Category: Artificial intelligence

Leaders are blindly ignoring the dangers of ‘confidently incorrect’ AI – and why it’s a massive problem

Why don’t scientists trust atoms? Because they make everything up. 

When Greg Brockman, president and co-founder of OpenAI, demonstrated the possibilities of GPT-4 – Generative Pre-trained Transformer 4, the fourth-generation autoregressive language model that uses deep learning to produce human-like text – upon launch on Mar. 14, he tasked it to create a website from a notebook sketch. 

Brockman prompted GPT-4, on which ChatGPT is built, to select a “really funny joke” to entice would-be viewers to click for the answer. It chose the above gag. Presumably, the irony wasn’t purposeful. Because the issues of “trust” and “making things up” remain massive, despite the incredible yet entrancing capabilities of generative artificial intelligence. 

Many business leaders are spellbound, stated futurist David Shrier, professor of practice (AI and innovation) at Imperial College Business School in London. And it was easy to understand why if the technology could build websites, invent games, create pioneering drugs, and pass legal exams – all in mere seconds.

Those impressive feats are making it more challenging for leaders to be clear-eyed, said Shrier, who has written books on nascent technologies. In the race to embrace ChatGPT, companies, and individual users, are “blindly ignoring the dangers of confidently incorrect AI.” As a result, he warned that significant risks are emerging as companies rapidly race to re-orient themselves around ChatGPT without being aware of – or ignoring – the numerous pitfalls.

The full version of this article was first published on Digiday’s future-of-work platform, WorkLife, in March 2023 – to read the complete piece, please click HERE.

WTF is the Turing trap – and how businesses that embrace AI can avoid it

All the recent chatter about ChatGPT and advancements in generative artificial intelligence has been impossible to avoid for business leaders. More than ever, they are being urged to embrace AI. 

True, if used correctly, it can improve efficiencies and forecasting while reducing costs. But many people make the mistake of thinking AI could – and should – be more human. 

Science-fiction tropes do not help this perception. Additionally, Alan Turing’s famous test for machine intelligence, proposed in 1950, has conditioned us to think about this technology in a certain way. Originally called the imitation game, the Turing test was designed to gauge the cleverness of a machine compared to humans. Essentially, if a machine displays intelligent behavior equivalent to, or indistinguishable from, that of a human, it passes the Turing test.

But this is a wrongheaded strategy, according to professor Erik Brynjolfsson, arguably the world’s leading expert on the role of digital technology in improving productivity. Indeed, the director of the Digital Economy Lab at the Stanford Institute for Human-Centered AI recently coined the term the Turing trap, as he wanted people to avoid being snared by this approach.

So what exactly is the Turing trap?

The full version of this article was first published on Digiday’s future-of-work platform, WorkLife, in March 2023 – to read the complete piece, please click HERE.

Stanford professor on the AI skills gap and the dangers of exponential innovation

ChatGPT and its ilk represent a welcome quantum leap for productivity, according to eminent AI expert professor Erik Brynjolfsson. But he adds that such rapid developments also present a material risk

Erik Brynjolfsson is in great demand. The US professor whose research focuses on the relationship between digital tech and human productivity is nearing the end of a European speaking tour that’s lasted nearly a month. Despite this, he’s showing no signs of fatigue – quite the opposite, in fact. 

Speaking via Zoom as he prepares for his imminent lecture in Oxford, the director of the Digital Economy Lab at the Stanford Institute for Human-Centered AI is enthused by recent “seminal breakthroughs” in the field.

Brynjolfsson’s tour – which has included appearances at the World Economic Forum in Davos and the Institute for the Future of Work in London – is neatly timed, because the recent arrival of ChatGPT on the scene has been capturing human minds, if not yet hearts. 

The large-scale language model, fed 300 billion words by developer OpenAI, caused a sensation with its powerful capabilities, attracting 1 million users within five days of its release in late November 2022. At the end of January, Microsoft’s announcement of a substantial investment in OpenAI “to accelerate AI breakthroughs” generated yet more headlines. 

ChatGPT’s popularity is likely to trigger an avalanche of similarly extraordinary AI tools, Brynjolfsson predicts, with a possible economic value extending to “trillions of dollars”. But he adds that proper safeguards and a better understanding of how AI can augment – not replace – jobs are urgently required.

What’s next in AI?

“There have been some amazing, seminal breakthroughs in AI lately that are advancing the frontier rapidly,” Brynjolfsson says. “Everyone’s playing with ChatGPT, but this is just part of a larger class of ‘foundation models’ that is becoming very important.”

He points to the image generator DALL-E (another OpenAI creation) and lists similar tools designed for music, coding and more. Such advances are comparable to that of deep learning, which enabled significant leaps in object recognition a decade ago. 

“There’s been a quantum improvement in the past couple of years as these foundational models have been introduced more widely. And this is just the first wave,” Brynjolfsson says. “The folks working on them tell me that there’s far more in the pipeline that we’ll be hearing about in the coming weeks.”

As much as I’m blown away by these technologies, the bottleneck is our human response

When pushed for examples of advances that could shape the future of work, he reveals that Generative Pre-trained Transformer 3 (GPT-3) – the language model that uses deep learning to emulate human writing – will be superseded by GPT-4 “within weeks. This is a ‘phased change of improvement’ compared with the last one, but it’ll be even more capable of solving all sorts of problems.” 

Elsewhere, great strides are being made with “multi-agent systems” designed to enable more effective interactions between AI and humans. In effect, AI tech will gain the social skills required to cooperate and negotiate with other systems and their users. 

“This development is opening up a whole space of new capabilities,” Brynjolfsson declares.

The widening AI skills gap

As thrilling as these pioneering tools may sound, the seemingly exponential rate of innovation presents some dangers, he warns. 

“AI is no longer a laboratory curiosity or something you see in sci-fi movies,” Brynjolfsson says. “It can benefit almost every company. But governments and other organisations haven’t been keeping up with developments – and our skills haven’t either. The gap between our capabilities and what the technology enables and demands has widened. I think that gap will be where most of the big challenges – and opportunities – for society lie over the next decade or so.”

Brynjolfsson, who studied applied maths and decision sciences at Harvard in the 1980s, started in his role at Stanford in July 2020 with the express aim of tackling some of these challenges. 

“We created the Digital Economy Lab because, as much as I’m blown away by these technologies, the bottleneck is our human response,” he says. “What will we do about the economy, jobs and ethics? How will we transform organisations that aren’t changing nearly fast enough? I want to speed up our response.”

Brynjolfsson spoke passionately about this subject at Davos in a session entitled “AI and white-collar jobs”. In it, he advised companies to adopt technology in a controlled manner. Offering a historical analogy, he pointed out that, when electricity infrastructure became available about a century ago, it took at least three decades for most firms to fully realise the productivity gain it offered because they first needed to revamp their workplaces to make the best use of it. 

“We’re in a similar period with AI,” Brynjolfsson told delegates. “What AI is doing is affecting job quality and how we do the work. So we must address to what extent we keep humans in the loop rather than focus on driving down wages.”

Why AI will create winners and losers 

The risk of technology racing too far ahead of humanity for comfort is a familiar topic for Brynjolfsson. In both Race Against the Machine (2011) and The Second Machine Age (2014), he and his co-author, MIT scientist Andrew McAfee, called for greater efforts to update organisations, processes and skills. 

AI can benefit almost every company. But governments and other organisations haven’t been keeping up with developments – and our skills haven’t either

How would he assess the current situation? “When we wrote those books, we were optimistic about the pace of technological change and pessimistic about our ability to adapt,” Brynjolfsson says. “It turns out that we weren’t optimistic enough about the technology or pessimistic enough about our institutions and skills.”

In fact, the surprising acceleration of AI means that the “timeline for when we’ll have artificial general intelligence” should be shortened by decades, he argues. “AGI will be able to do most of the things that humans can. Some predicted that this would be achieved by the 2060s, but now people are talking about the 2030s or even earlier.”

Given the breakneck speed of developments, how many occupations are at risk of obsolescence through automation? 

Brynjolfsson concedes that the range of roles affected is looking “much broader than earlier thought. There will be winners and losers. Jobs will be enhanced in many cases, but some will be eliminated. Routine work will become increasingly automated – and there will also be a flourishing of fantastic creativity. If we use these tools correctly, there will be positive disruption. If we don’t, inequality could deepen, further concentrating wealth and political power.” 

How to apply AI in the workplace

How, then, should businesses integrate AI into their operations? First, they must avoid what Brynjolfsson has labelled the Turing trap. 

“One of the biggest misconceptions about AI – especially among AI researchers, by the way – is that it needs to do everything that humans do and replace them to be effective,” he explains, arguing that the famous test for machine intelligence, proposed by Alan Turing in 1950, is “an inspiring but misguided vision”.

Brynjolfsson contends that a “mindset shift” at all levels – from scientists and policy-makers to employers and workers – is required to harness AI’s power to shape society for good. “We should ask: ‘What do we want these powerful tools for? And how can we use them to achieve our goals?’ The tools don’t decide; we decide.”

One of the biggest misconceptions about AI is that it needs to do everything that humans do and replace them

He adds that many business leaders have the wrong attitude to applying new tech in general and AI in particular. This amounts to a “pernicious problem”. 

To illustrate this, he cites Waymo’s experiments with self-driving vehicles: “These work 99.9% of the time, but there is a human safety driver overseeing the system and a second safety driver in case the first one falls asleep. People watching each other is not the right path to driverless cars.”

Brynjolfsson commends an alternative route, which has been taken by the Toyota Research Institute, among others. When he was in Davos, the institute’s CEO, Dr Gill Pratt “told me how his team has flipped things around so that the autonomous system is used as the guardian angel. Creating a self-driving car that works in all possible conditions is tough, but humans can handle those exceptions.” 

With a person making most decisions in the driving seat, the AI intervenes “occasionally – for instance, when there’s a looming accident. I think this is a good model, not only for self-driving cars, but for many other applications where humans and machines work together.” 

For similar reasons, Brynjolfsson lauds Cresta, a provider of AI systems for customer contact centres. Its products keep humans “at the forefront” of operations instead of chatbots, whose apparent Turing test failures continue to frustrate most people who deal with them. 

“The AI gives them suggestions about what to mention to customers,” he says. “This system does dramatically better in terms of both productivity and customer satisfaction. It closes the skills gap too.”

Does Brynjolfsson have a final message for business leaders before he heads off to give his next lecture? “We need to catch up and keep control of these technologies,” he says. “If we do that, I think the next 10 years will be the best decade we’ve ever had on this planet.”

This article was first published by Raconteur, as part of the Future of Work special report in The Times, in February 2023

The best business uses for automation

Every business leader knows that robotics and AI can reduce operating costs and free up employees for more enjoyable tasks. But how is automation fitting into common business functions?

Finance

Finance professionals spend a chunk of their time collecting, tracking and chasing receipts and invoices – up to 2.7 working days every month, according to research by spend management specialists Moss. Yet up to 16 working hours for every 100 transaction-related tasks could be saved by adopting an automated spend management platform. That’s according to Saray Hamarneh, strategy and business development manager at Moss.

Waste-management company Biffa has triumphed after binning its old cash-collection system. Emily Munnoch, the firm’s finance director for shared services, explains that an AI-powered order-to-cash platform has helped to secure and accelerate cash flow – by expediting invoice payments and managing disputes and credit risk. “Our dunning success rate has improved by 22.5%, which has reduced overdue debt and improved cash flow for the business,” she says.

And there are further benefits. “All of our credit controllers love using the platform, and it has enhanced customer communications because we can now communicate electronically with more than 99% of our customer base,” she adds.

Elsewhere, Ilija Ugrinic, commercial solutions director at Proactis, an international payments software business, offers two examples. His company saved Screwfix £100,000 year-on-year after introducing “one standardised, integrated automation solution that streamlined receipt, approval and exception handling”. Additionally, Wigan Council, which deals with around 90,000 invoices a year, improved invoice processing by 66% using Proactis’ solution and generated an annual saving of £120,000.

HR and recruitment

Shayne Simpson is managing director of TechNET IT Recruitment. He admits that he took a risk in choosing a solution that automates recruitment processes and communication with candidates using staffing software company Bullhorn’s cloud-based platform. But he insists that the gamble has paid off. 

“In the last six months we have saved 28,609 hours, sent 144,269 automatic emails with a 53% read rate, and sent 45,852 texts,” says Simpson. “All of this equates to the admin of 30 full-time consultants being completed by a robot every month.”

Jason Heilman is Bullhorn’s senior vice-president for automation, AI and talent experience. He points out that the average recruitment firm currently automates more than 20,000 emails, texts, updates, notes and tasks each year. “Cumulatively, this represented an estimated saving of 2.5 million employee hours in 2021 alone, equal to freeing up three hours every day per recruiter,” he says.

Chris Underwood, managing director for executive search consultancy Adastrum, though, is ambivalent. “It’s important to question the reliability of AI in implementing the diversity and inclusion agenda during recruitment,” he warns. “Take Amazon, for example, which no longer uses AI in HR as it discovered its AI-driven candidate screening discriminated against women.

“Removing the human element from HR will only frustrate and limit the candidate’s company experience if interviews are robotic.”

Legal and compliance

The legal sector has been slow to take up AI and robotics. “The scope for efficiencies in legal processes is staggering,” says Jonathan White, legal and compliance director at National Accident Helpline. “While law firms have been behind the curve, we’re beginning to see significant advantages, particularly in automating processes around creating documents with common features such as non-disclosure agreements.” JPMorgan’s contract analysis solution, Coin, can reportedly complete 36,000 hours’ worth of legal work in mere seconds, White explains.

Tom Dunlop, co-founder and CEO of legal tech developer and provider Summize, claims to have developed the world’s first integrated contract lifecycle management solution. “The average reported time to review one contract manually is approximately 92 minutes,” he says. “With large organisations managing an average of 350 contracts each week, speeding up this process makes a huge difference.” Summize’s product, which uses AI and natural language processing, means a contract can be created in under two minutes and then the first-pass review in under five minutes. “Clients report time savings of 85% or more compared to manual processes,” he adds.

With nearly a quarter of a million legal contracts stored within one central system, Elliott Young, chief technology officer at Dell Technologies UK, required such a solution. “The legal team was reading approximately 800 contracts per quarter, so processing the repository would have taken 212 quarters or 53 years,” he says. Instead, a proof-of-concept system that combined AI and humans achieved the same results in months.

Marketing

“Automation presents a huge opportunity to build on the foundations of our relationships with customers,” says Carlene Jackson, CEO of Brighton-based digital transformation consultancy Cloud9 Insight. “If a customer follows you on social media, that could trigger a private message which encourages them to download a guide from your website.” That message could then generate timely emails with useful content based on pageviews or links which they have accessed on subsequent visits. 

Natalie Cramp is CEO of data science consultancy Profusion and agrees. “Automating even basic processes like email builds and sends can save marketing teams a lot of time and money. It can also, crucially, increase marketing effectiveness while removing the potential for human error.”

Of course, mistakes can still creep in. In January 2020, for instance, Aviva accidentally called all the customers in its email base “Michael”. Cramp continues: “If businesses can dedicate time to more complex automation, such as data management and algorithms, these can fuel highly personalised customer journeys and lead to a huge impact on customer experience with vastly increased sales.”

Nick Mason, co-founder and CEO of Turtl, a content automation platform, says that personalised content can generate up to 10 times more subscribers. “You can cut the time to produce sales proposals by 90% if you use pre-existing automation engines to create personalised digital documents,” he says.

Customer service

For Virgin Media O2, which has around 47 million customers in the UK, automating its contact centre was a strategic imperative – not least because uncoordinated messaging to the business’s 7,000 agents was leading to inconsistencies and knowledge gaps. 

Last October, it overhauled its processes using Intradiem’s intelligent automation solution. The platform was used to deliver training directly to agents’ desktops; to send notifications to help keep call-handling time within preset thresholds and to facilitate their ability to take breaks on time and to use the off-phone time to stay up to date on internal communications, explains Faye Herring, Virgin Media’s workforce planning manager.

“Within four months of launch, more than 3,500 hours of offline time were delivered to agents’ desktops via Intradiem to make productive use of what had previously been wasted available time,” she says. “And it reduced the average call-handling time by up to 60 seconds.”

Greg Adams, regional vice-president for the UK and Ireland at Dynatrace, offers an equally impressive example. His company’s work enabled UK health and life insurance company Vitality to adopt a proactive servicing model. “Its customer service teams are automatically notified when Vitality’s members encounter errors in their digital experience, so they can contact members and resolve the issue instead of waiting for them to get in touch to ask for help,” Adams says. 

He adds that the proactive customer support capability has helped Vitality to reduce policy lapse rates among members who come up against problems in their digital journey by 65%.

This article was first published by Raconteur in November 2022

How organizations can spot future workforce skills gaps

With technology-powered change being the only constant in the digital age, what skills will pay the bills in the next five years? Moreover, how could — and should — organizations identify the potential gaps in the near future and train employees or hire accordingly to plug them?

According to global data analyzed by LinkedIn, the skillsets required for jobs have changed by 25% from 2015 to 2021. “This figure is expected to double by 2027,” said Becky Schnauffer, LinkedIn’s head of global clients in EMEA and LATAM. 

These findings were mirrored by a Boston Consulting Group report published in May, which showed that 37% of the top 20 skills requested for the average U.S. job had changed from 2016. But which industries have been impacted the most, and which others are at risk?

The LinkedIn Future of Skills report calculated that since 2015, the top three sectors to have experienced the most significant change in required skillsets are hardware and networking (31%), energy and mining (27%), and construction (26%). 

The full version of this article was first published on DigiDay’s future-of-work platform, WorkLife, in November 2022 – to read the complete piece, please click HERE.

The appliance of prescience

Advances in artificial intelligence are giving organisations in both the public and private sectors increasingly powerful forecasting capabilities. How much further down this predictive path is it possible for them to go?

Minority Report, Steven Spielberg’s 2002 sci-fi thriller based on a short story by Philip K. Dick, explores the concept of extremely proactive policing. The film, starring Tom Cruise, is set in 2054 Washington DC. The city’s pre-crime department, using visions provided by three clairvoyants, can accurately forecast where a premeditated homicide is about to happen. The team is then able to dash to the scene and collar the would-be murderer just before they strike.

While police forces are never likely to have crack teams of incredibly useful psychics at their disposal, artificial intelligence has advanced to such an extent in recent years that its powerful algorithms can crunch huge volumes of data to make startlingly accurate forecasts.

Could a Minority Report style of super-predictive governance ever become feasible in the public sector – or, indeed, in business? If so, what would the ethical implications of adopting such an approach be?

There is a growing list of narrow-scope cases in which predictive analytics has been used to fight crime and save lives. In Durham, North Carolina, for instance, the police reported a 39% fall in the number of violent offences recorded between 2007 and 2014 after using AI-based systems over that period to observe trends in criminal activities and identify hotspots where they could make more timely interventions.

AI has also been used to tackle human trafficking in the US, where it has helped the authorities to locate and rescue thousands of victims. Knowing that about 75% of child trafficking cases involve grooming on the internet, the government’s Defense Advanced Research Projects Agency monitors suspicious online ads, detects coded messages and finds connections between these and criminal gangs.

In Indonesia, the government has partnered with Qlue, a specialist in smart city technology, to predict when and where natural disasters are most likely to strike. Its systems analyse flood data collected from sensors and information reported by citizens. This enables it to identify the localities most at risk, which informs disaster management planning and enables swifter, more targeted responses.

While all these cases are positive examples of the power of predictive AI, it would be nigh-on impossible to roll out a Minority Report style of governance on a larger scale. That’s the view of Dr Laura Gilbert, chief analyst and director of data science at the Cabinet Office. “To recreate a precognitive world, you would need an incredibly advanced, highly deterministic model of human behaviour – using an AI digital-twin model, perhaps – with low levels of uncertainty being tolerable,” she says. “It’s not certain that this is even possible.”

An abundance of information is required to understand a person’s likely behaviour, such as their genetic make-up, upbringing, current circumstances and more. Moreover, achieving errorless results would require everyone to be continuously scrutinised.

“Doing this on a grand scale – by closely monitoring every facet of every life; accurately analysing and storing (or judiciously discarding) all the data collected; and creating all the technology enhancements to enable such a programme – would be a huge investment and also cost us opportunities to develop other types of positive intervention,” Gilbert says. “This is unlikely to be even close to acceptable, socially or politically, in the foreseeable future.”

Tom Cheesewright, a futurist, author and consultant, agrees. He doubts that such an undertaking would ever be considered worthwhile, even in 2054. “The cost to the wider public in terms of the loss of privacy would be too great,” Cheesewright argues, adding that, in any case, “techniques for bypassing surveillance are widely understood”.

Nonetheless, Vishal Marria, founder and CEO of enterprise intelligence company Quantexa, notes that the private sector, particularly the financial services industry, is making great use of AI in nipping crimes such as money-laundering in the bud. “HSBC has pioneered a new approach to countering financial crime on a global scale across billions of records,” he says. “Only by implementing contextual analytics technology could it identify the risk more accurately, remove it and enable a future-proof mitigation strategy.”

Alex Case, senior director in EMEA for US software company Pegasystems, believes that governments and their agencies can take much from the private sector’s advances. Case, who worked as a deputy director in the civil service from 2018 to 2021, says: “The levels of service being routinely provided by the best parts of the private sector can be replicated in government. In contrast with the dystopian future depicted in Minority Report, the increasing use of AI by governments may lead to a golden age of citizen-centric public service.”

Which other operations or business functions have the most to gain from advances in predictive analytics? Cheeswright believes that “the upstream supply chain is an obvious one in the current climate. If you can foresee shortages owing to pandemics, wars, economic failures and natural disasters, you could gain an enormous competitive advantage.”

The biggest barriers to wielding such forecasting power are a lack of high-quality data and a shortage of experts who can analyse the material and draw actionable insights from it. “Bad data can turn even a smooth deployment on the technology side into a disaster for a business,” notes Danny Sandwell, data strategist at Quest Software. “Data governance – underpinned by visibility into, and insights about, your data landscape – is the best way to ensure that you’re using the right material to inform your decisions. Effective governance helps organisations to understand what data they have, its fitness for use and how it should be applied.”

Sandwell adds that a well-managed data governance programme will create a “single version of the truth”, eliminating duplicate data and the confusion it can cause. Moreover, the most advanced organisations can build self-service platforms by establishing standards and investing in data literacy. “Data governance enables a system of best practice, expertise and collaboration – the hallmarks of an analytics-driven business,” he says.

Gilbert offers business leaders one final piece of advice in this area: recruit carefully. She argues that “a great data analyst is worth, at a conservative estimate, 20 average ones. They can often do things that any number of average analysts working together still can’t achieve. What’s more, a bad analyst will cost you both money and time.”

And, as Minority Report’s would-be criminals in discover to their cost, time is the one resource that’s impossible to claw back.

This article was first published in Raconteur’s Future of Data report in October 2022

Strike out: Industrial action could accelerate the shift to automated jobs

Set against the backdrop of a cost-of-living crisis, the so-called “summer of discontent” in the U.K. — which has seen strikes from railway workers, criminal barristers, Post Office employees, teachers, airport staff, healthcare staff, and others—looks likely to extend through the winter. And the feeling of dissatisfaction is not limited to the U.K., with workers downing tools across the globe.

Although the U.K. lawyers finally stepped away from the picket line in early October, accepting the government’s 15% pay raise, Royal Mail staff and railway workers are currently participating in long-running industrial action to resolve disputes about salary and working conditions. 

Ironically, the crux of the matter is job security, yet the prolonged absence from work only strengthens the argument for investing in automation that will, ultimately, reduce headcount.

The full version of this article was first published on DigiDay’s future-of-work platform, WorkLife, in October 2022 – to read the complete piece, please click HERE.

‘It’s a future that’s upon us’: Will robots ever have the top jobs?

How would you feel about having a robot boss? And not just a line manager but the head honcho of the company.

You might think this is an idle, hypothetical question. Indeed, back in 2017, then-Alibaba CEO Jack Ma stated we are mere decades from having robots at the helm of organizations. He predicted that by 2047, a robot CEO would make the cover of Time magazine.

And yet, those provocative guesstimates from five years ago now look generous. In late August, the world’s first artificial intelligence-powered, humanoid robot CEO, called Mika, was appointed to the top job at Dictador, a luxury rum company.

The full version of this article was first published on DigiDay’s future-of-work platform, WorkLife, in October 2022 – to read the complete piece, please click HERE.

How employee monitoring has shifted from creepy to empowering HR teams

A friend giddily informed me a few days ago that she had “found the perfect eraser.” Perplexed as to why something that rubs out pencil marks would evoke such glee, I asked for more details. “This eraser is the ideal weight; I can rest it on the space bar, so the screen stays awake if I leave the desk,” she said. “That way, my manager thinks I’m still being active at my computer.”

Employees who feel they are being observed for no good reason tend to find a way to game the system, argued Brian Kropp, group vp and chief of research for Gartner’s HR practice. “If your employer is trying to screw you by creepily monitoring you, there are various things you can do to screw them over,” he said.

For instance, he revealed that if computer mouse activity is being tracked, then an analog watch can help. If you position the mouse on the watch, then the second hand creates just enough motion to make it still active.

Monitoring is on the rise, though. According to Gartner’s research, around 30% of the medium and large corporate organizations it assesses had tracking systems in place before the pandemic. “Now the percentage is more than 60%,” said Brian Kropp, group vp and chief of research for Gartner’s HR practice.

This article was first published on DigiDay’s future-of-work platform, WorkLife, in September 2022 – to read the complete piece, please click HERE.

How technology can help financial services organisations reach younger generations

Smartphone apps, gamification and proactive support are some of the ways operators can engage the digital natives of today and tomorrow

Baby boomers might have a majority of global wealth today, but tomorrow it will be different. Indeed, by 2030, Europe’s younger generations – millennials and gen z – are due to inherit around £2.3 trillion from their parents, according to recent estimates. How can financial service operators cash in on this great wealth transfer?

In 2022, client-facing teams operating in the financial service industry can – and must – leverage technology to build meaningful relationships with younger generations who are digital natives. 

Indeed, over a third (34%) of 18- to 34-year-olds would choose a different financial services provider if they were expected to visit a branch in person, according to VMware’s recent Digital Frontiers 4.0 report, which surveyed over 2,000 UK consumers. 

Similarly, Marqeta’s 2022 Consumer Money Movement report reveals generational differences. Over half (54%) of gen z – born between 1997 and 2012 – can’t recall their PINs, and more than three-quarters (77%) feel confident enough with contactless payments to leave their wallets at home and just go out with their phones. 

Consider a Chase study from 2021 indicated that 99% of gen z and 98% of Millennials use mobile banking apps, compared to 86.5% of gen x and 69.5% of Boomers.

“Younger markets live on their smartphones,” says Ben Johnson, CEO of digital transformation consultants BML Digital. “Everything needs to be available via the app, and the mobile experience has to match the ease of something like Snapchat or Pinterest.” 

Prakash Pattni, managing director of financial services digital transformation in EMEA for IBM, agrees. “Ultimately, younger consumers want to access their accounts, lock missing cards, make virtual payments and transfer money to others swiftly and securely,” he says. “Financial institutions must develop easy-to-use applications with superior uptime that can easily integrate with other apps.”

Gamification and proactive support

How can financial services operators generate trust with younger generations? “Technology is the answer,” posits Somya Patnaik, a market product manager specialising in real-time payments at ACI Worldwide. “They must bring more innovative features that will engage young people and improve their consumer experience.”

Gamification in financial services is winning a lot of trust among young consumers, suggests Patnaik. So, for instance, insurance companies might build an app that tracks fitness activities against pre-agreed goals, which, if hit, unlock rewards like cheaper insurance or gym memberships. This insight chimes with George Ioannou, managing partner at design experience company Foolproof. Learning patterns around digital activities differ according to age. Where the older generations turn to Facebook for information, younger generations are growing up using gaming platforms such as Fortnite and Discord servers. 

“This may speak to using gamified models of education within financial applications to facilitate learning, perhaps even in a sandbox, and therefore a safe environment,” says Ioannou. 

Ioannou argues that technology enables financial services organisations to become more proactive in supporting customers, and younger generations want more advice about money matters now than ever. “Operators need to step up and actively educate their users,” he adds. 

Research from Personetics, a global fintech, published at the end of June shows in the past three months only 22% of UK customers feel their primary bank has communicated with them about dealing with the cost-of-living crisis. Further, over half (53%) would consider moving banks if a rival offered better money management support and personalised advice.

Reliable source of truth 

Financial education is now starting young. NatWest is currently offering a children’s pocket-money application for free to customers. “Last year, we acquired Rooster Money, a children’s prepaid debit card and app,” explains Fay Wood, head of acquisition and digital security authentication. “We wanted to do more in the space for children.”  

She also stresses the importance of working with expert partners to provide access to apps at speed. “Five or ten years ago, we would have built something like Rooster Money in-house.”

Alongside proactive apps, social media is an invaluable tool for sales and marketing teams in the financial service industry looking to use tech to appeal to younger customers. Here, states Amanda Le Brocq, head of strategy at Marcus by Goldman Sachs, is where organisations can add value. 

“Young people are increasingly getting financial information from social media platforms such as TikTok and Instagram,” she says. “But with so much content available, people can easily get the wrong information. Today, it is essential that financial services companies provide a compelling digital offering, so young people can consume content online and know it is coming from a reliable source.”

Operators wanting to engage younger customers must look further and deeper, says Meghana Nile, insurance CTO at Fujitsu. “Social media and peers influence a lot of the purchasing decisions, meaning financial services companies that have a reputation for having ethical and sustainable practices will attract buyers from gen z, who in 2030 will be the dominant purchasing demographic.”

This article was first published in Raconteur’s The new financial services client experience insights report, sponsored by Seismic, in August 2022

Five ways financial services operators can build trust in the digital age

With cybercrime on the rise, customers expecting a better online banking experience, and more players in the market, organisations should push for positive reviews, cut back on nuisance communication, and be transparent

American business magnate Warren Buffett’s warning that “it takes 20 years to build a reputation and five minutes to ruin it” is a precious lesson worth heeding by financial services operators seeking to generate trust in the digital age. 

After working hard to claw back favour following the global economic crash in 2008, the industry generally impressed during the pandemic. But with cybercrime on the rise, customers expecting a better online banking experience, and more players in the market, building trust is increasingly challenging. 

A report published in April by global cybersecurity company Imperva, based on responses from almost 7,000 consumers across Australia, Singapore, the United Kingdom, and the United States, found that 63% of people don’t trust financial services organisations to keep their data safe. Clearly, there is much work to do.

Here are five ways financial services operators can build trust in the digital age.

1. Actively push for positive reviews

When was the last time you didn’t buy something because a bad review put you off? It’s the same for financial services operators. Hence why those in the sector must do more than monitor online reviews, suggests Jeremy Helm, a financial analyst at Modern World Business Solutions. “You need to be actively pushing to gain positive reviews,” he says. “You can set up an automated email via Trustpilot that goes out a week after a purchase is complete.”

And if the reviews are not favourable, learn from them. “Don’t ignore them,” continues Helm. “Others will be reading the negative reviews before making a purchase, so make sure to answer the complaint promptly and politely. But also, if you’re not to blame, there is nothing wrong with highlighting where the issue lay respectfully and factually.”

2. Cut back on nuisance communication

A recent freedom of information request, made by customer communication firm Quadient, showed an increase in spam communications from financial services operators over the past year, which is eroding consumer trust, according to the company’s principal of banking and financial services, Andrew Stevens.

“Operators urgently need to cut back on nuisance communication – irrelevant or non-useful contact, which only damages trust and drives customers away,” he says. The FOI request showed 8,796 banking-related spam calls and texts were reported to the Information Commissioner’s Office in 2021 – 38% higher than the 2020 figure. Additionally, insurance-related nuisance calls and texts rose by 40%, with 3,989 complaints.

“Our research shows 43% of consumers are willing to blacklist businesses for sending spam,” continues Stevens. “Instead of bombarding customers with irrelevant offers and deals, they should remember that every piece of communication is an opportunity to win customers’ trust. For instance, by providing useful information to help them save money amid the ongoing cost-of-living crisis.”

3. Learn from tech titans and be clear about values

“Interestingly, the five most trusted brands across any industry globally are all large-scale tech firms,” says Nick Chadbourne, CEO of LMS, which supplies conveyancing services. “They provide a seamless cross-platform experience that is personalised to individual users. Google is probably the best example.” 

He spots a paradox, though. “These companies are probably utilising our data for commercial gain more than any other business. Yet, there is a perceived trust from consumers. This is partly because of how these businesses fit with their values. But also because they deliver great customer experience and hyper-personalisation. Financial services firms could benefit and build trust by taking a similar approach.”

Sébastien Marotte, president of EMEA at content management company Box, agrees. However, he calls for greater clarity about data use. “The best way for financial service organisations to build and maintain trust is through open and transparent compliance reporting.”

4. Don’t forget the importance of human touch

Financial services organisations collect more information on their customers than any other industry, according to Adam Mayer, a director at data and analytics firm, Qlik. “Trust is imperative to this industry – and needs to be built from the ground up,” he says. “Don’t forget the importance of a human touch when building trust in digital technologies.” 

While AI and predictive analytics can generate powerful recommendations, employees will provide oversight into actual decision-making, Mayer adds. “And, more importantly, they will explain those decisions to the customer. Blending human and machine insights improves the accountability actions being made, which helps smoothen some of the hurdles around trust and regulation.”

Additionally, ensuring employees have the requisite data literacy to understand, question and apply the predictive forecasts to their decision-making process is critical.

5. Show your AI workings

As more financial services are investing in AI solutions, it’s vital to show how decisions have been made. “Explainable AI addresses one of the key issues for banks using AI applications, as they typically operate as ‘black boxes’ offering little if any discernible insight into how they reach their decisions across lending and fraud detection and to improve customer service,” says Hani Hagras, chief science officer at banking software company Temenos.

He provides an example. “With buy now pay later (BNPL), Temenos Explainable AI provides additional transparency, enabling the customer to understand why a particular flavour of BNPL was recommended to them and make an informed choice. This increases trust in the BNPL service and puts the customer in control.”

This article was first published in Raconteur’s The new financial services client experience insights report, sponsored by Seismic, in August 2022

How financial services operators are dialling up conversational AI to catch out fraudsters

Organisations are using new technology to analyse the voices of those posing as customers in real time while reducing false positives

Great Britain is the fraud capital of the world, according to a Daily Mail investigation published in June. The study calculated that 40 million adults have been targeted by scammers this year. In April, a reported £700m was lost to fraud, compared to an average of £200m per month in 2021. As well as using convincing ruses, scammers are increasingly sophisticated cybercriminals.

If the UK does go into recession, as predicted, then the level of attacks is likely to increase even further. Jon Holden is head of security at digital-first bank Atom. “Any economic and supply-chain pressure has always had an impact and motivated more fraud,” he says. He suggests that the “classic fraud triangle” of pressure, opportunity and rationalisation comes into play. 

Financial service operators are investing in nascent fraud-prevention technologies such as conversational AI and other biometric solutions to reduce fraud. “Conversational AI is being used across the industry to recognise patterns in conversations, with agents or via chatbots, that may indicate social engineering-type conversations, to shut them down in real time,” continues Holden. “Any later than real time and the impact of such AI can be deadened as the action comes too late. Linking this to segmentation models that identify the most vulnerable customers can help get action to those that need it fastest and help with target prevention activity too.”

This last point is crucial because educating customers about swindlers is not straightforward. “Unfortunately, there will always be vulnerable people being scammed,” Holden says. “The banks are doing a lot of work to identify and protect vulnerable customers, but clever social engineering, often over a long period, will always create more victims of romance scams, investment scams, or purchase scams when victims send money for goods never received.”

How AI can help fight fraud

AI is a critical tool to fight fraud. Not only does it reduce the possibility of human error but it raises the flag quickly, which enables faster, smarter interventions. Additionally, it provides “far better insight of the cyber ecosystem”, adds Holden, “almost at the point of predictive detection, which helps with both threat decisioning and threat hunting”. 

Jason Costain is head of fraud prevention at NatWest, which serves 19 million customers across its banking and financial services brands. He agrees it is vital for conversational AI to join the chat. Because the call centre is an important customer service channel and a prime target for fraudulent activity – both from lone-wolf attackers and organised crime networks – he resolved to establish more effective security mechanisms while delivering a fast, smooth experience for genuine customers. 

In late 2020, NatWest opted for a speech recognition solution by Nuance, a company which Microsoft recently acquired. It screens every incoming call and compares voice characteristics – including pitch, cadence, and accent – to a digital library of voices associated with fraud against the bank. The software immediately flags suspicious calls and alerts the call centre agent about potential fraud attempts.

Since our initial implementation of AI three years ago, the improvements to alert quality have been incredible

Before the end of the first year of deploying the Nuance Gatekeeper system, NatWest had screened 17 million incoming calls. Of those, 23,000 led to alerts and the bank found that around one in every 3,500 calls is a fraud attempt. As well as a library of ‘bad’ voices, NatWest agents now have a safe list of genuine customer voices that can be used for rapid authentication without customers needing to recall passwords and other identifying information. That knowledge enables the bank to identify and disrupt organised crime activities to protect its customers and assist law enforcement.

“We’re using voice-biometric technology to build a clear picture of our customers’ voices and what criminal voices sound like,” Costain says. “We can detect when we get a fraudulent voice coming in across our network as soon as it happens. Using a combination of biometric and behavioural data, we now have far greater confidence that we are speaking to our genuine customers and keeping them safe.”

He estimates the return on investment from the tool is more than 300%. “As payback from technology deployment, it’s been impressive. But it’s not just about stopping financial loss; it’s about disrupting criminals.” For instance, NatWest identified a prolific fraudster connected to suspect logins on 1,500 bank accounts, and an arrest followed.

“For trusted organisations like banks, where data security is everything, the identification of the future is all about layers of security: your biometrics, the devices you use, and understanding your normal pattern of behaviour,” adds Costain. “At NatWest, we are already there, and our customers are protected by it.”

Benefits of investing in conversational AI

There are other benefits to be gained by investing in conversational AI solutions. Dr Hassaan Khan is head of the School of Digital Finance at Arden University. He points to a recent survey that indicates almost 90% of the banking sector’s interactions will be automated by 2023. “To stay competitive, organisations must rethink their strategies for improved customer experience. Banks are cognisant that conversational AI can help them be prepared and meet their customers’ rising demands and expectations,” he says.

This observation chimes with Livia Benisty. She is the global head of anti-money laundering at Banking Circle, the B2B bank relied on by Stripe, Paysafe, Shopify and other big businesses, responsible for settling approximately 6% of the world’s ecommerce payments. “With AML fines rocketing – the Financial Conduct Authority dished out a record $672 million (£559m) in 2021 – it’s clear that transaction monitoring cannot cope in its current state,” Benisty says. “That’s why adopting AI and machine learning is vital for overturning criminal activity.”

She argues, however, that many in the financial services industry are reluctant to invest in the newest AML solutions for fear of being reprimanded by regulators. “If you’re a bank, you come under a lot of scrutiny and there’s been resistance to using AI like ours,” she says. “AI is seen as unproven and risky to use but the opposite is true. Since our initial implementation of AI three years ago, the improvements to alert quality have been incredible. AI alleviates admin-heavy processes, enhancing detection by increasing rules precision and highlighting red flags the naked human eye could never spot.”

Even regulators would be impressed by the results revealed by Banking Circle’s head of AML. More than 600 bank accounts have been closed or escalated to the compliance department, thanks to AI-related findings. Further, the solution “dramatically reduces” the so-called false positive alerts. “It’s well known the industry can see rates of a staggering 99%,” adds Benisty. “In highlighting fewer non-risky payments, fewer false positives are generated, ultimately meaning more time to investigate suspicious payments.”

As the economy weakens, and criminals grow stronger, financial services operators would be wise to dial up their conversational AI capabilities to improve customer experience today and pave the way to a password-less tomorrow.

This article was first published in Raconteur’s Fraud, Cybersecurity and Financial Crime report in July 2022

‘I was thrown off a project because I misheard’: Deaf inclusivity in the workplace still an issue

The LinkedIn profile image of culture and behavioral change consultant Simon Houghton, shows him wearing a black mask with white writing that reads: “I’m deaf. I can’t read your lips with your mask on.”

Houghton, based in Reading in the U.K., has significant hearing loss so relies heavily on lipreading when communicating – a skill which became even harder to use during the pandemic when everyone wore masks. And while the rise of virtual meetings has helped to some extent (people still turn their cameras off blocking lipreading), workplaces still don’t cater well enough to people with hidden conditions like deafness or severe hearing loss.

To boost awareness Houghton launched social enterprise WeSupportDeafAwareness during the pandemic. His message is clear: not enough is being done to support deaf workers, who make up a large chunk of the population. Consider that 1.5 billion people – almost 20% of the global population – live with a degree of hearing loss, according to the latest World Health Organization calculations. 

Houghton has had to pay a heavy price for this lack of inclusivity at work. One of his worst memories he still recalls. “I was working for a big-four management consultancy firm and was thrown off a project because I misheard an action during a client meeting,” he said. 

This article was first published on DigiDay’s future-of-work platform, WorkLife, in July 2022 – to read the complete piece please click HERE.

What does the advent of sentient AI really mean for businesses and the workforce?

The futuristic notion that a machine will one day become self-aware, for good and evil, has been a staple of science fiction. So when a Google engineer reckoned the company’s Language Model for Dialogue Applications (LaMDA) program had achieved “sentience” in mid-June, it triggered both alarm and glee.

A fortnight before Lemoine’s claim, Elon Musk announced that a prototype of Tesla’s humanoid robot, “Optimus,” would be unveiled in September. Last August, the billionaire suggested the 173-cm, general-purpose bot would have “profound implications for the economy” and be capable of carrying out everyday tasks, including supermarket shopping. 

So, how significant are these two headline-grabbing development for businesses? What, back in the realms of science fact and reality, could the advent of sentient AI mean for the future of work? And what should business leaders be doing, if anything, to prepare for this challenge and opportunity?

This article was first published on DigiDay’s future-of-work platform, WorkLife, in July 2022 – to read the complete piece please click HERE.

How companies are attempting to tackle diversity ‘blind spots’ at the hiring stage

In an attempt to root out all biases – conscious or unconscious – at the hiring stage, more organizations are overhauling their recruitment processes.

For many, that’s meant stripping their recruitment methods to the bare bones and examining everything from how language in job ads can influence who applies, to improving interview questions so they focus on a person’s aptitude and skill, rather than background and experience.

This article was first published on DigiDay’s future-of-work platform, WorkLife, in July 2022 – to read the complete piece please click HERE.

Sales talk: how conversational AI can win over customers

Conversational AI can mimic human interactions. With today’s consumers turned off by the hard sell, the technology holds strong potential for businesses

When it comes to sales, businesses should reverse Elvis’s famous advice: a little more conversation and a little less action, please. 

The secret to success with today’s consumers revolves around small talk and a long-term approach. Direct approaches – seeking to add notches to the sales equivalent of a bedpost – are a huge turn-off for customers. 

Happily, so-called conversational AI is now mature enough to assist adroitly with the more mundane topics, enabling humans to enter the chat room later, at the most appropriate point.

Conversational AI refers to tech solutions such as chatbots or virtual agents that use vast volumes of data, machine learning and natural language processing to imitate human interactions. Businesses today must adopt the technology as a matter of urgency, with laggards likely to lose out.

Technology doesn’t have working hours like a human employee does, meaning that customers can gain the help they desire on their terms

Over 70% of customers expect conversational service, meaning human-like interactions – complete with emojis, gifs, images and videos – whenever they engage with a brand, according to Zendesk. But only 40% of businesses can deliver this successfully. 

Little wonder the global software-as-a-service company recently announced new capabilities for its Sunshine Platform, a customer relationship management service, including conversational automation via bot technology. The upgrade enables organisations to expand automation to messaging apps such as Facebook Messenger and WhatsApp and allows them to build and train custom bots to address common issues.

“A quick conversation can resolve most things in life,” says Matthias Goehler, Zendesk’s chief technology officer in EMEA. “Embracing advances in AI to deliver conversational exchanges with customers easily is a natural direction for customer experience (CX) teams to take.”

Resolving customer issues 

One of the most significant benefits of conversational AI is that all customer communications are retained, Goehler adds. This means a more complete picture is achieved, allowing businesses to understand people’s personal preferences better and enrich their experience. It facilitates a personalised, data-driven service, removing some of the burdens on human agents and empowering them to do more for the customer in less time, he says.

“A conversational approach makes interactions more informed – built with the context of the customer’s history. When done right, it can even help increase a customer’s spending with you by making useful and simple recommendations to purchase from within a chat.”

Katie King is the author of two books about AI for sales and marketing and a member of the government’s All-Party Parliamentary Group Taskforce for the enterprise adoption of AI. Companies that embrace conversational AI will charm employees and customers alike, she says. 

“Often, many of the queries that cross the service agent’s desk are frequently asked questions with simple answers,” she says. “While these queries might be easy to answer, they still take up valuable time and limit the agent’s capabilities to handle some of the more complex issues. It’s overwhelming and leads to faster employee burnout and potential staffing issues for the company.”

Conversational AI can help tackle this challenge, so appeals to many organisations, notes King. “AI can cut out that first step of the process by engaging the customer and potentially resolving their issue without human intervention,” she says. “Additionally, technology doesn’t have working hours like a human employee does, meaning that customers can gain the help they desire on their terms.”

When done right, it can even help increase a customer’s spending with you by making useful and simple recommendations to purchase

With the surge in energy prices, concerned customers of E.ON – the largest energy and renewable electricity supplier in the UK – have certainly wanted help. Conversational AI is easing the load. 

Nikolai Berenbrock is the company’s head of conversational experiences. He says the company currently has more than 50 conversational AI solutions across the group, serving customers and employees and covering about 30% of demand. “This has enabled us to offer a better customer service experience and a massive reduction in our operational costs,” Berenbrock says.

E.ON uses AI to automate repetitive tasks so that agents are “available to jump in where they can make a valuable difference”, he adds. The technology “allows us to scale our customer service in a location and time-independent way, so that we can be where our customers are by offering our service on our website in a LiveChat channel, WhatsApp, Facebook Messenger, telephony channel, etc, whenever they need us, 24/7.” 

Talking up the possibilities

Jason Costain is head of fraud prevention at NatWest, which serves 19 million customers across 12 banking and financial services brands. He offers another example of how conversational AI is being utilised. 

“Using voice-biometric technology, we’re building a clear picture of our customers’ voices and what criminal voices sound like,” he says. “We can detect when we get a fraudulent voice coming in across our network as soon as it happens. Using a combination of biometric and behavioural data, we now have far greater confidence that we are speaking to our genuine customers and keeping them safe.”

Demand for conversational AI isn’t limited to customer experience, says Goehler. “We’re seeing huge demand from companies using our solutions for employee experience, with tickets filled by corporate employees jumping 31% last year – nearly double the rates seen by customer-facing support teams at B2B and B2C companies,” he says, signposting the direction of travel.

Despite the clear advantages of conversational AI and the momentum behind the technology, Goehler sounds a note of caution to business leaders who, to quote another Elvis song, can’t help falling in love with the technology. “While just over half of EMEA companies report that chatbots are becoming more human-like, AI can’t – and shouldn’t – be a 100% solution,” he says.

Zendesk research indicates more than 60% of customers will walk away after one poor experience – up 22% from last year. Perhaps this shouldn’t be a surprise. After all, who can blame their suspicious minds?

This article was first published in Raconteur’s AI for Business report in June 2022

Where should cash-strapped public sector organisations allocate funds?

Upskilling employees, smarter outsourcing and new technology could help reduce costs and reduce debt – and deliver better service

TS Eliot’s poem The Waste Land, published exactly a century ago, begins with the words: “April is the cruellest month.” One hundred years on, considering the exorbitant rise of energy costs for British citizens and businesses in April 2022, it’s hard to disagree. Unfortunately, it appears worse is to come, with many feeling the world will end with a whimper – so how can the public sector cope?

On 5 May, the Bank of England lifted interest rates to a 13-year high and forecast that inflation would soar above 10% in the coming months, warning that the surging rise in living costs could plunge the economy into recession this year. But it’s not only citizens who are squeezed; the public sector is already in the red – just as demand for public services is likely to reach unprecedented levels.

The latest Office for National Statistics figures show that total public sector debt stood at £2,344 billion at the end of March 2022. This is equivalent to 96.2% of Gross Domestic Product (GDP), a level not seen since the early 1960s.

Further, public sector net borrowing was £151.8 billion in the year to March 2022. This was the third-highest borrowing figure since records began in 1947, and is around 6.4% of GDP.

Given this gloomy backdrop, how should public sector organisations plagued by money worries invest in technology solutions that best serve struggling citizens? Granted, costly gambles on the metaverse and vanity projects are not a good idea right now, but what’s the best way to allocate funds?

Jon Crowcroft is a co-founder of iKVA, an artificial intelligence knowledge management company, chair of The Alan Turing Institute, and Marconi professor of communications systems in the computer laboratory at the University of Cambridge. He is well placed to answer these critical questions.

Investing in skills to address huge delivery challenges

“My advice would be to match the budget to the current skills base, or organisations will face the challenge of undertaking a huge retraining exercise that will overwhelm their resources,” he says. “Government departments such as transport, energy and healthcare are relatively technologically advanced and staffed by individuals who inherently use technology for timetabling systems, power grid maintenance and data analysis. Computing is embedded into job roles in these departments, particularly in healthcare.”

Other areas, such as the legal sector, have more limited skills, Crowcroft says. Their relative ability should inform where additional funds will be required to support the deployment of technological solutions. 

Alex Case is public sector industry principal at Pegasystems and a former senior civil servant at 10 Downing Street and the Cabinet Office, who recently oversaw cross-Whitehall Brexit delivery. He has also led large-scale public sector reform initiatives in the UK and Canada – and is in no doubt of the scale of the task ahead.

“The government continues to face huge delivery challenges, from coronavirus, Brexit, the war in Ukraine or the cost-of-living crisis, including dealing with backlogs, driving levelling up, getting the health service back on track, transforming social care and dealing with the safety of tall buildings. These need government operations to run effectively and efficiently and for the least amount of cost possible.”

Low-code can revolutionise how government designs and builds IT. It can help a business to get what it wants and needs from a new system, not the system the IT team thinks the business needs

Low-code software development uses drag-and-drop features instead of extensive coding language to build applications. The result is that it is faster to complete and non-professional coders can use it. This makes it an excellent option to accelerate innovation and reduce costs, suggests Case. Its uses across government departments could include streaming and improving outdated and clunky customer service processes, digitising inefficient and complex programmes and back-office processes, and modernising debt collection while reducing fraud.

“Low-code can revolutionise how government designs and builds IT. It can help a business to get what it wants and needs from a new system, not the system the IT team thinks the business needs.”

Additionally, he says this approach can bridge the frequent divide between business users, subject matter experts, product owners, and the technical design and developer teams.

Where, though, should the public sector focus its investment now? Crowcroft contends that it is less where and more how the money should be spent, celebrating the increased adoption of AI. “During the pandemic, the public sector successfully used AI and automation to meet increased demand for services,” he says. 

“AI can automate bureaucratic processes that are currently resource-intensive, reducing the human workload. This will offer cost-savings, improve accuracy, and enable people to do other things that have a positive return for their organisations, such as analysing data to identify where other improvements can be made.”

An example of this is in the care sector, says Crowcroft. By automating some of the paperwork, the amount of time a care worker can spend with people in need increases. “The processes at the human level are reflected in documentation, and that shouldn’t be the case anymore,” he adds.

One obvious way for the public sector to reduce costs is by being smarter with outsourcing while improving in-house skills. For instance, the value of contracts awarded by the UK government and public bodies to consultants was £2.5bn in 2020-21, as organisations used the private sector to deal with the pandemic. 

“Consultants will always have a place in the public sector,” concludes Crowcroft. “But using technology to unlock data insights and training our people to understand the information – will improve confidence in their decision-making.”

Is low-code the answer to public sector worries?

“The government knows that low-code can help take the pressure off and has invited proposals for innovative platforms and software for digital public services,” says Mark Smitham, lead for public sector marketing at Mendix, a low-code platform. “Their shared vision is to deliver more user-centred, cost-effective, local public services through open, collaborative and reusable work.”

He suggests Knowsley Council is a prime example of a local service provider that used low-code to adapt to the increased demand from residents and local businesses. “In just 24 hours, the council built an application that enables Knowsley residents to request assistance or volunteer their services to support their local community,” Smitham continues. “This application connected people who need help with those who can help, providing support for 7,000 vulnerable residents.”

Elsewhere, a low-code platform is being used to address the growing issue of financial debt with core business transformation at StepChange, the UK’s largest debt management charity, says Alex Case, public sector industry principal at Pegasystems. “Additionally, low-code solutions are being deployed to tackle costly fraud and errors for the Department for Work and Pensions. It is transforming how the country registers land and property, and even supporting how the Ministry of Defence recruits essential skills to predict and deal with a fast-paced and changing environment.”

This article was first published in Raconteur’s Public Sector Technology report in May 2022

Fast-track to remote-first success: Experienced experts reveal their tips so others can accelerate their journeys

When Airbnb CEO Brian Chesky unveiled the company’s remote working policy at the start of May, in only 105 words, there was much to admire about its boldness and simplicity. However, one detail concerned Paul McKinlay, vp and head of remote for Cimpress/Vista, which implemented a similar strategy two years ago. It was Chesky’s comment that remote working “will become the predominant way companies work 10 years from now.”

The Airbnb boss’s prediction is supported by electronics firm Ricoh Europe’s research, which polled 3,000 employees in the U.K. and Ireland, France, Germany, Spain, Italy and the Netherlands last month. Almost half of the respondents (47%) think we’ll all work remotely in a decade’s time and that the traditional office space won’t exist.

But for Boston-based McKinlay that timeframe isn’t nearly fast enough. He warned that global leaders need to “act much sooner” and develop fully-fledged hybrid and remote-friendly working models for the benefit of their team members, shareholders and business results.

WorkLife spoke to a range of execs from different companies, which have already implemented successful hybrid and remote-first models, for tips on what to focus on. Here’s what they had to say ….

This article was first published on DigiDay’s future-of-work platform, WorkLife, in May 2022 – to continue reading please click HERE.

Web creator Sir Tim Berners-Lee on the future of data

Data literacy will drive innovation, easing global warming and empowering citizens, according to Sir Tim Berners-Lee and Sir Nigel Shadbolt

Billions of us use the World Wide Web as our primary tool to interact online. Today, its creator Sir Tim Berners-Lee is on a new mission: to ensure data is used appropriately to create the public sector of the future.

Berners-Lee partnered with artificial intelligence (AI) expert Sir Nigel Shadbolt in 2012 to found the Open Data Institute (ODI). At the ODI Summit in early November, the pair of computer scientists warned that now is a pivotal moment. As we hurtle into the digital era powered by data-hungry algorithms and AI, it’s critical to collaborate with good intentions and maximise the potential of technology, for the sake of the planet and its inhabitants. 

The acceleration of digital transformation necessitated by the coronavirus chaos is exciting, but there’s a responsibility for authorities around the world to keep pace with this incredible change. Those in power must set standards, encourage data to be opened and shared responsibly, and narrow the ever-widening skills gap. The quicker that data literacy in both private and public sectors can be improved, the better for everyone.

As Berners-Lee points out, the pandemic has unconsciously boosted public awareness of how data can save and enrich lives. “Something that took off hugely was communication through data, with the government telling us to ‘flatten the curve’ [and limit the spread of the virus],” he says. “I would imagine that the data literacy of the general population has gone up a chunk.” 

Driving change 

By improving their data literacy, leaders and members of the public could understand and challenge how data is presented, Shadbolt suggests. As public sector technology and its application develops in the coming years, fuelled by more and better-quality data, greater scrutiny will help shape products and services for the digital era. 

The opening of more data sources will super-charge the public sector of the future and drive innovation, says Shadbolt. The chair of the ODI – who’s been principal of Jesus College at Oxford University since 2015, among other roles – points to the success of open data pioneer Transport for London (TfL). Often held up as an exemplar of open data, TfL offers data feeds and guidelines about air quality, cycling, walking, planning and more. 

In 2017, Deloitte calculated that TfL’s release of open data generated annual economic benefits and savings of up to £130 million for travellers, the capital and the organisation itself. Additionally, many private businesses have taken advantage and cashed in on the open application programming interfaces (APIs).

“Imagine that a lot of data relevant to everything climate-related was just being routinely published using standard APIs,” Shadbolt continues. “It’s what we saw happen with TfL. And there’s just a bunch of sectors and areas to go for.”

However, it can be dangerous to blindly follow data. Shadbolt wonders whether Boris Johnson’s refrain during the pandemic that the government would “follow the data” to justify its pandemic-related decisions coronavirus sent out the wrong message. “It was quite a bad phrase, in some respects,” he says, “because while there should be a basic ability to understand the data, we need to interrogate and critique that data.”

Data can be good, but it never gives a complete picture

Questioning data sources is not just essential to fight fake news on social media and elsewhere – it will also enable public sector organisations to build greater trust, Berners-Lee says. With more connected data, they could trigger a shift from reactive to proactive services. 

It’s a virtuous circle, because trusted and quality datasets will widen the possibilities and reach of public sector technology and empower citizens. “Provenance is important for data quality, and provenance is important for trust,” he says.

Building trust

For example, Berners-Lee says a doctor should be able to look at the digital notes of a person with diabetes and open a data narrative explaining how this diagnosis was made and other relevant history. Public trust in the data used by the public sector is central to the adoption of technologies and services, he points out.

The general public seemed to go into different categories regarding coronavirus data, Berners-Lee says. Some accepted recommendations for pushing the curve down, but others “don’t listen to the same people as we might. Instead, they find groups of people –

the conspiracy theorists – usually on social media, who make up all kinds of strange things about the pandemic, vaccines or climate change, for that matter.”

Shadbolt says experts act in good faith with the information available at a specific time, but their visibility is limited if they have scant amounts of data. The wider the variety of good quality data sources, the fuller the picture. “We’ve talked a lot about how it’s important, particularly during the pandemic, not to regard the scientists, medics and people in white coats as telling you the whole truth,” he says. “They’re trying to give the best information, very often under conditions of considerable uncertainty.” We must take a nuanced approach, he argues, understanding that “the data can be good, but it never gives a complete picture.”

Those in the public sector and beyond must be “critically reflective” of data. “All our responses are made, in a sense, standing on the edge of error. But that’s what science is: it can believe something is wrong and can revise what we believe as these things unfold.” 

While the collaborative use of data will create smarter public services in the UK, this approach is crucial on a larger scale if humanity is to overcome its biggest challenges. It’s been vital in the response to coronavirus, while a cooperative, non-competitive and can-do attitude is also essential to reduce global warming.

“We’ve just been living through an existential crisis – a global pandemic – and we’re in the midst of another one unfolding, with the climate challenge,” says Shadbolt. “Data will be an essential part of [solving this]: the infrastructure, the institutions we might need, the trust we have [in its use], and our literacy.”

Sir Patrick Vallance, the UK’s chief scientific advisor, echoed this view at the 2021 United Nations Climate Change Conference (COP26). He warned that the challenge of global warming is a greater risk than Covid-19 and more people will die from it than the pandemic if the public sector doesn’t act quickly. Vallance also said the climate crisis could last 100 years and require “a combination of technology and behavioural change”.

Provenance is important for data quality, and provenance is important for trust

Shadbolt concurs but stresses that opening data and boosting cross-sector collaboration will accelerate meaningful change on a macro and micro scale and increase the capabilities of public sector technology. “While environment data is in the news because of COP26, there is other information that can help spur action,” he says, hinting that greater transparency from public sector organisations will ratchet up pressure on private companies to keep clean. For example, he notes that data on utility companies discharging sewage will help the Environment Agency, which struggles with funds and support. 

“We are starting to gain a sense of what data’s going to make a difference – everything from emissions to insulation. There’s a whole network of interconnected data types that we can bring together, much of it held in the public sector, and some of it held in the private sector,” he says. “We need to begin that work on joint public-private enterprises, though we are beginning to see the private sector, with its commitments to ESG, saying ‘we now have to have a public purpose as well as a private one.’” Publishing some of this data “would be a great first step”, he adds. 

Information advantage

Berners-Lee and Shadbolt were appointed as information advisors to the government in June 2009. The duo led the team that developed data.gov.uk, a single point of access for UK non-personal governmental public data. This offers real-time information on a range of topics, such as government spending, digital service performance, crime and justice, transport and more.

When the pair founded the not-for-profit ODI nine years ago, the mission was to “connect, equip and inspire people around the world to innovate with data”. Almost a decade later, the ODI continues to provide free and paid-for training courses and learning materials both in-house and online. These cover theory and practice surrounding data publishing and use. The ODI has long championed open data as a public good, but always emphasised that effective governance models are necessary to protect citizens.

Some 20 months since the start of the coronavirus crisis, people are beginning to appreciate the ODI’s work and concerns around data standards. “When the pandemic began we provided a data publication template,” says Shadbolt. “The challenge was so many people wanted to contribute data. It needed sorting and we had to determine what was helpful. If there was just a little more awareness around open standards to publish data, so that it is in a more interoperable format, it would be better for everyone.”

For public sector technology to thrive, however, public trust is critical, says Berners-Lee, who notes a difference in attitudes to tech in the UK compared to the US. “Typically in the UK people trust the government and don’t trust [the tech] industry, and in the US people trust industry and don’t trust the government,” he says. More should be done to assuage fears about how tech giants handle user data, he adds. “To an extent, it’s how people are brought up and therefore cultural. But for people in the UK to trust these large American companies then you need to have serious legislation and regulation.”

The backlash against the allegedly avaricious Facebook, which according to a recent whistleblower puts user engagement ahead of safety, is a cautionary tale for public sector organisations seeking to embrace technology solutions and partner with companies without fully knowing their policies on data privacy and other questionable values, suggests Berners-Lee. More than ever, at the outset, digital products must be “good by design”.

Data management is integral to these processes. Here too the coronavirus has proven useful, testing the robustness of so-called ‘trusted research environments’. “In these environments, the data stays behind a firewall and it’s modelled and analysed with tools that can go behind the firewall,” Shadbolt explains. “The data never actually leaves the highly secure data storage areas where 47 million patient records are linked, but incredible insights are gained.”

Offering an alternative, he says: “The other solution is to leave the data with the people who generate it, which is very local. There are different technical solutions there and there are different institutions we can build to share this. It’s a complicated area, but the ODI is looking very carefully at making data sharing more effective.”

Unfinished business

What does the future hold for the ODI as it nears its 10-year anniversary? “We started off explaining to people working in the public sector how to put your data on the web,” says Berners-Lee. Now, however, “we realise it’s important to cover the whole spectrum, from public to private, but it’s also about developing policies as well.”

This assessment chimes with Shadbolt. “There is unfinished business,” he says. “The whole commitment to getting data out there was started with open data initiatives that were very much focused around the public sector – everything from hospital data to educational data to transport data. That work has gone well. We’re now looking at extending those learnings. As governments move on [in their digital transformation journeys], you want to ensure that momentum is kept up and that the infrastructure is there to help sustain publishing the data out.”

Returning to the global climate crisis, he says of the ODI’s mission: “We did anticipate that in trying to build a trusted research data ecosystem it would become one of the consequential questions for the future of the planet and the future of our wellbeing. There’s a huge amount of work to do. We’re trying to make sense of it in terms of programmes of work, from data literacy to institutions, from ethics to infrastructure.”

Shadbolt adds: “Fundamentally the ODI’s work is about listening, it’s about trying to take ideas and put them in a format that allows that to scale. We may be an organisation of 60-odd people but we think we can have a fantastic impact and so we need to reach out and sustain ourselves to make a better future.”

This article was first published in Raconteur’s Public Sector Technology report in December 2021

Enriching and empowering: realising the potential of data-enabled public services

Out of necessity, public bodies dialled up their digital services during the pandemic, but now is a pivotal moment to consider how to achieve a joined-up, secure, frictionless citizen experience

When considering the rapid and radical shift to digital services in the public sector during the coronavirus crisis, Ernest Hemingway’s line from The Sun Also Rises of bankruptcy happening “gradually, then suddenly” comes to mind. In this case, though, the prognosis is somewhat more optimistic.

The hurried but necessary jump into the digital era has enabled people to be empowered and enriched by data-driven public services. Now the leap has been made, the direction of travel is clear. However, there is still work to be done before achieving a connected, frictionless digital experience that benefits the state and its citizens.

“Data-driven, smart digital technologies have provided crucial support to public bodies through the pandemic, but they’ve also allowed our under-pressure services to become smarter and more responsive to our needs as citizens,” says Steve Thorn, executive director at Civica, whose software helps sustain and enhance public services around the world.

“For some public services, the digital journey was already well underway, and the pandemic catalysed this journey. For others, such as our schools, the pandemic required a more fundamental change, with face-to-face teaching giving way to online classrooms.”

Thorn singles out the track and trace applications and vaccination certificates as “prime examples of the power of data-driven, smart technologies to deliver better outcomes for citizens,” and says that more outstanding capabilities are within reach. But, he warns, the government must take its next steps carefully. 

“Public bodies across Britain and the rest of the world already sit on rich seams of data, which are growing by the day as our society becomes more digitised,” he says. “Raw data is, though, of little value. Data must be collected, managed, used and shared effectively if it is to deliver any real benefits.”

Standards, skills and sharing

To better navigate the route ahead, with the ultimate goal of providing a connected, frictionless customer experience to citizens, Civica works with the public sector on what it calls the three ‘Ss’ – namely standards, skills and sharing. 

Thorn says: “Any public body, be it a parish council or Whitehall department, must ensure that it has robust standards in place for managing data, the right people with the right skills to use that data and finally, processes in place to share data safely and effectively, so it is it is delivering the best outcomes for the greater number of people.”

Andrew Hood, chief executive of Edinburgh-based analytics consultancy Lynchpin, agrees that now is a good time for the public sector to reflect on the good and the bad digital offerings throughout the coronavirus crisis. He sees great potential in Internet of Things (IoT) technology but similarly urges caution. “The pandemic has surfaced a lot of the practical opportunities and threats around data sharing and IoT in obvious terms when viewed through the lens of things like contact tracing apps and digital vaccine passports,” Hood says.

For some public services, the digital journey was already well underway, and the pandemic catalysed this journey. For others, such as our schools, the pandemic required a more fundamental change, with face-to-face teaching giving way to online classrooms

He points to the different strategies taken by the UK’s four nations in terms of deploying open source versus proprietary solutions. “There is potentially much to learn from what has worked well and less well when considering other similar applications outside of the pandemic,” he says.

“Whether to centralise or decentralise how data is shared across millions of devices became a very key consideration for contact-tracing apps. How [do we] achieve enough sharing to enable the outcome of alerting those that had been nearby others without creating Minority Report-style databases of the movements of the entire population?”

The software robot revolution 

For David Burrows, public sector industries leader at UiPath, a robotic process automation dollar unicorn, the benefits of the public sector doubling down on automation and IoT technologies to create a more streamlined physical service for citizens – for example, with smart roads, touch-fre metering and much more – are compelling. 

Further, with the UK effectively gaining data sovereignty post-Brexit, the government is perfectly positioned to speed ahead of other European nations if all key stakeholders use the exact strategy roadmap and collaborate.

But to improve citizens’ experiences and public services, alike, and to make use of better infrastructure, it comes back to managing data. “Automation is one tool being used by UK government to achieve the frictionless digital experience needed to improve public services and more effectively serve citizens,” says Burrows. “As software robots can handle huge volumes of data more quickly and efficiently than humans can, it can significantly streamline back-office activity and reduce the risk of administrative bottlenecks.”

He points to the recent work UiPath has done with the Department for Environment, Food and Rural Affairs’ National Licencing and Permitting Service for water abstraction – taking water from an underground or surface source, such as a river, stream or canal. “Once the team has made the technical expert decision on whether a licence should be issued or rejected, there is significant administration to be done to inform the applicant and to update internal and external consultees and the IT system,” says Burrows.

Now, software robots can handle this admin work, cutting the non-decision-making admin down from 65 minutes per transaction to just shy of seven minutes. “The result,” he says, “is that citizens can have their licenses in a fraction of the time, all while public servants can concentrate on more valuable work.”

Looking further ahead, Burrows adds: “With some 22% of government infrastructure decision makers recently telling Forrester that their departments will implement RPA in some shape or form by the end of this year, there is no doubt that automation will continue to play a significant role in government customer strategy.”

Also scanning the horizon and hoping for more joined-up public services and tools that will enrich the lives of citizens, is Thorn. “The pandemic has provided many great examples of how digital technologies can solve individual challenges – be that supporting homeschooling or allowing GPs to interact with patients at a distance. But digital transformation is more than solutions to individual problems.”

Offering a final word of advice, he adds: “Digital transformation is a wider journey towards a future where our public services are ultimately better able to anticipate and respond to our changing needs as citizens and as a society.”

And, as encouraging as the progress that has been made in the last two years especially has been, we are at a pivotal moment. As such, the potential of connected public services is likely to be realised gradually, not suddenly – and that’s no bad thing.

This article, sponsored by Vonage, was first published on Raconteur in December 2021