artificial intelligence Archives — Page 2 of 3 — Carrington Malin

February 6, 2020
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The tech giant’s new chatbot could make AI-powered communication more conversational and even more profitable

Since the launch of Apple’s Siri a decade ago, more than 1.5 billion virtual assistants have been installed on smartphones and other devices. There can be few electronics users who don’t recognise the enormous promise of conversational AI. However, our seemingly hard of hearing virtual assistants and awkward artificial intelligence chatbot conversations have also proven the technology’s limitations.

Anyone who uses AI assistants is sure to experience frequent misunderstandings, irrelevant answers and way too many ‘I don’t know’ responses, while many corporate chatbots simply serve up pre-defined bits of information whether you ask for them to or not. So, while we have seen massive advances in natural language processing (NLP) during recent years, human-to-AI conversations remain far from ‘natural’.

But that may soon change.

Last week, a team from Google published an academic paper on ‘Meena’, an open-domain chatbot developed on top of a huge neural network and trained on about 40 billion words of real social media conversations. The result, Google says, is that Meena can chat with you about just about anything and hold a better conversation than any other AI agent created to-date.

One of the things that Google’s development team has been working on is how to increase the chatbot’s ability to hold multi-turn conversations, where a user’s follow-up questions are considered by AI in context of the whole conversations so far. The team’s solution has been to build the chatbot on a neural network, a set of algorithms modeled loosely on the way the human brain works, which is designed to recognise patterns in data. This neural network was then trained on large volumes of data to create 2.6 billion parameters, which inform those algorithms and so improve Meena’s conversation quality.

Creating conversational computer applications that can pass for human intelligence has been a core theme for both computer science and science fiction since the fifties. Alan Turing, the famous British World War II codebreaker and one of the founding fathers of AI theory, developed a test to measure if a computer system can exhibit intelligent behaviour indistinguishable from that of a human in 1950. Since then, the Turing Test has been somewhat of a Holy Grail for computer scientists and technology developers.

However, Google’s quest to develop a superior chatbot is far from academic. The global AI chatbot market offers one of the best examples for how AI can drive revenue for businesses. Business and government organisations worldwide are investing in chatbots, in an effort to enhance customer service levels, decrease costs and open up new revenue opportunities. According to research company Markets and Markets, the global market for conversational AI solutions is forecast to grow from $4.2 billion (Dh15.4bn) in 2019 to $15.7bn by the year 2024.

Chatbot solutions built for large enterprises have the ability to carry on tens of thousands of conversations simultaneously, drawing on millions of data points. Global advisory firm Gartner Group has found AI chatbots used for customer service can lead to reductions in customer calls, email and other enquiries by up to 70 per cent.

All this industry growth and customer service success is taking place despite the innumerable issues that users encounter when trying to have customer service conversations with AI chatbots. As consumers, we are now conditioned to dealing with technology that doesn’t quite work. If the benefits outweigh the frustration, we’re happy to work around the problem. We rephrase our questions when a chatbot can’t interpret our request or choose from the options offered, rather than try to solicit further information. Or, if we feel the conversation is just too much effort for the reward, we just give up.

The latent opportunity for virtual customer assistants is that they could play an active role in defining needs and preferences in the moment, whilst in conversation with the customer, helping to create highly personalised services. Today, programmers have to limit the options that customer service chatbots offer or too many conversations result in dead-ends, unmet requests and frustrated customers. So, choices offered to customers by chatbots, are often as simple as A, B or C.

If developers can increase a chatbot’s ability to hold a more natural human conversation, then chatbots may have the opportunity to solicit more actionable data from customer conversations, resolve a wider range of customer issues automatically and identify additional revenue opportunities in an instant.

Given how fast the chatbot technology market is growing, the payback from enabling AI chatbots to bring customer conversations to a more profitable conclusion could register in the billions of dollars.

This story was first published in The National.


February 4, 2020
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The WEF worked with more than 100 companies and tech experts to develop a new framework for assessing risk and AI.

Companies are implementing new technologies faster than ever in the race to remain competitive, often without understanding the inherent risks.

In response to a growing need to raise awareness about the risks associated with artificial intelligence, the World Economic Forum, together with the Centre for the Fourth Industrial Revolution Network Fellows from Accenture, BBVA, IBM and Suntory Holdings, worked with more than 100 companies and technology experts over the past year to create the ‘Empowering AI Toolkit’. Developed with the structure of a company board meeting in mind, the toolkit provides a framework for mapping AI policy to company objectives and priorities.

Developed with the structure of a company board meeting in mind, the toolkit provides a framework for mapping artificial intelligence policy to company objectives and priorities.

Any board director reading through WEF’s Empowering AI Toolkit will find it valuable not because it delivers any silver bullets, but because it can provide much-needed context and direction to AI policy discussions – without having to hire expensive consultants.

The new framework identifies seven priorities, like brand strategy and cybersecurity, to be considered from an ethics, risk, audit and governance point of view. The toolkit was designed to mimic how board committees and organisations typically approach ethics, policy and risk.

Artificial intelligence promises to solve some of the most pressing issues faced by society, from ensuring fairer trade and reducing consumer waste, to predicting natural disasters and providing early diagnosis for cancer patients. But scandals such as big data breaches, exposed bias in computer algorithms and new solutions that threaten jobs can destroy brands and stock prices and irreparably damage public trust.

Facebook’s 2018 Cambridge Analytica data crisis opened the world’s eyes to the risks of trusting the private sector with detailed personal data. The fact that an otherwise unknown London analytics company had drawn data on 50 million Facebook users without their permission not only drew public backlash, it sent Facebook’s market value plunging $50 billion within a week of the episode being reported.

In addition to Facebook’s Cambridge Analytica woes, there have been a number of high-profile revelations that artificial intelligence systems used by both government and business have applied hidden bias when informing decisions that affect people’s lives. These include a number of cases where algorithms used by big companies in recruitment have been biased based on the race or gender of job candidates.

There is some awareness that new technologies can wreak havoc if not used carefully – but there isn’t enough. And it can challenge corporate boards to predict where a pitfall may present itself on a company’s path to becoming more tech-savvy.

Despite all the warning signs, there remains an “it can’t happen here” attitude. Customer experience company Genesys recently asked more than five thousand employers in six countries about their opinions about AI and found that 54 per cent were not concerned about the unethical use of AI in their companies.

Many corporations have established AI working groups, ethics boards and special committees to advise on policy, risks and strategy. A new KPMG survey found that 44 per cent of businesses surveyed claimed to have implemented an AI code of ethics and another 30 per cent said that they are working on one.Since AI is an emerging technology, new risks are emerging too. Any company could use a road map.

One of today’s biggest AI risks for corporations is the use of, as WEF calls them, ‘inscrutable black box algorithms’. Simply put, most algorithms work in a manner only understood by the programmers who developed them. These algorithms are often considered to be valuable intellectual property, further reinforcing the need to keep their inner-workings a secret and thus removed from scrutiny and governance.

There are already a number of collaborations, groups and institutes that are helping to address some of these issues. The non-profit coalition Partnership on AI, founded by tech giants Amazon, DeepMind, Facebook, Google, IBM and Microsoft, was established to research best practices to ensure that AI systems serve society. Last year, Harvard Kennedy School’s Belfer Center for Science and International Affairs convened the inaugural meeting of The Council on the Responsible Use of Artificial Intelligence, bringing together stakeholders from government, business, academia and society to examine policymaking for AI usage.

However, the speed and ubiquitous nature of artificial intelligence mean that even accurately defining certain risks remains a challenge. Even the best policies must allow for change. The good news is that WEF’s new AI toolkit is available free-of-charge and so could prove to be of immediate value to commercial policymakers the world over.

This story was first published in The National.


January 28, 2020
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Our AI first world is emerging standing on the shoulders of the mobile-first world, but it will also raise its own generation of AI natives

Google CEO Sundar Pichai called it a few years ago in a letter to company shareholders, when he said that we’re all moving from a mobile-first world to an AI first world. On the face of it, this seemed quite straightforward to understand. Businesses are seeing artificial intelligence become embedded into more and more processes, with software developers making it easier and easier for companies to leverage AI across their organisations. Meanwhile, consumers are already using a wide variety of applications that are supported by AI every day, drawing on Big Data, machine learning, computer vision and natural language processing (NLP).

However, Google’s corporate strategy is also a prediction of a new world to come and a fundamental shift in human behaviour. Our new AI first world isn’t simply a world where AI is embedded into all technology, nor just a way for organisations to improve performance and save money. Truly pervasive AI will mean that there will be few human actions where AI assistance is not available and for consumers, their first touch point for any brand will be AI. The early signs of this are clearly visible today.

Businesses are already trying to make our lives easier, whilst drawing in consumers to have deeper relationships with their brands, by using AI to provide consumers with more timely and appropriate interactions, prompted by personalised recommendations and communications. More often than not though, these AI supported communications are limited to certain channels.

AI is also being used more extensively to engage and converse with the consumer, exchanging information and providing feedback, 24/7. A recent survey of 450 customer service and support leaders worldwide by Gartner found that 37 percent are either piloting or using AI bots and virtual customer assistants (VCAs).

Gartner forecast that chatbots and VCAs will be used in 25 percent of customer service and support operations by 2020, although estimates today range from 23 percent to 80 percent. However, what is clear is that companies that have implemented chatbots are reporting reductions in customer calls, email and other enquiries, which Gartner says may be reduced by up to 70 percent of pre-AI volumes.

Crucially, Gartner also points out that AI will be a major force in shaping customer self-service. In the future, AI will empower customer-led approaches to service, where a customer’s preferred option may be i) do it myself, ii) let’s do it together iii) let my AI bot do it for me, or iv) let our AI bots do it together.

Today, when most consumers think about interacting with AI, they tend to think of a device or channel such as Amazon’s Alexa Echo, or Android’s Google Assistant or the Apple and Microsoft alternatives. More and more will have experience of chatting with AI bots via Facebook, Whatsapp or company websites, and an increasing number will talk to call centre AIs when contacting their bank, telecom or other service providers.

No doubt, virtual assistants are going to be instrumental in creating our new AI first world. However, these are destined to become a utility, embedded into almost every device, process and transaction imaginable. This means that whether you are watching TV, shopping at the mall or dining in a restaurant, your first point of contact with any brand could be conversational AI.

Every business, therefore, is going to be under increasing pressure to become an AI first business, and to do so at a speed that few today are prepared to even consider, even those in the midst of that very process. So, let’s take a step back and review the case of mobile-first marketing.

The phrase ‘mobile-first’ started to gain popularity about ten years ago. In fact, Luke Wroblewski’s book ‘Mobile First’ was published in 2009. This new approach to consumer marketing strategy was taken in response to the new generation of smartphones usage, which arguably began with Apple’s 2007 iPhone launch. Smartphones, social media and new location-specific services were driving demand for mobile broadband. And, in turn, marketing started to revolve around SoMoLo engagement (social, mobile and local).

As has often been the case, marketing technology lagged behind. Mobile marketing and services were prohibitively difficult manage and integrate with online marketing, CRM and in-store retail. Mobile marketing was, a first, limited to a few mobile channels and lacked integration with the rest of the marketing ecosystem, fragmenting customer journeys.

However, over the past five years we’ve seen mobile marketing become integrated. CRM systems, analytics, marketing managing platforms, advertising media placement, software deployment and payment transactions can now all be managed using integrated tools that allow more of a 360 degree view of the business. Brands recognise that consumers are using smartphones to do product research and browse options, even as they walk around their stores, and they now have the technology to offer and integrate mobile experiences with a wide variety of channels: whether they are paid, earned, shared or owned.

The swift rise of connected mobile devices forced marketers and martech developers to create integrated, cross-platform, omnichannel strategies and solutions that allow for a more seamless customer experience and give a business a 360 degree view of communications. This is important, since — as we’re seeing today — adding new channels into marketing management systems and CRM, such as AI chatbots, is no great hurdle to jump.

Just how integrated your mobile brand experience is, currently depends on where you live. China has the highest usage of mobile payments, with a mobile payment penetration rate of 35.2 percent. Alipay, WeChat Pay and other online payment apps are popular in almost all cities in China and this year an estimated half a billion Chinese will using their mobile devices to pay in brick-and-mortar stores, restaurants and other retail outlets.

Our future AI first world is obviously going to emerge standing on the shoulders of the mobile-first world.

Google launched its answer to Amazon Alexa in 2016 and, due to the widespread adoption of its Android mobile platform, was able to make the virtual assistant available in 80 countries and 30 languages within two years. Today, Google Assistant is available on more than 1 billion devices.

So, from an AI first communications point of view, businesses can already engage with consumers across a range of AI conversational interfaces, to include chatbots, voice assistants, call centres and email. What’s yet to be developed is the interoperability that allows a brand to chat with you via Facebook Messenger, then call you via an AI call centre and then, perhaps, greet you via an AI voice assistant when you walk into their showroom: all whilst seamlessly continuing the same thread of conversation.

Technology vendors such as Amazon, Google, IBM, Microsoft and Nuance Communications are all investing in the development of end-to-end conversational platforms that allow organisations to engage in complex conversations using the same conversation agent across multiple platforms.

It’s early days for end-to-end conversational platforms, but, for example, it is already possible to develop a virtual customer assistant using IBM’s artificial intelligence platform Watson, then use that VCA to communicate via Amazon Alexa or Google. If this is developed to integrate with IBM’s next-generation call center Voice Gateway, with a little help from a cloud communications platform like Twilio, the same technology can be used to make and receive voice calls, send SMS and converse with customers via Whatsapp.

The development of these multi-purpose conversational platforms will, ultimately, give organisations the ability to create, deploy and manage conversation agents anywhere the technology exists for a consumer to interact. Voice assistants are already starting to be used in automobiles, public transport, retail stores, museums, restaurants and many other scenarios. So, why not refrigerators, automatic doors, escalators and soda machines too?

All of this means that consumer expectations for AI first services are going to soar rapidly, putting pressure on businesses to not only cover the bases, but to innovate to create engaging customer experiences. To do this, organisations have a lot to learn very quickly. AI first communication requires technology, new knowledge and skills, customer experience and, of course, lots of data.

Unlike previous waves of technology that have required users to learn about how the technology works in some detail in order to derive value from it, conversational AI makes it easy for consumers to engage and benefit from an almost infinite variety of AI supported services without ever reading a manual.

Consumer adoption is going to be fast and, as people grow weary of mobile HTML pages and typing data requests, so they going to be more open to innovative new AI voice experiences. AI voice communication will simply become the path of least resistance.

In fact, as the next generation of consumers come online, they will be growing up with AI first services. Our latest Generation Zs and their successors will grow up ‘AI natives’, with their own needs, preferences, behaviours and habits developing in tune with the new AI first world. The only respite for businesses today is that for the next ten years most of their customers will, at least, remember how to deal with them without help from artificial intelligence.

This story first appeared on My AI Brand (Medium)


January 22, 2020
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I was delighted to be able to contribute to Damian Radcliffe‘s Middle East technology predictions feature for ZDNet, rounding up expert predictions for 2020 on 5G and 4G adoption, venture funding, retail tech and artificial intelligence.

I was asked: as the Middle East and North Africa’s spending on AI continues to grow, will the region ever become more than simply a consumer of artificial intelligence?

Read the full article here.


December 30, 2019
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Will AI take your job? Of course not, but that’s hardly the right question.

The semantics used by the technology industry about AI and its impact on jobs have started to grate on me a bit. The future of work is changing faster than ever before and it will drive many new opportunities and new career paths. In the short term, the reality is that a lot of people will lose their jobs, but that’s something no technology leader wants to be quoted as saying, in particular when they could be holding forth on our bright AI-powered future.

IBM CEO Ginni Rometty said – a couple of years ago now – that AI will impact 100 percent of current jobs, which, of course, is now common sense. AI’s impact on jobs is also a complex subject and its dangerous to try to sum it up in one simple concept. However, by and large, that’s what many tech leaders are doing, with “AI won’t take your job” as the reassuring umbrella message that the whole drive towards AI adoption seems to fly under. The answer is both straightforward and misleading. No, AI won’t take your job, anymore than a gun will shoot you: that requires a human.

The fly in the tech industry’s ointment is that their customers are not always ‘on message’. Many large employers have already commented over the past year that one of the benefits that AI brings to them is the ability to do more with less staff, some even going further and stating plainly that the technologies are allowing them to cut volumes of staff.

There are now a growing number of studies that highlight huge changes in the number of current jobs that will be phased-out due to the introduction of automation. In October, a report on the banking sector from Wells Fargo & Co. estimated 200,000 job cuts across the US banking industry over the next decade, including many customer service functions. Often, the big numbers in such reports are necessarily ‘fuzzy’. Statistics often include jobs that employers will phase out by head-count freezes, jobs that will no longer be specified for new operations, plus actual redundancies.

Forecasts for the elimination of certain jobs are embraced by the technology industry as evidence that the nature of work is changing and that old jobs must die in order for new, technology-enabled jobs to be created. One can already see from Linkedin’s top emerging jobs lists for 2019, that specialist roles in artificial intelligence development, robotics, data science and data security are all fast-growing. This is the crux of the now commonplace – but, as yet, unsubstantiated – argument that AI will create more jobs than it eliminates.

How much of ‘the future’s so bright’ narrative is used by the tech industry to distract us from the here and now? On conference platforms all over the world, big tech typically urges employers to focus about how AI can enhance productivity, help define new business models and benefit customers, and not to simply save costs by replacing workers. However, for any business that aims to be competitive in our global economy, must look at ways to cut costs as well as ways to increase efficiencies. As more AI-powered solutions are developed that reduce the need for human workers, more jobs are cut.

Food delivery platform Zomato announced that it was laying off some 600 people in September, claiming that most of these jobs will be automated following continued investment in technology systems.

Earlier in the year budget airline AirAsia confirmed that it had closed nine call centres as a result of its AI chatbot customer service project. No redundancies were mentioned and it’s assumed that most, if not all, call centres were outsourced.

Banks all over the world have used automation to cut countless thousands of jobs over the past ten years and AI will allow them to cut thousands more.

Meanwhile, global economic analysis firm Oxford Economics estimates that automation will eliminate up to 20 million manufacturing jobs worldwide by 2030.

According to the 2019 Harvey Nash / KPMG CIO Survey, one third of CIOs say their companies plan to replace more than 20 percent of job roles with AI/automation within 5 years, although 69 percent also believe new job roles will compensate for those lost. Many agree that the new technology-powered job roles created will compensate for current jobs lost. This also, clearly, means different things to different people. A new data science role may sound great when you’re at college or, perhaps, already involved in digital data, but not so much if you’re a call centre agent with 10 years’ experience who’s just been let go.

So, to me at least, it seems disingenuous for technology leaders to hide behind technicalities, calling out warnings of job losses as a result of AI as being misinformed, unjustified or not presenting the entire picture. Cost savings are a powerful driver of AI adoption and, for many organisations, those savings will be made by cutting jobs. There’s room for the tech industry to be a little more honest about that.

This story first appeared on Linkedin.


December 19, 2019
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The potential for emotion recognition is huge, but scientists at the university argue the technology is still too new to be reliable

A growing number of employers are requiring job candidates to complete video interviews that are screened by artificial intelligence (AI) to determine whether they move on to another round. However, many scientists claim that the technology is still in its infancy and cannot be trusted. This month, a new report from New York University’s AI Now Institute goes further and recommends a ban on the use of emotion recognition for important decisions that impact people’s lives and access to opportunities.

Emotion recognition systems are a subset of facial recognition, developed to track micro-expressions on people’s faces and aim to interpret their emotions and intent. Systems use computer vision technologies to track human facial movements and use algorithms to map these expressions to a defined set of measures. These measures allow the system to identify typical facial expressions and so infer what human emotions and behaviours are being exhibited.

The potential for emotion recognition is huge. According to Indian market intelligence firm Mordor Intelligence, emotion recognition has already become a $12 billion (Dh44bn) industry and is expected to grow rapidly to exceed $90bn per year by 2024. The field has drawn the interest of big tech firms such as Amazon, IBM and Microsoft, startups around the world and venture capitalists.

Advertisers want to know how consumers respond to their advertisements, retail stores want to know how shoppers feel about their displays, law enforcement authorities want to know how suspects react to questioning, and the list of customers goes on. Both business and government entities want to harness the promise of emotion recognition.

As businesses the world over look to AI to improve processes, increase efficiency and reduce costs, it should come as no surprise that AI is already being applied at scale for recruitment processes. Automation has the strongest appeal when an organisation has a volume of repetitive tasks and large volumes of data to process, and both issues apply to recruitment. Some 80 per cent of Fortune 500 firms now use AI technologies for recruitment.

Emotion recognition has been hailed as a game-changer by some members of the recruitment industry. It aims to identify non-verbal behaviours in videos of candidate interviews, while speech analysis tracks key words and changes in tone of voice. Such systems can track hundreds of thousands of data points for analysis from eye movements to what words and phrases are used. Developers claim that such systems are able to screen out the top candidates for any particular job by identifying candidate knowledge, social skills, attitude and level of confidence – all in a matter of minutes.

As with the adoption of many new AI applications, cost savings and speed are the two core drivers of AI-enabled recruitment. Potential savings for employers include time spent on screening candidates, the numbers of HR staff required to manage recruitment and another safeguard against the costly mistake of hiring the wrong candidate for a position. Meanwhile, the message for candidates is that AI can aid better job placement, ensuring that their new employer is a good fit for them.

However, the consensus among scientific researchers is the algorithms developed for emotion recognition lack a solid scientific foundation. Critics claim that it is premature to rely on AI to accurately assess human behaviour, primarily since most systems are built on widespread assumptions not independent research.

Emotion recognition was the focus of a report published earlier this year by a group of researchers from the Association for Psychological Science. The researchers spent two years reviewing more than 1,000 studies on facial expression and emotions. The study found that how people communicate their emotions varies significantly across cultures and situations, and across different people within a single situation. The report concluded that, for the time being, our understanding of the link between facial expression and emotions is tenuous at best.

Unintentional bias has become the focus of growing scrutiny from scientists, technology developers and human rights activists.

Many algorithms used by global businesses have already been found to have bias related to age, gender, race and other factors, due to the assumptions made whilst programming them and the type of data that has been used to feed machine learning. Last year, Amazon shut down an AI recruiting platform after finding that it discriminated against women.

One thing is for sure: regardless of the potential merits of emotion recognition and whether it prevents or promotes your chances of being offered a job, it is likely to remain the subject of debate for some time to come.

This story was first published by The National


November 22, 2019
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With the US and China dominating artificial intelligence development, what chances do smaller nations have?

Over the past two years, a national artificial intelligence (AI) strategy has come to be seen as a pre-requisite for digital competitiveness and an essential pillar of national governance for the Fourth Industrial Revolution. So, Singapore unveiling a new, updated national AI strategy last week has received global attention.

In common with the UAE, Singapore was one of the first countries to announce a national AI strategy, back in 2017. The new one, unveiled by the Deputy Prime Minister Heng Swee Keat on the last day of Singapore’s FinTech Festival last week, is holistic and zeros in on some specific national goals. Importantly, it also leverages investments already made by the government in education, technology development, infrastructure and innovation.

Developed by the Smart Nation Digital Government Office (SNDGO), the AI strategy not only identifies key areas that can be enabled by AI and the necessary resources to support nation-wide AI adoption, but also aims to set out Singapore’s stall as a leading global hub for the development, testing and export of AI applications. Recently ranked by the think tank Oliver Wyman Forum as the city most ready for AI, Singapore’s play for a greater role in the development of commercial and government AI systems has many things going for it.

Against the backdrop of the China-US trade war, Singapore is geographically and politically well placed to encourage both Chinese and American investment in AI ventures, at a time when cross-border foreign direct investment and venture capital between the two AI powerhouses is at its lowest level since 2014. Meanwhile, the combination of the country’s willingness to implement AI and the small size of the nation itself, make it an ideal testbed for AI developers to try-out their solutions before exporting them to larger countries, where implementation may face more obstacles and have higher costs.

Singapore’s strategy identifies key enablers for AI innovation and adoption, including the development of talent, data infrastructure and creating a progressive and trusted environment for AI. However, crucially, it also picks five core development projects designed to bring early benefits, plus create opportunities for local innovation and investment. By choosing AI-enabled projects that both address national challenges and deliver a visible impact on society and the economy, Singapore is also preparing the proof of concept for its goal of becoming a global hub for the development of AI technologies.

It’s no coincidence that the UAE, Finland and Singapore all first committed to national AI strategies in 2017, alongside large nations such as Canada and China, but well ahead of most of the world. All three countries have populations under 10 million, have relatively large economies and have been able to stay ahead of the technology curve.

The forward-looking policy and smaller size of these countries has helped to make embracing new technologies faster and more achievable than for many larger countries with bigger budgets, often allowing them to leapfrog global competitors.

Finland, Singapore and the UAE were all early pioneers of e-government, helping to develop new digital government processes. They were all also early adopters of new mobile standards and consumer services including mobile broadband.

So, it makes perfect sense that smaller digital-savvy countries should be able to take leadership positions in the fast-developing world of AI.

It is now well-known that the UAE was the first country in the world to bring AI decision-making into government at a cabinet level, naming His Excellency Omar Sultan Al Olama Minister of State for Artificial Intelligence in October 2017. In April of this year, the cabinet approved the UAE’s AI Strategy 2031.

The UAE has also made strategic investments in a number of new ventures to ensure that the UAE becomes not only an early adopter, but also a leading producer of AI applications. Last week Abu Dhabi National Oil Company (Adnoc), one of the world’s largest oil production companies, announced a joint venture with UAE AI group G42 to create artificially intelligent applications for the energy sector.

Other high profile AI investments in the UAE include a world-class AI research institute in its capital, the world’s first dedicated artificial intelligence university and Chinese AI provider SenseTime’s plans to open a Europe, Middle East and Africa research and development centre in Abu Dhabi.

Singapore’s new national AI strategy makes a convincing case for prioritising the development of a homegrown AI industry, in line with the country’s core strengths and challenges. The UAE has its own set of strengths and challenges, and these too, provide a golden opportunity for it to become one of the world’s leading AI producers.

This story was first published by The National


November 2, 2019
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Do brands need AI avatars of themselves? Last week at London’s One Young World Summit, Biz Stone co-founder of Twitter and Lars Buttler, CEO of San Francisco-based The AI Foundation, announced a new concept they called ‘personal media’ and claimed that artificial intelligence is the future of social change. The Foundation is working on new technology that Buttler says will allow anyone to create an AI avatar of themselves, which would look like them, talk like them and act like them. Empowered by AI avatars, people will then be able to, potentially, have billions of conversations at the same time.

So, what does this new kind of AI communications mean for brands?

Continue reading this story on Linkedin


October 31, 2019
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Twitter co-founder Biz Stone and Lars Buttler, chief executive of San Francisco-based The AI Foundation, introduced a new concept of ‘personal media’, enabled by artificial intelligence at last week’s One Young World Summit in London. The company is developing technology to allow anyone to create an artificial version of themselves to represent their interests anytime, anywhere. These personal avatars will look, sound and act like their creators.

According to the Stone and Buttler, just as the world moved from the mass media era to the social media era, it will now begin to move into the age of ‘personal media’.

Continue reading this story on The National.


September 19, 2019
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Google CEO Sundar Pichai delighted the audience at the Internet giant’s annual developer event Google I/O last year with a demonstration of an upcoming feature for Google Assistant currently called Duplex. Live in front of the Mountain View audience, Pichai showed Google Assistant making a telephone call to a hair salon, talking to the salon representative who answered the phone, negotiating the time of the appointment and making a booking for the user.

The Google Duplex demo gave the audience (and Youtube viewers around the world) a tiny glimpse into our artificial intelligence future: a future where our intelligent devices will be able to make our calls, restaurant reservations, flight bookings and buy us tickets for the theatre.

Continue reading this article on Arabnet.