Maryland’s move toward sign language interpreter licensure was intended to strengthen the quality of interpreting services, and protect access of people who use those services. That goal matters. But there’s a major problem baked into the process that the most recent amendments to the licensure are trying to address: making high-impact policy decisions with low-quality data.
And when the data is incomplete, inconsistent, or missing entirely, the results are actually predictable. Rules get built around assumptions. Timelines get set without a clear view of workforce reality. Decisions that shape people’s livelihoods and people’s access to interpreting services are made using numbers that don’t reflect the full picture.
This is not a small issue. It’s the difference between a system that improves access for the most people and a system that accidentally narrows it.
The circular problem: bad data creates bad decisions
Here’s the cycle I keep seeing:
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We start with incomplete data.
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Decision makers build policy based on that incomplete data.
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The policy creates new barriers or unintended consequences for the people it’s meant to serve.
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Then adjustments are proposed, but those adjustments are still shaped by the same data gaps that caused the problem in the first place.
It creates a cycle that can subtly hinder access, even as everyone works to “resolve” the issue. For example, efforts to enhance protections for sign language users in obtaining quality interpreting services may unintentionally create additional barriers. These barriers stem from the very real national shortage of qualified interpreters who meet established standards, coupled with a very low graduation rate from interpreting programs and the numerous challenges faced by new practitioners entering the workforce.
Maryland’s current reality reflects how complicated this is. Even the state’s timelines have shifted. A 2026 fiscal and policy note for Senate Bill 645 describes delaying key licensing requirements and deadlines, pushing the date by which an individual must be licensed to provide services in Maryland to July 1, 2027. That delay may create breathing room, but it also underscores the same question: Are we building the right system if we can’t accurately measure the landscape we’re regulating?
What data is missing and why it matters
There are a few major gaps that keep showing up in interpreting discussions:
1) How many people use sign language interpreting services in Maryland and where?
We often cite national estimates, such as roughly 500,000 Deaf or hard-of-hearing Americans who use ASL. But state-level planning needs actual local numbers. How many ASL users that use interpreting services are in Maryland? How many are children in schools? How many are older adults in healthcare systems? How many are DeafBlind and require specialized access? How many are typically within mental health, medical, legal, and education? Without this, policy can’t target the highest-need areas.
2) How many interpreters are actually available in Maryland?
Even basic workforce counts can vary depending on the source and definitions. For example, one public comment document notes “498 RID certified interpreters identified by RID as living in Maryland,” and then breaks down how few hold certain specialty credentials (like SC:L for legal interpreting). Deaf Services Unlimited’s summary map lists Maryland at 487 RID-certified interpreters. The fact that these numbers don’t perfectly match is not a “gotcha.” It’s evidence of the problem. Furthermore, how many qualified interpreters who don’t hold national certification are there? If we can’t confidently answer “how many,” it’s difficult to create fair requirements or realistic enforcement.
3) Who needs help the most?
Shortage impacts are not evenly distributed. Rural communities feel it differently than urban ones. Healthcare emergencies are different from scheduled events. Legal settings require specialized skill. Education requires a different kind of competence. Data should help prioritize the most critical gaps first. Without it, policy risks treating everything as equal when it isn’t.
The national shortage makes the need for data even more urgent
Nationally, the shortage is real and documented across sectors. DSU’s research cites the 50-to-1 ratio between Deaf/Hard-of-Hearing ASL users and interpreters, and notes that locating a “suitable” interpreter is not just a numbers issue but a specialization and preference issue.
And here’s the part that should shape every policy conversation: becoming a certified ASL interpreter is not quick. I have been an interpreter educator for over twenty five years and most students are not ready upon graduation to join the workforce. This is not the fault of the student, even DSU cites that the path can take five to ten years for aspiring interpreters to achieve fluency, cultural competency, and passing rigorous certification exams.
So when people allude to fixing the shortage by requiring more credentials, we have to be honest about the timeline. Even if you take the midpoint of that training window, it suggests it would take around seven years to rebuild a workforce from scratch. That’s not a precise national forecast, but it is a realistic inference from the documented training timeline.
Which means a policy that shrinks the pool of working interpreters faster than we can train new ones will predictably reduce access in the short term.
What better data could look like
If Maryland wants interpreter licensure to truly improve outcomes, we need a stronger foundation:
- A consistent, statewide count of active interpreters (not just certified, but actually working and available interpreters)
- Better visibility into service demand by region and setting (education, healthcare, legal, employment)
- Clear tracking of specialty qualifications and where the gaps are most severe
- Regular, transparent reporting so the community can see what’s changing and why
Data doesn’t replace Deaf leadership or community input. But it should support it. Good policy is not built on guesses.
If we want legislation that helps the most people, we need numbers that reflect the most people. Until then, we will keep circling the same problem, making changes based on incomplete information, and wondering why access still feels like a gamble.
By Dave Coyne
If you want to connect to discuss this topic further, please reach out to me at dcoyne@gatewaymaryland.org to schedule a time to meet.
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