Fair AI Development
Open-source tools for bias detection, benchmarking, and model transparency.
Social Impact Tech Foundation
Eliminating AI bias for social equity.
Technoplus Master Mind Group tackles the root of AI harm: bias. We build fair systems, audit high‑stakes AI, and co-design solutions with the communities most affected.
120
Bias audits delivered
60
Communities served
14
High‑risk AI sectors
Our Core Problem: AI Bias
- Gender and racial bias in hiring & lending
- Language & dialect bias in speech and NLP
- Disability bias in accessibility and health AI
- Geographic & socioeconomic bias in services
The Bias Crisis
AI bias is not a technical glitch. It is a justice issue.
Biased data and unequal representation can make algorithms deny loans, misdiagnose patients, and reinforce systemic discrimination. We focus on eliminating harmful bias across real-world systems that affect people’s livelihoods and dignity.
Algorithmic Discrimination
Unfair outcomes in hiring, finance, housing, and criminal justice systems.
Data Inequality
Underrepresented or stereotyped groups missing from training data.
Systemic Amplification
Feedback loops that deepen inequities across education, health, and access.
Solutions
Practical approaches to detect, reduce, and prevent AI bias.
Representative Data Collection
Ethical, consent‑based datasets that reflect real communities.
Algorithmic Auditing
Third‑party audits for high‑stakes AI used in health, finance, and public services.
Community-Centered Design
Co‑design with impacted groups to ensure fairness by default.
Bias Education & Training
Workshops for engineers, policymakers, and community advocates.
Policy & Advocacy
Accountability standards and responsible AI regulations.
Impact
Measurable progress toward fair AI systems.
We track bias reduction, representation gains, and policy improvements across sectors. Metrics below are representative and should be updated with verified data.
0
% bias reduction in audited models
0
% parity in evaluation benchmarks
0
Bias auditors trained
0
Policy changes influenced
Competitions
Recognition for social impact innovation in agriculture.
AgriHack
Applied ML tools for smallholder farmers to improve yields, resilience, and access to market insights.
Learn moreFeed the Future — Fall Armyworm Tech Prize
Recognized for ML-based pest forecasting tools for smallholder farmers across food systems.
Learn moreFunding
Past support and inspiration.
We have previously been funded through social impact and innovation programs to deploy ML technologies for smallholder farmers and bias‑aware decision tools across public services. Our approach is inspired by social impact tech firms that prioritize measurable outcomes.
Replace or expand these links with official funding confirmations as needed.
Mastermind Group
A multidisciplinary coalition focused on bias elimination.
Research & Ethics
Fairness Scientists
Bias detection, evaluation metrics, and responsible AI research.
Community Advocates
Impact Partners
Co‑designing solutions with affected communities and local leaders.
Policy & Partnerships
Alliance Builders
Aligning policymakers, funders, and builders around accountable AI.
Testimonials
Community voices on bias and trust.
“The audit helped us find bias in our screening tool and rebuild it with fairness as a requirement.” — Talent platform partner
“We finally saw our language community represented in the dataset.” — Community advocate
“Bias mitigation is now part of every AI procurement decision we make.” — Public sector leader
Allies
Mission-aligned collaborators for bias-free AI.
Human rights groups
Public agencies
Research labs
Grassroots networks
Impact investors
Contact
Let’s build the future together.
Share how you want to collaborate, fund bias audits, or volunteer.