Welcoming Robots to the Team

Posted on : 30-05-2018 | By : richard.gale | In : Finance, FinTech, Innovation

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Research suggests that that the adoption of Robotic Process Automation (RPA) and AI technologies is set to double by 2019. This marks a fundamental change in how organisations work and the potential impact on employees should not be underestimated.

For many years we have seen robots on the factory floor where manual processes have been replaced by automation. This has drastically changed the nature of manufacturing and has inevitably led to a reduction in these workforces.  It is understandable therefore, that we can hear the trembling voices of city workers shouting, “the robots are coming!”

Robotic software should not be thought of as the enemy but rather as a friendly addition to the IT family.  A different approach is needed. If you were replacing an excel spreadsheet with a software program an employee would see this as advantage, as it makes their job quicker and easier to do, therefore welcome the change. Looking at RPA in the same way will change the way employees view its implementation and how they feel about it.

There is no doubt that in some cases RPA is intended as a cost saver but organisations that see RPA as simply a cost saving solution will reap the least rewards. For many companies who have already completed successful RPA programmes, the number one priority has been to eliminate repetitive work that employees didn’t want or need to do. Approaching an RPA project in a carefully thought out and strategic manner will provide results that show that RPA and employees can work together.

Successful transformation using RPA relies on an often used but very relevant phrase  “it’s all about the People Process and Technology”.  You need all three in the equation. It is undeniable that automation is a disruptive technology which will affect employees outlook and affect the way they work. Change management is key in managing these expectations. If robots are to be a part of your organisation, then your employees must be prepared and included.

Perhaps it’s time to demystify RPA, and see it for what is really is, just another piece of software! Automation is about making what you do easier to execute, with less mistakes and greater flexibility. It is important to demonstrate to your staff that RPA is part of a much wider strategic plan of growth and new opportunities.

It is vital to communicate with staff at every level, explaining the purpose of RPA and what it will mean for them. Ensure everyone understands the implications and the benefits of the transition to automation. Even though activities and relationships within an organisation may change this does not necessarily mean a change for the worst.

Employees must be involved from the start of the process. Those individuals who have previously performed the tasks to be automated will be your subject matter experts. You will need to train several existing employees in RPA to manage the process going forward.  Building an RPA team from current employees will ensure that you have their buy- in which is crucial if the implementation is to be a success.

With any new software training is often an afterthought. In the case of RPA training is more important than ever, ensuring that the robots and employees understand each other and can work efficiently together. Working to train RPA experts internally will result in a value-added proposition for the future when it comes to maintaining or scaling your solution.

When analysing the initial RPA requirements, a great deal of thought must be given to the employees who are being replaced and where their skills can be effectively be redeployed. Employee engagement increases when personnel feel that their contribution to the organisation is meaningful and widespread.

Consultation and collaboration throughout the entire process will help to ensure a smoother transition where everyone can feel the benefits. Following a successful RPA implementation share the results with everyone in your organisation.  Share the outcomes and what you have learnt, highlight those employees and teams that have helped along the way.

The robots are coming! They are here to help and at your service!

AI Evolution: Survival of the Smartest

Posted on : 21-05-2018 | By : richard.gale | In : Innovation, Predictions

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Artificial intelligence is getting very good at identifying things: Let it analyse a million pictures, and it can tell with amazing accuracy which show a child crossing the road. But AI is hopeless at generating images of people or whatever by itself. If it could do that, it would be able to create visions of realistic but synthetic pictures depicting people in various settings, which a self-driving car could use to train itself without ever going out on the road.

The problem is, creating something entirely new requires imaginationand until now that has been a step to far for machine learning.

There is an emerging solution first conceived by  Ian Goodfellow during an academic argument in a bar in 2014… The approach, known as a generative adversarial network, or “GAN”, takes two neural networksthe simplified mathematical models of the human brain that underpin most modern machine learningand pits them against each other to identify flaws and gaps in the others thought model.

Both networks are trained on the same data set. One, known as the generator, is tasked with creating variations on images it’s already seenperhaps a picture of a pedestrian with an extra arm. The second, known as the discriminator, is asked to identify whether the example it sees is like the images it has been trained on or a fake produced by the generatorbasically, is that three-armed person likely to be real?

Over time, the generator can become so good at producing images that the discriminator can’t spot fakes. Essentially, the generator has been taught to recognize, and then create, realistic-looking images of pedestrians.

The technology has become one of the most promising advances in AI in the past decade, able to help machines produce results that fool even humans.

GANs have been put to use creating realistic-sounding speech and photo realistic fake imagery. In one compelling example, researchers from chipmaker Nvidia primed a GAN with celebrity photographs to create hundreds of credible faces of people who don’t exist. Another research group made not-unconvincing fake paintings that look like the works of van Gogh. Pushed further, GANs can reimagine images in different waysmaking a sunny road appear snowy, or turning horses into zebras.

The results aren’t always perfect: GANs can conjure up bicycles with two sets of handlebars, say, or faces with eyebrows in the wrong place. But because the images and sounds are often startlingly realistic, some experts believe there’s a sense in which GANs are beginning to understand the underlying structure of the world they see and hear. And that means AI may gain, along with a sense of imagination, a more independent ability to make sense of what it sees in the world. 

This approach is starting to provide programmed machines with something along the lines of imagination. This, in turn, will make them less reliant on human help to differentiate. It will also help blur the lines between what is real and what is fake… And in an age where we are already plagued with ‘fake news’ and doctored pictures are we ready for seemingly real but constructed images and voices….