The Apple of my AI – GDPR for Good

Artwork by @aga_banach

Our common perception of machine learning and AI is that it needs an immense amount of data to work. That data is collected and annotated by humans or IoT type sensors to ensure the AI has access to all the vast information it needs to make the correct decisions. With new regulations to protect stored personal data like GDPR, does this mean AI will be at a disadvantage from the headache on restrictions for IoT and data collection? Maybe not!

What is GDPR and why does it matter?

For those who are outside of the European Union, GDPR (General Data Protection Regulation) is designed to “protect and empower all EU citizens data privacy”. Intending to return the control of personal data to individual citizens, it grants powers like requests for all data a business holds on them, a right to explanation for decisions made and even a right to be forgotten. Great for starting a new life in Mexico but will this impact on how much an AI can learn due to the limiting of information?

What’s the solution?

A new type of black box learning means we may not need human data at all. Falling into the category of ‘deep reinforcement learning’, we are now able to create systems which achieve super human performance in a fairly broad spread of domains. AIs are able to generate all training data themselves from simulated worlds. The poster-boy of this type of machine learning is AlphaZero and its derivatives from Google’s Deep Mind. In 2015 we saw the release AlphaGo which demonstrated the ability for a machine to become better than a human in a 5–0 victory against Go (former) champion Mr Fan Hui. AlphaGo reached this level by using human generated data of recorded professional and amateur games of Go. The evolution of this however was to remove the human data with AlphaGo Zero, beating its predecessor AlphaGo Lee 100:0 using 1/12th the processing power over a fraction of the time, and without any human training data. Instead AlphaGo Zero generated its own data by playing games against itself. While GDPR could force a drought of machine learning data in the EU, simulated data from this kind of deep reinforcement learning could re-open the flood gates.

Playing Go is a pretty limited area (though AlphaZero can play other board games!) and is defined by very clear rules. We want machine learning which can cover a broad spread of tasks, often in far more dynamic environments. Enter Google… again… Or rather Alphabet, the parent company of Google and their self-driving car spinoff Waymo. Level 4 and 5 autonomous driving presents a much more challenging goal for AI. In real time the AI needs to categorise huge numbers of objects, predict their paths in the future and translate that into the right control inputs. All to get the car and it’s passengers where they need to be on time and in one piece. This level of autonomy is being pursued by both Waymo and Tesla, but seemingly Tesla gets the majority of the press. This has a lot to do with Tesla’s physical presence.

Tesla has around 150,000 cars on the road equipped and boasted over 100 million miles driven by AutoPilot by 2016. This doesn’t even include data gathered while the feature is not active or more recent data (which I am struggling to find — if you know please comment below!). Meanwhile Waymo has covered a comparatively tiny 3.5 million real world miles, perhaps explaining the smaller public exposure. Google thinks it has the answer to this, again using deep reinforcement learning, meaning that their vehicles have driven billions of miles in their own simulated worlds, not using any human generated data. Only time will tell whether we can build a self-driving car, which is safe and confident on our roads alongside human drivers without human data and guidance in the training process. The early signs for deep reinforcement learning look promising. If we can do this for driving, what’s to say it can’t work in many other areas?

Beyond being a tick in the GDPR box there are other benefits to this type of learning. DeepMind describes human data as being ‘too expensive, unreliable or simply unavailable’, the second of these points (with a little artistic license) is critical. Human data will always have some level of bias, making it unreliable. On a very obvious level, Oakland Police Department’s ‘PredPol’, a system designed to predict areas of crime to dispatch police, trained on historical and biased crime data. It resulted in a system which dispatched police to those same historical hotspots. It’s entirely possible that just as much crime was going on in other areas, but by focusing its attention on the same old area and turning a blind eye to others the machine struggled to break human bias. Even when we think we’re not working on an unhealthy bias our lives are surrounded by unconscious bias and assumptions. I make an assumption each time I sit down on this chair that it will support my weight. I no doubt have a bias towards people similar to me, believing that we could work towards a common goal. Think you hold no bias? Try this implicit association test from Harvard. AlphaGo learned according to this bias, whereas AlphaGo Zero had no bias and performed better. Looking at the moves the machine made we tend to see creativity, a seemingly human attribute in its actions, when in reality their thought processes may have been entirely unlike human experience. By removing human data and therefore our bias machine learning could find solutions in possibly any domain which we might never have thought of, but in hindsight appear a stroke of creative brilliance.

Personally I still don’t think this type of deep reinforcement learning is perfect, or at least the environment it is implemented in. Though the learning itself may be free from bias, the rules and play board, be that a physical game board or rather road layout, factory, energy grid or anything else we are asking the AI to work on, is still designed by a human meaning it will include some human bias. With Waymo, the highway code and road layouts are still built by humans. We could possibly add another layer of abstraction, allowing the AI to develop new road rules or games for us, but then perhaps they will lose their relevance to us lowly humans who intend to make some use from the AI.

For AI, perhaps we’re beginning to see GDPR as an Apple in the market, throwing out the old CD drive, USB-A ports or even (and it still stings a little) headphone jacks, initially with consumer uproar. GDPR pushing us towards black box learning might feel like we’re losing the headphone jack a few generations before the market is ready, but perhaps it’s just this kind of thing that creates a market leader.

AI, VR and the societal impact of technology: our takeaways from Web Summit 2017

Together with my Digital Innovation colleague Morgan Korchia, I was lucky enough to go to Web Summit 2017 in Lisbon – getting together with 60,000 other nerds, inventors, investors, writers and more. Now that a few weeks have passed, we’ve had time to collect our thoughts and reflect on what turned out to be a truly brilliant week.

We had three goals in mind when we set out:

  1. Investigate the most influential and disruptive technologies of today, so that we can identify those which we should begin using in our business
  2. Sense where our market is going so that we can place the right bets now to benefit our business within a 5-year timeframe
  3. To meet the start-ups and innovators who are driving this change and identify scope for collaboration with them

Web Summit proved useful for this on all fronts – but it wasn’t without surprises.  It’s almost impossible to go to an event like this without some preconceptions about the types of technologies we are going to be hearing about. On the surface, it seemed like there was a fairly even spread between robotics, data, social media, automation, health, finance, society and gaming (calculated from the accurate science of ‘what topic each stage focused on’). However, after attending the speeches themselves, we detected some overarching themes which seemed to permeate through all topics. Here are my findings:

  • As many as 1/3rd of all presentations strongly focus on AI – be that in the gaming, finance, automotive or health stage
  • Around 20% of presentations primarily concern themselves with society, or the societal impact of technology
  • Augmented and virtual reality feature in just over 10% of presentations, which is significantly less than we have seen in previous years

This is reflective my own experience at Web Summit, although I perhaps directed myself more towards the AI topic, spending much of my time between the ‘autotech / talkrobot’ stage and the main stage. From Brian Krzanich, the CEO of Intel, to Bryan Johnson, CEO of Kernel and previously Braintree, we can see that AI is so prevalent today that a return to the AI winter is unimaginable. It’s not just hype; it’s now too closely worked into the fabric of our businesses to be that anymore. What’s more, too many people are implementing AI and machine learning in a scalable and profitable way for it to be dispensable. It’s even getting to the point of ubiquity where AI just becomes software, where it works, and we don’t even consider the incredible intelligence sitting behind it.

An important sub-topic within AI is also picking up steam- AI ethics. A surprise keynote from Stephen Hawking reminded us that while successful AI could be the most valuable achievement in our species’ history, it could also be our end if we get it wrong. Elsewhere, Max Tegmark, author of Life 3.0 (recommended by Elon Musk… and me!) provided an interesting exploration of the risks and ethical dilemmas that face us as we develop increasingly intelligent machines.

Society was also a themed visited by many stages. This started with an eye-opening performance from Margrethe Vestager, who spoke about how competition law clears the path for innovation. She used Google as an example, who, while highly innovative themselves, abuse their position of power, pushing competitors down their search rankings to hamper the chances of other innovations from becoming successful. The Web Summit closed with an impassioned speech from Al Gore, who gave us all a call to action to use whatever ability, creativity and funding we have to save our environment and protect society as a whole for everyone’s benefit.

As for AR and VR, we saw far less exposure this year than seen at events previously (although it was still the 3rd most presented-on theme). I don’t necessarily think this means it’s going away for good, although it may mean that in the immediate term it will have a smaller impact on our world than we thought it might. As a result, rather than shouting about it today, we are looking for cases where it provides genuine value beyond a proof of concept.

I also take some interest from the topics which were missing, or at least presented less frequently. Amongst these I put voice interfaces, cyber security and smart cities. I don’t think this is because any of these topics have become less relevant. Cyber security is more important now than ever, and voice interfaces are gaining huge traction in consumer and professional markets. However, an event like Web Summit doesn’t need to add much to that conversation. I think that without a doubt we now regard cyber security as intrinsic to everything we do, and aside from a few presentations including Amazon’s own Werner Vogels, we know that voice is here and that we need to be finding viable implementations. Rather than simply affirming our beliefs, I think a decision was made to put our focus elsewhere, on the things we need to know more about to broaden our horizons over the week.

We also took the time to speak to the start-ups dotted around the event space.  Some we took an interest in like Nam.r, who are using AI in a way which drives GDPR compliance, rather than causing the headache many of us assume it may result in. Others like Mapwize.io and Skylab.global are making use of primary technological developments, which were formative and un-scalable a year ago. We also took note of the start-ups spun out of bigger businesses, like Waymo, part of Google’s Alphabet business, which is acting as a bellwether on which many of the big players are placing their bets.

The priority for us now is to build some of these findings into our own strategy- much more of a tall order than spending a week in Lisbon absorbing.  If you’re wondering what events to attend next year, Web Summit should be high up on your list, and I hope to see you there!

What are your thoughts on these topics? Leave a reply below, or contact me by email.

Learn more about Aurora, Sopra Steria’s horizon scanning team, and the topics that we are researching.

How Queen can teach us about Customer Expectations in the Digital Age

“I want it all, I want it all, and I want it now!”.

Little did Freddie Mercury realise back in 1989 how prophetic his lyrics would be in describing the future of customer expectations. Although it’s likely that this subject wasn’t at the forefront of his thinking as Brian May penned the track, it did touch on the themes of ambition and social upheaval, both of which are highly relevant in today’s complex and constantly changing service landscape.

The fact is that the average customer in 2017 expects more, and this is increasingly the case within the younger age groups. Younger service consumers have grown up in an age where the Internet has always been a thing, apps are part of everyday life, and the ability to Snapchat an image to your friend two thousand miles away and get an instant response is not only possible, it is expected. Technology has, to all intents and purposes, liberated us from the shackles of conventional communication.  We can now speak to our friends and family pretty much anywhere and at any time, using an array of services to get the job done.  The rise of instant messaging via SMS and subsequent evolution to asynchronous messaging via apps such as WhatsApp and Facebook Messenger have changed the way in which people communicate, at a fundamental level.

Over time, these technologies have become the new normal, and they continue to evolve. A perhaps unexpected implication of this is the change in expectations that customers have of their service providers. For many it feels jarring to switch from a seamless and frictionless conversation with a friend via WhatsApp to then have to call, for instance, a retailer’s customer service helpline, using the actual phone bit of their phone, deal with the automated response system, wait in a queue and then have to speak to a real live human in an effort to get what should, in theory, be a relatively simple piece of assistance. The immediacy, convenience and ‘always’ on nature of app-based services and mobile communications technologies has given customers a taste of the future; namely autonomy.  Instant access to what you need, when you need it and via the channel of your choice is rapidly becoming the new normal for large swathes of the population.

Research bears this out.  A recent UK survey of one thousand consumers showed that 65% were happier using chat services to talk to businesses than five years ago, and that 68% would rather use chat than either email or phone. This is a trend that is only going in one direction as the consumer demographic is populated by increasing numbers of young and technologically savvy folk who would think nothing of flitting between a conversation with their BFF in one instance and their mobile phone provider support desk in another, on Facebook Messenger, in real time.  On the bus.  At midnight.

In short, the very existence of these emerging technologies is making us, as people, more impatient, more selfish, and increasingly demanding, and this is starting to rub off on how we approach our service providers. If you are providing your customers with any kind of digital experience, whether this be via Web or Mobile, people now simply expect an experience similar to that obtained elsewhere within the digital domain. But let’s be real here for a moment. Providing a service normally reliant on people that can simultaneously tick those boxes of ubiquity and immediacy is, quite frankly, a real challenge.

Availability of people and skills to service your customers will always be a constraint, and simply adding new channels only compounds this issue.  The advent of useful Artificial Intelligence, however, will address this constraint. Intelligent bots to augment chat, messaging and voice channels can provide your existing workforce with the additional manpower (botpower?) needed to bridge the experience gap between ubiquitous immediate access to assistance, and sitting in a call queue.  These bots won’t replace your human workforce, but they will work alongside them to do the initial triage, understand and respond to common questions, route enquiries to the appropriate team or, in time, enable real-time transactional processing (e.g. buying a train ticket).

As a service provider, if you don’t respond to this challenge, you will be ignored.  It takes less than a nanosecond to close an App and go elsewhere, and probably only slightly longer to make the decision to do so, when the experience does not meet expectations. Adding friction to your engagement processes will push customers away, and it is simply not an option to do nothing. If your business fails to respond to the roll-call of providing a seamless digital customer experience, you will get left behind, and possibly quicker than you might think.

So when you’re thinking about how to encourage your customers into your digital embrace, think of Freddie Mercury and remember his primal scream; “I want it all and I want it now!”.

What do you think? Leave a comment below or contact me by email.

“AI Neutrality”: A proposed manifesto for artificial intelligence user experience design

What makes a great artificial intelligence (AI) driven user experience? Here are my thoughts…

1. Design AI services end to end – the disruptors that have transformed the travel, holiday and retail sectors over the last twenty years succeeded by focusing aggressively on improving their own single channel online experience. AI user experience design must also adopt this strict one channel approach to service delivery – every user journey should be simple, relevant, no fuss and always getting better because it’s being delivered by an artificial intelligence end to end.

2. Go beyond mobile  The interconnectivity of AI enables any environment or physical object to positively affect all of our five senses (such as connected home technology like heating and lighting devices that responds to a user’s mood). AI design should always be pushing to transcend the user interface constraints of existing service platforms (particularly the visual and audio experience of mobile) to truly reflect and improve how we use our senses to interact with the world around us.

3. Addressable media is a key user journey –  AI has the potential to utilise a complex range of historic and contextual customer data to deliver targeted, personalised advertising – for example, UK broadcasters are adopting programmatic technology to deliver specific adverts at individual households in real time. Yet if designed poorly such disruptive engagement risks coming across like hard selling that overwhelms or irritates a customer (consider the negative reaction of customers to pop up web ads that apply a similar approach). Consequently, it’s vital that AI driven addressable media is treated as a form of user experience that requires research, design and testing to ensure customers are empowered to consume it on their own terms.

4. Hardwire ethics and sustainability –  the positive disruption to our lives from social media has enabled these services to grow rapidly and organically by billions of users worldwide. Yet this has also led to these platforms becoming so big it’s challenging for their service providers to effectively manage and safeguard the user content they share. Drawing from this experience, and combined with public calls for the proactive regulation of AI, it’s essential artificial intelligence products and services have the right ethics and sustainability values in their core design as they are likely to grow even faster and bigger than social media.

5. Champion “AI Neutrality” – artificial intelligence has the power to transform all our lives like the internet before it. A fundamental principle driving the success of the web has been “net neutrality” – that internet data services should be supplied as a form of utility (like electricity, gas, water) in a non-discriminatory way to all customers. Access to simple AI services should be similarly “neutral” – a basic human right that is complemented by differentiated, chargeable products and services from over-the-top producers.

If you would like more information about how artificial intelligence can benefit your business, please leave a reply below or contact me by email.

Artificial intelligence customer experience design: the frictionless theme park?

Many theme parks offer an additional paid service that provides a virtual queuing bot that gives the paying customer immediate access to a ride during an allocated time slot with minimum fuss. This can deliver a smoother customer experience while enabling the park operator further monetisation opportunities through differentiated ticket prices.

But such services are not perfect. For example, like real queues, virtual ones can still get filled up (so reducing availability of time slots), a customer can’t simply change their mind at the last minute and expect an alternative ride to be available at the same time and many of these systems don’t reflect other dynamic factors that could affect ride enjoyment like poor weather.

So how could Artificial Intelligence (AI) potentially address these challenges? Here are some ideas…

One opportunity is to apply retail thinking to personalise the end to end experience – via mobile, an AI could suggest rides to visit throughout the day based on a customer’s social media updates, current and expected volume/demand for an attraction and forecast weather. In “the background” (i.e. the Cloud), the AI is constantly analysing customer behaviour in the park to drive these suggestions to help manage the people flow through different areas and rides to minimise friction for all. This capability could also enable the operator to offer on the spot additional services (like offering the chance to immediately access any roller coaster ride for a small charge) to further delight and surprise a customer during their visit.

Conversely, such an application of AI may be counter to what an operator wants to offer – after all, exciting theme park experiences come from customers being spontaneous when choosing their next desired ride or attraction. Accepting such unlimited freedom is not possible – this still leaves the risk of friction (like boredom) when a customer is waiting for the next experience to become available. An AI could turn this “dead time” into an experience in itself – using it as an opportunity to send personalised media content and offers to a customer’s mobile or tablet to consume while queuing for a ride. Alternatively, the AI could create social events for people in the park to interact with each other like mobile gaming competitions or dating. Such services could also be linked to third party promotions to generate further revenue for the theme park operator.

These illustrative use case ideas are based on one key assumption – most customers visiting a theme park at the same time will follow the guidance or direction given by an AI consistently, even when it results in a lesser personal experience than intended (but results in all participants gaining mutual benefit). This notion that AI can effectively influence human behaviour at scale in one place (like a theme park) is a major challenge for Artificial Intelligence Customer Experience Design.

If you would like more information about how artificial intelligence can benefit your business, please leave a reply below or contact me by email.

Intelligent personal assistants: an opportunity for retailers?

Alexa is arguably the tipping point for intelligent personal assistants; with Amazon’s open source approach to sharing its app (“skill”) development capabilities the sky’s the limit for this new, disruptive form of natural language driven customer experience. But what could retailers make of this opportunity? Here are some ideas…

It’s not the hardware but the cloud analytics that matters

Critical to any retailer using an intelligent personal assistant to innovate their brand is that these use cases should primarily focus on the business outcomes from using its cloud analytics capabilities, not the front-end device itself.

A retailer, for example, could use Alexa to provide instore guidance to shoppers to help them find items or make simple queries, physical customer browsing behaviour captured in the cloud that when combined with online experiences enables deeper, more contextual forms of personalisation across all this retailer’s channels.

An opportunity to simplify (and risk of complicating) customer journeys

A unique strength of an intelligent personal assistant is that it has the potential to smartly rationalise customer queries and transactions – an opportunity to turn chatbots into compelling conversational experiences a customer would have a preference for using over engaging a person or using a digital channel.

But there remains a significant user experience design challenge for its natural language driven interface – at what point does the buying journey become too complex for this channel and risks increasing friction for a customer? Any form of customer experience that requires a customer to look at detailed product information or make comparisons between products could be difficult and hard to follow through spoken voice generated content alone.

Alexa’s use of APIs could enable a retailer to combine this channel with its mobile e-commerce site (or in-store tablets) for example to create a seamless, holistic experience where complex information is shared visually driven by a customer’s voice commands and smartly informed by Alexa’s AI.

Bricks and mortar as a truly experiential destination

Perhaps the most exciting thing about Alexa (and intelligent personal assistants in general) is the potential for them to create unique, personalised experiences instore – a direct, deep relationship between a customer and a retailer’s brand. And because its cloud driven this enables interconnectivity (IoT) with other instore technologies such as targeted digital signage, interactive mirrors, social media engagement and mobile point of sale.

If you would like more information about how digital transformation can benefit your retail business, leave a reply below or contact me by email.

Shopping with Artificial Intelligence: The frictionless family customer experience?

With Amazon, Facebook and Google all adopting an open source approach to development of their artificial intelligence (AI) services, what could this innovation mean for a family shopping on the High Street? Here are some ideas…

An end to Saturday morning parking mayhem – having to spend half an hour queuing to get into a shopping centre car park only to find out the only spaces left are on the hundredth floor can be a miserable start (and end) to a Saturday shop for the whole family.

An AI personal assistant could reduce the friction of this inconvenience by reserving a suitable car parking space at the shopping centre in advance, based on the family’s store preferences, accessibility requirements and other factors, like forecast weather. It can then send the reserved space location to the family’s in-car GPS and automatically pay for its ticket. The more an AI can effectively integrate or communicate with other systems the greater the convenience for customers.

No more bored kids looking at their mobiles – the family have spent hours traipsing from store to store failing to be engaged by any of these retail experiences. The kids are just itching to get their phones out to start socialising with their friends, and mum and dad are getting the feeling they are better off buying online.

An AI could transform the friction of this irrelevant customer experience by giving in-store products ‘personality’ –  a product can introduce itself using spoken voice to these customers (via a store branded mobile app for example), talk about its unique selling points and answer potentially any question about its suitability – all personalised using buying and social insights the AI has about the family. The more an AI can effectively apply analytics to create experiential, contextual shopping experiences, the more compelling and delightful bricks and mortar stores become for customers.

Empowered shopping without added wrinkles – So the family have found things they need and discovered lots of things they want, but mum and dad aren’t comfortable with uncontrolled spending across their bulging wallet of bank cards.

An AI could help remove the friction of this uncertainty by acting as a single channel for these customers to manage their disparate bank services in one place, giving on the spot advice about saving and spending to enable the right purchasing decisions and provide a secure, easy to use payment system using customer voice recognition (biometric authentication). The more an AI can create a platform that combines and simplifies a range of complex services; the better mobility customers have on the High Street – experiences that rival anything offered by online retailers.

If you would like more information about how digital transformation can benefit your organisation please contact the Sopra Steria Digital Practice.