ashleylbarth@gmail.com

ashleylbarth@gmail.com

Verified Identity

Balancing rigorous security with seamless human experiences for millions of global users.

Role

Senior Product Designer, Trust & Safety

TL;DR

I authored the framework that balances human friction with platform security, positioning verification as a defensive moat against global fraud and aligning leadership around a new industry standard.

Verified Identity

Balancing rigorous security with seamless human experiences for millions of global users.

Role

Senior Product Designer, Trust & Safety

TL;DR

I authored the framework that balances human friction with platform security, positioning verification as a defensive moat against global fraud and aligning leadership around a new industry standard.

Business & User Impact

Outcome

LinkedIn put its name on professional trust long before it put a checkmark next to anyone's. Before this project, there was no scalable way to verify who anyone actually was. This project was about making that promise real. I led design for a verified identity system that had to work for members checking a box, enterprise partners building on top of an API, and regulators watching closely from the sidelines. It had to be seamless and rigorous at the same time. Those two things are usually in tension. That was the interesting part.

LinkedIn put its name on professional trust long before it put a checkmark next to anyone's. Before this project, there was no scalable way to verify who anyone actually was. This project was about making that promise real. I led design for a verified identity system that had to work for members checking a box, enterprise partners building on top of an API, and regulators watching closely from the sidelines. It had to be seamless and rigorous at the same time. Those two things are usually in tension. That was the interesting part.

Business

100M+ verified members

8 major partners integrated

New B2B revenue stream

User

+60% profile views for verified members

+50% post engagement

+30% connection requests

Users

100M+ verified members

8 major partners integrated

New B2B revenue stream

+60% profile views for verified members

+50% post engagement

+30% connection requests

Business

100M+ verified members

8 major partners integrated

New B2B revenue stream

User

+60% profile views for verified members

+50% post engagement

+30% connection requests

Users

100M+ verified members

8 major partners integrated

New B2B revenue stream

+60% profile views for verified members

+50% post engagement

+30% connection requests

Opportunity & Approach

Strategy

Opportunity

Professional identity online is a mess. People misrepresent credentials. Bots masquerade as professionals. And platforms mostly shrug. LinkedIn had the scale and the credibility to actually do something about it, but only if the solution worked for real people across every kind of background, device, and use case. We weren't just designing a feature. We were setting a bar. The question wasn't whether to build a verified identity system. It was whether we could build one people would actually trust, and keep trusting as it grew.

Professional identity online is a mess. People misrepresent credentials. Bots masquerade as professionals. And platforms mostly shrug. LinkedIn had the scale and the credibility to actually do something about it, but only if the solution worked for real people across every kind of background, device, and use case. We weren't just designing a feature. We were setting a bar. The question wasn't whether to build a verified identity system. It was whether we could build one people would actually trust, and keep trusting as it grew.

Article headlines about dangers of AI
Article headlines about dangers of AI

Approach

Scaling verification off-platform without diluting trust or over-collecting data. Keeping verification free made it viable as shared infrastructure rather than a gated feature.

Scaling verification off-platform without diluting trust or over-collecting data. Keeping verification free made it viable as shared infrastructure rather than a gated feature.

Keeping verification free for everyone enabled:

Network effects

Network effects

Portable verification increased trust and engagement as adoption grew

A strategic moat

A strategic moat

Defensible, partner-aware identity beyond a single platform

Future revenue

Future revenue

A foundation for B2B API monetization once infrastructure was established

UX Research, Risk Workshops

Findings & Risks

Before designing anything, we mapped the ways it could go wrong. Legitimate users blocked by edge cases. Bad actors finding the gaps. Partners integrating incorrectly and quietly eroding trust at the source. Good research on a project like this isn't just about validation. It's about cataloging the failure modes before they ship.

Before designing anything, we mapped the ways it could go wrong. Legitimate users blocked by edge cases. Bad actors finding the gaps. Partners integrating incorrectly and quietly eroding trust at the source. Good research on a project like this isn't just about validation. It's about cataloging the failure modes before they ship.

Key findings

Spectrum of verification types from basic to full with details

A single signal needs to be elastic

Instant reassurance for low-stakes moments. Deep credibility when it matters most.

A single signal needs to be elastic

Instant reassurance for low-stakes moments. Deep credibility when it matters most.

Side by side of a verified freelance hiring profile vs. verified dating app. profile
Side by side of a verified freelance hiring profile vs. verified dating app. profile
Side by side of a verified freelance hiring profile vs. verified dating app. profile

Protect the network: Trust doesn't transfer

You can't just plug identity signals from one ecosystem into another without diluting the entire brand.

Protect the network: Trust doesn't transfer

You can't just plug identity signals from one ecosystem into another without diluting the entire brand.

Risks

Every risk had a designed response. That was the point.

Inconsistent verification eroding trust

Inconsistent verification eroding trust

Strict partner criteria. Protect existing trust signals, avoid brand dilution and bad press.

Strict partner criteria. Protect existing trust signals, avoid brand dilution and bad press.

Partners handling identity data crating privacy/regulatory risk

Kill-switch architecture to prevent misuse or spoofed badges

Kill-switch architecture to prevent misuse or spoofed badges

Verification stuck inside LinkedIn limiting platform value

Beta with 5 vetted partners. Stress-test the UX, API, and business assumptions before scaling.

Beta with 5 vetted partners. Stress-test the UX, API, and business assumptions before scaling.

Internal & External Resources

My Deliverables

The work spanned strategy through production. Here's what I owned.

System architecture mapping — figuring out what had to be true before anything got designed

System architecture mapping — figuring out what had to be true before anything got designed

Verification badging UI, interaction design, and management experiences

Verification badging UI, interaction design, and management experiences

Member-facing verification flows across iOS and Android

Member-facing verification flows across iOS and Android

System documentation that makes the next project faster (external and internal)

System documentation that makes the next project faster (external and internal)

Design & Business

Where it got interesting

Self-Serve vs. Assisted

Tension

Business wanted quality control, Engineering wanted scale, Legal/Brand wanted guardrails.

Decision: Both/Phased

Launch with vetted partners to validate trust patterns, then expand to self-serve once safeguards were established.

Safety Signal vs. Marketing

Tension

Marketing pushed for prominent branding; Legal wanted explicit technical language; partners wanted flexibility.

Decision: Safety Signal

A subtle, credibility-first badge ("Verified on LinkedIn") that behaved like a safety signal, not an ad. Users trusted verification more when it felt protective, not promotional.

Fixed vs. Adaptive Data

Tension

Partners needed different trust depth; a single access level either over-exposed data or limited usefulness.

Decision: Adaptive

Three-tier consent model adapting verification depth by use case: Basic (yes/no), Standard (verification type), Full (details with explicit consent).

What I did

My Role

Project responsibilities:

  • Off-platform verification lead: Strategy, governance, partner experience

  • Cross-functional orchestration: Aligned engineering, legal, product teams

  • Business development: Design liaison in partner negotiations, UX as deal differentiator

  • Scaled impact: Partner playbooks adopted across 8+ integrations

  • Unified strategy: Consolidated on/off-platform verification into single system

At scale, strategy is the most important craft. The badge mattered. The infrastructure mattered more.

All cases

(3)

All cases

(3)

All cases

(3)