Bill Overview
Title: Algorithmic Accountability Act of 2022
Description: This bill requires certain businesses that use automated decision systems to make critical decisions to study and report about the impact of those systems on consumers. Critical decisions include those that have a significant effect on a consumer's life such as the cost or availability of health care, housing, educational opportunities, or financial services. The Federal Trade Commission (FTC), in consultation with relevant stakeholders, must issue regulations to implement the bill. The bill provides for enforcement by the FTC and specified state officials. Further, the bill establishes a Bureau of Technology to advise the FTC about the technological aspects of its functions.
Sponsors: Sen. Wyden, Ron [D-OR]
Target Audience
Population: Consumers impacted by automated decision systems in critical life areas like healthcare and finance
Estimated Size: 250000000
- Businesses using automated decision systems for critical decisions operate globally across various sectors, including healthcare, finance, education, and housing.
- Consumers who are affected by decisions related to healthcare, housing, education, or financial services form a portion of the global population.
- The enforcement and regulatory guidance will primarily occur in the United States, but international businesses with operations in the US may also need to comply.
- Many countries and regions have laws governing automated decision systems, so the global population may see indirect effects if businesses globally adjust practices in anticipation of similar legislation in other markets.
Reasoning
- This policy affects a large slice of the U.S. population given its connection to critical services that everyone might use at some point, such as healthcare and finance.
- Individuals directly affected by the policy are diverse, including different backgrounds, ages, occupations, and economic statuses.
- Given budget constraints, the policy will focus on certain segments with potentially higher impacts, like low-income individuals or those frequently interacting with automated systems.
- The population distribution includes both urban and rural residents as digital services permeate across these areas.
- Variations in impact are expected, from those who notice significant benefits due to increased transparency and fairness, to those who see little direct effect because they are less exposed to automated decision-making systems.
Simulated Interviews
Medical Billing Specialist (Los Angeles, CA)
Age: 48 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 20.0 years
Commonness: 7/20
Statement of Opinion:
- I think it's really important that businesses are held accountable for their automated systems, especially in healthcare.
- These systems can be a black box, and something like this can ensure they're doing the right thing.
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 | 8 | 5 |
Software Engineer (Austin, TX)
Age: 36 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- I'm relieved to see regulations coming into place. Algorithms can sometimes make mistakes or perpetuate biases.
- This move will push companies to be more responsible.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 9 | 8 |
| Year 5 | 9 | 8 |
| Year 10 | 8 | 8 |
| Year 20 | 8 | 7 |
Retired School Teacher (Memphis, TN)
Age: 60 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- I don't use a lot of those new technologies, but I understand why they'd need checking.
- It's good to know they're thinking about these things, even if it doesn't change much for me.
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 | 7 | 7 |
| Year 10 | 7 | 6 |
| Year 20 | 6 | 6 |
Financial Analyst (New York, NY)
Age: 27 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 15.0 years
Commonness: 4/20
Statement of Opinion:
- My firm is going to need to make changes to comply, which is good for consumers, maybe not for us employees.
- I just hope it doesn't lead to layoffs or increased workload without more training.
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 | 8 | 6 |
| Year 20 | 7 | 5 |
College Student (Portland, OR)
Age: 20 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 15.0 years
Commonness: 8/20
Statement of Opinion:
- This sounds beneficial for my generation since we use so much technology for education.
- Ensuring fairness and transparency could improve access to opportunities.
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 | 8 | 7 |
| Year 20 | 8 | 7 |
Small Business Owner (Columbus, OH)
Age: 45 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- I worry about extra compliance costs even though I don't use these technologies intensely.
- Small businesses might get caught up needlessly.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 5 | 5 |
| Year 5 | 5 | 5 |
| Year 10 | 5 | 4 |
| Year 20 | 5 | 4 |
Mortgage Loan Officer (Cleveland, OH)
Age: 54 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- It's about time something like this was put into place, but I hope the training follows.
- Automated systems need more transparency to avoid biases in big decisions.
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 | 7 | 6 |
| Year 20 | 7 | 5 |
Freelance Data Scientist (San Francisco, CA)
Age: 31 | Gender: other
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 4/20
Statement of Opinion:
- This legislation could lead to more ethical practices in the industry.
- Might create more consulting opportunities for someone like me.
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 | 9 | 7 |
| Year 10 | 9 | 7 |
| Year 20 | 8 | 6 |
Fast Food Worker (Birmingham, AL)
Age: 19 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 0.0 years
Commonness: 9/20
Statement of Opinion:
- I'm probably not impacted since I don't really use automated services like that.
- It's important for people who rely on those systems though.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 5 | 5 |
| Year 5 | 5 | 5 |
| Year 10 | 5 | 5 |
| Year 20 | 5 | 5 |
Stay-at-Home Parent (Rural Kansas)
Age: 43 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- I don't feel it will change much for people like me out here.
- It's a good move for city folks who deal with these systems daily.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 6 | 6 |
| Year 5 | 6 | 6 |
| Year 10 | 6 | 6 |
| Year 20 | 6 | 6 |
Cost Estimates
Year 1: $120000000 (Low: $80000000, High: $160000000)
Year 2: $100000000 (Low: $60000000, High: $140000000)
Year 3: $100000000 (Low: $60000000, High: $140000000)
Year 5: $100000000 (Low: $60000000, High: $140000000)
Year 10: $100000000 (Low: $60000000, High: $140000000)
Year 100: $100000000 (Low: $60000000, High: $140000000)
Key Considerations
- Compliance costs will primarily burden affected businesses, which will pass on some costs to consumers.
- Establishing a new Bureau of Technology requires significant upfront investment.
- The effect on GDP and tax revenue could vary depending on how effectively businesses adapt to new regulations.