Artificial Intelligence: The new entertainment experience?

Artificial Intelligence (AI) can radically transform how we interact with a range of services, with Amazon’s Alexa being a notable example growing rapidly in popularity. But in what ways could AI disrupt how we use and consume entertainment? Here are some ideas…

Dynamic film narrative

An AI can use Machine Learning to find hidden insights in a data set to identify remedial action. This capability could be used to enable a film viewer to directly interact with a film’s narrative – pausing the action any time to tell the AI (or even the film’s characters themselves?) how they think and feel about the story. Sentiment that an AI can then analyse in the cloud to learn what an audience wants next that’s fed back to the content producer – greater plot exposition, more of their favourite characters or action. AI-driven blockbuster entertainment that never flops!

Game voice user interface

Natural Language Processing (NLP) enables an AI to understand and respond to spoken and written commands. In terms of a console gaming experience, NLP could transform such experiences. Rather than using a controller to direct and interact with non-player characters within a game, the player could talk to them directly, naturally – a new level of gameplay design that creates truly immersive experiences.

Personalised content maker

AI’s ability to analyse massive amounts of data from potentially any source is enabling deeper, richer forms of Personalisation. Could an AI use this capability to create brand new content (stories, images, even films or music) to an individual’s specific tastes and mood? On demand entertainment that always delights, never gets boring or ends – the perfect TV channel you won’t want to switch off!

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

Doing more with less: digital transformation and social care

In a recent blog, I highlighted the need to shift thinking in government from efficiency to productivity. I used the example of education and highlighted innovations that might increase productivity through digitisation of teaching services and communication. I now want to extend the debate by looking at social care.

Social care services cover a range of home support services provided for the young and the elderly and people with disabilities, to assist people to remain in their own homes and communities. In England, social care is predominantly the responsibility of local authorities. They are facing unprecedented pressure due to rising demand and an increase in customer expectations. Growing numbers of older people often have increasingly complex needs.

At the same time future spending on social care is very uncertain. According to the Institute for Fiscal Studies, demographic pressures will cause per-capita spending to fall in the absence of additional funding. And local authority revenues are expected to fall by 7.4% between 2015 and 2020.

Social care providers are adopting new models for delivering care

Where is this happening? Connecting Care is a partnership across the Bristol, North Somerset and South Gloucestershire area. The partnership comprises 17 different organisations (including the three councils, hospital trusts, ambulance trusts, GPs and community health providers) with 14 individual client record systems interacting between them. Client data is gathered from each participating organisation and carefully matched to display an integrated data set for each person.

This is one example of service integration through voluntary cooperation between the public, private and community sectors. Where there is a cultural shift, with services integrated through digitisation, there are substantial benefits for:

  • Administration: Supporting integrated case management systems, with a broader overview of needs and options to inform individualised planning and cross-sector coordination, using tablets for care plans, risk assessments, health assessments, safeguarding and medication (documented on the system in real time).
  • In home care and support: A combination of digital records and web-based access to information for staff and enhanced communication tools for service users and their family and friends, ultimately allowing service users to organise leisure activities and plan their own care and support.
  • Financial support: Increasing digitisation of the payment of financial support, including determining and verifying eligibility, and calculating and making benefits payments, ultimately leading to greater choice between different care options.

The major limitations of the digital social care market are not the shortage of technology

Innovation uptake is slow compared to other parts of the public sector. It is important to recognise that there are a number of complex challenges to successful digital transformation . Most of these challenges relate to the human dimension – the readiness for change amongst citizen’s and service users to an increasingly digital environment, and concerns about the privacy and security of personal data.

The practical reality is that the speed of advancement in technologies undoubtedly exceeds the speed with which the potential benefits can be realised in the delivery of social care. So, what are the practical steps that the public sector can take to speed up the deployment of innovations in social care and protection?

  • Step 1 – Greater transparency of processes and operations and encouraging participation of public, private and community stakeholders in policy making and service design.
  • Step 2 – Promote engagement and co-operation across different levels of government through adequate incentives, quickly moving to the pooling of resources and shared agreements and targets.
  • Step 3 – Develop clear business cases to sustain the funding and focused implementation of digital technologies projects.
  • Step 4 – Build institutional capacities to manage and monitor project implementation, with a significant emphasis on procurement and contracting practices.
  • Step 5 – Integrated data and better usage to measure productivity and efficiency in all parts of the value chain of public service delivery.

These practical steps do not just apply to social protection – they are equally relevant to other public services, including, health, education and other welfare services.

I’ve been really enthused by the examples of productivity enhancing innovations provided by public servants since my last blog. I would like to hear from more public servants about how they are using technology to enhance how they work and deliver services to the public – please get in touch by leaving a message or sending an 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.

What’s in a name? Shifting the debate in Government from efficiency to productivity

Government often thinks of efficiency and productivity as two sides of the same coin. But the reality is that they are very different. And this difference will become ever more important. The government needs budget cuts that maintain (or even increase) the volume and quality of key public services.

The term efficiency is used to identify the minimal amount of inputs that an organisation needs to use to produce products or services. Or doing the same with less. For the past decade, through various spending reviews, Ministers have asked Civil Servants to streamline services. This has led to a drastic reduction in the number of public servants: the Civil Service is at its smallest since the Second World War. Local government had to address more immediate and significant budget cuts (and central government could learn from how they did this).

This translates into savings because government spends less on wages and other staff related costs. Other (often lesser but important) sources of efficiency include improvements to government procurement and reductions to fraud, error and debt.

The former Prime Minister, David Cameron, described this approach in the following terms:

What we are showing is that deficit reduction and an opportunity society are not alternatives. They can complement each other. Because with a smarter state, we can spend less and deliver more.

Just like businesses, government needs to constantly adapt and change to improve public services and reduce costs.

But the benefits from improving efficiency are starting to peter out

There is evidence that key public services are being pushed to the limit. For example, violence in prisons rose sharply since 2014, with assaults on staff increasing by 61 per cent in two years. And in other areas, such as the health service, there is a constant upward pressure on demand and costs due to a growing and ageing population, which suffers from an ever-rising tide of complex chronic conditions.

There is a limit to how far government can cut staff numbers. The Ministry of Justice has plans to employ 2,500 new prison officers to make our prisons more safe and secure. And thousands of prison officers at jails in London and south-east England are to get pay rises of up to £5,000 to boost staffing levels. Other key public services, including border controls and tax collection, have also had to rethink staff cuts.

So, if efficiency has run out of steam then what about productivity?

The term productivity is used to assess how an organisation is succeeding in progressively developing its performance. Or doing more with the same. Productivity enhancing changes are often far reaching and innovative, particularly in high impact areas such as education, healthcare and social care and protection.

Government initially made investments in digitisation, generally with a focus on improving efficiency in administrative services that support frontline service delivery. These services were more user-focused and relied on greater use of digital technologies, including the UK Government’s cloud first policy.

So far so good. But as government departments are placed under ever greater scrutiny, including the modelling of further cuts through the Treasury’s Efficiency Review, they need to look at more innovative changes in service design and delivery. The use of digital technologies must move beyond the back-office and front-office administrative processes and be applied to direct service delivery.

The next step – public service reform and the integration of technology

Education is one example of how this use of technology enabled organisational change can enhance productivity. My formative education in the 1970s and 1980s was premised on relatively little change. Teachers rarely took account of preferred learning styles. The global revolution of online teaching and learning through massive online open courses was a long way off.

The so-called fourth industrial revolution requires us to be agile and to be bold. The pace of change, driven by technology and globalisation, is so fast that two thirds of children starting at school this year will work in jobs that do not even exist yet.

Education is changing and becoming more efficient. Most students have access to laptops and tablets both at home and school (although we must always be wary that some students might not have access to technology or necessary skills). Teaching and learning is supported through online resources that share knowledge. Administrative processes are being digitised.

But it is worth looking to other countries for inspiration and examples of productivity boosting investments. Denmark, Finland and Estonia have already developed digital tools that save teachers’ time when revising tasks and exams, they are building new markets to provide digital learning materials, to be shared across schools and they are developing an online ‘education cloud’ to join up educational platforms and materials.

I would like to hear from teachers and public servants, across local and central government, to share and understand how they are using technology and adopting new ways of working. Please leave me a message, or contact me by email and we can continue the discussion.

The rise of the Intelligent Machine

So it’s Tuesday evening and I’m watching the BBC 10 O’clock news. There’s an article being aired around the impact that technology-driven automation is going to have on the labour market which is suggesting that by 2035, 35% of the total UK employment market may be at risk of displacement. This is a pretty sobering statement, and gives rise to philosophical debate around the impact that this will have – not just on those members of the workforce affected, but also on our education system and the nature of employment opportunity in the advent of the automation revolution. Should we be teaching our children differently, right now, to prepare them for this? How do we second guess those jobs that are likely to become obsolete and thus help our children to focus their energies in those areas less likely to be impacted? Are we in danger, as some have prophesised, of creating an unemployable underclass?

Only time will tell, and it’s human nature to want to predict the worst case scenario, but quite often the reverse scenario is the more likely outcome.

Historically speaking, advances in technology, robotics and automation have not resulted in a commensurate rise in unemployment numbers but have actually increased employment

Deloitte executed a study on this subject using census data going back to 1871 and found that, whilst certainly some jobs have been made largely redundant by technology, the labour market has responded by switching to roles in care, service and education sectors. Knowledge-based industries in particular have benefitted from the ubiquitous availability of data, and increasing ease of communication. People are generally wealthier as the costs of goods and services have dropped which, rather amusingly, has seen a 1000% rise in bar staff (so we now know where all of our extra cash is going).

But this new wave of technology, the rise of artificial intelligence and intelligent machines, will likely have an equally material impact on knowledge based industries as robotics and technology assisted machinery has had on manual labour based ones. Companies such as IBM are spearheading this movement with technologies such as Watson. Cognitive computing platforms that are able to ‘think’ in human-like ways, they can reason, understand context, and use previous experience to make future predictions and inform decision making. They are capable of conversing in natural language and, when used in conjunction with big data repositories, are able to present insight that would otherwise be impossible to achieve using conventional computational systems. Perhaps more importantly, when used in conjunction with process automation engines, they are able to execute tasks. Process automation is not a new technology – we’ve been achieving this to varying degrees of complexity for many years now. What cognitive technologies bring to the table, however, is the ability to deal with decisions. Theoretically a cognitive system can execute complex processes that, under normal circumstances, would be wholly reliant on human interaction to complete due to the inherent necessity to think, to reason, and to bring knowledge into the equation. The future potential for such technologies is only now starting to be truly understood.

If, like me, you have an overactive imagination you may be imagining a cognitive system like IBM’s Watson to be some kind of huge supercomputer with flashing lights akin to the WOPR in the seminal 1983 classic film, WarGames. Indeed the WOPR was capable of natural language processing (it could talk), it could ‘learn’ through trial and error (albeit via circa 1000 games of tic tac toe) and it was capable of making informed decisions based on access to a wide range of data (Russian nuclear missile launch trajectories). But the reality is that Watson is highly scalable and not nearly so resource hungry. When it won the US TV show Jeopardy! in 2011, beating two of the show’s most prolific and successful contestants in the process, it did so running on 100 IBM POWER 750 servers running in a massively parallel computing cluster. Since then, IBM has refined the code for enterprise use such that it can now run on a single server platform, or directly via the Cloud. The Watson algorithms are being embedded in multiple different enterprise applications, tuned for different use cases, and are already being adopted in major banking and healthcare applications, to name but a few.

Other companies are also now offering enterprise solutions that have cognitive capabilities behind them, and one area that is garnering quite a bit of interest of late is the Virtual Digital Assistant, also commonly known as (an intelligent) chatbot. If you’ve ever used a customer service chat box online, you may be familiar with the concept of a ‘bot’ that can ask certain pre-canned questions or relay information prior to handing you off to a human operator. Bots are also often used in web chat applications for things like providing help on how to use the service itself.

Historically bots have been pretty dumb. They possess no innate intelligence, and simply work from a script. Go off-script, and the bot will simply not understand the question.

Chatbots that use cognitive algorithms, on the other hand, possess two unique and potentially game changing characteristics. Firstly, the can converse using natural language, so the experience is a very close approximation to that when conversing with a real human. Secondly, they can go off-script – they can interpret questions or instructions and combine stored knowledge with probabilistic algorithms to provide you with a response that is highly likely to be appropriate and possibly even useful! Such systems need to learn over time, and can even be trained, so their true potential is not unlocked immediately. Their potential, however, is huge, the use cases are many.

So what of the impact of such technologies? For the consumer, the likes of Amazon’s Alexa or Apple’s Siri will only become more capable and increasingly useful. Integration with home automation systems and access to consumer services are the obvious starting points. At present, the vast majority of service integration is limited to vendor’s entertainment and media services, but thinking outside of the box, consider the implications of using such technology to engage with other types of service providers. Want to pay your bank bill? Why not ask Alexa to do it for you? Need to register a complaint with your utility provider? Why not have Siri do it for you? Need to book a taxi? …Cortana?! As consumer service provider organisations begin to digitise their customer engagement channels, this kind of opportunity for integration begins to open up, paving the way for a new era in automated service fulfilment.

For the enterprise the impact is likely to be significantly more material. Efficient gains made via labour arbitrage, for instance, will shift to those enabled by technology arbitrage, as automation, driven by cognitive platforms, drives the cost of service down and the quality of service up. The impact this will have on traditional delivery models could be both rapid and significant. Service providers using cheap labour to deliver cost-effective knowledge-centric services will likely need to re-evaluate their models to remain competitive. Junior roles within organisation, many of which may be traditional routes in to the industry, will need to adapt to cater to those areas that support these new technology capabilities, or else see themselves replaced by them. Commercial models too will need to adapt as customers choose to move increasingly toward consumption or outcome based models, rather than those dictated by headcount or traditional performance related targets. The opportunities are there in abundance for those providers – and consumers – who choose to embrace the technology. Indeed, in this particular case, the WOPR was way off target when it philosophically announced that “…the only way to win is not play”. Whilst that may be true of Global Thermonuclear War, it certainly isn’t true of intelligent computing platforms within the enterprise.

As for me, I’m off to play a nice game of chess…

What are your views? Leave a reply below or, if you would like to learn more about these topics, please contact me by email.

How mentoring at a hackathon helps focus on idea generation and develops potential

I love being a mentor, and recently I was part of a team who ProductForge invited to their three-day, competitive healthcare hackathon at CodeBase, Edinburgh to mentor the teams taking part and get engaged with the exciting projects that were going on and involved in idea generation and helping the teams come up with a single idea to focus on, then guiding in any way that we could.

Participants form small cross-functional teams to work on a product prototype with support from industry experts in the NHS and the wider technology community. It’s an opportunity for participants to develop new skills, network with professionals, meet potential employers or even kick-start their own company.

Image of hackathon participantsAs with any event of this nature, there was a tangible feeling of excitement – everyone was talking intensely, gesturing and sketching ideas. Some of the teams had pretty solid ideas of what they wanted to do, while others were still in the brainstorming stage – whatever their stage of idea development, the amount of energy, always impressive.

For those teams that had an idea to go forward with, I offered to run a breakout workshop focusing on UX design. For those that hadn’t picked an idea yet, we spent some time trying to help to focus their ideas on something they could work on.

Picture of hackathon particpantsThe workshop got the teams thinking about who they were creating their apps for, explaining that the smaller their focus target audience, the better they could target their research and the clearer they would be of their required functionality.

This message was made continually throughout the day, and it was great to see some of the teams altering their projects to focus on more specific user groups.

The whole day was a lot of fun, and everyone from our team was disappointed to leave at the end.

I’m one of many at Sopra Steria who spend time mentoring – especially with young people still in education who might need some help developing their full potential. It’s all part of our commitment to making a positive difference to the communities in which we live and work, and I’d recommend it to anyone.

Do you have experience in mentoring outside of your workplace? 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.