artificial intelligence Archives — Page 2 of 3 — Carrington Malin

January 10, 2021
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My New Year’s Linkedin poll about changes in how people feel about their ethical concerns regarding AI doesn’t prove much, but it does show that 2020 did little to ease those concerns.

Opinions and our level of understanding about artificial intelligence can vary a great deal from person to person. For example, I consider myself a bit of a technophile and an advocate of many technologies including AI, with a higher than average level of understanding. However, I harbour many concerns about the ethical application, usage and the lack of governance for some AI technologies. My knowledge doesn’t stop me having serious concerns, nor do those concerns stop me from seeing the benefits of technology applied well. I also expect my views on the solutions to ethical issues to differ from others. AI ethics is a complex subject.

So, my intention in running this limited Linkedin poll over the past week (96 people responded) was not to analyse the level of concern that people feel about AI, nor the reasons behind it, but simply whether the widepread media coverage about AI during the pandemic had either heightened or alleviated people’s concerns.

The results of the poll show that few people (9%) felt that their ethical concerns about AI were alleviated during 2020. Meanwhile, a significant proportion (38%) felt that 2020’s media coverage had actually heightened their ethical concerns about AI. We can’t guess the level of concern among the third and largest group – the 53% that voted 2020 ‘hasn’t changed anything’ – however, it’s clear that 2020 media coverage about AI brought no news to alleviate any concerns they might have either.

Artificial intelligence ethical concerns poll 2020

Media stories about the role of AI technologies in responding to the coronavirus pandemic began to appear early on in 2020, with governments, corporations and NGOs providing examples of where AI was being put to work and how it was benefiting citizens, customers, businesses, health systems, public services and society in general. Surely, this presented a golden opportunity for proponents of AI to build trust in its applications and technologies?

Automation and AI chat bots allowed private and public sector services, including healthcare systems, to handle customer needs as live person-to-person communications became more difficult to ensure. Meanwhile, credit was given to AI for helping to speed up data analysis, research and development to find new solutions, treatments and vaccines to protect society against the onslaught of Covid-19. Then there was the wave of digital adoption by retail companies (AI powered or not) in an effort to provide digital, contactless access to their services, boosting consumer confidence in services and increasing usage of online ordering and contactless payments.

On the whole, trust in the technology industry remains relatively high compared to other industries, but, nevertheless, trust is being eroded and it’s not a surprise that new, less understood and less regulated technologies such as AI are fueling concerns. Fear of AI-driven job losses is a popular concern, but so are privacy, security and data issues. However, many people around the world are broadly positive about AI, in particular those in Asia. According to Pew Research Center, two thirds or more of people surveyed in India, Japan, Singapore, South Korea and Taiwan say that AI has been a good thing for society.

Since the beginning of the pandemic, AI’s public image has had wins and losses. For example, research from Amedeus found that 56% of Indians believe new technologies will boost their confidence in travel. Meanwhile, a study of National Health Service (NHS) workers in London found that although 70% believed that AI could be useful, 80% of participants believed that there could be serious privacy issues associated with its use. However, despite a relatively high level of trust in the US for government usage of facial recognition, the Black Lives Matter protests of 2020 highlighted deep concerns, prompting Amazon, IBM and Microsoft to halt the sale of facial recognition to police forces.

Overall, I don’t think that AI has been seen as the widespread buffer to the spread of Covid-19 as it, perhaps, could have turned out to be. Renowned global AI expert Kai-Fu Lee commented in a webinar last month that AI wasn’t really prepared to make the decisive difference in combating the spread of the new coronavirus. With no grand victory over Covid-19 to attribute to AI, its role over the past year it’s understandable that there was no grand victory for AI’s public image either. Meanwhile, all the inconvenient questions about AI’s future and the overall lack of clear policies that fuel concerns about AI remain, some even attracting greater attention during the pandemic.

This article was first posted on Linkedin.


September 5, 2020
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The Saudi national artificial intelligence strategy is to be launched at the Global AI Summit, which will now take place virtually from 21-22 October*, according to a statement from the Saudi Data and Artificial Intelligence Authority (SDAIA) on Friday. It was disclosed in August that the national AI strategy presented by the authority (since named the National Strategy for Data & AI) had been approved by King Salman bin Abdulaziz Al Saud. PWC has forecast that AI could contribute $135 billion (or 12.4%) to Saudi Arabia’s GDP by the year 2030.

Established by royal decree in August 2019, the SDAIA was given the mandate to drive the national data and AI agenda for transforming the country into a leading data-driven economy, and has developed Saudi Arabia’s national AI strategy over the past year. Although the details of the plan have been kept under wraps, the new strategy is expected to contribute to 66 of the country’s strategic goals, which are directly or indirectly related to data and AI.

The SDAIA has already reached a number of milestones since its inception, establishing three specialised centres of expertise: the National Information Center, the National Data Management Office and the National Center for AI. It has also begun building one of the largest data clouds in the region by merging 83 data centres owned by over 40 Saudi government bodies. More than 80 percent of government datasets have so far been consolidated under a national data bank.

Meanwhile, the authority has been using AI to identify opportunities for improving the Kingdom’s government processes, which may result in some $10 billion in government savings and additional revenues.

Originally slated for March 2020, the Global AI Summit will discuss AI, its applications, impact on social and economic development, plus global challenges and opportunities. The event aims to connect key decision makers from government and public sector, academia, industry and enterprise, tech firms, investors, entrepreneurs and startups.

October’s virtual summit will be organised into four tracks:

    • Shaping the new normal;
    • AI and governments;
    • Governing AI; and
    • The future of AI.

The Global AI Summit aims to tackle the challenges faced by countries around the world, from technical to ethical. Details of the agenda and speaker platform for the Global AI Summit have yet to be announced, although the presentation of the Saudi national artificial intelligence strategy is bound to be a highlight.

*Updated 17 September 2020

Also read: Saudi national AI strategy announced with investment target of $20 billion – 21 October 2020


August 21, 2020
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A great roundup about artificial intelligence in the Middle East by Damian Radcliffe, Carolyn S Chambers Professor in Journalism at the University of Oregon, which quotes me commenting on Saudi Arabia and the United Arab Emirates. With IT spending in the Middle East and Africa (MEA) forecast by IDC to reach $83 billion this year, AI is going to become an increasing focus.

IDC also predicts that investment in AI systems across MEA will hit $374.2 million this year, up from $261.8 million in 2018 and a projected expenditure of $310.3 million in 2019. However, with many AI technologies in high demand since the arrival of the Covid-19 pandemic, one has to wonder how this will affect IDC’s forecasts – not just in the MEA region, but globally too.

Saudi Arabia and the UAE had both begun investing in new AI technologies for government use, planning how to encourage AI-powered innovations and looking at regulatory requirements for their Fourth Industrial Revolution future. However, the advent of coronavirus has certainly fueled both interest and investment in artificial intelligence, with public and private sectors investing in automation, data analysis, robotics, health and safety systems, plus technologies to enhance contactless delivery of consumer services.

Despite forcing the cancellation of many high tech events around the region, the pandemic has also, arguably, fast tracked government plans and policies to harness AI and create a business environment conducive to driving successful digital economies. The UAE is reported to have improved plans for leveraging AI consistent with its national AI strategy, while Dubai announced a new comprehensive drone law in July. Meanwhile, Saudi Arabia approved its own national artificial intelligence strategy in August – and muted that it would soon introduce a comprehensive law to govern commercial and recreational drone use in the Kingdom.

For more on artificial intelligence in the Middle East read Damian’s full article here.


August 16, 2020
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The Indonesia National AI Strategy, now known as Stranas K.A. (Strategi Nasional Kecerdasan Artifisial), has been published. The new strategy was announced by the Minister of Research and Technology and head of the BRIN (the National Research and Innovation Agency) Bambang PS Brodjonegoro in an television address made last Monday to mark the country’s 25th National Technology Awakening Day. The minister also launched an electronic innovation catalogue, helping Indonesian technology developers to market their offerings and sell to government procurement offices.

Transforming Indonesia into a Fourth Industrial Revolution economy has become focus for the government over the past few years and the necessity of creating a digital-savvy workforce has become a top priority. Stranas K.A. aims to tie together many of the country’s digital initiatives and maps closely to Visi Indonesia 2045, the country’s broad economic, social, governance and technology development strategy. The National Artificial Intelligence Strategy Framework provides an at-a-glance view of how these different goals are held in context.

Stranas K.A. aims to support five national priorities, where the government believes that artificial intelligence could have the biggest impact on national progress and outcomes.

Health services – With 268 million people living across 6,000 of Indonesia’s total 17,504 islands, delivering a consistent standard of healthcare is a national challenge. The archipelago also faces increased risks from global disease outbreaks such as SARS and, recently, Covid-19. The country’s response to the pandemic has already somewhat accelerated plans for smart hospitals and health security infrastructure.

Bureaucractic reform – With a civilian civil service of about 4 million, reforming the government’s highly centralised administration remains a significant challenge. Indonesia is lagged in implementation of digital services, according to the United Nations E-Government Development Index (EGDI), ranking below Borneo, Malaysia, Singapore, Thailand and Vietnam. President Joko Widodo has promised to create a citizen-centric digitised service government (Pemerintahan Digital Melayani) in the next five years.

Education and research – Education is integral to Visi Indonesia 2045 and the move towards online schooling during the Covid-19 pandemic has laid bare the country’s digital divide. The pressures of the digital economy are also recognised by development plans. According to the government, Indonesia needs a digital workforce of 113 million by 2030-2035.

Food security – According to President Widodo, food security remains Indonesia’s top priority and the Food Security Agency focuses on three main areas: food availability, food accessibility and food utilisation. Food, agriculture and fisheries government departments and agencies have already begun using satellite technology, machine learning and smart farming to better plan, forecast and manage agricultural production and natural resources.

Mobility and smart cities – The number of people living in Indonesia’s urban areas is now close to 60 percent and is expected to rise to 70 percent of the total population by the year 2050. The government currently plans to develop 98 smart cities and 416 smart districts, under Indonesia’s 100 Smart Cities Plan.

Indonesia National AI Strategy, August 2020

Meanwhile, the Indonesia national AI strategy identifies four key focus areas:

    1. Ethics and Policy
    2. Talent Development
    3. Infrastructure and Data
    4. Industrial Research and Innovation

Indonesia is already one of South East Asia’s biggest investors in artificial intelligence, with IDC’s 2018 Asia-Pacific Enterprise Cognitive/AI survey finding that 25 percent of large organisations in the country have adopted AI systems (compared with 17% in Thailand, 10% in Singapore and 8% in Malaysia).

Smart cities, one of Stranas K.A.’s five top priority areas, have been identified as a fundamental building block for Indonesia’s Industry 4.0 future. Last year President Widodo announced plans to create a new futuristic smart city capital on the island of Borneo, to replace Jakarta. The new capital will rely heavily on sustainable smart city systems, cleantech and infrastructure run by emerging technologies such as 5G, AI and IoT (Internet of Things). Originally slated for completion by 2024 (pre-pandemic) and estimated to cost $33 billion, the project reportedly received an offer by Japanese multinational investor SoftBank Group to invest up to $40 billion.

The Indonesia National AI Strategy details a programme roadmap for both its four key focus areas and the five national priorities, for which it considers plans as short-term (2020-2024) and longer-term (2025-2045). All in all, the strategy document identifies 186 programmes, including many that aim to develop the plans, pilot schemes, policies and regulations, plus checks and balances, necessary to drive the overall strategy.

Underpinning the acceleration of Indonesia’s artificial intelligence journey, Stranas K.A. includes plans for national standards, regulations and an ethics board to ensure that usage of AI is in accordance with the country’s Pancasila values system.

The development of the 194-page National Artificial Intelligence Strategy was coordinated by the Agency for the Assessment and Application of Technology or BPPT, a non-ministerial government agency under the coordination of the Ministry for Research and Technology, and was widely anticipated to be announced in July or August. A wide variety of public and private sector organisations contributed to the plan including government ministries, universities, industry associations and national telecom providers.

Although many of the programmes and initiatives detailed in the Indonesia National AI Strategy can be found in existing government strategies, plans and policy, Stranas K.A. is nevertheless highly ambitious. The success of the overall plan will likely rest heavily on how many of the foundation programmes it is able to get off the ground during the next 4-5 years.


February 10, 2020
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As our world becomes AI First, we’ll soon see a new generation of AI natives – those that have never known a world without AI assistance – with their own set of needs, behaviours and preferences.

My daughter learned to recite the alphabet from Youtube when she was three and taught both her mother and grandmother how to use Netflix at age four. It was then when she discovered Google Voice Search and was delighted when she searched for the children’s rhyme There was an old woman who swallowed a fly and instantly discovered a video of the song. Since then, of course, she’s become a user of Amazon Alexa, Google Home and — now seven years old —has her own tablet, but nevertheless still borrows mobile devices from anyone that will allow her to amuse herself with apps and voice queries. For parents these days, this is the new normal.

The unprecedented accessibility of today’s technology begs many questions for parents, educators, healthcare professionals and society as a whole. Until the arrival of the iPad’s tap and swipe interface, literacy served parental control very well. If your child couldn’t type — or at least read — then they could not do very much with the Internet, discover content, participate in digital messaging or, most importantly, use digital devices to get into any trouble.

In the 80s, access to computers was mostly limited to those that wanted to learn MS DOS commands. With the proliferation of Microsoft Windows in the late 90s, users had to, at least, be able to read. In the 2000s, rich visual cues for point-and-click navigation on the Internet had begun to take over, but this still required a basic level of technical expertise to engage. Fast forward to 2019 and many homes have multiple, always-on devices that can be activated by voice commands. The only requirement the system makes of the user, is that they can speak a few words.

In the early 2000s, educational institutions, government departments and child welfare groups began campaigning in earnest for child safety on the Internet, raising awareness, for the most part, of dangers facing children from the age of 9 years old upwards that might have been using the Internet unsupervised. Today, with the increasing popularity of artificial intelligence-powered virtual assistants and other smart devices, your child could be accessing the Internet at age three or four. At first, they won’t be able to do very much with that access, but they learn fast!

So, now our globally-networked, AI-powered technology has become accessible even to tiny tots, what impact does this have on parenting, learning and a child’s cognitive development?

Throughout most of the past two decades, the American Academy of Pediatrics stood by its strict recommendation to parents of absolutely no screen time of any kind before the age of 2 years old. For parents with iPads and TV sets in the house trying to enforce this increasingly controversial rule, this was both frustrating and perplexing. It was hard to understand what the harm was in a one year-old watching an hour of TV or nursery rhymes on an iPad. In 2016, the AAP repealed its no-screen rule and instead introduce a more practical set of guidelines for parents raising children in a multi-media environment.

Unfortunately for the AAP, it is likely that their new set of technology guidelines for parents will be obsolete quite soon. AI voice technologies are being rapidly adopted around the world, with the likes of Alexa and Google Assistant being incorporated into a wider and wider range of devices and becoming commonplace in households globally.

As any family that has these devices at home will already know, children can turn out to be the biggest users of virtual assistants, both via mobile devices and via smart speakers. Whilst the language barrier prevents one and two year olds accessing the technology, today’s parents can expect that it won’t been too long after hearing baby’s first words that baby starts talking to AI.

Although circumstances obviously vary from child to child, according to their development and affinity to the technology, having always-on AI voice in the room raises its own set of questions.

For example, when does a child become aware than an AI voice device is not actually human? Is feeling empathy for a software programme a problem?

Should we, in the process of teaching our young children to be courteous, insist that they use pleases and thank yous when giving voice commands? If not, what are the implications of children growing up, from an early age, getting used to giving commands, while most parents are trying to teach them to be more polite?

Young children today are our first generation of AI natives. They will be the first generation to grow up never having known a world that wasn’t assisted by artificial intelligence. As the digital native generations before them, their needs and behaviours will be shaped by and in tune with prevailing technologies.

Whilst we can expect many false starts, artificial intelligence is going to be widely embraced by education systems to teach, tutor, test and grade school children and their work. In fact, it will prove to be pivotal to 21st century education.

Today, China is far into the lead in piloting new AI-powered school programmes. Some 60,000 schools in China — or nearly a quarter of those in the country — are currently piloting an AI system which grades student papers, identifies errors and makes recommendations to students on improvements such as writing style and the structure or theme of essays. A government programme led by scientists, the AI system is not intended to replace human teachers, just improve efficiency and reduce time spent on reviewing and marking student papers. Teachers can then invest more time and energy in teaching itself.

Chinese after-school tutoring platform Knowbox has raised over $300 million in funding since its launch in 2014, to help school students learn via apps that provide highly personlised curated lessons. It’s already working with 100,000 schools in China and has its sights set on the global education market.

Meanwhile, China is in the advanced stages of developing curricula on AI theory and coding for primary and secondary schools. Guangdong province, which borders Hong Kong and Macau, introduced courses on artificial intelligence to primary and middle school students from September 2019. The programme will be piloted in about 100 schools in the province, but by 2022 all primary and middle schools in the region’s capital Guangzhou will have AI courses incorporated into their regular curriculum.

Singapore launched its Code for Fun (CFF) schools programme in 2014 in selected schools, at first targeting about 93,000 students. Developed by the Ministry of Education and IMDA (the Infocomm Media Development Authority) the 10-hour programme teaches children core computing and coding concepts via simple visual programming-based lessons. All primary schools in Singapore will have adopted the programme by 2020.

Children growing up during the next decade, will simply take AI for granted, as a pervasive new wave of AI-powered services supports their every want and need. However, just as this new generation will find it hard to understand what life was like before AI, older generations will find some of the new habits and behaviours of AI natives unfathomable.

For better or for worse, the drivers for AI development and deployment are economic and commercial. So, we can expect brands and commercial services to continue be at the forefront of innovation in AI. Which means, just as previous generations have been characterised as being self-involved — beginning with the original ‘Me Generation’ of Baby Boomers, so AI natives are likely to struggle to explain themselves in a world that seemingly revolves around them.

There’s been much public comment over the past ten years to suggest that Millennials — the age group born between 1981 and 1996 — have developed to be more narcissistic than previous generations. The familiar argument credits social media and ecommerce with driving the need for young people’s excessive attention and instant gratification. Although, it is true that every generation of adults seem to view the population’s youth as narcissistic.

“The children now love luxury; they have bad manners, contempt for authority; they show disrespect for elders and love chatter in place of exercise. Children are now tyrants, not the servants of their households. They no longer rise when elders enter the room. They contradict their parents, chatter before company, gobble up dainties at the table, cross their legs, and tyrannise their teachers.”

– Socrates, 5th Century B.C. Greek philosopher.

University researchers in Europe and the U.S. have been trying to ascertain whether there has been a clear increase in narcissism for the past decade, but the truth has been found to be less straightforward than common prejudices.

A study by a joint European-U.S. university research team published in Psychological Science, suggested that there was a ‘small and continuous decline’ in narcissism among college students from 1992 to 2015. A recent study led by, then University of Mannheim, researcher Eunike Wezel and due to be published in the Journal of Language and Social Psychology found that, overall, narcissism seems to decline with age.

What is clear, is that young people in our globally-connected and information-rich world do appear to be better educated and more worldly-wise than previous generations, often having more confidence and being far more concerned with climate change, the destruction of our environment and the future of our planet.

So, as our technology becomes AI first, we can hope that ubiquitous access to knowledge, education and tools to empower individual aspirations is going to be a positive thing.

On the home front, a big part of the problem with parental control is that until very recently computer systems have never been developed with the under-tens in mind: let alone the under-fives. In the past, due to the technical knowledge required and the convenient literacy barrier, software developers rarely had to take children into account. This is now changing quite swiftly.

Amazon introduced a child-focused version of its Echo smart speaker a year or two ago, with a parental control dashboard which gives parents the options to limit access, set a cut-off for bedtime and choose what Alexa skills their children are permitted to use. It also released a ‘Say the Magic Words’ skill to help teach children good manners.

Meanwhile, Google is continuing to develop the capabilities of Family Link, a parental control hub for family Google accounts introduced in 2017. It boasts features such as setting screen time limits, approving Android Apps and even the ability to lock children’s devices remotely. Google also allows parents to set up Google Home voice profiles for their children.

Both Google and Amazon allow virtual assistant users to turn-off payment features to avoid accidental Barbie doll or remote-controlled toy orders.

The arrival of AI in our homes presents new challenges for parents, not entirely unlike the arrival of the television, video games, cable TV or the home broadband Internet connection. At first parents and child experts alike will struggle to put the benefits and risks of AI voice devices into context. Many children will succeed at this faster than either one.

This story first appeared on My AI Brand (Medium)


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.