LET’S THINK INTELLIGENTLY ABOUT AI

Posted on : 30-04-2018 | By : kerry.housley | In : Uncategorized

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Currently there is a daily avalanche of artificial intelligence (AI) related news clogging the internet. Almost every new product, service or feature has an AI, ‘Machine Learning’ or ‘Robo something’  angle to it. So what is so great about AI? What is different about it and how can it improve the way we live and work? We think there has been an over emphasis on ‘machine learning’ relying on crunching huge amounts of information via a set of algorithms. The actual ‘intelligence’ part has been overlooked, the unsupervised way humans learn through observation and modifying our behaviour based on changes to our actions is missing. Most ‘AI’ tools today work well but have a very narrow range of abilities and have no ability to really think creatively and as wide ranging as a human (or animal) brain.

Origins

Artificial Intelligence as a concept has been around for hundreds of years. That human thought, learning, reasoning and creativity could be replicated in some form of machine. AI as an academic practice really grew out of the early computing concepts of Alan Turing and the first AI research lab was created in Dartmouth college in 1956. The objective seemed simple, create a machine as intelligent as a human being. The original team quickly found they had grossly underestimated the complexity of the task and progress in AI moved gradually forward over the next 50 years.

Although there are a number of approaches to AI, all generally rely on learning, processing information about the environment, how it changes, the  frequency and type of inputs experienced. This can result in a huge amount of data to be absorbed. The combination of the availability of vast amounts of computing power & storage with massive amounts of information (from computer searches and interaction) has enabled AI, sometimes known as machine learning to gather pace. There are three main types of learning in AI;

  • Reinforcement learning — This is focused on the problem of how an AI tool ought to act in order to maximise the chance of solving a problem. In a particular situation, the machine picks an action or a sequence of actions, and progresses. This is frequently used when teaching machines to play and win chess games. One issue is that in its purest form, reinforcement learning requires an extremely large number of repetitions to achieve a level of success.
  • Supervised learning —  The programme is told what the correct answer is for a particular input: here is the image of a kettle the correct answer is “kettle.” It is called supervised learning because the process of an algorithm learning from the labelled training data-set is similar to showing a picture book to a young child. The adult knows the correct answer and the child makes predictions based on previous examples. This is the most common technique for training neural networks and other machine learning architectures. An example might be: Given the descriptions of a large number of houses in your town together with their prices, try to predict the selling price of your own home.
  • Unsupervised learning / predictive learning — Much of what humans and animals learn, they learn it in the first hours, days, months, and years of their lives in an unsupervised manner: we learn how the world works by observing it and seeing the result of our actions. No one is here to tell us the name and function of every object we perceive. We learn very basic concepts, like the fact that the world is three-dimensional, that objects don’t disappear spontaneously, that objects that are not supported fall. We do not know how to do this with machines at the moment, at least not at the level that humans and animals can. Our lack of AI technique for unsupervised or predictive learning is one of the factors that limits the progress of AI at the moment.

How useful is AI?

We are constantly interacting with AI. There are a multitude of programmes, working, helping and predicting  your next move (or at least trying to). Working out the best route is an obvious one where Google uses feedback from thousands of other live and historic journeys to route you the most efficient way to work. It then updates its algorithms based on the results from yours. Ad choices, ‘people also liked/went on to buy’ all assist in some ways to make our lives ‘easier’. The way you spend money is predictable so any unusual behaviour can result in a call from your bank to check a transaction. Weather forecasting uses machine learning (and an enormous amount of processing power combined with historic data) to provide improving short and medium term forecasts.

One of the limitations with current reinforcement and supervised models of learning is that, although we can build a highly intelligent device it has very limited focus. The chess computer ‘Deep Blue’ could beat Grand-master human chess players but, unlike them, it cannot drive a car, open a window or describe the beauty of a painting.

What’s next?

So could a machine ever duplicate or move beyond the capabilities of a human brain. The short answer is ‘of course’. Another short answer is ‘never’… Computers and programmes are getting more powerful, sophisticated and consistent each year. The amount of digital data is doubling on a yearly basis and the reach of devices is expanding at extreme pace. What does that mean for us? Who knows is the honest answer. AI and intelligent machines will become a part of all our daily life but the creativity of humans should ensure we partner and use them to enrich and improve our lives and environment.

Deep Learning‘ is the latest buzz term in AI. Some researchers explain this as ‘working just like the brain’ a better explanation from Jan LeCun (Head of AI at Facebook) is ‘machines that learn to represent the world’. So more general purpose machine learning tools rather than highly specialised single purpose ones. We see this as the next likely direction for AI in the same way, perhaps, that the general purpose Personal Computer (PC) transformed computing from dedicated single purpose to multi-purpose business tools.

GDPR – Are You Ready?

Posted on : 30-04-2018 | By : kerry.housley | In : compliance, Consumer behaviour, Cyber Security, Data, data security, GDPR

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It is less than a month until the General Data Protection Regulation (GDPR) comes into force, but after two years of preparation, how many businesses are GDPR ready? The latest flurry of figures suggest that many businesses are nowhere near prepared for the new legislation’s demands that they: re-establish a legal basis for using people’s data (whether that’s consent or otherwise), are able to quickly respond to subject access requests, can delete people’s data if asked to, the list goes on!

So, what does all this mean for your organisation? Well, firstly, there is no need to panic. Hopefully, you have made a start on your compliance journey, even if you’re not going to make the deadline.  Any business that deals with personal data in the UK is currently bound by the terms of the Data Protection Act.  If you comply with the Data Protection Act, then you will have made a great to start towards GDPR compliance. Regardless of GDPR, any business that takes the needs of its customers seriously will already be taking all the appropriate steps to protect its customers information.  Cyber crime and data theft is ever increasing, and organisations must be prepared for a breach and be confident they can deal with it quickly with minimum fall out. Reputational damage can lose you customers and seriously dent your profits.

There has been much GDPR hype over the last few years with talk of extortionate fines and punitive actions should your business fail to comply. The frenzy whipped up by the media and the new GDPR “experts” is unfounded says Elizabeth Denham, the Information Commissioner.  The Information Commissioners Office (ICO) do not intend to start dishing out harsh fines as soon as the regulation comes into place and neither will they target smaller organisations because they will be easier to catch.  The purpose of the ICO has always been to protect peoples’ data and to help business to do this by providing policy and guidance. It follows the carrot before the stick approach and has always viewed issuing large fines as a large resort. Ms Denham has been quoted as saying the implementation of GDPR will not alter this business-friendly approach.

That said, there is no denying the new regulation and the obligations placed upon all business to comply. At this late stage with a round a month to go, all organisations who have not yet addressed GDPR should try to achieve as much as possible in the run up to the 25th May deadline, to build up their compliance and demonstrate that information security is a priority for their business.

  • It is important to show that your organisation takes GDPR seriously and has taken action and has a plan in place to become GDPR ready.
  • Evidence of action taken is crucial.
  • Review all the personal data you hold, where is it, what is it, why do you need it, how long you need to hold it for, and who do you share it with.
  • Identify whether you are the data controller or data processor of this data.
  • Review of all policy and procedures in place around data protection and identify any gaps.
  • Review all contracts, who process personal data on your behalf, update all contracts with a data privacy clause which shows that processor is protecting the data on your behalf as the controller.
  • Demonstrate that you have a tried and tested Incident Response and Data Recovery plans in place should a breach occur.

You’re far less likely to suffer a significant fine if you show documentation of the GDPR compliant processes you have implemented and show a detailed roadmap of achieving anything that you still need to do.

GDPR isn’t all about the race to comply. Once you have tackled your data protection issues your customers will be happy, and you will have minimised the breach of data risk for your organisation. Everyone’s a winner!

OK Google, Alexa, Hey Siri – The Rise of Voice Control Technology

Posted on : 30-04-2018 | By : kerry.housley | In : Consumer behaviour, Finance, FinTech, Innovation, Predictions

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OK Google, Alexa, Hey Siri…. All too familiar phrases around the home now, but it was not that long ago that we did not know what a ‘smart phone’ was! Today most people could not live without one. Imagine not being able to check your email, instant message friends or watch a movie whilst on the move.  How long will it be before we no will no longer need a keyboard, instead talking to your computer will be the norm!

The development of voice activated technology in the home will ultimately revolutionise the way we command and control our computers. Google Home has enabled customers to shop with its partners, pay for the transaction and have goods delivered all without the touch of a keyboard. How useful could this be integrated into the office environment? Adding a voice to mundane tasks will enable employees to be more productive and free up time allowing them to manage their workflow and daily tasks more efficiently.

Voice-based systems has grown more powerful with the use of artificial intelligence, machine learning, cloud-based computing power and highly optimised algorithms. Modern speech recognition systems, combined with almost pristine text-to-speech voices that are almost indistinguishable from human speech, are ushering in a new era of voice-driven computing. As the technology improves and people become more accustomed to speaking to their devices, digital assistants will change how we interact with and think about technology.

There are many areas of business where this innovative technology will be most effective. Using voice control in customer service will transform the way businesses interact with their customers and improve the customer experience.

Many banks are in the process of, if they haven’t done so already, of introducing voice biometric technology. Voice control enables quick access to telephone banking without the need to remember a password every time you call or log in. No need to wade through pages of bank account details or direct debits to make your online payments instead a digital assistant makes the payment for you.

Santander has trialled a system that allows customers to make transfers to existing payees on their account by using voice recognition. Customers access the process by speaking into an application on their mobile device.

Insurance companies are also realising the benefits voice control can bring to their customers. HDFC  Insurance, an Indian firm, has announced the launch of its AI enabled chatbot on Amazon’s cloud-based voice service, Alexa. It aims to offer a 24/7 customer assistance with instant solutions to customer queries. Thereby creating an enhanced customer service experience, allowing them to get easy access to information about policies, simply with the use of voice commands.

It could also help to streamline the claims process where inefficiencies in claims documentation take up insurers’ time and money. Claims processors spend as much as 50% of their day typing reports and documentation; speech recognition could rapidly reduce the time it takes to complete the process. US company Nuance claims that their Dragon Speech Recognition Solution can enable agents to dictate documents three times faster than typing with up to 99% accuracy. They can use simple voice commands to collapse the process further.

Retailers too are turning to this technology. With competition so tough on the high street retailers are always looking for the ultimate customer experience and many believe that voice control is a great way to achieve this. Imagine a mobile app where you could scan shopping items, then pay using a simple voice command or a selfie as you leave the store. No more queuing at the till.

Luxury department store Liberty is a big advocate of voice control and uses it for their warehouse stock picking. Using headsets and a voice controlled application, a voice controlled app issues commands to a central server about which products should be picked. For retailers voice control is hit on and off the shop floor.

So, how accurate is voice recognition? Accuracy rates are improving all the time with researchers commenting that some systems could be better than human transcription. In 1995 the error rate was 43%, today the major vendors claim an error rate of just 5%.

Security is a major factor users still face with verification requiring two factor authentication with mobile applications. However, as the technology develops there should be less of a need to confirm an individual’s identity before commands can be completed.

As advances are made in artificial intelligence and machine learning the sky will be limit for Alexa and her voice control friends. In future stopping what you are doing and typing in a command or search will start to feel a little strange and old-fashioned.

 

How long will it be before you can pick up your smart phone talk to your bank and ask it to transfer £50 to a friend, probably not as far away prospect as you might think!!