The University of Baltimore

Community Insights

From listening to action

Community Insight Briefs

These briefs summarize patterns in administrator-approved stories and turn them into possible actions for human review. They describe participating respondents—not all Baltimore residents.

Community perspectives

Plan for different needs and trust conditions

These evidence-informed lenses summarize prior engagement research. They are not demographic groups or classifications of individual respondents.

Perspective evidence was not consistently ZIP-coded, so these lenses remain citywide and do not change with the ZIP filter.

Practical NavigatorWants useful help with everyday tasks but needs a clear, trusted starting point.
Accessibility-Powered AchieverUses AI to reduce access barriers and manage demanding work, learning, or community responsibilities.
Labor and Learning GuardianProtects livelihoods, professional judgment, and the human relationships essential to learning.
Community BuilderSees AI as a practical amplifier for small organizations, entrepreneurs, and neighborhood problem-solving.
Responsible Systems StewardSupports strategic AI adoption when privacy, transparency, equity, and human accountability are designed in.
Compare perspectives and use the advisor
Visible follow-through

Track what is proposed, assigned, and completed

Only database-backed actions from approved Insight Briefs appear here. A suggested owner is not an assigned owner, and a proposed action is not a completed impact.

Open full Action Playbooks
Explore the evidence

Open interactive charts and tables

Compare approved participation patterns by ZIP, sector, persona lens, and action horizon, then inspect the public evidence table.

Explore Insight Data
Approved insight brief · 5 stories

Draft Community Insight Brief: AI Learning, Privacy, and Workplace Preparation

Active ZIP filter: All represented ZIPs. The five synthetic pilot responses are from ZIP codes 21201, 21217, 21218, 21223, and 21224, with one approved story from each ZIP. Findings describe these participating pilot respondents only and should not be generalized to all Baltimore residents.

Synthetic pilot evidence

What we heard

One participant valued AI support for summarizing dense material and improving clarity, while retaining control over their voice and decisions.

Approved synthetic pilot story from ZIP 21224: “A participant values AI for summarizing dense material and improving clarity while retaining control of their voice and decisions.”

Evidence count: 1
One participant wanted neutral information for comparing AI tools, including costs, limitations, and privacy practices.

Approved synthetic pilot story from ZIP 21201: “A participant wants a neutral comparison of AI tools, including costs, limitations, and privacy practices.”

Evidence count: 1
One participant identified a need for plain-language guidance for small organizations about information that should never be entered into AI tools.

Approved synthetic pilot story from ZIP 21218: “A participant says small organizations need plain guidance about information that should never be entered into AI tools.”

Evidence count: 1
One participant said introductory AI learning would be more approachable through a library workshop with a person available to answer questions.

Approved synthetic pilot story from ZIP 21223: “A participant would find introductory AI learning more approachable in a library workshop with a person available to answer questions.”

Evidence count: 1
One participant wanted practical guidance about possible AI-related changes to administrative work and skills that could help them prepare.

Approved synthetic pilot story from ZIP 21217: “A participant wants practical guidance on how AI may change administrative work and which skills would help them prepare.”

Evidence count: 1

Possible service gaps

  • Accessible, neutral comparisons of AI tools that address costs, limitations, and privacy practices. possible

    One synthetic pilot participant requested this type of comparison; no matching resources or initiatives were returned in the supplied catalog.

  • Plain-language guidance on information that should not be entered into AI tools, including guidance usable by small organizations. possible

    One synthetic pilot participant identified this need; no matching resources or initiatives were returned in the supplied catalog.

  • Beginner-oriented AI learning with live human question-and-answer support in a trusted setting such as a library. possible

    One synthetic pilot participant described this learning format as more approachable; no matching resources or initiatives were returned in the supplied catalog.

  • Practical workforce-preparation guidance regarding potential AI-related changes to administrative work and relevant skills. possible

    One synthetic pilot participant requested this guidance; no matching resources or initiatives were returned in the supplied catalog.

  • Confirmed availability or absence of relevant local services. insufficient data

    The supplied resource and initiative matching returned no entries, but catalog coverage may be incomplete.

Recommended actions

  1. quick win Develop a short, plain-language draft guide covering common AI privacy cautions, including examples of information to avoid entering into AI tools, and clearly label it for review rather than as final policy guidance.

    Possible owner: Local public-interest digital literacy, privacy, or small-organization support partners

    Validate by: Review the draft with small-organization participants, privacy practitioners, and affected community members before distribution; document disagreements and needed revisions.

  2. quick win Map existing public AI-learning, privacy, workforce, and tool-comparison resources before concluding that services are absent.

    Possible owner: Resource-catalog steward or community information partner

    Validate by: Ask libraries, workforce providers, small-organization support providers, and community participants to verify coverage and identify missing or inaccessible offerings.

  3. medium term Co-design and pilot a beginner AI learning session with live question-and-answer support, potentially in a trusted community setting such as a library.

    Possible owner: Library system or community-based learning partner

    Validate by: Recruit a broader, voluntary group of affected participants to test format, accessibility, language, scheduling, and whether human support improves approachability.

  4. medium term Test a neutral AI tool-comparison format that presents costs, limitations, privacy considerations, and uncertainty without endorsing a specific tool.

    Possible owner: Digital literacy or consumer-information partner

    Validate by: Have participants with varied levels of AI familiarity assess whether the comparison is understandable, balanced, current, and useful for their decisions.

  5. long term Co-design practical workforce-preparation materials focused on administrative work, possible task changes, transferable skills, and worker questions about AI use.

    Possible owner: Workforce development partner, labor-serving organization, or employer-support intermediary

    Validate by: Validate content with administrative workers and relevant worker-serving groups; avoid presenting predicted job impacts as certain unless supported by separate evidence.

Follow-up metrics

Targets are MVP planning assumptions until replaced by measured pilot results.

  • Number and diversity of voluntary participants engaged in validation, reported separately from this pilot sample.
    Baseline: 0 real validation participants recorded · Target: 15 voluntary participants across at least 3 ZIPs and 3 role contexts · Current: 0 real validation participants recorded
  • Participant-reported usefulness, clarity, accessibility, and trustworthiness of privacy guidance, tool comparisons, workshops, and workforce materials.
    Baseline: Not yet measured · Target: At least 80% rate the materials useful, clear, accessible, and trustworthy · Current: Not yet collected
  • Number of questions asked and answered during pilot learning sessions, with privacy-preserving thematic summaries.
    Baseline: 0 pilot-session questions recorded · Target: At least 20 questions logged; 90% answered live or within 5 business days · Current: 0 pilot-session questions recorded
  • Participant-reported confidence in identifying information not to enter into AI tools before and after reviewing guidance.
    Baseline: Establish with a pre-session confidence question · Target: Improve correct privacy-safety responses by at least 20 percentage points · Current: Not yet collected
  • Participant-reported ability to compare AI tools using costs, limitations, and privacy considerations.
    Baseline: Establish with a pre-session comparison exercise · Target: At least 75% correctly apply the cost, limitation, and privacy rubric · Current: Not yet collected
  • Catalog verification results: number of existing relevant resources and initiatives confirmed, added, or found unavailable.
    Baseline: 7 current verified records: 5 resources and 2 initiatives · Target: At least 12 verified records; 100% reviewed within the 90-day cadence · Current: 7 current verified records
  • Feedback from administrative workers and worker-serving organizations on the relevance and uncertainty framing of workforce-preparation materials.
    Baseline: 0 administrative workers or worker-serving organizations consulted · Target: 8 administrative workers and 2 worker-serving organizations; at least 70% rate materials relevant · Current: 0 consultations recorded

Limitations

  • Evidence consists of five human-approved public story texts and excludes private raw submissions and personal identifiers.
  • All five responses are synthetic pilot responses for workflow demonstration, not collected community testimony.
  • The sample size is 5, with one response from each represented ZIP; no topic is supported by more than one respondent.
  • Results describe participating pilot respondents only and must not be generalized to all Baltimore residents or to residents of any represented ZIP.
  • The evidence provides no demographic, sector, role, frequency, outcome, or service-use data beyond the supplied story text.
  • No matching resources or initiatives were returned, but resource and initiative matching depends on maintained catalog coverage and may be incomplete.
  • Interpretations and service gaps are provisional and require validation with affected communities before consequential action.