AI & Data
AI Safety & Responsible AI Challenges
AI Safety & Responsible AI challenges put you inside the work of making AI systems trustworthy before they ship. You'll build skills in AI ethics, AI bias, and fairness metrics, learning to surface problems through hallucination detection and a working grasp of adversarial concepts.
From there you'll take on the harder edges — adversarial robustness research and red-team operations for foundation models — and translate them into AI governance frameworks anchored in the NIST AI Risk Management Framework and EU AI Act risk classification, the way responsible AI teams actually operate. Each challenge you solve earns a verified credential you can share with recruiters.
Recommended Challenges
· AI governance frameworks Clear- AnalysisIntermediateNew
Map a Healthtech Startup's Triage Bot to the EU AI Regulation
Read the EU AI Regulation's Annex III (high-risk areas) carefully. Classify the triage bot's components and explain whether the system is high-risk; if so, enumerate the applica…
- Regulatory Analysis
- Ai Governance Frameworks
- Risk Mapping
AI Law, Policy, and Regulation - CodeIntermediateNew
Prototype Constitutional-AI Style Guardrails for an Internal Chatbot
Author a 'constitution' of 15 to 20 principles tailored to internal research use (no IP leakage, no off-label medical claims, no personnel-data fishing, etc.). Implement a criti…
- Constitutional Ai
- Alignment Techniques
- LLM Evaluation
AI Safety and Alignment - AnalysisIntermediateNew
Auditing Bias in a Fintech Credit Scoring Model
Conduct a quantitative fairness audit using a public proxy dataset (e.g., the UCI Adult or Give Me Some Credit dataset re-framed as BNPL decisions) and apply at least three fair…
- Algorithmic Fairness
- Ai Audit
- Regulatory Analysis
AI, Ethics and Society - StrategyBeginnerNew
Pitch a Regulatory Sandbox Application for an Edtech AI Product
Read the EU AI Regulation's regulatory-sandbox provisions. Pick a member-state sandbox program (Spain, Norway-as-EEA, or a German-state pilot are publicly documented options) an…
- Regulatory Analysis
- Ai Governance Frameworks
- Product Strategy
AI Law, Policy, and Regulation Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- StrategyBeginnerNew
Design an Internal AI-Use Policy for a Mid-Cap Bank
You receive the bank's existing IT-acceptable-use policy and a description of which AI tools are being rolled out (an internal Anthropic Claude wrapper for general use; a code-c…
- Ai Governance Frameworks
- Policy Design
- Responsible Ai
AI Ethics, Fairness, and Responsible AI - StrategyBeginnerNew
Responsible AI Policy for a HR-Tech Scale-up
Working as a cross-functional team, produce a Responsible AI Policy that addresses: permitted/prohibited use cases, human oversight requirements, data minimization, vendor due d…
- Ai Usage Policy
- Ai Governance Frameworks
- Stakeholder Management
AI, Ethics and Society - StrategyIntermediateNew
Design a Compliance Strategy for an AI Robo-Advisor in the EU
Anchor the work on the published EU AI Regulation risk classification (limited vs. high-risk systems) and the European Securities and Markets Authority guidelines on robo-advice…
- Ai Governance Frameworks
- Regulatory Analysis
- Product Strategy
AI and Quantitative Finance - StrategySeniorNew
Run a Mock Algorithmic-Discrimination Investigation for a Hiring-Tech Vendor
As a 3-person team, design and execute a 3-week mock inquiry. Produce: (1) the demand letter you imagine the regulator sending (scope, legal basis, data requested); (2) the vend…
- Regulatory Analysis
- Algorithmic Fairness
- Ai Governance Frameworks
AI Law, Policy, and Regulation - Browse challenges
Explore role
Product Manager
Ship product that solves real user problems. Combine user research, prototyping, and stakeholder alignment to turn ambiguous briefs into measurable wins — the role at the centre of modern software teams.
- AnalysisSeniorNew
Write a Copyright Risk Memo for a Foundation-Model Lab's Training Set
Cover (1) US fair-use exposure for training on web-scraped text and code, including the current state of pending major lawsuits at the time of writing; (2) the EU TDM exceptions…
- Copyright Law
- Regulatory Analysis
- Risk Mapping
AI Law, Policy, and Regulation - AnalysisIntermediateNew
Draft GDPR + AI Act Data Provisions for a Training-Data Vendor
Anchor the work on (1) GDPR Articles 28 (processor obligations) and 32 (security), (2) the EU AI Regulation's data-governance article for high-risk systems, and (3) the EDPB's p…
- Data Protection Law
- Contract Redlining
- Regulatory Analysis
AI Law, Policy, and Regulation
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
Industry teams behind a decade of practitioner briefs
Hiring from this pool?
Sponsor a challenge and meet candidates through actual work.
Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.