Technology + Creativity at the BBC Feed

Technology weapons in the disinformation war

2020-11-17T09:46:16+00:00

Photo by Camilo Jimenez on Unsplash

You’re browsing social media and you see something that doesn’t look right. What do you do? You can search for information about the source or the material itself but you may not find the answer. What if there was a technology-based solution that could help – some kind of signal that would reassure you that what you’re seeing hasn’t been tampered with or misdirected?

This question has been posed by many organisations and individuals in the last couple of years as the scourge of disinformation has grown. Now Project Origin, a collaboration involving the BBC, the CBC/Radio Canada, Microsoft and The New York Times is working on a solution.

Essentially, we are seeking to repair the link in news provenance that has been broken by large-scale third-party content hosting. What do we mean by broken provenance? Most large social media platforms have features such as verified pages or accounts but outside of these, there are countless re-posts of content that was originally published by another person or organisation. In some cases, this content is simply re-uploaded and shared. In others, a re-upload is accompanied by some new context. Users also modify the content - for humour, for brevity, and in some cases, with malicious intent.

Photo by Marvin Meyer on Unsplash

Our objective is to derive signals with respect to content coming from publishers or originators to allow consumers to be reassured about its source and the fact that it has not been manipulated. It’s a huge task and we’re very much aware that others are doing excellent work in this space, as well as in the wider disinformation sphere. The Content Authenticity Initiative, for example, has carried out some excellent work, focusing, in the first instance, on securing the provenance of images from the point of capture.

We’ve divided the problem into three main areas - giving the content item an identifier, finding a way to allow it to take that identifier with it on its journey and safely storing the information that will allow it to be checked.

Firstly, each digital image, video or audio file is represented by a very specific sequence of bits, so specific that we can safely identify even the smallest differences from the content that was originally produced. These sequences of bits are, understandably, enormous, but thankfully, we can lean on a concept called cryptographic hashing as a way of allowing us to represent them as a short string through secure hash algorithms. We can be confident that there is effectively a zero probability that two pieces of content share the same hash.

To know who generated the content hash, we need another tool – a key. Public-private asymmetric keys are in common use on today’s internet – helping us carry out e-commerce amongst other things. They allow a publisher to digitally sign a document which is linked to a piece of content – containing for example data about the content and the hashes that represent it - by creating something we call a manifest. Again, maths is our hero here with some complex cryptography ensuring that only the person with the private key could have signed the manifest and this can be verified using the corresponding public key.

The way a browser on a PC knows that this signature is bona fide is via a piece of standard internet functionality provided by a Certificate Authority – a trusted third party that checks the public key it’s being offered belongs to the right party.

Finally, at the heart of a provenance system we need a way of maintaining a reliable and consistent database of manifests. For Origin we plan to use the Microsoft Confidential Consortium Framework (CCF) as the heart of the manifest and receipt storage. The Provenance System built around this to deal with the various media registration and queries will be based on Microsoft’s AMP (Aether Media Provenance)

Unlike the permissionless blockchain solutions made famous by cryptocurrency, CCF is a ‘permissioned’ system. These are sometimes called ‘green blockchains’ since they do not need to consume large amounts of energy to determine consensus – there is enough trust between parties controlling the system to allow the nodes to act on a much simpler basis.

To sum up, we are developing a machine-readable way of representing data about a content item in a way that allows a publisher to tie or ‘bind’ the specific content item to the data and have it stored safely for future retrieval by a user.

So what’s next? On the technology front we’re determining how to ensure that the content, its manifest and the cryptographic binding – the signed hashes and certificates that link the content you have to the details - are all conveyed together. We're also working on what to do when data is not present or has been altered. What happens for example if content has been clipped or transcoded in a useful and legitimate way?

We’re also keen to determine how this kind of technology can help in a wider media and technology community where there are many tools operated by a range of different organisations. An important element of our work has been trying to understand the APIs or common interfaces that might be standardised so a single device can discover and query different systems - including those used for content creation. And we’re launching a formal standards effort to define APIs and systems specifications for media provenance across the whole media ecosystem.

Gaming for public good

2020-07-28T09:06:38+00:00

On March 4th 2020, sneaking in before lockdown, BBC Technology Strategy & Architecture in partnership with BBC Academy Fusion hosted and live streamed a great Lunch & Learn event. The topic was using gaming for public good, so I was excited to attend.

The event kicked off with lunch and an opportunity to network and try things out. BBC Blue Room, BBC Research & Development, and guests SpecialEffect demonstrated the latest in games technology. Nearby, BBC Children’s game Nightfall was set up to play. Attendees included interested BBC staff, many of whom had worked in the games industry, and a number of invited guests.

Steffan Powell kicks off the event

We were welcomed by journalist and presenter Steffan Powell. Host of BBC Radio 1’s The Gaming Show and a senior reporter for Newsbeat, Steffan brought subject knowledge along with his enthusiasm and energy. He shared that in the UK video gaming revenue is worth more than music and movies combined. Half the population game. Over 3 million watch eGames. The industry has its own Bafta games awards, and that museums like the V&A have created exhibitions on video games.

The talks kicked off with Si Lumb (BBC Research & Development) and Phil Rich (BBC Digital Partners) providing a snapshot of the gaming industry, and reasons the BBC should take notice and explore gaming as a content medium.

Over the past 6 years, the time 16-25 year olds spend with video games has tripled. More than half would like a career in the industry. Over 70% of 18-35 year olds play video games, and about 46% of gamers are female.

Si Lumb and Phil Rich sharing a snapshot of the gaming industry

The market isn’t all about hardware and game titles. Gaming is increasingly something to watch as a spectator. It has bigger audiences than traditional sporting events thanks to social media, video streaming and services like Twitch. Not surprising when the average video gamer is 43 and raising children, who both play and watch video games. The multi-player social game popular with younger audiences, Fortnite, had a total prize pool of $100,000,000 in 2019, and Netflix consider Fortnite a major competitor for audience time. British eSports are trialling tournaments in schools. And as Si eloquently positioned it, “Strictly Come Dancing is just Battle Royale in sequins”.

Technology improvement enables high quality games to optimise as smaller file sizes, similar to video clips. MS XBox, Amazon and Google are taking gaming into the cloud. Interactive and object-based media add into the mix. While Virtual or Augmented Reality provide more immersive experiences or deep fakes as actors in film or television. Further industry convergence has seen Unreal, a gaming engine, used to flood the Weather Channel studios, build the virtual world in which The Lion King remake was filmed, and create locations and scenery for The Mandalorian TV series.

Match of the Day using green screen in a highly adaptable virtual studio

Augmented reality, interactive video and deep fakes are of interest to the BBC, as are eSports qualifications, Minecraft for educational purposes, innovations addressing physical and mental health issues, providing accessible social interaction... the list goes on. From Newsbeat reports, to its documentary on Hideo Kojima. From This Game Changed My Life podcast, to The Game Show on Radio 1. From experimental content like interactive Casualty and a virtual Queen Vic or Tardis, to Nightfall the game. There’s a lot to gaming, and the BBC is taking notice and exploring.

Recently the BBC Children’s Games team launched Nightfall, their first multiplayer online game for children. Ashleigh Middleton and James Woodham presented the rationale and strategy behind the game.

James Woodham and Ashleigh Middleton presenting Nightfall

Nightfall is set in a dream world, where players are battling anxieties and fears. Players can explore freely and use the light from their torch to extract negativity from the nightmares they encounter. However, they need to collaborate with other players in order to deal with the biggest nightmares. The community of players feedback on what the nightmares should be and how the characters should look. Contracted companies Good Boy and Mira do the game development and artwork.

Aware that games are very popular with children, the team wanted to explore where the audience are. Part of the BBC’s mission “to act in the public interest” is to entertain. For children this can be done within games. The team want to create games that provide a safe, social, collaborative space, live in real time. The games can also take an informative and ethical stance as they are non-commercial. There are no ad purchases. No chatting with strangers. And kids can play with their friends.

For example, Nightfall can introduce temporary branded zones within the game. The first of these is a Blue Planet zone. The zone should help grow the audience and provide marketing opportunity. It also directly addresses known concerns and worries of the audience.

Screenshot as Nightfall introduces the Blue Planet zone

Nightfall and the Blue Planet zone within it are live and proving popular. Other partnerships are being prepared and will go live soon. There are plans to stage scheduled events and challenges. As well as discussions around turning off or disabling the game at night, when children should be sleeping.

The BBC is not alone in recognising the potential of games as a tool for learning and creative innovation. Stephen Reid from Immersive Minds shared inspiring stories and thoughts from their pioneering use of games and other interactive technologies to teach and educate young people.

Stephen Reid shares his enthusiasm and inspiring stories of educating through games

His own Eureka moment came after asking his class to tell him something they knew that he didn’t. One pupil knew how to slow-mo TV by holding the play button on the remote for 6 seconds. Apparently, they found out by experimenting, fearless of breaking something that could be reset or fixed. When he asked the class what this was useful for, he got a roomful of different ideas.

Stephen deduced that kids have a simple process around tools, uninhibited by experience. They identify a problem, find something that works, learn how to use it, and apply it to the problem.

Are we inspiring our students? Are we challenging kids enough, to solve real world problems for social good? In Egypt, Stephen visited a school where the classrooms and attitude were both fun and inspiring. He challenged the kids to find and solve real problems during the three months until his next visit. When he returned, one group had made a drone. They taught themselves how from the internet, including the lithium batteries. The drone was for detecting and countering an airborne plant pathogen affecting their parents rice straw crop.

A history classroom in Egypt sports a full-size stegosaurus skeleton moulding on its outer wall

Elsewhere, Stephen challenged some younger kids to build a hydro-electric power dam with Lego bricks. They learned that energy is created by turbines underneath the dam, not where the water flows over it. Then they recreated their dam in Minecraft to see it working and how weather could affect energy production. One kid worried about the fish in the river and discussed it with their father, who helped devise a solution. The next day they added a series of stepped pools at the side of the dam, so that fish could safely bypass it.

Other students were challenged to recreate a local ruin using Minecraft. They visited and measured the ruin. In the process, learning about its history and the fire that had destroyed the original building. They decided to create the full pre-fire building in Minecraft, using stone for the ruins that remained and wool painted like stone elsewhere. Then they recreated and watched the fire in Minecraft, and 3D-printed their version of the ruin.

Creative games like Minecraft can provide a much richer learning experience. Students could recreate Pompeii, Monet’s studio, world wonders, and more. They can build using bricks or learn and only use code.

In Africa, in a poor area that is lucky to get 3 hours of electricity in a day, Stephen met a man on the street showing kids how to create things from refuse. He provided a laptop and 3D-printer with a few supplies, then showed the man how to use it, along with tinkerCAD and Minecraft. The kids designed and printed small low-cost toys to sell in the city, and over a few months managed to raise enough money to build a school. Yet in the UK 3D-printers languish in school cupboards because no-one knows how to work them.

Stephen’s not short list of games that can be used for educational purposes

Second generation gamers don’t settle for what is given by the developers. They want to modify and hack the game, similar to the early simple gamers of the 70s and 80s.

Little Big Planet can be used for climate change game creation. Assassins Creed and Age of Empire can be used to teach history. Democracy can be used to teach politics. Kerbal Space Program can be used to teach rocket building. Ark can be used to teach about dinosaurs, food chains and ecology systems. Universe Sandbox can be used to teach about the effect of small changes. Riven can be used for teaching languages and number systems. Portal can teach physics. Valiant Hearts can teach about war from a dog’s point of view. Drone can teach about modern warfare and ethics. Interland can teach about internet and data safety. Life Is Strange looks at mental health, depression, culture, and immigration. A Normal Lost Phone covers alcoholism, refugees and more.

And this is only getting started with how games and interactive technology can be used for learning and education.

It’s also important to ensure everyone can participate. Tom Donegan from SpecialEffect spoke about the life-changing impact of making games and technology accessible and inclusive for people with severe disabilities.

Tom Donegan explains the positive impact of making gaming accessible to all

SpecialEffect started out trying to provide access for the physically disabled to play games, initially for educational purposes. While the work is led by an occupational therapist approach, they have found that access to games has a wider impact. Games connect a player socially when they’re unable to do other activities. Games give some independence and sense of achievement, provide a release and are something to look forward to. To some extent, video games level the playing field when playing with others.

Gaming can open doors to enjoyment, creativity and social connection that would otherwise be closed

Sometimes adaptations are as simple as providing a joystick or a couple of suitably large buttons. Other times it requires highly complex multi-modal personalised controls such as an eye-brow switch combined with eye-tracking and voice commands. The recent XBox Adaptive Controller helps simplify creating such custom set-ups.

SpecialEffect also do much collaboration, research and design to develop custom control hardware, such as improved Eye Gaze technology, and interfaces for using it. And the costs are significantly reducing, which also improves accessibility.

The event wrapped up with a panel conversation chaired by Steffan Powell. Discussing the significance of “gaming for the public good” were:

Dr Maria Stukoff – Director of the Salford University Maker Space and Co-Chair of eSports Industry Collaboration,
Stephen Reid – Founder and Director of Immersive Minds and Creative Consultant with Microsoft Education, who had previously spoken about his work during the event,
Jordan Erica Webber – a freelance presenter and journalist who is the resident gaming expert for Channel 5’s The Gadget Show and co-author of Ten Things Video Games Can Teach Us: (about life, philosophy and everything),
Elle Osili-Wood – an award-winning video game presenter and journalist, named as one of the most influential women in gaming.

Steffan chairing the panel on gaming for public good at the BBC

Steffan kicked off by asking about their perceived attitude of the BBC in regards to gaming. Jordan wishes BBC departments would talk with each other more, to move beyond the basics of what video games are and how they are not damaging children. Elle is working on several BBC projects about the artistic, scientific benefits and technology aspects of games, and would like more stakeholders to move past the concept of games being juvenile or insignificant. Maria described games as content-rich immersive storytelling not dissimilar to TV dramas or documentaries and would love to see the BBC have its own Twitch channel. Education works well by doing and problem solving, and it’s surprising the BBC isn’t already doing more. Stephen meets similar attitudes in education with teachers, who would love the BBC to add some weight to the positive side of games and speed up the needed change in attitude, so that conversations no longer start on the back foot.

The next question was about trends. Elle, an editor for PlayStation’s YouTube channel, recently helped create a 12-episode professionally edited series of playing a game, based around the challenges. Jordan highlighted that online content for audiences has been around for some time and is becoming more professional and interactive with the audience. Maria shared that Fortnite’s best player Ninja has 231 million hours of live-watched play, ratings competitive with the top sports and Netflix shows. She also pointed out that XR (extended reality) will change the gaming and eSports environment to be even more immersive in significant ways. Jordan pointed out that the BBC could add quality control to eSports production that YouTube doesn’t or could learn from. Stephen shared that 84m people in US will watch eSports by 2021, almost as much as NFL, so eSports is definitely a big trend.

When asked what the BBC could do differently in the gaming space, Stephen jumped on education as a key area that isn’t being addressed yet, in particular supporting teachers. Elle shared how games improve literacy, social and communication skills, can improve physical fitness, emotional regulation, and help with conditions like ADHD and Dyslexia, and that there are numerous scientific studies proving all that. Stephen pointed out that gaming is play based learning, though it has become digital, and we need to advocate more for play.

Asked if there is room for more representation on TV, there was a resounding yes. Elle pointed out that online and gaming is now more mainstream than TV. Jordan shared that suitable content formats are needed for TV, such as documentary, as daily news on eSports has too slow a turnaround. Maria pointed out the need for regulatory shaping and normalising of gaming as content.

Asked if the BBC should make games, as they did 20 years ago, again there was a resounding yes. The Hitchhiker’s text adventure game was fondly remembered.

Asked about their opinion on the balance between play and education in games, Stephen shared insights from a recent 3-year study on games for learning Maths, where the kids hacked the game to do what they wanted. Kids recognise enforced learning. Environment, mechanics and narrative all matter. Elle emphasised the importance to work with people with experience as storytellers, writers and researchers.

Final thoughts hoped the BBC would become more proactive than reactive in regard to gaming, with more around the stories and art of games, content no one else would create. Steffan shared that more is happening, and Stephen mentioned BBC Build-it Scotland, that recreated the country 1:1 in Minecraft, and got over 10,000 responses to build local places.

With more time afterward to check out Nightfall and the latest in games technology, there was plenty to talk about as the event wrapped up. Hopefully this is just the beginning of much more to follow.

Find out more and stay tuned for further updates at: https://canvas-story.bbcrewind.co.uk/gaming-for-the-public-good/

Me, you and the machine

2020-07-20T09:24:37+00:00

We’re relying on a wide set of actions and tools to help us deal with the current pandemic. The BBC is playing its part to inform, educate and entertain. And for us and others, digital technologies are playing a key role. In this blogpost, I discuss the BBC’s approach to one of most important set of digital tools: 'machine learning'.

The term machine learning (ML) covers a range of computer systems which learn from experience. With Covid-19, we know ML techniques are being used for contact mapping and predicting the effectiveness of drugs.

One reason ML is being deployed here is that it is being deployed everywhere. Tools that can be trained on vast data sets and learn and improve as a result are behind social media feeds, computer vision and robotics, financial and weather models, and of course the improved machine translation and voice recognition systems that many of us use every day.

Many of these areas are directly relevant to the BBC and its day-to-day operations. The Design and Engineering division I lead has been looking at them closely for some time, exploring ways in which machine learning can help us to enhance what the BBC offers our audiences.

We believe that ML can help us respond to audience expectations, especially from ‘digital native’ younger audiences. A key area is content discovery and recommendations. Audiences no longer accept having to put significant effort into searching for what they want. They want a personalised offer, which feels both relevant and fresh – something ML can help us to provide.

And ML can help us innovate. There is potential to transform the ways we make programmes, the way we run as a business, and of course the ways we do our journalism. Examples include speeding up video compression or finding ways of detecting and flagging disinformation.

It's not surprising that we should be looking at ML in this way: the BBC has always worked with new technologies to offer the best user experience we can. This is why we created iPlayer and Sounds, and developed approaches like our Global Experience Language (GEL), the BBC’s shared design framework. As ML has developed, we have started to explore how to use the technologies responsibly and efficiently. We have also developed a set of principles governing our deployment of ML technologies.

I want to be clear about where our ambitions lie. We are not Microsoft, Google or Baidu. We don't have their amounts of data, money or computing power. We are not aiming to compete with them by developing our own machine learning frameworks, or performing advanced research in novel algorithms.

But the BBC is a fertile environment for applying ML techniques. We have unique types of problems to solve, and we have the ability as an organisation to draw from almost one hundred years of experience in storytelling. We are ambitious in the desire to explore the positive impact of applying ML to our operations.

What does this mean in practice?

The first thing we think through is whether a ML solution is needed. We then assess the benefits of each application to both individuals and society. An example would be designing the BBC’s content recommendation engines to broaden our audience’s horizons. This is because we think there is both individual and public value in discovering new perspectives, music or experiences – not simply finding more of the same.

We also ensure that we use our resources efficiently. ML requires a solid data platform and a consistent and modern approach to experimentation across our portfolio of products and services. It is important to maintain a central and coordinated approach so that, as an organisation, we can deploy scarce capability in the most effective way and optimise on learning quickly.

We pair our Machine Learning capabilities with human judgement and diversity of experience. This applies both from a technology development perspective - where we bring together technical experts (e.g. data scientists, UX designers, product specialists) with editorial, policy, legal and R&D colleagues, and in terms of our audience experience - where the BBC’s automated curation will sit alongside human curation.

Finally, we recognise the need for collaboration and co-operation with other industries and organisations in maturing our approach with ML. Collaborations which allow media and technology companies to bring their expertise together in the public good will create more powerful experiences than anything we can do alone.

Machine learning has enormous potential to transform not just the BBC but every other organisation. I want us to use it to connect with people more effectively, to bring out the strengths of our storytelling and to find new ways of communicating our trusted journalism. I hope the power of machines will help me and my colleagues create something new, compelling and distinctively BBC for each member of our audience.

Coronavirus and tech responsibility

2020-04-22T08:57:55+00:00

As we live through the Covid-19 crisis and assess the significant changes it has brought, there’s a growing view that we may want to make some of these more permanent. Technology has been at the heart of our response with media and technology companies quickly drawing on deep reserves of innovation and ingenuity to support the biggest and most sudden societal upheaval in a generation. From tracking the virus to helping to keep us well and happy, responses have been wide-ranging and varied.

Whilst we know this can never be an exhaustive process, we are tracking some of these and logging them over the course of the crisis and musing on what we might learn and take on into the era post lockdown. We’ve looked at this under the BBC’s three tenets of informing, educating and entertaining, and while we’re aware of the significant amount of work being done inside the corporation we've focused mainly on what we’ve learned from outside.

In the information field we’ve seen social media companies and others make active attempts to remove Covid-19 misinformation or alert users to false claims. Facebook has used overlays to highlight fake news posts. Twitter has removed tweets from politicians and even world leaders while WhatsApp are limiting message spread to try to limit the dissemination of fake stories. NewsGuard and BT partnered with DCMS to raise awareness of a free tool to help the UK public identify fake news and learn about the dangers of COVID-19 misinformation. Other tech companies are reportedly working with the Cabinet Office counter-misinformation unit. Social media companies have also acted to boost trusted news & public health sources. Some have also made health advice and hyperlinks to the WHO or NHS prominent on the home screen or during advert breaks. New information tools are emerging such as thes WHO bot on WhatsApp and initiatives such as TikTok’s #SafeHands challenge. There’s been a focus on making information universally available – offering access to key services for free, for example. UK mobile networks agreed to offer ‘data free’ access to the NHS website. And with news organisations suffering because of a loss of advertising revenue, Facebook announced $100m of support via its journalism project.

In education, a vast array of online resources to help home-educators have been made available online, from fitness programmes to art instruction. Premium services such as Carol Vorderman’s maths course have been offered for free. Microsoft’s streaming service Mixer added an education category and of course the BBC’s major Bitesize initiative has offered new resources as the lockdown continues into the new school term.

There’s been a veritable entertainment bonanza with theatres and other arts providers offering free access to a wide range of content. New media formats have hit the mainstream such as ITV’s virtual Grand National (with a cycling format to follow). Live streamed concerts, talk-shows, plays and gaming have taken off - some for charitable purposes- StreamAid on Twitch for example. To date, more than 38 million people have watched Andrea Bocelli’s free online Easter concert from Milan’s Duomo. To cope with the uptick in bandwidth needed, media companies have reduced streaming quality to reduce strain on networks (Netflix, Disney+, Apple TV). Community and conferencing apps like Houseparty and Zoom have also seen huge growth and been used imaginatively to create events such as virtual choral and orchestral performances.

Separately we looked at the response to mapping the crisis itself. Amazon, Microsoft and Palantir - as well as London-based Faculty AI – are working with Government to model the healthcare response to the pandemic and provide interactive dashboards for the NHS. It is unclear to what extent UK mobile phone operators will supply user anonymous location and usage data to the Government to create movement maps, reportedly with a 12- to 24-hour delay, to discover whether the public are abiding by lockdown rules (an initiative which ICO has approved). Google and Apple announced that they would partner to develop interoperable APIs to facilitate user tracing via Bluetooth. Public Health authorities could then draw on this technology to release tracing apps: a NHS app is under development. Big questions remain about user take-up and privacy (as well as the availability of necessary testing). Meanwhile, on a local level, a Covid-19 Tech Response (CTR) group was set up to co-ordinate the supply of technology talent. They’ve brought 400 volunteers together, many of them supporting local Mutual Aid groups.

In terms of how the BBC might learn from the emerging initiatives – above and beyond the excellent work it’s doing with Bitesize and events such as the Big Night In we looked at:

Shared experiences - In isolation, more than ever, we’ve sought experiences which unite us from friendship group Zoom quizzes to remote family meals. Co-watching (finding ways to congregate around a particular TV experience, live or VOD at the same time) was a trend that the BBC's Blue Room team picked up at CES from one of the exhibitors Dabby. If we think this will be a behaviour that outlasts lockdown, should we develop co-watching/listening functionality as a way of boosting our mission of bringing the nation together?

Dialogues - The BBC has a long history in connecting communities - an excellent example being local radio phone–ins. We’ve often struggled to find the digital iteration of this with the demise of message boards, and user comments on stories can feel thin and combative. Local communities are organising via Facebook or Whatsapp groups, but could we do more to be a digital forum for community dialogue to link up volunteers, offer information on local resources and host conversations? And should we explore machine learning solutions to help with the otherwise overwhelming moderation task?

Mental Health tools - Citing WHO guidance, our own mental health content has encouraged audiences to limit time spent reading or watching news on the pandemic, which can prompt anxiety and stress. The BBC news site and app are offering curations on ‘long reads’ or more uplifting personal stories, and other news providers are separating ‘in other news’ sections or offering Covid free newsletters. What might we do in response to this?

On the other side of the coin we looked at an area where we felt caution might be needed. Data has the potential to model, limit and help solve this crisis, and urgent new public/private partnerships are springing up. The BBC could play a role in this and longer term developments. We need to weigh the trade-offs: providing trusted resources for our audiences and pulling together in a moment of national crisis versus privacy & consent issues, and the risk of compromising audience trust and our independence. Our expertise with partnerships will be tested like never before but we have much to contribute from our research and experience with privacy-preserving technologies.

Understanding public service curation: What do ‘good’ recommendations look like?

2019-12-17T13:24:25+00:00

Unless you know exactly what you’re after, finding the BBC content that is exactly right for you can be a little like looking for a needle in a haystack. Some challenges we face at the BBC are:

1. We produce a vast quantity of content, at a rough estimate, around 2000 pieces of new content a day. In terms of our ‘shop window’, we have a good number of promotional areas and slots – on homepages, in our apps, on our schedules and on our social media feeds – but simply not enough to accommodate all our content.

2. When content makes it to a prominent promotional slot, it will, of course, get good traffic, but there is no guarantee that the person for whom that content is most relevant will see it at the time. And once that content loses its place it will be hard to find, indeed, no one will know it exists unless they are armed with determination and the greatest of digital search skills.

3. Colleagues working in curation have an incredible ability to seek out the best content and ensure that it is labelled in a way that maximises its impact, but they simply can’t read, watch or listen to all of our output. There is just too much of it.

So far, so familiar.

Personalised recommendations, fuelled by the power of machine learning, are what every forward-thinking media and tech organisation is doing to put the content that audiences would most enjoy right in front of them. The BBC has automatic recommendations in Sounds , on iPlayer and on some news language services like BBC Mundo, which use strategies like content similarity, popularity and collaborative filtering.

The curatorial challenge for the BBC becomes more interesting and complex, because our guiding principles relate so strongly to delivering public service value to the audience. We cannot simply work out what would get the most clicks, and show that to our audiences (although ensuring content is attractive to our audiences is important). Instead, we are required:

To provide impartial news and information to help people understand and engage with the world around them
To support learning for people of all ages
To show the most creative, highest quality and distinctive output and services
To reflect, represent and serve the diverse communities of all of the United Kingdom’s nations and regions and, in doing so, support the creative economy across the United Kingdom
To reflect the United Kingdom, its culture and values to the world

These requirements, written into our Royal Charter are why editorial values are woven into our Machine Learning Engine Principles and why those working in machine learning work closely with editorial teams. I recently conducted a deep exploration of what public service curation means to an organisation like the BBC, so that we can begin to identify some of the signals that can help us as we build next level public service recommendations services.

Around 80 editorial staff, involved in some way with digital curation or content creation, took part in the discussion. Around 40 Design & Engineering colleagues observed those discussions, mostly those working in areas related to data science and engineering, metadata and research. Five criteria for public service curation emerged:

1. We want our content to reach and engage as large an audience as possible. We have a role in the national conversation by bringing the most important and resonant stories of the day to the attention of our audiences, as well as prioritising content, that is popular and has universal appeal for the greatest number of people. Examples of this might include content that brings people together like Strictly Come Dancing or content of global importance like Seven Worlds, One Planet, both of which have an impact on the national and cultural conversation. Popular and impactful content also represents good value for money.

2. In a seemingly contradictory move, we don’t always optimise for peak popularity. We make and promote content that aims to appeal to different audiences, groups, communities, regions and perspectives. We want to showcase content that feels personal. Take the podcast Netballers, which is about a sport with less national impact than, say, Premier League football. In terms of feeling relevant, it’s a win for women, young and BAME audiences. And it reflects an aspect of British culture. By its nature, it doesn’t get as many downloads as the Peter Crouch podcast, but it serves to inform and entertain those with a passion for netball.

3. We strive always to bring audiences something new - newly released music, new writers, new presenters, untold stories, news about events and stories of national significance, information about emerging technologies, research, discoveries, perspectives, major drama series, ways of storytelling. This quest for the new is the kindling that starts the national and cultural conversation in the first place. The BBC produces a lot of this type of content, but it is not easily identified by engines which are based on collaborative filtering alone*.

4. We provide useful, helpful, practical information, explainers and fact checks, which makes us a trusted source of information: that could be a news story, or revision notes for a Chemistry GCSE, or recipes for a quick mid-week meal, or sports results.

5. We have enormous breadth and depth which means that there is something for everyone: there is variety by topic, tone, format, duration, location, level of expertise and age suitability and relevance.

Our long term ambition is to use this thinking to build recommendation systems which can broaden our audience’s horizons, providing different perspectives and stories and experiences that they might not otherwise have come across. But this is complex - and a recommender that can effectively deal with as multi-faceted an editorial issue as impartiality is extremely challenging and will take significant time to develop.

For now, curation in the context of our recommenders involves upholding our editorial values and finding ways to surface the most relevant and compelling content for each user. All the content the BBC makes for our UK audiences, one way or another, is public service, so our recommendations will of course always have a public service flavour.

I’m excited that we have already built models with business rules about increasing breadth (in the Sounds recommender) and depth (in the World Service recommenders), and as well as reflecting editorial values around sensitivity. For example, on the Sport recommender, due for release next year, we’ve taken the curatorial decision that content from rival teams will not be shown together in a set of recommendations.

We can learn so much about public service by sharing the editorial point of view as we iterate and refine our approach. I’ll be working in collaboration with editorial colleagues and data scientists to ensure these public service curation criteria inform the BBC’s future recommendations engines.

Lastly, we also recognise that the power of machine learning - of which recommendations is a part - can only get us so far. Machines cannot understand all the subtleties, complexities and nuance of editorial decision making. An algorithm will have trouble identifying what is entertaining or fresh or authentic without significant human assistance. A machine can help only up to a point to accurately tag content in a metadata system before a human verifies the machine’s choices and hits ‘publish’.

So at the BBC, we’ll be maintaining a human hand in content creation and discovery. We need both humans and machines to best serve our audiences; editorial colleagues are highly skilled at making and promoting our content and machines can help amplify those skills. More and more, what recommendations can do is help locate the needle in the haystack in the first place - and exactly the right needle for you.

*Which is why we have built a factorisation machine for our Sounds recommender which combines collaborative filtering with content matching. For more detail see Developing personalised recommendation systems at the BBC.

Leveraging the Tor Network to circumvent blocking of BBC News content

2019-10-30T08:18:33+00:00

BBC News and Tor logos

The BBC World Service's news content became available on the Tor network last week in a move that attracted wide media attention.

The decision to go ahead with setting this service up came at a time when BBC News is either blocked or restricted in several parts of the world.

For example, in Egypt, Iran and China, our audiences are finding it either impossible or difficult to access our content without the use of a circumvention tool, such as a VPN.

The Tor network is an overlay network on the internet, which provides increased security and is resistant to blocking.

The BBC is not the first leading organisation to have a direct presence on the Tor network. Facebook has been there since 2014; the implementation of the social media platform on the network was built by Facebook engineer Alec Muffett, who later left Facebook and subsequently assisted the New York Times in setting up their own Tor site.

As a result of his experiences, Alec created the Enterprise Onion Toolkit (EOTK), which makes it easier for any organisation to set themselves up on the Tor Network.

With help from the BBC Online Technology Group, Alec prototyped a solution based on the EOTK for the BBC World Service. The BBC has an unusually complex domain name configuration, and the prototype proved that the EOTK could handle this complexity well.

The implementation for the BBC was carried out by the Open Technology Fund (OTF) and Alec continues to be a key contributor. The OTF is one of the leading Internet freedom organisations in the world, who have found prominence through funding and vetting numerous information security and internet freedom projects.

Why an Onion service?

From a technical standpoint, the Tor network is a subset of the internet we know and use every day, and is accessed by users using a modified browser. The key feature of the Tor network is that it is fully encrypted. That’s to say, it hides the location of users, and the protocol it uses is continuously updated to maintain resistance to blocking.

This explains why it is a strong solution for the problem of internet censorship and secure communications and why it is being used by a large number of journalists, bloggers and internet users who live in muzzled media environments.

Users can already access the BBC (for example https://bbc.com/persian) on the Tor Browser to circumvent blocking. The user’s connection enters the Tor Network in one country, runs through at least three servers, then exits the Tor Network to the BBC website from another country. While successful in circumventing blocking, this route is exposed to censors who might monitor activity on the last exit server, which is unencrypted, or even tamper with it.

An alternative, called an Onion service, uses the Tor Network’s own address scheme where domain names end with “.onion”. In this case, traffic is directed to a dedicated node on the Tor Network for that service.

This allows the traffic between the Tor Network and the content provider to travel a trustworthy path. This also removes the risk associated with exit nodes.

An additional benefit is that the routing within the Tor Network is simplified when using an Onion service. This provides a much higher performance, which is especially noticeable when watching video.

The Tor Browser is available for Windows, MacBook and Linux computers, as well as Android phones. Alternative browsers, such as Brave or the Onion Browser (for iPhones) can also be used. These browsers can be used for both .onion and classic URLs.

The BBC homepage, with a URL accessed through the Tor network.

Is there different BBC content on the Tor network?

The BBC content on the Tor network is not different from that which is accessible to our international audiences under normal conditions.

The experience is similar to being in Ireland or the East Coast in the USA for example. Users will be able to access World Service radio, TV and websites in over 40 languages, as well as the news in English.

Content which is not available internationally, such as BBC iPlayer, will continue to be unavailable on the BBC Onion service. Users within the UK appear as international users when they use the BBC Onion service.

Technical risks

An aspect of setting up an Onion service for the BBC was the question of whether technical BBC assets will be placed on the Tor Network or whether the Onion service needs to be technically trusted by the BBC in any way.

Onion services are https-based and therefore do require their own server certificates and the certificate for the BBC Onion domain is separate from other BBC certificates. This allows users to trust that they are actually reaching BBC content.

The Onion service has to rewrite all of the URLs in order to make the BBC site work inside the Tor Network. It is therefore essential that the Onion service is operated securely and by a trusted team.

The work done by the EOTK platform does not involve placing any BBC assets on the Tor network itself. Neither does it need to be provisioned with any passwords or certificates to access BBC systems. To the BBC, it appears like a normal group of international users.

Content on the Tor network is therefore proxied through the Onion service and there is no additional web hosting commitment.

The BBC's duty of care

Some countries, such as Russia, China and the UAE, have passed laws to regulate the sale and distribution of tools such as VPNs.

For example, the UAE prohibits the use of VPNs to access illegal content. However, BBC content is not illegal in the UAE.

The promotion of the Onion site by the different BBC services will include clear warnings that users should be aware of their legal environments and should not use it if it might put them or those close to them under any risk or danger.

Information controls then and now

Controls placed by governments on access to information and trusted news are not new at all.

During the Cold War, some governments used to jam the shortwave radio broadcasts of the BBC World Service to stop their populations from listening to BBC. Then, the BBC circumvented these measures by providing new frequencies or changing frequency values to confuse jammers.

These controls are now moving on to the internet. At a time when internet freedom has been declining consistently and online information controls are growing, the BBC World Service continues to pursue its mission by providing an additional online news presence on the Tor Network.

The BBC News Onion site can be accessed at https://www.bbcnewsd73hkzno2ini43t4gblxvycyac5aw4gnv7t2rccijh7745uqd.onion (Link updated October 2021)

Scaling responsible machine learning at the BBC

2019-10-04T09:32:44+00:00

Machine learning is a set of techniques where computers can ‘solve’ problems without being explicitly programmed with all the steps to solve the problem, within the parameters set and controlled by data scientists working in partnership with editorial colleagues.

The BBC currently uses machine learning in a range of ways – for example to provide users with personalised content recommendations, to help it understand what is in its vast archive, and to help transcribe the many hours of content we produce. And in the future, we expect that machine learning will become an ever more important tool to help the BBC create great audience experiences.

The BBC was founded in 1922 in order to inform, educate and entertain the public. And we take that purpose very seriously. We are governed by our Royal Charter and public service is at the heart of everything we do. This means that we act on behalf of our audience by giving them agency and that our organisation exists in order to serve individuals and society as a whole rather than a small set of stakeholders.

With Machine Learning becoming a more prevalent aspect of everyday life, our commitment to audience agency is reflected in this area as well. And so in 2017, we submitted a written commitment to the House of Lords Select Committee on Artificial Intelligence in which we promised to be leading the way in terms of responsible use of all AI technologies, including machine learning.

But what does this mean in practice?

For the last couple of months, we have been bringing together colleagues from editorial, operational privacy, policy, research and development, legal and data science teams in order to discuss what guidance and governance is necessary to ensure our machine learning work is in line with that commitment.

Together, we agreed that the BBC’s machine learning engines will support public service outcomes (i.e. to inform, educate and entertain) and empower our audiences.

This statement then led to a set of BBC Machine Learning Principles:

The BBC’s Values

1. The BBC’s ML engines will reflect the values of our organisation; upholding trust, putting audiences at the heart of everything we do, celebrating diversity, delivering quality and value for money and boosting creativity.

Our Audiences

2. Our audiences create the data which fuels some of the BBC’s ML engines, alongside BBC data. We hold audience-created data on their behalf, and use it to improve their experiences with the BBC.

3. Audiences have a right to know what we are doing with their data. We will explain, in plain English, what data we collect and how this is being used, for example in personalisation and recommendations.

Responsible Development of Technology

4. The BBC takes full responsibility for the functioning of our ML engines (in house and third party). Through regular documentation, monitoring and review, we will ensure that data is handled securely. And that our algorithms serve our audiences equally and fairly, so that the full breadth of the BBC is available to everyone.

5. Where ML engines surface content, outcomes are compliant with the BBC’s editorial values (and where relevant as set out in our editorial guidelines). We will also seek to broaden, rather than narrow, our audience’s horizons.

6. ML is an evolving set of technologies, where the BBC continues to innovate and experiment. Algorithms form only part of the content discovery process for our audiences, and sit alongside (human) editorial curation.

These principles are supported by a checklist that gives practitioners concrete questions to ask themselves throughout a machine learning project. These questions are not formulated as a governance framework that needs to be ticked off, but instead aim to help teams building machine learning engines to really think about the consequences of their work. Teams can reflect on the purpose of their algorithms; the sources of their data; our editorial values; how they trained and tested the model; how the models will be monitored throughout their lifecycle and their approaches to security and privacy and other legals questions.

While we expect our six principles to remain pretty consistent, the checklist will have to evolve as the BBC develops its machine learning capabilities over time.

The Datalab team is currently testing this approach as they build the BBC’s first in-house recommender systems, which will offer a more personalised experience for BBC Sport and BBC Sounds. We also hope to improve the recommendations for other products and content areas in the future. We know that this framework will only be impactful if it is easy to use and can fit into the workflows of the teams building machine learning products.

The BBC believes there are huge benefits to being transparent about how we’re using Machine Learning technologies. We want to communicate to our audiences how we’re using their data and why. We want to demystify machine learning. And we want to lead the way on a responsible approach. These factors are not only essential in building quality ML systems, but also in retaining the trust of our audiences.

This is only the beginning. As a public service, we are ultimately accountable to the public and so are keen to hear what you think of the above.

Music Memories and Memory Radio

2019-09-25T09:16:31+00:00

As part of BBC Music Day we are expanding the Music Memories tool, including content for ageing BAME communities living with dementia. We are also launching a Memory Radio service designed by, and for, people living with dementia.

In 2018 I wrote about the launch of BBC Music Memories - a free, globally available website to help people with dementia reconnect with their most powerful memories by finding music from their past, and creating a playlist of personally meaningful music.

Since the initial launch, the BBC has helped bring together more than 100 organisations with an interest in dementia and music, and as a result, during the week of BBC Music Day 2019 (26th September) more than 800 music and dementia events will be taking place around the UK.

On BBC Music Day 2019, we are launching an enhanced version of BBC Music Memories which now includes three new categories of music: In addition to the Popular, Classical and Theme Tunes categories, we have added UK Regional Music, which offers traditional songs from England, Northern Ireland, Wales and Scotland; International Music which offers songs from the 20 countries with the largest ageing immigrant populations living in the UK; and Social Music, which includes nursery rhymes, football songs, pub songs, scout and brownie songs as well as music from the major religions.

People can submit their playlists to the BBC using our anonymous survey. This data will help researchers in music and dementia help others to make recommendations that will help others find their own personally memorable music.

The BBC Music Library team, along with colleagues from around the BBC managed to find hundreds of new tracks in each of the new categories. We hope that there is now some music that will mean something to everyone, regardless of where they are from.

As before, in order to make this service free and globally available, for copyright reasons we have only been able to include 30 seconds of each popular track or 60 seconds for classical music. Once an initial playlist has been created on BBC Music Memories, we would encourage people to use other music services or stores to get hold of the full-length tracks.

We have also launched Memory Radio - three longer-form music and archive-based programmes made specifically for people with dementia, and designed in consultation with people with dementia and professional carers.

There is one Memory Radio show for each of the 1940’s, 1950’s and 1960’s. Each show starts at the beginning of the decade, offering a mixture of music, news archive and popular radio programmes from that year, and then moves forward through the decade.

The programmes might sound a little different to a ‘normal’ radio programme: the pace is deliberately slow and has a consistent level of energy; there are long pauses between each section; and we try to avoid speech over a music track to optimise the clarity of the spoken word. There are small, simple quizzes included in the programmes, and each programme is accompanied by a downloadable Index and Activity Guide which is designed to be used by carers in a family or care home environment to stimulate conversation and reminiscence.

Memory Radio is available on the Music Memories website, on BBC Sounds and on Alexa voice assistants.

Background
If you didn’t read the original blog post from 2018, I’ll describe again some of the thinking and theory behind music and dementia.

Music and Memory

Evidence shows that music can help people with dementia to feel and live better, and we wanted to build on the success of the award-winning BBC Reminiscence Archive, using content from the BBC’s archives to help improve the lives of people with dementia.

The thinking behind BBC Music Memories is quite simple, and is based on the principle of the ‘reminiscence bump’ - people tend to recall more from their adolescence and early adulthood - and the phenomenon that structures of the brain that process music can remain intact when other cognitive functions deteriorate.

Musical Reminiscence

Reminiscence work - the recalling and sharing of life events - is increasingly being used to help people with dementia have meaningful conversations with family and carers, and increase their wellbeing and quality of life. Such conversations can be beneficial for both the person with dementia and the families and carers around them.

BBC Music Memories helps people with dementia to find personally meaningful music - perhaps the tracks they listened to as a teenager or in early adulthood - and create a ‘playlist’ of their favourites, to be used as a starting point for reminiscence. We hope that BBC Music Memories will also be used in a family setting, perhaps with a grandparent and grandchild taking it in turns to find their own personally memorable music, and talking about the tracks and the memories that accompany them.

What happens next?

We are planning some research in to how Music Memories and Memory Radio are used by people with dementia, their families and carers, and will use any insights to improve and add to the service in 2020.

BBC Music Day

BBC Music Day is the annual celebration of the power of music to change lives with events and broadcasts across the week of 26 September. The theme this year is music and wellbeing. As part of this, music legend Nile Rodgers is the Ambassador for an unprecedented collaboration that brings together 85 organisations including Alzheimer’s Society, Alzheimer Scotland, Age UK, Playlist for Life and the NHS, to help bring music to everyone with dementia in the UK by 2020. The initiative has inspired over 800 events across the UK, from pop-up nightclubs and raves at care homes to intergenerational singing sessions, all celebrating the power of music to change lives.

Across the week of BBC Music Day, over 2,000 events in total will take place celebrating music and wellbeing, including pop up performances, interviews, musical takeovers and short films by artists including Craig David, Ed Sheeran, Lewis Capaldi, Liam Gallagher, Anne-Marie, Guy Garvey, Professor Green, Ray BLK, Keane, Naughty Boy, Nina Nesbitt and more.

Navigating the data ecosystem technology landscape

2019-09-03T12:46:36+00:00

Credit: Jasmine Cox

Want to message your Facebook friends on Twitter? Move your purchased music from iTunes to Amazon? Get Netflix recommendations based on your iPlayer history? Well, currently you can’t.

Many organisations are built on data, but the vast majority of the leading players in this market are structured as vertically integrated walled gardens, with few (if any) meaningful interfaces to any outside services. There are a great number of reasons for this, but regardless of whether they are intentional or technological happenstance (or a mixture of both), there is a rapidly growing movement of GDPR supercharged technologists who are putting forward decentralised and open alternatives to the data-moated household names of today. For the BBC in particular, these new ways of approaching data are well aligned with our public service ethos and commitment to treating data in the most ethical way possible.

Refining how the BBC uses data, both personal and public, is critical if we are to create a truly personalised BBC in the near term and essential if we want to remain relevant in the coming decades. Our Chief Technology and Product Officer Matthew Postgate recently spoke about the BBC’s role within data-led services, in which he outlined some of the work we have been doing in this respect to ensure the BBC and other public service organisations are not absent from new and emerging data economies.

Alongside focused technical research projects like the BBC Box, we have been mapping the emerging players, technologies and data ecosystems to further inform the BBC’s potential role in this emerging landscape. Our view is that such an ecosystem is made up of the following core capabilities: Identity, data management (storage, access, and processing), data semantics and the developer experience, which are currently handled wholesale in traditional vertical services. A first step for us is hence to ascertain which of these core capabilities can realistically be deployed in a federated, decentralised future, and which implementations currently exist to practically facilitate this.

Identity, a crucial component of the data ecosystem, proves who users say they are providing a true digital identity. Furthermore we expect standard account features such as authentication and sharing options via unique access token that could enable users to get insights or to share data to be part of any offering. We found that identity, in the context of proving a user’s identity, was not provided by any of the solutions we investigated. Standard account features were present, ranging from platform specific implementations, to decentralised identifier approaches via WebID, and blockchain based distributed ledger approaches. As we strongly believe it is important to prove a user is who they say they are, at this point we would look to integrate solutions that specialise in this domain.

Data management can be further broken down into 3 areas:

Data usage and access, involves providing integration of data sources with an associated permission and authorisation model. Users should have complete governance of their data and usage by data services. Strong data security controls and progressive disclosure of data are key here. Given our investigation is based around personal data stores (PDS) and time series sensor/IoT device data platforms to capture personal, public and open data, providing access and controls around sharing of data was a fundamental capability of all offerings. All of them provided significant granularity and transparency to the users about what data is being stored, its source and usage by external services.
Data storage must provide high protection guarantees of users’ data, encrypted in transit and at rest, giving users complete control and transparency of data lifecycle management. Again, this is a fundamental requirement, such that storage is either a core offering of any platform or outsourced to external services that store data in strongly encrypted formats.
Data processing mechanisms to allow users to bring “algorithms” to their data, combined with a strong contract based exchange of data. Users are in control and understand what insights algorithms and services derive from their data. These might include aspects such as the creation of reports, creation and execution of machine learning models, other capabilities that reinforce the user’s control over how their personal data is used for generated insights. Through contract and authorisation based approaches users have complete audit trails of any processing performed which provides transparency of how data is utilised by services, whilst continuously being able to detect suspicious or unauthorised data access. Our investigations found that processing of data is either through providing SDKs that heavily specify the workflow for data processing, or no provisioning at all, leaving it to developers to create their own solution.

Data model and semantics refers to mechanisms that describe (schemas, ontologies) and maintain the data domains inside of the ecosystem, which is essential to provide extensibility and interoperability. Our investigations found this being approached in a wide spectrum from:

no provision requiring developers to come to conclusions about the best way to proceed
using open standards such as schema.org and modeling data around linked data and RDF
completely proprietary definitions around schemas within the system.

Finally the developer experience is key. It requires a set of software development tools to enable engineers to develop features and experiences as well as being able to implement unique value propositions required by services. This is the strongest and most consistent area across all our findings.

In summary our investigations have shown that there is no one solution that provides all of our identified and required capabilities. Crucially the majority of the explored end user solutions are still commercially orientated, such that they either make money from subscribers or through associated services.

So with the number of start-ups, software projects and standards that meet these capabilities snowballing, where might the BBC fit into this increasingly crowded new world?

We believe that the BBC has a role to play in all of these capabilities and that it would enhance our existing public service offering: to inform, educate and entertain. A healthy ecosystem requires multiple tenants and solutions providers, all adhering to core values such as transparency, interoperability and extensibility. Only then will users be able to freely and independently move or share their data between providers which would enable purposeful collaboration and fair competition toward delivering value to audiences, society and industry.

The BBC was incorporated at the dawn of the radio era to counteract the unbridled free-for-all that often comes with any disruptive technology, and its remit to shape standards and practices for the good of the UK and its population stands today as it did in 1927. With a scale, reach and purpose that is unique to the BBC, it is strongly congruent with our public service duty to help drive policy, standards and access rights to ensure that the riches on offer in these new ecosystems are not coopted solely for the downward pursuit of profit, and remain accessible for the benefit of all.

Looking at the BBC's role in data-led services

2019-06-19T08:20:47+00:00

It’s been a busy time in my team over the last few months – with updates to BBC Sounds and iPlayer, 5G trials in Orkney (and in London), UHD trials for the FA Cup, Doctor Who launching in Virtual Reality and those teams behind the scenes that keep our broadcast and online services going day-after-day.

But one area that keeps on coming up when I’m out and about speaking at conferences, or at meetings with our partners - is the question of data – how we use it, how we share it and its potential to help us understand the world around us.

Not a week goes by without stories about data. There are negative stories, about data being used to target you with specific messages or sell you more, or leaks of personal data to third-parties. But there are also positive stories, like using big data to help reduce carbon emissions or helping the justice system work better.

This has made me think about the BBC’s role in this new ‘data economy’ – and what that should be.

How we use your data

At the BBC, we use data to make what we provide you, our viewers, listeners or readers, even better. It helps us tailor our products and services to be more about you – recommending programmes or content we think you might like, or alert you to the fact your favourite sport team has just scored (or lost a match). We also use it to ensure we’re making something for all audiences – and helps find gaps when we commission programmes and services.

But is there more that we could be doing to ensure data is used for good – that the data you give organisations is not just used for commercial gain but is used in a way that helps you and potentially your wider community? We think, potentially, yes.

That’s why we’ve started to work with teams here at the BBC and other partners on specific projects to help us identify what public service value we can bring to these new markets driven by data.

To be clear – we’re experimenting at this stage, and we will learn what works, what people might like – and what areas we think the BBC can help with, as we go along. We’re particularly interested in learning about how organisations can share data to get new insights and how people can safely move their data around. And, we know that when it comes to data, people are rightly concerned about privacy, safety and security. That’s why these trials will start small and controlled, so participants will have signed-up clear in knowing what, why and how their data is being used.

So what have we been up to?

Late last year, the DCMS published a report which looked at the potential of personal data portability to stimulate innovation and competition in the UK. It found that the ability to safely and securely move personal data around could unlock huge economic and societal gains, but that there are big practical issues (both in the way organisations share data and how consumers use it) to resolve first.

Following this, (and with DCMS, ICO and CDEI as observers), we’re involved in two controlled trials of data sharing by 25 individuals. These trials tests how it could be practicality possible to put a person in control of the data they share about themselves with other companies and what concerns this brings up.

The first trial is cross-sector, with the participants signing up to share data from a range of commercial companies – as well as the BBC. You can find out more about that here.

The second looks at bringing together data from media providers into a BBC data store (or what we’re calling internally a BBC Box) to improve people’s experiences when watching or listening to programmes. Bill has blogged about this here.

What’s next?

Over the coming months, we’ll continue looking at this area – with more experiments and closed trials.

We’ll be sharing more about what we learn – and look at what value the BBC can bring you – ensuring this market develops in a way that maximises the huge potential benefits of data and shares them as widely as possible.

I'll be in touch.

AI's hurdles to doing good

2019-03-29T09:31:29+00:00

How easy is it, really, to achieve social good with AI? The decidedly thought-provoking discussion at the recent 'BBC Machine Learning Fireside Chats presents: AI’s Hurdles to Doing Good’ was hosted by Tse Yin Lee, a senior journalist in News and Current Affairs.

The provocation...
We’ve seen AI’s use in the commercial sector explode, but what about the charity sector? There is huge room for AI to do social good, but given that charities are not traditionally at the sharp end of technology, the path is not without challenges. Is the data available to support the effort? Are there enough experts who understand not just algorithms, but the environments they’re working in? How do you even begin to check your project for ethical risks? How do smaller charities cope? How do you compete with larger companies who can pay staff significantly more?

The panel...

Julie Dodd, Director of Digital Transformation and Communication @ Parkinsons UK
Julie is Parkinson’s UK’s director of digital transformation and communications. She’s also written The New Reality, a study into how non-profit organisations can approach digital transformation and use digital technology for change. Among other things, Parkinson’s is currently working with Benevolent AI to try and identify at least three currently available medicines that can be re-purposed to address the condition and two brand new ways to treat it with new drugs.

Giselle Cory, Executive Director @ DataKind UK
DataKind is an organisation that is itself a charity whose volunteers support other charities and social enterprises, providing data science expertise and services such as exploratory analysis and prototyping. Projects they’ve worked on include helping homeless organisations identify issues people sought advice on before becoming homeless and analysing possible reasons why people progress differently in a shelter. It’s helped Global Witness to uncover potential corruption with open data and the Citizens Advice Bureau to better identify emerging social issues to support their staff training.

Michelle Eaton, Programme Manager in the Government Innovation Team - Data @ Nesta
Michelle worked with the Essex Police Force for 11 years - starting in community policing before moving on to performance analysis, and then to strategic change, where she led the Essex Centre for Data Analytics. Now she oversees Nesta’s Offices of Data Analytics programme, which helps governments reform their services, and recently wrote a blog defending the use of AI in policing.

The discourse…

Giving the panel a chance to show off, Tse posed her first question: “What’s the most exciting thing you do with AI?”

Giselle jumped in first and explained how DataKind had worked on a predictive model for a food bank to help identify people in the line of the food bank who might be in need of extra support. Exploring the topic more, Giselle was clear in stating that this model, and others like it, should exist to help advisors, and not act as the primary decision maker; relying wholly on AI-generated decisions is a dangerous game to play, especially with decisions that have deep ethical grounding.

Julie followed, explaining how they, Parkinson’s UK, have partnered with Benevolent AI to aid with the complex process of drug discovery. Their platform impressively trawls through millions of Parkinson's-related papers, looking for clues which humans may have missed. They hope to shorten the process in finding answers for new treatments to Parkinson’s.

Michelle explained how, at Nesta, they are not immediately looking to implement AI solutions to solve problems; instead, they are more focused on looking into the wider problems, from problem identification through to implementing a solution, where AI is not always the answer.

Tse then went on to ask the panel about perceptions from leadership of AI in organisations, from before the the introduction of AI to the organisation, through to implementing a fully AI-driven solution.

Continuing her earlier train of thought, Michelle highlighted how “an AI solution is not a silver bullet”. She went on to explain that a crucial part of the process is gathering data and understanding the problem space, and communicating these findings back to leadership. Only then, once you have your findings and have formed good partnerships, do you progress forward. Luckily, the leadership at Nesta was very receptive to this process.

Giselle talked next, paraphrasing the quote from Matt Velloso, “If it’s written in Python, it’s probably machine learning, if it’s written in PowerPoint, it’s probably AI”. She went on to explain that “AI as a concept is hard to hold”, and there’s lots of steps involved in getting actual AI into non-profits; there is a spectrum of ‘data maturity’ and most small non-profits are clustered towards the bottom - which is where DataKind come in to help. A lot of what they do is completely unrelated to Data Science, it’s about holding hands, creating a safe space in order to empower people to feel confident when using data. Julie explained how, in a lot of cases, for charitable organisations the culture is somewhat ready to embrace AI, but the data is not accessible. Where she has started to see success is when the focus is put on gathering the right data first, and then using it to effectively present the business case to leadership so the projects have full backing and understanding throughout the organisation. In addition, when taking on a new project, they set up a periodic review to asses ‘data maturity’ across the organisation. She added the amusing observation, made through the questionnaires, that as the staff understand the problem space more, the scores for data confidence go up, and the scores for data accessibility go down!

“How easy is it to recruit the data scientists you need?” Tse looked to the panel for answers.

Charities often can’t afford to pay market rates. Julie explained how at Parkinson's UK, even though they have over 500 people, that’s not enough - they need more to scale. The job market is currently squeezed for data roles, causing market rates to increase beyond what charities can afford to pay; they find they get candidates who either join for the love of the cause, or candidates who enjoy the flexibility that comes with working in a charity. Drawing on her experience as a police community support officer, Michelle explained how she traversed through various roles within the police and eventually came out in a rather different role, overseeing Nesta’s Data Analytics programme, and its thanks to this journey that she greatly values aptitude and attitude over skills.

Tse then talked through a list of somewhat provocative headlines negatively covering AI in healthcare and policing and asked the panel what they thought of them.

Acknowledging her bias, Michelle began by stating she’s emotionally invested in the police so it’s difficult to criticise them. Due to factors such as the police being stretched, demand rising, and the front line shrinking, the police have to look for new ways of doing things, complementary methods. These stories often miss the outcomes of projects, they miss the actual good. The positive aspects, such as doing these things to better understand threats to the public, and understanding how to protect people better, are rarely talked about. She then continued discussing how the police are making a real effort to develop these capabilities transparently and are considering all the ethical implications upfront, whilst in constant communication with experts. Julie made an interesting point that the negative headlines in healthcare have acted as the seed for more ‘grown up’ conversations about AI in healthcare - she says it grounds these concepts to reality and moves us away from the ‘AI will save us all’ and ‘AI sounds great, let’s do a thing’ mindsets.

“Do you think the sense of mission in a charity can blind them to the possible ethic problems of the way they are using data?”, Tse asked.

Any organisation dealing with vulnerable people tend to approach their cohort with a duty of care and are therefore generally cautious with these kinds of things, Giselle explained. That doesn’t mean there won’t be mistakes, she continued, there are examples of partnerships between charities and commercial sector companies which may not be entirely ethically sound. Expanding on partnerships, Michelle talked about Parkinson’s UK’s partnership with Benevolent AI and the challenges they have faced with data ownership, intellectual property, and the immaturity of legal frameworks surrounding partnerships such as these. She also expanded on the difficulties of reward - should the person's data who it was originally from be rewarded? Julie added that with charities, strong ethical frameworks are usually fundamental to the organisation so there’s less concern about misuse of data compared to the commercial sector.

The floor was then opened for questions from the crowd. We discussed Geographical differences in data ability, Giselle discussed how some areas have very strong government specialists, some have lots of highly skilled people volunteering, and some areas really struggle for non-profits. A question on using data sources in charities as a revenue generating asset was posed to the panel; Julie informed us that charities in the UK are often working together and sharing a lot, and there are rich ongoing conversations regarding how to make open data platforms; Michelle added that Nesta are looking into data trusts and data collaboratives as a way to incentivise sharing.

After a few more rounds of questions, some lovely nibbles, and a beer or two, the event drew to a close!

For more details about upcoming events, visit BBC Machine Learning Fireside Chat.

BBC Music Memories

2018-09-27T23:05:10+00:00

“The power of music to integrate and cure. . . is quite fundamental. It is the profoundest nonchemical medication." Oliver Sacks, Professor of Neurology and Psychiatry at Columbia University

Today, on BBC Music Day 2018, we are launching BBC Music Memories, a website designed to use music to help people with dementia reconnect with their most powerful memories. We are also launching a survey - integrated into the website - which aims to help discover the nation’s favourite music memories. The survey data will help researchers suggest tunes that could bring back memories for people who have developed dementia or other brain conditions.

BBC Music Memories is incredibly simple to use on PC, tablet or smartphone. It has a simple user guide along with helpful links to further dementia support resources. We worked with experts from music and dementia charities, including Playlist For Life, on the design and shape of the service.

Music and Memory

Evidence shows that music can help people with dementia to feel and live better, and we wanted to build on the success of the award-winning BBC Reminiscence Archive, using content from the BBC’s archives, to help improve the lives of people with dementia.

The thinking behind BBC Music Memories is quite simple, and is based on the principle of the ‘reminiscence bump’ - people tend to recall more from their adolescence and early adulthood - and the phenomenon that ‘whilst verbal communication and associated thought processes deteriorate in dementia, the brain structures involved in the processing of musical information often remain intact’.

Musical Reminiscence

Reminiscence work - the recalling and sharing of life events - is increasing being used to help people with dementia have meaningful conversations with family and carers, and increase their wellbeing and quality of life. Such conversations can be beneficial for both the person with dementia and the families and carers around them.

BBC Music Memories helps people with dementia to find personally meaningful music - perhaps the tracks they listened to as a teenager or in early adulthood - and create a ‘playlist’ of their favourites, to be used as a starting point for reminiscence. We hope that BBC Music Memories will be also be used in a family setting, perhaps with grandparent and grandchild taking it in turns to find their own personally memorable music, and talking about the tracks and the memories that accompany them.

The Music

Working with the BBC Music Library, we researched the most popular music from the last 100 years, and produced a list of around 120 tracks for each decade from 1920 up to the present day. Many of the earlier tracks, despite being hugely popular at the time, were pretty difficult to find, but the Music Library team did a fantastic job of tracking them down and digitising them. The BBC Photo Library also managed to find many unique images of the performers from the archives, and we have added these evocative images to the website.

We also selected the 23 most popular classical composers, and for each composer, selected their 20 most played pieces. And finally, we selected the theme tunes from 100 BBC TV and Radio shows.

In total, these add up to around 1800 clips of music that can be listened to for free, and added to a playlist. The playlist can also be printed off, and has a box where people can note down their memories related to each track.

Give it a try and share your playlist with the nation

Why not give it a try? To begin, select whether you want to browse through classical, popular music or theme tunes. Then, choose a composer or decade. When in the ‘popular’ category, within each decade you can also filter by musical genre. Add some favourites, and then share your favourites via our anonymous survey, helping researchers in to music and dementia help others to create their own playlists of personally memorable music.

BBC Music Memories is launching on September 28th as part of BBC Music Day - an annual celebration of the power of music to change lives. We hope that BBC Music Memories, in some small way, will do exactly that.

My Life, My Data, #MyTomorrow

2018-05-24T14:17:03+00:00

Tomorrow(’s World) starts today.

Personal data is one of the most important issues we’re all grappling with these days, but it can all feel so confusing and abstract that we tend to dismiss it with a mixture of 😕, 🤯, ¯\_(ツ)_/¯.

What is personal data anyhow? It’s data about you, but is it your friend, or your enemy? Often when it comes to personal data, a sense of dystopia can understandably prevail - we’re being spied on, manipulated, and our civil liberties are under threat. Meanwhile, services that collect data about us have become so useful and seemingly indispensable (and those Buzzfeed quizzes ain’t gonna do themselves).

In a world where it can often feel that things are constantly happening to us, how can we influence our own futures in a positive, active way?

It’s in this context that the General Data Protection Regulation (GDPR) kicks into effect this Friday, 25 May 2018 - and it’s a game-changer for people living in the UK and Europe when it comes to their rights to privacy in the digital age and what they can actively do with data about themselves.

To help audiences explore the implications of this monumental intervention, Tomorrow’s World is launching “My Life, My Data, #MyTomorrow”, a campaign about people and communities shaping the future by taking control of the data they create. The campaign starts today and runs for the following week.

Using short films, interactive experiences, and conversations across social media, Tomorrow's World will help explain just how exciting and important personal data is.

Highlights of the “My Life, My Data, #MyTomorrow” campaign include:

“Future Values, or A Short Ride in an Intelligent Machine” Data about you is helping drive the development of artificial intelligence. “Future Values, or A Short Ride in an Intelligent Machine” which launches today on BBC Taster, will send you into a “what if?” future built atop your own data. You’ll exchange banter with the artificial intelligence behind a driverless taxi, and discover the guiding principles that make up your own deepest values. Experience “Future Values, or A Short Ride in an Intelligent Machine". Read more about Charisma.ai, the cutting edge conversational storytelling technology behind this pilot.

“My Life, My Data” A short film (5 minutes) hosted by Leila Johnston and Alex Lathbridge takes us on a fast-paced journey to explore what is personal data and how is it currently used. Brought to life with animations by Jamie Squire, the short film reminds us of the quid pro quo that comes with access digital services such as Facebook, Google and Instagram: nothing comes for free. View here.

“Instagram Chatbot” To illustrate the power of data about you and how it is driving the development of machine learning, our “Instagram Chatbot" will analyse your next Instagram post and compare it with thousands of others to estimate how people will react to it. The chatbot will then create a unique, personalised short video explaining why and to illustrate the power of personal data. Try it here.

“Donate Your Data Day” A short film (10 minutes) that imagines a not-to-distant future where we can donate data about ourselves en masse, using a click-to-donate button on our mobile phones. Galvanised around a gently satirical global 'Donate Your Data Day', the audience can decide what data to donate and who to donate it to, showing their support by becoming a data donor with their own Data Donor Card. View here.

Tomorrows World presenters Leila Johnston and Alex Lathbridge

“Meet the Personal Data Superheroes” A special episode of the Tomorrow’s World podcast explores the work of people making a difference when it comes to our data rights. Meanwhile, on social media, BBC presenters, journalists, and influencers - including Radio 1 Newsbeat’s Tina Daheley, CBBC’s Katie Thistleton and BBC Click’s Spencer Kelly - discuss the importance of the data we're creating everyday. Listen here.

"How Do You Feel About Your Data? A Survey" - a timely research project from Tomorrow's World partners The Open University, on their new nQuire citizen science platform. How much personal information are you happy to share? What should companies be allowed to do with the data you create? Audiences can contribute to this short survey and give their views on data protection. View here.

The “My Life, My Data, #MyTomorrow” campaign will make you smile and think, and ask you to reconsider your preconceptions about the relationship between us, the data we create, and the companies, governments, and other organisations that use that data.

So what comes next?

This is just the beginning, and there's much more to do. People are recognising their rights and starting to take greater control of the data they create. They are actively helping create a future their grandchildren will want to live in. We can all join in.

Together, we're creating #MyTomorrow.

Read more about the Tomorrow’s World partnership between Science Museum Group, Wellcome, The Open University, the Royal Society, and the BBC.

Your data matters

2018-05-22T14:04:00+00:00

Last May, we updated everyone on our plans to make the BBC more personalised and relevant to you. We can give you more of what you love when we understand you better, and also make sure that as a public service, we make something for everyone.

We now have over 15 million people with BBC accounts using the BBC’s websites and apps in the last month. What’s more, they are also using BBC websites and apps more than people who are not signed in. 64% of BBC account users visit BBC online more than 2 days per week, compared to 46% of all users. And when they are on BBC websites and apps, people with BBC account spend an additional hour per week than people not signed in.

Your personal data is helping power this transformation. We can’t provide you with a meaningful personal or tailored experience without this information, but it is ultimately your data. And your data matters.

The General Data Protection Regulation, or GDPR for short, is coming into enforcement in the next week. It makes sure that businesses clearly explain to you why they collect your personal data, and how they use it. It is an evolution of the Data Protection Act, and gives you new and important rights.

As we’ve said before, we’ve built our new BBC account system with GDPR in mind, but we’re always reviewing our processes, technology and governance.

We use your personal data for different reasons, and it’s important we are transparent to you why we collect and use this data. Our site ‘Using The BBC’ spells out, in plain English, what we will (and importantly won’t) do with your data. It also can help you exercise your GDPR rights, such as changing some of your details in Settings.

How have we prepared for GDPR?

For starters, you should not need to be a rocket scientist to know your rights. We’ve updated our policies to make them even more transparent and clear.

What are my rights?

We’ve created a new section in Using The BBC all about GDPR to help you understand what your rights are, how you can exercise them with the BBC and get help.
We’ve also innovated and developed technology with data privacy at the heart of what we create. Below are a couple of examples of the kind of work we’ve done to prepare for GDPR.

Privacy for children

We want to help you make sure that your child can only watch programmes, read comments and upload their creations in a space that is age appropriate and suitable to them. For this reason, we’ve developed a way for parents or guardians to register their child which is simple and easy to do, but more importantly is safe and secure for the entire family. We want your children to get great experiences on BBC websites and apps, and play our part to help protect them.

Privacy by design

This little button means a lot to us.

We really want you to have a personalised experience, like picking up where you left off watching a show, getting recommendations on programmes you might like or getting notifications about your favourite football team. But you have the right to turn off these features if you don’t want them. Our analytic services team has worked hard to develop a technical solution that can do this easily, and ensure your privacy.

What’s next?

We have some fantastic events coming this summer, from the Biggest Weekend to FIFA World Cup and Wimbledon. Your data is helping us learn what you like, so we can make sure you get the best out of this summer, and improve our services for you in the future.

AI for the good of society

2018-05-21T14:45:24+00:00

Ali Shah, Head of Emerging Technology and Strategic Direction, looks at how AI might be used to create more social mobility.

I come from an immigrant family – my parents migrated to the UK from Pakistan in the 1960’s. My father started working in an engineering factory in Sheffield, and my mother worked as a housewife. Over the years they found work came and went as the economic conditions in the UK changed, and as more automation was introduced into the workplace. This meant work wasn’t always as stable as they would have liked, however they were able to take advantage of the education and healthcare provided by the public service institutions in the UK, to allow my siblings and me to study to university level. They instilled a work ethic, and sense of social responsibility in their children that has helped all of us to achieve a modicum of success in our respective fields. If my parents became labelled working class when they moved to the UK, then I think it’s fair to say that their children have moved to a more middle-class position in life. This is down to all the hard work, and sacrifices my parents had to endure, and not without a great deal of luck.

Many readers will recognise that the social group you start of in life with, and the amount of luck you have, seems to determine many of your outcomes in life. The socio-economic reasons behind this are complex – a BBC survey of the United Kingdom conducted in 2011 (and related academic analysis by Savage et al. (2013) found that there are seven different distinct social groupings in the UK – spanning familiar ones such as working class and middle class, through to elites. The difference between groups came down to the levels of economic, social and cultural capital each group possessed – with the elites having high levels of each type of capital.

The analysis showed that of those belonging to the elite category, 52% came from a family where the parents were already in a professional job. That is, it is much more difficult for you to move to the elite category if your parents are not already there or nearly there themselves. It was startling to see that only 4% of ethnic minorities in the UK belong to the elite group. Other research in 2016 by the Social Mobility Commission in the UK showed that children from working class backgrounds are less likely to achieve well paid jobs because they don’t have access to the networks of influence needed to navigate modern society. To break through, and realise their potential they need luck, and lots of it!

Therefore, it seems the equation for modern life is

**luck * (where you start + who you know)**

Can that be considered fair in modern society? And what impact will AI have on this?

The Nobel prize winning philosopher and economist Amartya Sen wrote “the success of a society is to be evaluated primarily by the freedoms that members of that society enjoy”

A healthy society recognises the balance and interplay between economic, social and other forms of capital – such as cultural. The grand challenge is to rebalance society so that the interplay of these different forms of capital is prioritised equally, and to ensure that luck is not a factor - if we are to agree with Sen then it is also the freedom that each citizen has to choose how to balance the economic, social and cultural capital available to them to realise their own goals, that will define if we have developed society for good.

So how can the recent phenomenal developments in AI help towards realising this grand ambition?

It won’t come to the surprise of the reader that so much of the recent news about AI has related to the projections about how many jobs will become automated. Estimates for the next 5-10 years range from 20-30% of jobs being taken by AI (often with a caveat that just as many new types of jobs will be created). This is the most common AI trope.

If the news isn’t about AI automating your job, then it’s usually about how AI has surpassed some human capacity at a task, and how it can be used to support you in your job or task. AI as helper is the second trope! Both of these tropes are welcome – the more jobs that can be automated, actually become automated, the better. And the more that each of us can benefit from an AI helper in our remaining jobs, the better. But we need to recognise that both of these tropes stem from one form of capital - namely economic capital.

The demands to become more productive, more efficient, to increase revenue, grow GDP, grow economic capital – for the state, corporation or citizen – are currently the catalyst for the developments in AI we are seeing. But as I said earlier, a healthy society isn’t one that only focuses on economic capital. It is the mix of different forms of capital, and the agency a citizen has to access them to achieve their goals, that defines a healthy society. And this is where the greatest power that AI has can be applied, but it’s one that we are not tapping into effectively.

The capacity of AI to act as a mirror to society, and to amplify our efforts and endeavours is AI’s greatest superpower. This power to reflect back and amplify can be used for benefit or harm, and perhaps even worse, squandered. The survey the BBC conducted in 2011 was the largest survey ever conducted of UK society – 161,400 people responded, and this allowed the researchers to not only build detailed profiles of each individual, but to then analyse and assess what unites us, and what divides us. Fast forward to today, and it is child’s play for retailers, banks, ISPs, media, and social media companies to develop profiles of citizens at the level of the BBC survey – in fact today it’s easier to go much further, and to develop an almost complete picture of society and citizens with the power of AI. And what is that data and power of AI used for? Well for the most part to show citizens ads, or suggest something else to watch, or something else to buy! Again, because the incentives are built around economic capital, it is quite understandable that the benefits derived from AI are aligned to economic gains.

What if this power of AI was used to reflect and amplify a more balanced society Would this allow us to build a new equation for life that focuses on how we might flourish as humanity?

If we can achieve this then the payoff is a society where arguments related to scarcity of resources, or to luck of the draw can be eliminated. But how might we enable this to happen?

It is at this point in the article that I am going to confess that there is no clear-cut roadmap or blueprint that we can follow to addressing these social issues with AI. But I will offer three short suggestions that all stem from my work in the BBC as a public service organisation, and what it means to be in the service of the public, and to think about the welfare of the citizen and society.

1. AI as helper – the focus has been on developing services by corporations that augment the worker. And in the consumer world, AI services that represent the company and extend its ability to help the consumer in some way. For example, smart, personal assistants are in my view extensions of the companies they emerged from, which while potentially very helpful, are none the less not very personal to me. As they are not completely loyal to me, it is not 100% certain that they will always have my interests at heart. What is needed is a shift to AI companion services that are loyal to the citizen, and can help the citizen gain more social, cultural and economic capital.

2. AI to amplify public service. Public service institutions have acted as the cornerstones of society – often providing essential services, or filling the gap that commercial enterprise doesn’t want to fill. These institutions are under pressure, with a lack of resources, increases in demand, and a multitude of other factors constraining their effectiveness and ability to support citizens. What is necessary is for public service institutions to amplify their efforts, and AI offers an avenue to achieve this. A public service knowledge graph, that connects public service institutions data, while allowing them to operate independently, and that draws the power of algorithms to identify opportunities that just wouldn’t be spotted by each individual institution on its own, has the capacity to offer citizens more joined up services. This approach of joining up doesn’t have to be limited to established institutions, and would in fact benefit greatly from any actor who supports the goal of increasing citizens’ access to the different forms of capital.

3. New forms of incentivising AI developments – As I mentioned, the recent phenomenal developments in AI have emerged from a demand to increase economic capital. The key performance indicators for industry are all linked to this. For the next epoch of AI development in service of society, it is essential that new key performance indicators are developed that treat social and cultural capital as equals to economic capital. What is essential to ensure these new KPIs are effective is to make them just as specific and measureable as economic ones. Specificity is the essential ingredient for the development of objective functions in AI.

Finally, not a suggestion per-se, but a reminder of what Amartya Sen considered the definition of a healthy society:

“the success of a society is to be evaluated…primarily by the…freedoms that…members of that society enjoy.”

We are often concerned in AI development circles of the risk of humanity losing agency to AI. It is worth remembering that without AI we have still managed to marginalise many in society and take away their agency – their capability and freedom to define their lives for themselves. As AI practitioners, perhaps first we should be concerned with how we might apply AI to society to increase the agency the most marginalised have – in other words, how can AI be used to increase the access to capitals needed for citizens to choose their own path. This it seems to me would be a simple definition of AI for good, and each empowered citizen can help develop society for the better.