Interview with Judy King, Director of Innovation at BBC Monitoring, UK.
Hi Judy, what is your background, and what is included in your current role at BBC Monitoring?
I joined BBC Monitoring as a researcher in November 1999, following two years teaching English in rural Japan. And I have been there ever since, apart from a brief stint working at the BBC News website.
After 18 years, I really understand what makes BBC Monitoring tick. And this is hugely beneficial in my current role in which I head up the innovation team. Our work is very varied. On any one day we could be running a pilot to try out a new tool with one of our regional teams, collaborating with the BBC’s NewsLabs team on language technology prototypes or advising other BBC teams on using Agile ways of working in the Newsroom.
What differs BBC Monitoring from other media monitoring companies?
Many companies in this area are tech firms using AI and machine learning for brand monitoring purposes. We are quite different. We don’t only rely on technology and algorithms to find relevant information.
We employ highly-skilled, multi-lingual journalists who have a deep understanding of the media environment they are covering. This enables them to navigate through the ever-growing number of sources to spot trends and find the stories that matter.
We have a long history of reporting on developments from the world’s media. We have been doing this since the Second World War after all! And we are able to draw on this deep archive to enable our users to make sense of the present.
What are the possibilities and benefits of automation of the editorial workflow?
BBCM’s role is to understand and navigate media ecosystems to find news, spot disinformation and give context to events. Not just one, but many ecosystems, in many languages. And it is changing fast. Gone are the days when you could watch one state TV station and read a couple of newspapers to know what is going on in a country. We can no longer successfully do our job without the help of automation and artificial intelligence.
We use tools to help us keep across social and online sources, but for broadcast media it is much more difficult. There are huge benefits for our journalists to have access to speech-to-text transcripts of the broadcasts they are watching – in the vernacular language. This would enable us to keep across many more TV sources, find the information that is relevant to our users and spend more time adding context and insight to the output that they are producing.
What are the challenges of automation?
I think that the main challenge is how to fully integrate automation into the journalists’ daily work. If we were to just bolt it on as another tool available for people to use, without considering the entire workflow, we would not be able to realise all the benefits that introducing speech-to-text and other automated technology could bring.
What would your advice be on how to meet those challenges?
I think it is all about piloting and getting the technology into the workflow as soon as you can.
Of course, you also need to set the right expectations with journalists. The quality of the transcript will not be perfect and you should be clear about that from the start.
But if you can get the technology in front of journalists – even if it is not perfect – then they can start to experiment with how the automated transcripts can help them produce even more creative and original journalism.
When it comes to introducing automation of the editorial workflow, what next steps will we see in the near future that will improve it even further?
I haven’t seen any speech-to-text technology in any language that is perfect (getting people’s names right, for example, is extremely difficult). But there is a lot of focus on language technology at the moment and it is improving all the time. Even now the accuracy of the transcripts can also be improved if coupled with other technology, such as face recognition and speech recognition.
There is currently a lot of discussion about “fake news.” What do you think about the balance in the discussion between the focus on fake news compared to real news (where all facts are correct in)?
It is an extremely complicated picture. In many cases it is unclear whether what we are seeing is misinformation, which you could describe as the inadvertent sharing of false information, or disinformation, which is the deliberate creation and sharing of false information.
Our journalists are highly skilled at verifying what they see on the media they are covering. In some cases, what they see are efforts by media outlets not just to mislead and misinform, but sow confusion, undermine public trust in the media, create the impression that you can’t get to the bottom of things – that there is no truth, no facts, just opinions.
Have you recently, or are you planning to, release any new technology-based solutions that will add to or improve services for your clients?
We are constantly looking for ways to improve our service to our customers. We recently introduced a new “fake news” tag onto our website to enable our users to more easily find articles on disinformation and propaganda. We are about to make improvements to our search functionality, to guide our users even more smoothly through our news and reference content, enabling them to quickly get to the information they need.
When it comes to the actual data behind the analysis that you do, what kind of data or media can be interesting in the future that you do not use for your analysis today?
In the future I envisage us doing a lot more big data work, analyzing trends and how they develop across time. For example, capturing a broader swathe of media content than we are currently capable of analyzing and using it to find stories hidden in the data. We would also want to integrate this with our vast archive of monitored media output, which dates back decades.
How do you think the monitoring industry will change in the next 5-10 years, and what are the greatest challenges ahead?
If, in the coming years, technology companies continue to make leaps forward in automation and machine learning, transcription and translation will become reliable. I think that will bring the biggest change to the media monitoring industry.
But even if the language technology does improve considerably, non-specialists will still need help to navigate the increasingly complex media environments around the world. BBC Monitoring will continue to develop a reputation as source specialists, guiding our users to what matters to them.
By Renata Ilitsky