Bill Overview
Title: Bots Research Act
Description: This bill directs the Federal Trade Commission to establish a task force to study and report to Congress and relevant federal agencies on the impact of automated accounts on social media, public discourse, and elections.
Sponsors: Rep. DeSaulnier, Mark [D-CA-11]
Target Audience
Population: Individuals globally who use social media
Estimated Size: 250000000
- The bill focuses on the impact of automated accounts, or bots, on social media.
- Bots can influence public discourse globally, affecting billions of social media users.
- Bots have been known to play roles in elections by spreading misinformation or influencing public opinion.
- Social media platforms have billions of global users, many of whom could be directly affected by bots.
- The bill's research will likely encompass global impacts, not just those affecting the United States.
- It primarily impacts any individuals who use social media, as they are exposed to bot activity.
Reasoning
- The cost and program size limits of the policy suggest it should carefully choose where to focus its research on bot impacts.
- Since the policy targets automated accounts on social media, the focus should be primarily on users who are most affected by bots, such as politically active individuals or those who regularly engage with trending topics.
- People not engaged in social media or who don't rely on it for news will likely be less or not impacted by the policy.
- While the majority of social media users might eventually benefit from the findings, their immediate perception or understanding of the impact might be low or none.
- Given the budget, direct impacts on individual wellbeing may be more qualitative and preventive rather than quantitative.
Simulated Interviews
Social Media Manager (New York, NY)
Age: 45 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- If the policy can reduce misinformation, it would be highly beneficial for my job and mental health.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 7 | 6 |
| Year 3 | 8 | 7 |
| Year 5 | 8 | 7 |
| Year 10 | 9 | 6 |
| Year 20 | 9 | 5 |
College Student (Los Angeles, CA)
Age: 22 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 8.0 years
Commonness: 15/20
Statement of Opinion:
- Understanding bot influence is crucial for democracy; this policy seems vital.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 6 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 6 |
| Year 10 | 8 | 5 |
| Year 20 | 8 | 5 |
Software Engineer (Seattle, WA)
Age: 34 | Gender: other
Wellbeing Before Policy: 8
Duration of Impact: 1.0 years
Commonness: 10/20
Statement of Opinion:
- This research is important but won't affect my daily life much.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 7 |
| Year 5 | 8 | 7 |
| Year 10 | 8 | 7 |
| Year 20 | 8 | 7 |
Retired (Austin, TX)
Age: 60 | Gender: female
Wellbeing Before Policy: 8
Duration of Impact: 0.0 years
Commonness: 20/20
Statement of Opinion:
- The impact of bots is more of a concern to my grandchildren.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 8 | 8 |
| Year 10 | 8 | 8 |
| Year 20 | 8 | 8 |
Marketing Specialist (Miami, FL)
Age: 29 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 8/20
Statement of Opinion:
- A reduction in bot activity could make my work less frustrating.
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 | 8 | 6 |
| Year 10 | 8 | 5 |
| Year 20 | 8 | 5 |
Teacher (Denver, CO)
Age: 40 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 7/20
Statement of Opinion:
- The policy can educate the public about bot influence, which is just as important as direct effects.
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 | 5 |
| Year 20 | 8 | 5 |
High School Student (Chicago, IL)
Age: 18 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 3.0 years
Commonness: 12/20
Statement of Opinion:
- I hope for a safer online environment, but I doubt the policy will be widely understood among people my age.
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 | 6 | 5 |
| Year 10 | 7 | 5 |
| Year 20 | 7 | 5 |
Journalist (San Francisco, CA)
Age: 50 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 12.0 years
Commonness: 3/20
Statement of Opinion:
- This policy aligns with my interest in improving the reliability of online information.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 8 | 7 |
| Year 3 | 9 | 7 |
| Year 5 | 9 | 7 |
| Year 10 | 9 | 6 |
| Year 20 | 9 | 6 |
Factory Worker (Detroit, MI)
Age: 32 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 0.0 years
Commonness: 18/20
Statement of Opinion:
- This policy doesn't seem to have any direct impact on my life.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 8 | 8 |
| Year 5 | 8 | 8 |
| Year 10 | 8 | 8 |
| Year 20 | 8 | 8 |
Graduate Student (Boston, MA)
Age: 28 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 8.0 years
Commonness: 6/20
Statement of Opinion:
- The policy could provide incredible data for my research.
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 | 8 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 8 | 6 |
Cost Estimates
Year 1: $6000000 (Low: $4000000, High: $8000000)
Year 2: $6000000 (Low: $4000000, High: $8000000)
Year 3: $6000000 (Low: $4000000, High: $8000000)
Year 5: $6000000 (Low: $4000000, High: $8000000)
Year 10: $0 (Low: $0, High: $0)
Year 100: $0 (Low: $0, High: $0)
Key Considerations
- The task force's effectiveness will hinge on accurate data access and collaboration with social media companies.
- Potential findings could influence future regulatory decisions significantly impacting digital communication landscapes.
- The scope of research will need to address rapidly evolving social media technologies and usage patterns.