The Relationship Between Age, Experience and Technology Use: The Translator Profile

The relationship between a translator’s age and technology is one of the most frequently voiced and least tested assumptions in the industry. The common view runs as follows: young translators take to tools, experienced translators keep their distance.

Contents

The assumption is not entirely groundless; its explanatory power, however, is a good deal weaker than supposed. Among the factors that shape decisions about tool use, age is more often than not nowhere near the top of the list.

Below we take up the problems with the assumption, the other variables that get confused with age, the two-way effect of experience, the differences in how people learn, and how age diversity within a team can be turned to account.

Why is the common assumption inadequate?

The first problem with the assumption is that it treats familiarity with devices and professional tool competence as one and the same thing. Someone who grew up with a phone does not automatically understand a translation memory; match rates and the logic of segmentation have to be learned separately.

The second problem is that age gets confused with other variables. Young translators have generally graduated more recently, so they are more likely to have taken a technology course. What is decisive is not age but the content of the education.

The third problem is the type of work. Experienced translators specialise over time in particular fields; in some of those fields the repetition rate is low and the gain from a memory is limited. The decision not to use a tool here has to do with the portfolio, not with age.

The fourth problem is how the data are read. In the research, the leading reason for not using a memory is having no need for it, at 50 per cent; price and the absence of client demand stand at about 40 per cent each, and finding it complicated at around 25 per cent (Pietrzak and Kornacki 2021, Table 6.11). Age does not stand out as an explanatory variable in that distribution.

The fifth problem is that the assumption confirms itself. When an experienced translator is never offered tool training, their not using one is counted as proof of the assumption. Yet the opportunity was never put before them. The same mechanism works in the other direction too: because a young translator is assumed to know the technical workflow, no support is given to them either, and the gaps grow unnoticed.

The variables that get confused with age

The table below sets out the real variables standing behind the age factor that is supposed to explain tool use.

Apparent factor	The real variable behind it	How to test it
Age	Period of graduation and curriculum content	Ask whether they took a technology course
Age	The repetition rate of the field of specialisation	Examine the text type and the repetition rate
Age	What the client portfolio demands	Ask what file formats the clients require
Age	Capacity to invest and volume of work	Look at whether the licence cost is affordable
Age	The existence of a support network	Ask who they turn to when a problem arises

The purpose of the table is not to claim that age has no effect at all. The purpose is to show that stronger explanations should be ruled out before moving to an explanation by age. When the questions in the right-hand column are asked, it is often found that the age explanation is no longer needed.

The licence row is particularly important. In the research, 91 per cent of translators own their own licence (Pietrzak and Kornacki 2021); that is, cost is an individual line of decision and is directly bound up with volume of work.

The two-way effect of experience

Experience affects technology use in two opposite directions. On the positive side, it makes the limits of a tool easier to see. An experienced translator notices more quickly that a suggestion coming from the memory does not fit the context.

This is a critical competence. Bowker (2005) draws attention to the risk of blind faith in translation memory; being able to reject a suggestion is a more valuable skill than being able to accept one, and it develops with subject knowledge.

On the negative side, experience hardens routines. To someone who has worked the same way for years, a new arrangement looks more like a loss than a gain. The cost of change is felt more concretely than its benefit.

The second negative effect is that the existing arrangement genuinely works. Changing a system that functions calls for a strong justification, and that justification is often not supplied; the tool is proposed before its usefulness has been demonstrated.

Experience, then, is neither an obstacle nor an enabler; what is decisive is whether the experience has turned into a body of knowledge that is questioned or into a closed routine.

Nor is that distinction hard to observe. A translator who questions their experience can explain why they would decide differently today from the way they decided in the past. A closed routine, by contrast, takes pride in not having changed and offers no reasons.

How does the way of learning change?

What changes with age is not the capacity to learn but the way of learning. Experienced users learn new information by attaching it to what they already know; where the right connection is made, this is a very fast route.

A practical conclusion follows: when explaining a tool to an experienced translator, you should start not from the menus but from a problem they know. If they are already living with a problem of terminological consistency, a termbase becomes meaningful.

Younger users, on the other hand, learn more by trying things out. They are strongly inclined to navigate the interface and guess. The method is fast, but it can leave conceptual gaps; it carries the risk of getting a result without knowing what one has done.

Both forms are incomplete. Speed with no conceptual foundation stops at the first serious problem; conceptual knowledge with no experimentation never turns into practice.

What they have in common is the effect of the working environment. Interrupted workflows and badly designed interfaces exhaust the capacity for attention in every age group (Ehrensberger-Dow and O’Brien 2015). Part of the difficulty of learning comes from the environment.

For that reason it is more productive to draw distinctions in training design by need rather than by age. The same group can contain a young user with a conceptual gap and an experienced user who lacks familiarity with the interface; each of them needs a different starting point.

Making use of age diversity in a team

A difference in age, set up properly, is a resource rather than a problem. The strengths of the two groups complement each other.

Younger members can try new tools out quickly and get past technical obstacles. Experienced members can see where the output is misleading and which decision carries risk.

Pairing works for that reason. On a project, the younger member takes on the set-up and the technical workflow while the experienced member makes the subject-matter decisions and does the final review. Each side learns from the other.

The second practice is a shared record. Collecting the technical problems encountered and their solutions in a shared file moves knowledge from the individual to the organisation. That record also stops the knowledge from being lost when someone leaves.

The third practice is sharing the reasoning behind decisions. An experienced member explaining why they rejected a suggestion is the kind of knowledge a younger member learns fastest, and it is written in no manual.

The cost of the assumption

The age assumption has a price of its own, and that price is usually left out of the reckoning. Because the assumption shapes decisions before the data do, it sends them the wrong way.

The first cost is in training. When experienced translators are not offered tool training, a potential gain is given up from the start. Yet this is the group best placed to see the limits of a tool most quickly.

The second cost is in the distribution of work. Handing complex technical files to younger members automatically can mean that subject-matter risk is overlooked. Technical workflow and subject-matter judgement are not the same skill.

The third cost is in recruitment. Screening by years of seniority or by age conceals the real criteria. A more accurate criterion is what the candidate has produced, and in which text types, over the past year.

The fourth cost is cultural. When the assumption is voiced openly, a defensive atmosphere takes hold in the team; nobody wants to say they do not know something, and learning stops.

The Türkiye context

In Türkiye the generational difference overlaps with a change in the curriculum. Translation technology courses have become widespread in recent years on translation and interpreting and translation studies programmes; new graduates are therefore more likely to have encountered the tools. This is a difference of programme, not of age.

Sworn translation presents a different picture. The workflow of translators who have long worked in this field is template-based and is built around notarial processes. Because the gain from a memory is limited, tool use can remain low; that is a fit with the type of work, not a closedness to technology.

The structure of Turkish also bears on the picture. Because of its agglutinative structure, exact match rates fall and fuzzy matches call for careful reading. Under those conditions the value of experience rises; the ability to assess a suggestion becomes more decisive than the ability to operate the tool.

Finally, support networks are not spread evenly across age groups. Online peer groups are filled more with younger users; experienced translators joining those networks is a factor that closes the learning gap quickly. This article is for general information and does not constitute legal advice.

What does this mean for you?

When you are choosing a supplier, age or years of seniority carries no information on its own. A young team may be fast but may fail to see subject-matter risk; an experienced team may be safe but may prove slow on the technical workflow.

For a more accurate assessment, you can follow these steps:

1. Ask not about years of seniority but about the work done in your own text type over the past year.
2. Confirm that translation and proofreading are carried out by different people.
3. Find out who runs the technical workflow in the team and who makes the subject-matter decisions.
4. Run a small trial with a complex file format; observe the communication as well as the speed.
5. Have it put in writing that the same team will work on continuing jobs.

These five steps place team structure on observation rather than on assumption. We have set out our team and process arrangement on the services page; if you would like to work out the right structure for your own project, you can use the quote form.

Frequently asked questions

Do young translators adopt technology more easily?

Familiarity with devices is generally higher; professional tools, however, call for a different kind of knowledge. Understanding the logic of a memory and match rates is not the same skill as using social media.

Does experience get in the way of technology use?

Not always. Because experience makes the limits of a tool easier to see, it supports critical use. What gets in the way is not experience but settled and unquestioned routines.

What determines tool use most?

The factors that stand out in the research data are the type of work, cost and client demand. The leading reason for not using a tool is having no need for it, at 50 per cent.

How can age diversity in a team be turned to account?

Younger members can try new tools out quickly, and experienced members can see where the output is misleading. Pairing the two gives better results than either group on its own.

Sources

• Pietrzak, P. and Kornacki, M. (2021). Using CAT Tools in Freelance Translation. London: Routledge Focus, Table 6.11.
• Bowker, L. (2005). Productivity vs Quality? Localisation Focus, 4(1), pp. 13-20.
• Ehrensberger-Dow, M. and O’Brien, S. (2015). Ergonomics of the Translation Workplace. Translation Spaces, 4(1), pp. 98-118.
• Rosen, L. D. and Maguire, P. (1990). Myths and Realities of Computerphobia: A Meta-Analysis. Anxiety Research, 3(3), pp. 175-191.