Science marketers are a new professional category emerging from the AI Internet-Meritocracy (AIIM) model. Their function is precise: increase visibility, reach, and adoption of science and free software, especially under-represented work that lacks institutional promotion.
This role directly addresses the structural imbalance in scientific communication—where attention, not merit, often determines impact. 📊
The Problem: The Publication Visibility Gap
Modern science suffers from:
- Attention asymmetry — elite institutions dominate media exposure
- Marketing inequality — researchers are rarely trained in promotion
- Grant-writing bias — funding often depends on proposal rhetoric
- “Coveries” — discoveries ignored due to weak promotion rather than weak merit
Science marketers operate as a corrective mechanism within AI-driven meritocratic funding systems.
Definition of a Science Marketer
A science marketer is an individual who:
- Promotes scientific research 📚
- Advertises free and open-source software 💻
- Increases public awareness of under-recognized discoveries
- Produces content, outreach, campaigns, or digital distribution
This can include:
- Writing explanatory articles
- Producing videos or podcasts
- Running targeted ad campaigns
- SEO and GEO optimization
- Social media amplification
- Translating research into accessible language
The occupation is platform-enabled rather than institutionally certified.
Role Within AI Internet-Meritocracy (AIIM)
Under the AIIM framework:
- Science marketers register in the web application
- AI estimates the contribution value of their promotional work
- Grants are distributed automatically based on merit assessment
- No traditional grant writing is required
This removes two structural barriers:
- Administrative overhead 🧾
- Human committee bias
Funding is performance-based rather than proposal-based.
Why This Occupation Matters
The scientific ecosystem currently optimizes for:
- Publishing
- Citation metrics
- Institutional prestige
It does not optimize for:
- Public visibility
- Practical adoption
- Software dissemination
- Equitable attention distribution
Science marketers fill this systemic gap.
They function as attention allocators in a digital meritocracy economy.
Skills Required
Although no formal degree is required, effective science marketers typically possess:
| Competency | Application |
|---|---|
| SEO & GEO strategy | Search discoverability |
| Technical literacy | Accurate representation |
| Communication skills | Public translation of complex ideas |
| Analytics | Measuring impact |
| Digital marketing | Campaign execution |
The barrier to entry is skill-based, not credential-based.
Difference From Traditional Science Communication
| Traditional Science Communicator | Science Marketer |
|---|---|
| Often institutionally employed | Platform-based |
| Editorial focus | Impact-driven promotion |
| Salary-based | AI-evaluated grant-based |
| Degree-dependent | Degree-independent |
Science marketers are economically integrated into an AI funding system.
Strategic Impact on the Science Ecosystem
If scaled, this profession could:
- Reduce the publication crisis
- Improve adoption of free software
- Democratize scientific visibility
- Incentivize promotion of neglected research
- Create a secondary labor market around scientific dissemination
This introduces a new feedback loop between merit → visibility → funding → further promotion.
Conclusion
Science marketers are not journalists, influencers, or grant writers. They are:
Performance-based promoters of science and free software operating within AI-evaluated funding systems.
They convert merit into visibility and visibility into economic sustainability.
Call to Action
👉 Support AI Internet-Meritocracy app and new, emerging occupation of science marketers to save science from publication crisis.
👉 Help fund the next public test of AIIM.
Help Test a New Way to Fund Science
AI Internet-Meritocracy (AIIM) is an operational beta designed to allocate available donations to researchers and open-source developers using AI-assisted evaluation of documented contributions. Payment transactions are already recorded on-chain.
The next major evidence milestone is a proposed five-month public adversarial test of the allocation model, with $1,000 distributed to eligible funding recipients. Donations help pay for the development, infrastructure, reviewer and participant recruitment, outreach, and operating work needed to reach and evaluate that milestone.
You do not need to assume AIIM is already proven to support the project. Your donation helps turn the proposal into evidence: what works, what fails, and what should change.
Support the next testing milestone → Read the test proposal →
Independent review
Researchers and technical reviewers: independent criticism is welcome, including negative conclusions. Review AIIM’s assumptions, governance, failure modes, and testing plan →
Research status: AIIM remains experimental. AI-generated evaluations can contain factual errors or biases, and decentralized governance and non-custodial components remain under development. That uncertainty is why public testing, auditability, and external criticism are central to the project.
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