Artificial Intelligence

Rainbird sponsors University of East Anglia's Moneyhack learning programme

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The Moneyhack initiative looks to produce future bankers, lawyers, accountants, business consultants and insurance specialists, in a way that anticipates and teaches the skills that students will need to succeed in the future as technology continues to advance.

These include the “soft skills” that will become so crucial to thriving businesses, as automation begins to refocus many roles away from repetitive tasks and towards delivering great service and new revenue.

The initiative’s seeks to help close the skills gap in our economy for years to come, after our recent study found that the main reason behind 81% of businesses not implementing AI is a shortage of talent in their workforce for building automation processes.

Rainbird was a supporting organisation alongside firms including Aviva, Barclays and Mills & Reeve.

Raphael Markellos, Professor of Finance at UEA, created and coordinated the programme and said: “Educational programmes in schools struggle to keep up with technological developments, particularly in the financial and professional services sector. Our initiative bridges this gap.”

James Duez, Rainbird CEO and longtime advocate of transparent automation to address the skills gap, said: “While a large part of addressing this problem lies with educators, it is hard for them to keep up with the pace of change. It is equally necessary that those behind these new technologies ensure they are transparent and designed to be understood by a greater proportion of the population.”

Read the full press release here.

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6 reasons why learning Rainbird is beneficial for your career

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  1. You’ll be a better consultant

Rainbird’s human-centric automation is a unique emerging technology in the industry, and understanding how it works is a huge advantage – both in being able to sell a Rainbird solution to your clients, but also through being the gate-keeper for a desirable commodity.

 

  1. You’ll improve your analytical skills

The skills needed to break down what we call ‘subject matter expertise’ for Rainbird involve understanding a set of human inferences that are not widely understood in the wider RPA (robotic process automation) landscape or by automation consultancies. The nature of the subject matter itself is also very different: whilst the data on which human judgements are based has long been available as subject matter, human judgements, and how those judgements are reached, has never been subject matter for automation before. We’ve even had clients tell us that the process of mapping out their business logic has forced them into the invaluable exercise of confronting, and re-evaluating, their own thinking.

 

  1. You’ll look at things differently

Traditionally, RPA technologies require that decisions are broken down into formalised logic, requiring the removal of nuance and complete, unambiguous datasets and processes for successful implementation. Before Rainbird, there was an industry standard possible for if-this-then-that process automation; now, authors in Rainbird learn to structure their reasoning, a skill that is completely unfamiliar to most solution consultants.

 

  1. You’ll be able to do business with clients that no one else can help

Successfully replicating human reasoning, instead of relying on a decision tree, is industry-changing. Applying a new technology to use cases that we’ve never been able to automate before, due to the multi-faceted nature of human inference, provides an undeniable competitive edge.

 

  1. You’ll be a sought-after resource.

Maintenance of this emerging strand of unique automated reasoning technology is going to be a sought-after and exceptionally rare skill – you can capitalise on your Rainbird understanding as knowledge maps proliferate in the RPA marketplace.

 

  1. You’ll be able to maximise other technologies more scalably.

Infrastructure in process flow automation is maturing, with big players like Blue Prism and PEGA expanding in the space. Learning Rainbird – the only technology that can tie together these embedded process flow systems in the same way as human reasoning currently does – is crucial in maximising these flow techs scalably. 

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How intelligent automation can future-proof businesses for changing regulation

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Whether it’s IFSR 17 in insurance, IR35 in accounting, the continued refinement of EU customer data policies, or any number of Brexit-based logistical challenges, businesses are having to scramble for the right tools to react to the impact of changing legislation. The result has been a boom in compliance personnel over the past decade. Surely there’s another way?

Discover with Rainbird’s Marcus Vassiliou how intelligent automation can help you stay on top and adapt to ever-changing regulations.

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81% of UK businesses say a shortage of talent is the biggest hurdle to AI adoption

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The research, conducted by Vanson Bourne on behalf of Rainbird, surveyed senior decision-makers in enterprise organisations. It found that the main reason behind businesses not implementing AI is a shortage of talent in their workforce for handling automation processes. While this was the overall biggest barrier to adopting AI in the UK, when broken down into professional services, financial services, insurance and IT, the data highlighted a number of different concerns across business functions.

View the full report.

James Duez, CEO at Rainbird, commented: “In order to truly understand what processes will benefit from AI, businesses must review their strategies. Rather than pushing AI investment into IT departments, organisations should recognise where the most important decisions are being made – within the business. Symbolic tools are business-friendly, rapid to work with and completely auditable and it is these that will unlock the streamlining and automation of operational decisions.”

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Neural networks can disempower human workers: the case for human intervention amidst rapid AI adoption

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Neural networks have become the alchemy of our age, the search for a magical, mystical process that allows you to turn a pile of data into gold. It is widely seen as a silver bullet that can generate new insights and expert decisions on an unprecedented speed and scale. Yet this ignores the reality that ‘deep learning’ systems are difficult to create or audit and most organisations lack the necessary in-house expertise or ‘data hygiene’ to use it effectively.

To read the full article, see Neural networks can disempower human workers: the case for human intervention amidst rapid AI adoption on Digitalisation World. 

 

 

 

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Ghosts in the Machine: How Machine Learning is Transforming Business

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According to new research from Rainbird – the AI-powered automated decision-making platform, 81% of those surveyed revealed that their organisation planned to increase investment in AI over the next five years. Of those who plan to increase spending on automation technologies, 22% suggested this investment would be significant. Interestingly, the financial sector is set to be the biggest adopter, with 94% of those surveyed planning to increase investment in AI over the coming years.

James Duez, CEO at Rainbird, commented: “AI should be brought into organisations to help employees, not hinder them. UK organisations – and beyond – need to fundamentally change the way they are adopting AI and, think beyond big data and machine learning. ‘Data scientists only understand black box solutions, and there are huge benefits to be had by moving towards more transparent symbolic technologies which can achieve automation outcomes beyond those available with data-only approaches. Such accessible tools also have the added benefit of addressing the skills gap by making AI far more accessible to employees without a degree in data science.”

To read the full article, see Ghosts in the Machine: How Machine Learning is Transforming Business on Silicon UK.

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Predictions of future robo-advice 'premature'

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Mr McNamara, chief executive of the fintech group Evalue discusses with Ben Taylor, CTO of Rainbird, the issue of regulation and the challenges businesses faced within the robo-advice space.

Mr Taylor said: “Regulation will look very different depending on what type of robo-advice is being used. It might be that we’re using statistical methods to do some prior analysis of data to do future predictions. Regulating that would be a very different kettle of fish to regulating some sort of human type reasoning, which you could explain. It depends on the underlying technology and what the customer outcomes are expected to be.”

To read the full article, see Predictions of future robo-advice ‘premature’ on The FTAdviser.

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91% of UK IT businesses say a shortage of talent is the biggest hurdle to AI adoption

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The adoption of Artificial Intelligence (AI) and automation technologies in the UK is still being stunted by a lack of digital skills in businesses according to new research by Rainbird, the AI-powered automated decision-making platform.

To read the full article, see 91% of UK IT businesses say a shortage of talent is the biggest hurdle to AI adoption on Digitalisation World.

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AI is matching doctors at image-based diagnosis

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Research suggests deep learning algorithms have become as good at image-based medical diagnosis as human doctors – and maybe even better.

“The feasibility of this approach must be considered hand-in-hand with the issue of trust,” added James Duez, CEO and co-founder of automation software vendor Rainbird.

“Any AI-powered decision must have an interpretable rationale if the technology is to be trusted and scale, a limitation to many machine-learnt approaches. That’s why in most cases, a human domain expert (in this case a radiologist) must review the AI opinion and put their name to it.”

To read the full article, see AI is matching doctors at image-based diagnosis on AI Business.

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Head of Scotland Yard warns reliance on AI in policing could lead to a dystopian future

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Cressida Dick acknowledged that AI-based tools had the potential to help fight crime but said the use of such tools had to be accompanied by strict rules to prevent abuse.

“The real problem with deep-learning AI solutions being used in policing is that they have the potential to make discriminatory decisions without being detected,” explained Ben Taylor, CTO at Rainbird, which develops AI-powered automation technologies.

To read the full article, see Head of Scotland Yard warns reliance on AI in policing could lead to a dystopian future on AI Business.

 

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