Policy Impact Analysis - 117/HR/6489

Bill Overview

Title: Infrastructure Grant Security Act

Description: This bill prohibits use of Strengthening Mobility and Revolutionizing Transportation grants to purchase, lease, or operate drones or other unmanned aircraft systems that are manufactured by companies subject to Chinese control or influence. (These grants support demonstration projects to support improved transportation efficiency and safety through the use of advanced smart city or community technologies and systems.)

Sponsors: Rep. Graves, Garret [R-LA-6]

Target Audience

Population: People reliant on transportation efficiency and safety improvements through advanced smart city technologies

Estimated Size: 15000000

Reasoning

Simulated Interviews

City Planner (Seattle, Washington)

Age: 45 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 12/20

Statement of Opinion:

  • The policy limits the tools we have available for our projects, potentially increasing costs.
  • We need to adjust our projects to rely on non-restricted technologies, which are often pricier.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 7
Year 2 6 7
Year 3 7 8
Year 5 7 8
Year 10 7 7
Year 20 6 7

Tech Entrepreneur (Los Angeles, California)

Age: 30 | Gender: female

Wellbeing Before Policy: 8

Duration of Impact: 5.0 years

Commonness: 5/20

Statement of Opinion:

  • Our business is hit directly as our partners are based in China.
  • We might have to pivot or find new partnerships, which isn't easy.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 4 8
Year 2 5 9
Year 3 6 9
Year 5 7 9
Year 10 8 8
Year 20 7 8

Agricultural Consultant (Houston, Texas)

Age: 60 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 10/20

Statement of Opinion:

  • The policy restricts drone options for farmers who need affordable and reliable monitoring solutions.
  • Could increase costs for farmers, affecting advice I can offer.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 6
Year 2 5 7
Year 3 6 7
Year 5 6 7
Year 10 6 6
Year 20 5 6

Logistics Coordinator (Miami, Florida)

Age: 27 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 3.0 years

Commonness: 15/20

Statement of Opinion:

  • Our delivery operations might face delays since we might not use the most efficient drones available.
  • Looking into alternative technologies but expect some initial disruption.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 7
Year 2 6 7
Year 3 6 7
Year 5 7 8
Year 10 7 8
Year 20 7 7

Academic Researcher (Chicago, Illinois)

Age: 50 | Gender: female

Wellbeing Before Policy: 9

Duration of Impact: 4.0 years

Commonness: 8/20

Statement of Opinion:

  • The restriction impacts data collection methodologies, requiring adaptations.
  • Could slow down research progress due to additional compliance checks.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 9
Year 2 8 9
Year 3 9 9
Year 5 9 9
Year 10 9 9
Year 20 8 8

Transport Engineer (New York, New York)

Age: 35 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 6.0 years

Commonness: 7/20

Statement of Opinion:

  • We have to reassess project budgets and timelines due to equipment changes.
  • There may be initial setbacks but long-term goals remain achievable.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 8
Year 2 7 9
Year 3 8 9
Year 5 8 9
Year 10 8 9
Year 20 8 8

Urban Developer (Austin, Texas)

Age: 42 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 7.0 years

Commonness: 9/20

Statement of Opinion:

  • This policy forces us to rethink some tech solutions.
  • Might slow down certain smart city initiatives until alternative solutions are found.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 7
Year 2 6 8
Year 3 7 8
Year 5 7 8
Year 10 7 8
Year 20 7 7

Software Developer (San Francisco, California)

Age: 28 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 4.0 years

Commonness: 14/20

Statement of Opinion:

  • We might have to redesign our software to suit new hardware, which is a huge effort.
  • Expecting an increase in workload but also potential opportunities to collaborate with new hardware providers.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 8
Year 2 7 8
Year 3 8 9
Year 5 8 9
Year 10 8 9
Year 20 8 8

Public Safety Officer (Phoenix, Arizona)

Age: 59 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 2.0 years

Commonness: 6/20

Statement of Opinion:

  • Our department's budget could be strained if we need to buy more expensive alternatives.
  • Policy could lead to gaps in surveillance coverage during transition.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 6
Year 2 5 6
Year 3 6 6
Year 5 6 6
Year 10 6 6
Year 20 6 6

Infrastructure Manager (Boston, Massachusetts)

Age: 40 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 13/20

Statement of Opinion:

  • It's a mixed bag - the grant helps a lot but finding compliant tech isn't easy.
  • We need to find a workaround or negotiate for more funds.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 7
Year 2 6 8
Year 3 7 8
Year 5 7 8
Year 10 7 8
Year 20 6 7

Cost Estimates

Year 1: $5000000 (Low: $3000000, High: $10000000)

Year 2: $5000000 (Low: $3000000, High: $10000000)

Year 3: $5000000 (Low: $3000000, High: $10000000)

Year 5: $5000000 (Low: $3000000, High: $10000000)

Year 10: $5000000 (Low: $3000000, High: $10000000)

Year 100: $5000000 (Low: $3000000, High: $10000000)

Key Considerations