Bill Overview
Title: Health and Location Data Protection Act of 2022
Description: This bill generally prohibits data brokers from selling, reselling, licensing, trading, transferring, or sharing an individual's health data or location data.
Sponsors: Sen. Warren, Elizabeth [D-MA]
Target Audience
Population: Individuals whose health or location data is managed by data brokers
Estimated Size: 250000000
- The bill targets data brokers involved in the handling of health and location data.
- Any individual with health or location data collected and managed by data brokers could be impacted.
- Virtually all individuals who use digital services could have their health or location data at some risk of being collected and sold.
- Most of the global internet-using population shares their data with various services that could potentially lead to those data being handled by a broker.
Reasoning
- The policy is aimed at preventing the selling of health and location data by data brokers, which serves the main target population of essentially anyone in the US using digital services potentially at risk from data brokers. This means a vast range of individuals with varying occupations, ages, and tech usage habits could be impacted, albeit with different magnitudes.
- Given the large scale of interaction between US residents and digital services, a significant proportion of the population could experience some level of impact, ranging from high (in cases where individuals already experienced data breaches) to low (for individuals unaware of their data being sold).
- The budget is constrained, with an initial yearly limit implying either a focus on critical enforcement areas or a broad but shallow impact across the population.
- It's crucial to include voices from across the socio-economic spectrum as data broker risk and awareness can significantly vary by demographic.
- Estimating self-reported wellbeing depends on how directly individuals perceive the threat of their data privacy being compromised and how the policy mitigates that risk.
Simulated Interviews
Software Engineer (San Francisco, CA)
Age: 32 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 15/20
Statement of Opinion:
- I am relieved that there's a policy focusing on data protection.
- It's long overdue given how much of our lives are online now.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 8 | 6 |
| Year 5 | 9 | 6 |
| Year 10 | 9 | 5 |
| Year 20 | 8 | 4 |
Health care provider (Austin, TX)
Age: 45 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 12/20
Statement of Opinion:
- I hope this measure will make my patients feel safer about their data.
- It's crucial for the trust in digital health solutions.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 8 | 6 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 9 | 4 |
| Year 20 | 9 | 4 |
Freelance Photographer (New York, NY)
Age: 28 | Gender: other
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 16/20
Statement of Opinion:
- I'm worried about how much of my location data could be sold.
- This new law might help protect my personal safety.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 7 | 4 |
| Year 5 | 8 | 4 |
| Year 10 | 7 | 3 |
| Year 20 | 6 | 3 |
Retired (Des Moines, IA)
Age: 60 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 3.0 years
Commonness: 8/20
Statement of Opinion:
- I don't use technology much, but I do worry about my health records being sold.
- The protection act sounds like a good idea.
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 | 6 | 5 |
| Year 10 | 6 | 5 |
| Year 20 | 6 | 5 |
Marketing Specialist (Chicago, IL)
Age: 38 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 8.0 years
Commonness: 14/20
Statement of Opinion:
- I think it's essential to limit the power of data brokers.
- This might restore some privacy into my digital life.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 7 | 4 |
| Year 5 | 8 | 4 |
| Year 10 | 7 | 3 |
| Year 20 | 6 | 3 |
Data Scientist (Seattle, WA)
Age: 24 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 10/20
Statement of Opinion:
- I've been advocating for stricter data laws.
- This policy aligns with how we should handle personal data.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 8 | 6 |
| Year 3 | 8 | 6 |
| Year 5 | 9 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 8 | 4 |
Entrepreneur (Miami, FL)
Age: 50 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 7.0 years
Commonness: 9/20
Statement of Opinion:
- This is good for business as consumer trust is crucial.
- I hope it enforces stricter compliance among data handlers.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 7 |
| Year 2 | 9 | 6 |
| Year 3 | 9 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 5 |
| Year 20 | 7 | 5 |
College Student (Boston, MA)
Age: 19 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 18/20
Statement of Opinion:
- I'm frequently online, so data privacy is a big concern.
- This law seems to be a step in the right direction.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 4 |
| Year 3 | 8 | 4 |
| Year 5 | 7 | 4 |
| Year 10 | 6 | 3 |
| Year 20 | 6 | 3 |
Public Health Official (Phoenix, AZ)
Age: 56 | Gender: other
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 11/20
Statement of Opinion:
- I believe this policy will enhance public confidence in health data policies.
- It could lead to better health outcomes.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 6 |
| Year 2 | 8 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 4 |
| Year 10 | 7 | 4 |
| Year 20 | 6 | 3 |
Farmer (Rural Kansas)
Age: 65 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 7/20
Statement of Opinion:
- I use some health apps, and I'm glad to know my data might be safer.
- It's good that the government is taking steps to protect us.
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 | 5 |
| Year 10 | 6 | 5 |
| Year 20 | 5 | 5 |
Cost Estimates
Year 1: $650000000 (Low: $500000000, High: $800000000)
Year 2: $600000000 (Low: $480000000, High: $720000000)
Year 3: $550000000 (Low: $450000000, High: $650000000)
Year 5: $500000000 (Low: $400000000, High: $600000000)
Year 10: $450000000 (Low: $350000000, High: $550000000)
Year 100: $250000000 (Low: $200000000, High: $300000000)
Key Considerations
- The balance between protecting privacy and enabling data innovation is crucial.
- Implementation costs might vary significantly with technological advancements in data handling.
- The potential benefit in consumer trust can lead to long-term economic benefits that are hard to quantify initially.