over time.
Simulated Interviews
Software Engineer (New York, NY)
Age: 34 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 10/20
Statement of Opinion:
- I think the policy is essential. I've experienced bias in automated systems first-hand, which affected my job prospects.
- It's great to see steps being taken to address biases, but its success depends on enforcement and transparency.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 7 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 7 | 5 |
HR Manager (Houston, TX)
Age: 41 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 3.0 years
Commonness: 12/20
Statement of Opinion:
- This policy could drastically change our hiring process, and that's needed to ensure fairness.
- I'm hopeful it will enforce fairer practices and reduce biases I worry about in our recruitment tools.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 6 | 6 |
| Year 20 | 6 | 6 |
Data Scientist (San Francisco, CA)
Age: 28 | Gender: other
Wellbeing Before Policy: 7
Duration of Impact: 2.0 years
Commonness: 8/20
Statement of Opinion:
- Ethics in AI is crucial, and this policy is a positive step.
- I'm eager to see how this develops the standards we apply in AI modeling.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 7 |
| Year 3 | 7 | 7 |
| Year 5 | 6 | 7 |
| Year 10 | 6 | 7 |
| Year 20 | 6 | 6 |
Retired (Chicago, IL)
Age: 64 | Gender: male
Wellbeing Before Policy: 4
Duration of Impact: 10.0 years
Commonness: 15/20
Statement of Opinion:
- It's reassuring to know there's an effort to make technology fair for all.
- I hope this policy will help marginal communities; technology should serve everyone equally.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 4 |
| Year 2 | 6 | 4 |
| Year 3 | 6 | 4 |
| Year 5 | 7 | 5 |
| Year 10 | 7 | 5 |
| Year 20 | 6 | 5 |
College Student (Los Angeles, CA)
Age: 22 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 3.0 years
Commonness: 14/20
Statement of Opinion:
- As I enter the workforce, I am anxious about automated systems unfairly affecting my job hunt.
- It's a relief to know there's a policy aiming to protect people like me from bias.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 5 |
Public School Teacher (Detroit, MI)
Age: 50 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 11/20
Statement of Opinion:
- I'm concerned AI will worsen the inequalities in student evaluations.
- The policy's attention to fairness might ensure a better future for our students.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 6 | 5 |
| Year 3 | 6 | 5 |
| Year 5 | 7 | 5 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 6 |
Small Business Owner (Phoenix, AZ)
Age: 37 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 3.0 years
Commonness: 13/20
Statement of Opinion:
- It's crucial that AI used in hiring is unbiased to maintain business integrity.
- I support initiatives that improve fairness in business operations.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 7 |
| Year 3 | 7 | 7 |
| Year 5 | 6 | 7 |
| Year 10 | 6 | 7 |
| Year 20 | 6 | 7 |
Civil Rights Advocate (Miami, FL)
Age: 30 | Gender: other
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 9/20
Statement of Opinion:
- The bill supports my work advocating for equal digital rights.
- It's an important step toward technological fairness.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 7 | 6 |
Government Analyst (Boston, MA)
Age: 55 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 10/20
Statement of Opinion:
- It's important for government programs to adhere to unbiased standards.
- This is a significant bill that could enhance how we measure governmental AI systems.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 7 |
| Year 5 | 8 | 7 |
| Year 10 | 7 | 7 |
| Year 20 | 7 | 7 |
High School Student (Seattle, WA)
Age: 18 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 18/20
Statement of Opinion:
- AI should be fair for all, and this bill seems like an important start to achieving that.
- I hope this paves the way for fairer technology use in our society.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 8 | 7 |
| Year 20 | 8 | 7 |
Cost Estimates
Year 1: $75000000 (Low: $60000000, High: $90000000)
Year 2: $62000000 (Low: $50000000, High: $76000000)
Year 3: $50000000 (Low: $40000000, High: $60000000)
Year 5: $55000000 (Low: $45000000, High: $65000000)
Year 10: $60000000 (Low: $50000000, High: $70000000)
Year 100: $68000000 (Low: $55000000, High: $80000000)
Key Considerations
- Ensuring the effectiveness of compliance enforcement across different levels of government.
- Balancing initial implementation costs with long-term savings and societal benefits.
- Addressing technological challenges and potential resistance in sectors heavily relying on automated decision systems.
- Considering international impacts, as the U.S. sets precedents that may influence global standards.