This is just a short post to share some exciting news. After around 18 months of writing (with some breaks), so many trips to the National Library of Scotland that I have a favourite seat in the Reading Room, and a few trips to try out some ideas in public, preorders for my new book: Interpreters vs Machines: Can Interpreters Survive in an AI-dominated World? are now open. (Click the title to go to the preorder page.)
This book deals with the biggest question in interpreting right now: do human interpreters stand a chance of professional survival, faced with the gathered might of the world’s biggest tech companies? It also deals with the second biggest question: which strategy offers our best hope?
After reading the research, taking an honest look at our profession and really thinking through what is actually going on right now, I have found some uncomfortable answers.
The answers are uncomfortable for everyone.
The answers are uncomfortable for interpreters as they force us to face up to some of the most difficult issues in our profession and practice. Failure to take seriously the challenges of machine interpreting leads inexorably to being replaced.
The answers are uncomfortable for makers of machine interpreting devices and apps as they force them to face up to the weaknesses in their understanding of interpreting. Failure to take seriously the need to actually understand what interpreters do will consign their best work to the world of geeky gadgets that never live up to their promise.
The answers are uncomfortable for the general public, even if they never think of buying a machine translation device, as they force us to face up to what it really means to live in a society where information is currency and where the technology we use to communicate might just control what we can and can’t say and how we say it.
This isn’t just a book about interpreting; it’s a book where I deliberately attempted to get to the truth of what it really means when people in the tech sector say they will replace people with machines. If you are an interpreter, a programmer with an interest in AI, deep learning or machine interpreting, or even just someone interested in the power and effects of technology, this book is for you.
As soon as the final release date is confirmed, I will bring you another update.
Is the rise in new platforms aimed at helping businesses buy in services like web design, translation, interpreting and writing actually doing real harm to both buyers and sellers?
Wherever you look, you will find a new platform aiming to bring together freelancers and their clients. You can search for graphic designers, web designers, translators, proofreaders, interpreters, just about any service that can be offered by freelancers from the comfort of the home office.
It seems like a marriage made in service aggregation heaven. The freelancers can get away with less marketing and the buyers can pick up the services they need for a very competitive price, while comparing different providers against one another. Seems ideal, right?
The Dark Side of the Platforms – The Freelance View
The most basic flaw in the “platform” or “service aggregation” model is that they tend to drive down prices. Despite all the talk of qualifications and verification and despite all the claims to the contrary, the likelihood is that buyers will be attracted to those who seem to be offering the lowest price, especially when it is difficult for an outsider to tell the difference between say, an MITI with DipTrans and 5 years of experience with MemoQ and a translator who learned French on a boozy weekend in Bordeaux but has a five star feedback rating and testimonials from their mates all saying how great they are.
That leads to the mental and economic horror of a blind auction, where freelancers have to guess what will be the lowest price that will get them the work but still pay their bills. As someone who started his career hoping against hope (and mathematical certainty) that platforms would be my business salvation, I can easily recount the effects of sending bid after bid, only for a tiny fraction to even get a response.
Any platform that encourages bidding on projects will eventually drive away the best freelancers to look for better pay and drive many of those who remain into risking their mental health. There are only so many hamster wheels you can run on before you get tired, after all.
The Dark Side of Platforms – The Buyer Side
If all this sounds like a freelancer carping, I get it. Still, I have to admit that I have used certain platforms to buy in services too, with varying results. In my case, I had a distinct advantage, as I was buying services that I knew very well so I knew exactly what to look for. Even then, the response was crazy.
Back seven or eight years ago, when I used what was then the leading platform for the service I was buying, one advert got forty responses when all I needed was three people. Of the forty responses, about twenty were easy to delete as they were irrelevant, fifteen were interesting but not up to the level I needed and five were truly useful. I still ended up pulling in help from beyond the reach of the platform anyway.
Imagine going through that process if you didn’t know a service. Given the growth of work platforms, it is likely that any business buying from them would be faced with four hundred responses, rather than forty. Once the time to filter through responses and find the really good ones is priced up, any potential savings will disappear in a whisp of smoke.
Unless I really know the service I want to buy and unless I really know what results I want, I have come to the conclusion that hiring via a platform is always going to be costly and may be risky too. In an age where customer reviews aren’t always reliable or relevant, how can you really trust that you are getting what you are paying for?
The Potential of Platforms
Platforms, of course, aren’t all bad. As a last try for a service where you have no previous leads, they can be useful. But they certainly aren’t cheaper or quicker than any other method and they come with real risks.
Platforms do have a potential to do a lot of good, especially for those with small networks and little experience. On either side, they can give new freelancers a leg up and give small businesses a chance to get service they really need.
But they can’t be a panacea.
A Better Way to Buy
It may sound strange but in an algorithm-driven, tech-dominated world, the best way to get work done is probably to step away from your screen and talk to people in real-life. The website you are reading was designed and built by the incredible Tom Jones (no, not that one!), whose brother I have known for years. My latest business cards were redesigned and printed by a local printer I met at a business event. I can find many more examples .
As a consultant interpreter, I only work with interpreters I have either worked with before or who are recommended by those interpreters or who a by trusted colleagues I haven’t managed to work with yet. In the unlikely event that I can’t find the right person using those methods, I have other contacts and use the list of members of the Institute of Translation and Interpreting.
When we work on the basis of referral, rather than trusting our business future to algorithms we didn’t right and platforms we don’t fully understand, we reduce the risk of buying services from the wrong people and getting the wrong results. Instead of trusting random reviewers, the best results come from trusting the experience of people we know and can easily contact if their recommendation turns out not to be helpful.
People not Platforms
In short, while the platforms are useful if you don’t have any network at all, they come with big risks. It will always be more beneficial to your business and to the people offering the service for you to take the time and talk to people you know to discover who is already doing a great job. So the next time you are looking for an interpreter, keep back from the platform edge.
For free advice on getting the right interpreter for your next event, drop me an email.
Five years ago, I wrote a cheeky post for the LifeinLINCS blog detailing some off-the-wall inventions that interpreters would love. Now, however, with the advent of machine interpreting software that can manage a basic conversation, I think it’s time to properly ask those who know their vector spaces from their z-tests if they could make us a single invention, which would ease the work of lots of conference interpreters.
The idea is very simple: one tricky problem in conference interpreting is that, even with the best research in the world, speakers seem able to find terms that the interpreters have never come across before. Worse, in the heat of a detailed speech, it is entirely possible that an interpreter could falter in finding that important term that that really did memorise but have suddenly forgotten.
Since Automated Speech Recognition (ASR) is now at the point where I no longer have to pass the phone to my wife when a phone system asks me to describe my issue and our smartphones are fast enough to do basic speech translation, surely we have the tech to fix that issue once and for all.
Here’s how I imagine it working.
While the speaker is talking, an ASR system scans the words and word clusters they use. Any words that are in the top 1000 most used words in the source language can be ignored but, if a word is rare, the system should automatically search the interpreter’s term bank for it. In fact, in an ideal world. the interpreter should be able to tell the system which domains they are working in (say, engineering, finance, HR) so it would prioritise rare words from that domain.
Since interpreters don’t want to be distracted, the system should then simply project the original term and its term bank version onto a rugged, travel-proof Heads-Up Display that the interpreter has placed in front of them.
But what if the term is rare and the interpreter hasn’t stored it already? In those cases, the system should be able to run parallel searches for it in the interpreter’s favourite term bases (think IATE, online and offline technical dictionaries, etc) and project the one or two most likely candidate translations.
There are a few technical headaches with this. In terms of language processing, teaching the system when to look up a single word term and when to treat a cluster as a term would be tricky. There is, after all a big difference between “shot” and “shot-blasting” and between “road” and “middle of the road”.
I’m no expert but it does seem that some kind of neural model and the ability to use the same system for semi-automated term mining beforehand might help the system “learn” what units count as a term in each domain. Possibly.
The second challenge is getting the user interface right. While experts in interpreter cognition, like Prof Kilian Seeber, have argued that interpreters simultaneously process information from multiple sources, there does still seem to be a point at which interpreters get overloaded. Add to this Prof Daniel Gile’s argument that there can be a gap between interpreters hitting an issue and it actually affecting their performance and you leave interface designers with the tricky task of ensuring that the system provides help when its needed but doesn’t distract interpreters when they’re doing fine.
There has been some research to try to fix that but it is still a challenge and it might take more research on problem triggers and performance drops to fix it for good. For the moment, using Heads-Up Displays, which allow the interpreters to still see through them, instead of asking them to look down from the speaker, would at least reduce the issue.
So, is anyone up for building one of those systems or testing one?