Artificial Intelligence

How long until we begin to see a ‘floating c-suite’

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Every company is becoming a technology company and, just as CTOs will need to speak business lingo, CEOs will need to be equally at ease with ‘geek-speak’ as they are talking to shareholders.

“The story of our changing board roles exemplifies the new hybrid technologist-entrepreneur that will come to define the C-suite of the future. Having started out as a technical CEO, I have now switched roles to become CTO”, says Ben Taylor.

To read the full article, see How long until we begin to see a ‘floating c-suite’  on CEO Today.

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Riding the learning curve

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Neural networks are being increasingly deployed across society in everything from predicting crime to policing financial fraud. They are helping make smarter insights and decisions at unprecedented speed and scale. “Yet the increasing use of machine-learning systems also poses little-known risks to privacy, legal accountability and security,” reiterates Ben Taylor, CTO, Rainbird.

To read the full article, see Riding the learning curve on Computer Security.

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Why Government must turn AI from a ‘black box’ into a glass house

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The use of Artificial Intelligence is already widespread across the public sector and even central government departments and this looks set to dramatically increase in coming years. It will bring some £17 billion in efficiency. Trust in public institutions could be jeopardized if the state begins to adopt forms of AI whose inner workings are not widely or easily understood.

To continue reading the full article, see  Why Government must turn AI from a ‘black box’ into a glass house on UK Tech News.

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The financial sector must embrace transparency in artificial intelligence to ensure fairness

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The recent news that the FCA is partnering with the Alan Turing Institute to explore the explainability of AI in financial services is a welcome development. While financial institutions are increasingly using AI to improve efficiency and productivity, there is little transparency in how so-called neural networks make decisions, putting organisations at risk of inaccurate and even fraudulent decisions. Even worse, it is far more difficult for financial institutions to audit bad decisions by AIs than it is to audit human decisions.

Read the full article, The financial sector must embrace transparency in artificial intelligence to ensure fairness on The Fintech Times.

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Captured and Codified: How human expertise is fixing the skills gap using AI

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We are irretrievably losing vital skills because many organisations keep their expertise locked in silos. This means valuable business acumen, skills and expertise are lost forever when the last cohort retires. Codifying human expertise is therefore useful for getting around the skills gap and preventing knowledge-silos.

It is vital to find a way of catching and categorising human skills so that organisations can quickly scale their pool of expertise to meet new demands even during a skills shortage. The key is to create familiar, user-friendly methods of explaining, recording and visualising the reasoning behind everything from insurance claims decisions to checks on meat imports.

To find out more, read the full article Captured and Codified: How human expertise is fixing the skills gap using AI, on Technology Business Today.

 

 

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Explainable AI and the rebirth of rules

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Artificial intelligence (AI) has been described as a set of “prediction machines.” In general, technology is great at generating automated predictions. But if you want to use artificial intelligence in a regulated industry, you better be able to explain how the machine predicted a fraud or criminal suspect, a bad credit risk, or a good candidate for drug trials.

Read the full article, Explainable AI and the Rebirth of Rules on Forbes.

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Regulating the inscrutable

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Ben Taylor, CTO of automated decision-making platform Rainbird and advisor to the All Party Parliamentary Group on AI (APPG AI) argues that it’s time for policymakers to collaborate more in the fight for AI transparency and not bury their heads in the sand hoping tech companies will self-regulate.

Read the full article, Regulating the Inscrutable on Technative.

 

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Transparency is critical to an AI-led future

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For too long, and in too many spheres of public life, labyrinthine AI systems that apply algorithms to huge datasets have been the norm in automation and, except for data scientists, not everyone is able to understand how they work. The consensus-building across Europe is that this mode of AI needs to be made more accessible and accountable – and rightly so. Promoting transparent, human-down AI is the way to make it happen.

Read the full article, Transparency is critical to an AI-led future on The European.

 

 

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Explainable AI: Dissecting the development of auditable artificial intelligence

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Ben Taylor, CTO of Rainbird, discusses the issues of transparency in the way that AI operates – especially when it comes to algorithms which make financial, legal or healthcare decisions

Read the full article, Explainable AI: Dissecting the development of auditable artificial intelligence on Computing.

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What if machines could teach themselves?

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One of the big conundrums with AI is the paradox that it will help solve the skills shortage across many sectors but will require skilled operators to ‘teach’ the machines how to think
Read the full article, What if machines could teach themselves? on  Racounter.
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