Artificial intelligence: governments see huge business potential, but ignore the downsides
Many governments are increasingly approaching artificial intelligence with an almost religious zeal. By 2018 at least 22 countries around the world, and also the EU, had launched grand national strategies for making AI part of their business development, while many more had announced ethical frameworks for how it should be allowed to develop. The EU documents more than 290 AI policy initiatives in individual EU member states between 2016 and 2020.
The latest is Ireland, which has just announced its national AI strategy, “AI – Here for Good”. It aims to become “an international leader in using AI to benefit our economy and society, through a people-centred, ethical approach to its development, adoption and use”.
This is to be obtained via eight policy commandments, including increasing trust in and understanding of AI by using an “AI ambassador” - a veritable AI high priest – to spread the message around the country. Another aspect is to promote AI adoption by Irish businesses and the government within a special moral and ethical framework. There are several shortcomings in this strategy, which it shares with similar efforts by other countries (leaving aside more obviously bad AI strategies, such as that underlying China’s surveillance state).
The hype is tripe
Such strategies uncritically share the hype and hysteria surrounding AI. A typical example would be the chief executive of Google’s owner Alphabet, Sundar Pichai, claiming in 2016 that “AI is one of the most important things humanity is working on. It is more profound than, I dunno, electricity or fire”.
He would say this, as his company’s business model critically depends on AI, and on people trusting the technology. Ireland’s strategy goes precisely along with such hype by repeating the claim that AI could double Irish economic growth by 2035. It doesn’t detail whose growth, or how.
The strategy lauds various useful existing AI-based apps – which, for instance, improve cycling infrastructure in Dublin, provide Irish language tools, save energy, and comfort dementia suffers – but it is hard to see how more of these could double economic growth.
Most notably, AI is central to a few digital platform firms such as Google, Apple, Facebook, Amazon and Alibaba - GAFAA for short. They enjoy winner-takes-most benefits due to the fact that current AI requires large amounts of data. As more people use your platform, the profitability of the data grows exponentially.
This has given a huge first-mover advantage to those companies that got it right, turning them into monopolists and gatekeepers. Digital platform firms disrupt existing businesses by out-competing them every time - a good example being how Google, basically an online search-engine, disrupted the advertisement-driven business model of newspapers, or how Apple is selling more watches than the centuries-old Swiss watch industry.
And increasingly, entrepreneurs have to compete on these platforms – for example, Amazon Marketplace. They can be at the mercy of abuses such as fake product reviews by competitors; rulings on such issues by the gatekeepers that are unpredictable and opaque; and sudden algorithm changes that can affect their business by making them, for example, less visible to potential customers. Then there is the phenomenon of digital subsistence entrepreneurs – online sellers who barely earn a living wage.
This radically different (anti-) competition landscape – sometimes labelled “platform capitalism” – has caused regulators and antitrust authorities substantial headaches. The EU recently adopted proposals for a Digital Markets Act (DMA) and a Digital Services Act (DSA), which try to rein in the actual and potential abuses on large AI-based digital platforms.
If AI and automation had been a force to reckon with, we would have seen skyrocketing labour-productivity growth and rising unemployment. Instead, we see stagnating productivity growth – for example, the UK’s is the lowest in 200 years - and some of the lowest unemployment rates in western economies in decades.
Ireland’s AI strategy ignores the above problems with platform capitalism. The name Google appears only once in the entire document, and Amazon and Facebook not at all. There is no reference to digital platforms, platform capitalism, the DMA, DSA or the EU’s many antitrust actions against Google. The omission is like Hamlet without the Prince.
Ireland’s AI strategy should have specified how and when AI will achieve the economic benefits it mentions – and who will reap them. It also should have offered a vision of how to make sure that the nation does not suffer from the GAFAAs or become a mere agent of them.
Firms don’t use it
The strategy also assumes that a lack of trust in AI is due to people not understanding the technology well enough. So voilà, teaching people data science and having an AI ambassador, like a modern-day prophet, is the answer. One may expect precisely the opposite outcome: the better people understand AI, the less they will trust it.
This would actually be desirable, of course. In the US, where understanding of AI is fairly advanced, adoption rates of AI are in fact meagre. A recent US Census Bureau survey of more than 800,000 US firms found that only 2.9% were using machine learning as recently as 2018. A 2020 survey by the European Commission also pointed to very low adoption levels.
Many other surveys confirm the low adoption rate of AI. Firms do not adopt it, not because they don’t trust it, but because it makes little business sense. It is too expensive, usually with paltry returns, and comes with an exorbitant environmental price tag – and all that before you factor in the domination of the incumbents.
Ireland’s “AI - Here for Good”, like many similar national strategies, seems to believe in miracles, for instance that various circles can be squared. These include enabling access to large volumes of relevant data for all firms while protecting everyone’s privacy, and turning the country into a powerhouse for training sizeable deep-learning models and massive data centres while cutting CO₂ emissions. It admits no trade-offs.
The implied message is that Ireland can pluck wonderful fruits from a thicket of thorns, just so long as it trusts in AI and adheres to its particular ethical commandments. Transhumanists, GAFAA, and other winners-takes-all in the digital economy will approve wholeheartedly.
The internet’s economic model is broken – here’s how we can fix it
Ethical technology start-up Bubblr has been on a seven-year journey to fix a broken internet. After the US patent office approved it’s patent for a design for an alternative economic model for the internet, it is now poised to transition from newly listed start-up to global technology player, with an ambition to become a fully-listed NASDAQ business within 18 months.
Why is the internet broken?
There are three key stakeholder groups in the current economic model for the internet: ordinary people who use it to search for information, services, and products; content providers who create content to be paid for and consumed; and online suppliers who use the internet as a marketing tool to acquire prospects and make online sales.
The underlying ad-tech economic model that currently powers the internet emerged by accident after the dot-com crash of 2000-2001. Until the crash, Google and other VC-funded dot-com businesses were not under pressure to monetise their products. When the VC community insisted on a shift to monetisation, they adopted the practices of the only industry making money online at the time: the adult entertainment business. Its ad-tech blueprint was based on banner ads, pay-per-click traffic and attribution mechanisms. It was never designed to be a longer-term sustainable model, and this reality now rings true for internet companies.
Here’s why. Ordinary people have realised that their personal data is being used and abused by bad actors. Searching for stuff on the internet using Google is becoming more laborious, involving a trawl through an exponentially larger swathe of poor search results.
Small businesses find themselves locked out of using Google or Facebook for marketing leads since it is too complex and expensive. In many cases, their online participation is diluted because the market sector forces them to use costly intermediaries. For example, the lodging sector must use booking agents such as booking.com or hotels.com, who take a significant percentage of generated revenue.
Content providers are receiving ever-smaller amounts of revenue from banner ads. This has led to the demise of established news outlets, especially those for local news. It has also led to the emergence of clickbait and publishing content that is often deliberately false and controversial to acquire more views and feed an advertising model instead of producing truthful, high-quality content.
Cracks are already visible in the established ad-tech model. A debate has emerged questioning the effectiveness of ad-tech expenditure on mobile devices. Procter & Gamble recently cut $200 million from its digital ad spend and increased reach by 10 per cent. Google is already losing search traffic for specific categories of goods and services. People are increasingly using single-purpose mobile apps to purchase things such as takeaways or train tickets. Mobile shopping is booming and has increased by 300 per cent in the past four years.
The digital manifestation of Bubblr’s patent is the company’s development of an ad-free marketplace. The ad-free marketplace is an alternative economic model for the internet that, by design, provides a superior stakeholder experience that is both fair and sustainable rather than the established ad-tech economic model that emerged by accident:
• Ordinary people can anonymously access the internet with their privacy protected, as there is no data harvesting or personal tracking.
• Small and medium-sized businesses can compete with large corporations based on their online performance in fulfilling customers’ needs, instead of how much they have in their marketing budgets.
• Content providers are rewarded for producing quality content without any third-party ad placements. The economics are based on content consumption rather than clicks.
Bubblr intends to lead the way for ethical tech firms. The ad-free marketplace is a technology platform that cuts across industries, services and products. It will disrupt how e-commerce functions and provide net-new technology for the masses, business partnerships, and licensing opportunities. It can fix the problems that now favor big tech, which can signal the beginning of the end for ad-tech.
Find out more about this "Moonshot" ethical technology company at www.bubblr.com
by Steve Morris CTO and Founder, Bubblr Inc.
How to help entrepreneurs adopt cutting edge technologies to grow their businesses
Entrepreneurs are known to drive innovation and progress in various fields. The Fourth Industrial Revolution has provided an unprecedented platform to do so.
This global concept was coined in 2016 by Professor Klaus Schwab. He said that this revolution entails “nothing less than the transformation of humankind” because it is the integration of technologies across the digital, physical and biological spheres. Moreover, the speed at which this is happening is influencing work, services, educational needs and people’s everyday activities.
Entrepreneurs have the potential to create entirely new ways of providing goods and services through technological innovations. In South Africa entrepreneurs have done so on various fronts.
One example is Jobox, a platform that helps optimise the freelance economy and assists in getting people employed. Another is Strait Access Technologies, a start-up company that’s driving breakthrough medical devices for heart valve replacement.
This requires a certain level of comprehension about what kinds of technologies are available, but also how they can enhance products and services with digital capabilities.
Our research aimed to find out what competencies entrepreneurs need so that they can best use current technologies to seize opportunities and create successful businesses. These technologies include artificial intelligence, adaptive robotics, the Internet of Things, big data, drones, 5G and cloud systems. All are continuously evolving.
What we looked for and what we found
Our study found that the technology landscape is vastly complex because of the potential for integration, as well as the fact that technologies are constantly evolving.
For entrepreneurs to develop relevant products, they need core competencies to tackle the new age technologies and reap the potential rewards.
Our study confirmed that innovation and creativity remain fundamental skills. But additional competencies are also needed. These include the ability to cross-link business units through digital connectivity, rapid prototyping, and understanding how data-driven decisions can enable automated and personalised service offerings.
To find out what entrepreneurs would need, we ourselves delved into advanced technologies – such as machine learning – to confirm the accuracy of interview transcriptions and identify any possible oversights. We also looked at 3D printing as a technology that entrepreneurs could use to rapidly prototype using computer aided design.
We applied this in one case where a company was creating a product that could be deployed from the ground to disable drones in places where they were not permitted.
For easier understanding, we split the Fourth Industrial Revolution technologies into three different layers. The first was the physical layer, which consists of robotics and drones. The second was the connectivity layer which connects these technologies, such as 5G. Finally the digital layer, where data processing helps formulate meaningful insights. Technologies that could be used here include cloud services and artificial intelligence.
What emerged was that entrepreneurs were capable of creating new ventures if they developed new competencies. One was industrial automation using the Internet of Things to connect devices across a water treatment plant. The Internet of Things allows physical devices collecting data in different locations to be connected and for the data to be shared. In this case this technology provided automated systems to ensure energy efficiency and could identify machinery breakdowns before they happened.
Another was a cloud based system using eye-tracking data to determine client engagement with textbooks. This was then used to note which areas were overlooked by students, or where there were areas of difficulty.
Our data analysis showed there was a wide scope for entrepreneurial competencies that could be used not only in a university context, but also in existing job roles.
South Africa needs to continue to make strides to harness potential benefits by supporting entrepreneurs. Although government has produced a white paper to this end, other efforts could be strengthened. These include raising awareness about government programmes and enhancing access to new forms of financing to launch businesses.
In addition, academic institutions and schools need to continually blend interdisciplinary skills towards competencies for graduates as well as those who engage in life-long learning. Most importantly, institutions must incorporate participation in some of the programmes that are already under way as well as forums where these skills can be applied.
If this development can be guided, South Africa’s entrepreneurial landscape can flourish. This won’t only drive economic growth. It will also get young people economically active and create jobs.
The post-cookie future: driving outcomes through context
As the third-party cookie fades away, marketers are seeking innovative solutions to help them step into the new marketing era.
In recent years, marketers have become familiar with talk of the “death of the cookie,” correlated with an increase in data privacy regulations, such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR).
Along with these limits placed on the use of third-party data by new data privacy laws, new standards are being set by tech companies, with Apple and Google taking two separate directions in paving the way to protect privacy, while enabling continued brand connections with consumers.
With these changes in mind, many industry players throughout the (m)adtech landscape are seeking innovative solutions that take a consumer-centric approach: businesses want to reach audiences where it matters, powered by compliant customer data, to build a strategy that drives personalisation and meaningful outcomes.
According to the Interactive Advertising Bureau (IAB) State of Data 2020 report, 57.1 per cent of respondents stated they have already increased their use of first-party data for targeting over the past 18 months. Additionally, the use of first-party and contextual data for targeting has increased as marketers look to make better use of the data-driven transformation in a privacy-compliant way.
Among the varied tactics and technologies surfacing in the post-cookie world, contextual targeting is once again making headlines, and for good reason. By design, this cookieless solution is not only privacy compliant, but built around the concept of in-the-moment marketing.
Contextual advertising in and of itself, however, is not new: the original method of keyword targeting was previously a favoured tactic for marketers looking to reach the right audience in “brand safe” environments. Yet, as we transition into new waters, we are seeing a resurgence in its popularity, while acknowledging that keyword-based targeting alone does not meet the needs of today’s sophisticated media buyers. The evolution of contextual targeting needs to move from being “yet another targeting tactic” to the driver of measurable outcomes.
Redefining context for the modern marketer
Marketers are seeking the same outcomes that they have done since the dawn of advertising: ensuring that their coveted brands will be seen at the right time, the right place, and in the right moment.
Context targeting (also referred to as suitability targeting) identifies in-the-moment marketing opportunities by analysing content along with the broad spectrum of data signals available to align consumer receptivity with the brand message. In fact, some studies suggest context targeting can increase purchase intent by 63 per cent when compared with audience or channel level targeting.
In a contextual paradox, this method is the exact opposite of “brand safety blocking” from the cookie-era, when it was all about negative avoidance, and has revealed one of the critical reasons why the tools of the last era are insufficient for modern marketer needs.
To identify in-the-moment marketing opportunities, next-gen context-targeting solutions must include a few key elements. First and foremost, they must be capable of analysing a variety of mediums with accuracy including text, video, audio and images – this is after all a generation that consumes ever-more content, with shifting and innovative formats across a plethora of connected devices. Secondly, marketers must extend their prior investment by leveraging targeting signals from their hard-earned first-party data. First-party data has a massive role to play in the new wave of contextual and is one of the richest forms of insight a brand can extract from. And lastly, and by no means least, marketers must look to optimise outcomes by turning campaign insights into actions that continuously drive increased performance.
Delivering outcomes through context
With the death of the cookie, the acknowledgement by Facebook that walled garden attribution is changing, and Google undertaking greater consolidation inside its ecosystem, we are at a unique moment in time where we can redefine the outcome to one that makes sense, is measurable and, most importantly, actionable.
Defining a digital media outcome as the closest point to the transaction which can be accurately measured and correlated back to advertising dollars is the best way to start. By defining the digital outcome as the closest point, we have built flexibility into the definition. It evolves with brands as they make investment choices in technology and partners while providing clarity to all who strive to build a better ecosystem together.
The great news is that these types of outcomes can now be achieved by using real-time contextual data signals, clearly redefining what a contextual platform should be able to do for marketers in the modern era.
Looking to the new wave of contextual intelligence
Now is the time for marketers to take a deeper dive into the contextual landscape as they ready themselves for the inevitable identity shift to fall into place.
What won’t change in the cookieless world is marketers’ need for differentiation. It won’t change the fact that publishers need funding from advertising to survive. And, perhaps most importantly, consumers will still want personalised advertising and content experiences, tailored to them, their needs and preferences, while feeling protected against data fraud. Contextual targeting and the advancements wrapped around innovative solutions today stands strong as a solution for each of these needs, offering marketers more confidence that their ads are relevant, safe and suitable.
As the programmatic industry evolves it is time to work together to push the creative boundaries for clients and campaigns, and what better place to begin than delivering true marketing outcomes through the power of context.
To find out more, please contact Silverbullet at www.wearesilverbullet.com
by Umberto Torrielli, Co-founder and CSO, Silverbullet and 4D
Digital transformation for digital native businesses
Digital Transformation is about real change from old to new in pursuit of value generation in a changing landscape. Large Enterprises often embark upon Digital Transformation to stay relevant in face of new and evolving challenges. These common sets of challenges range from legacy systems to legacy processes, culture and/or mindset.
While the above is true for Large Enterprises, Digital Transformation has a different meaning in the context of Digital Native Businesses. Digital Natives are those businesses that have their inception in the last 10 years and use digital medium as their primary mechanism of value creation. They don't suffer from legacy baggage.
Digital Native businesses share the following common technological characteristics that shape their digital transformation needs:
Hazel Oliver, CTO of Nimbla, has been in the digital space for more than two decades and has travelled across realms of technological transformation. In the above video, Hazel shares her IT journey from working in Traditional Corporations to Digital Natives with the Searce’s Executives. She centres around the requirement for Digital Transformation in Digital Natives. Watch Full Video Here!
The cloud technology available is changing constantly. The advent of containers and Kubernetes means that more can be done with fewer resources and at a lower cost. For digital natives, the Cloud's ever-changing benefits are significant. Previously, cloud service providers only provided infrastructure; currently, they offer a full range of services, including infrastructure management. This relieves its clients of labour and allows them to focus on value creation rather than mundane responsibilities like keeping the lights on.
Helping Digital Natives Scale Faster
Digital natives need to free themselves from the constraints of technological self-sufficiency if they are to achieve high levels of growth. Digitally native businesses need to accelerate using emerging technologies such as automation and machine learning. By partnering with third parties who have specialist skills, they will be able to make the most of the efficiencies that emerging technologies offer.
The specialist third parties with in-depth knowledge of unused technological opportunities are a powerful way forward for these businesses to increase effectiveness and reduce operational risks. It takes a Digital Native to understand a Digital Native! Searce is a Google Cloud Platform-focused Cloud Native Consulting firm. Searce works with digital native businesses all over the world to help them expand 10x faster by leveraging Cloud, Data, and Artificial Intelligence. Visit Searce.com to learn more about Searce.
All things considered, even advanced Digital Natives can’t expect to know everything about everything. Need a partner who will help you RAMP by#SolvingforBetter ? Visit searce.com to learn more about Searce, Inc.
I’m a Luddite. You should be one too
I’m a Luddite. This is not a hesitant confession, but a proud proclamation. I’m also a social scientist who studies how new technologies affect politics, economics and society. For me, Luddism is not a naive feeling, but a considered position.
And once you know what Luddism actually stands for, I’m willing to bet you will be one too — or at least much more sympathetic to the Luddite cause than you think.
Today the term is mostly lobbed as an insult. Take this example from a recent report by global consulting firm Accenture on why the health-care industry should enthusiastically embrace artificial intelligence:
'Excessive caution can be detrimental, creating a luddite culture of following the herd instead of forging forward.'
To be a Luddite is seen as synonymous with being primitive — backwards in your outlook, ignorant of innovation’s wonders, and fearful of modern society. This all-or-nothing approach to debates about technology and society is based on severe misconceptions of the real history and politics of the original Luddites: English textile workers in the early 19th century who, under the cover of night, destroyed weaving machines in protest to changes in their working conditions.
Our circumstances today are more similar to theirs than it might seem, as new technologies are being used to transform our own working and social conditions — think increases in employee surveillance during lockdowns, or exploitation by gig labour platforms. It’s time we reconsider the lessons of Luddism.
A brief — and accurate — history of Luddism
Even among other social scientists who study these kinds of critical questions about technology, the label of “Luddite” is still largely an ironic one. It’s the kind of self-effacing thing you say when fumbling with screen-sharing on Zoom during a presentation: “Sorry, I’m such a Luddite!”
It wasn’t until I learned the true origins of Luddism that I began sincerely to regard myself as one of them.
The Luddites were a secret organisation of workers who smashed machines in the textile factories of England in the early 1800s, a period of increasing industrialisation, economic hardship due to expensive conflicts with France and the United States, and widespread unrest among the working class. They took their name from the apocryphal tale of Ned Ludd, a weaver’s apprentice who supposedly smashed two knitting machines in a fit of rage.
The contemporary usage of Luddite has the machine-smashing part correct — but that’s about all it gets right.
First, the Luddites were not indiscriminate. They were intentional and purposeful about which machines they smashed. They targeted those owned by manufacturers who were known to pay low wages, disregard workers’ safety, and/or speed up the pace of work. Even within a single factory — which would contain machines owned by different capitalists — some machines were destroyed and others pardoned depending on the business practices of their owners.
Second, the Luddites were not ignorant. Smashing machines was not a kneejerk reaction to new technology, but a tactical response by workers based on their understanding of how owners were using those machines to make labour conditions more exploitative. As historian David Noble puts it, they understood “technology in the present tense”, by analysing its immediate, material impacts and acting accordingly.
Luddism was a working-class movement opposed to the political consequences of industrial capitalism. The Luddites wanted technology to be deployed in ways that made work more humane and gave workers more autonomy. The bosses, on the other hand, wanted to drive down costs and increase productivity.
Third, the Luddites were not against innovation. Many of the technologies they destroyed weren’t even new inventions. As historian Adrian Randall points out, one machine they targeted, the gig mill, had been used for more than a century in textile manufacturing. Similarly, the power loom had been used for decades before the Luddite uprisings.
It wasn’t the invention of these machines that provoked the Luddites to action. They only banded together once factory owners began using these machines to displace and disempower workers.
The factory owners won in the end: they succeeded in convincing the state to make “frame breaking” a treasonous crime punishable by hanging. The army was sent in to break up and hunt down the Luddites.
The Luddite rebellion lasted from 1811 to 1816, and today (as Randall puts it), it has become “a cautionary moral tale”. The story is told to discourage workers from resisting the march of capitalist progress, lest they too end up like the Luddites.
Today, new technologies are being used to alter our lives, societies and working conditions no less profoundly than mechanical looms were used to transform those of the original Luddites. The excesses of big tech companies - Amazon’s inhumane exploitation of workers in warehouses driven by automation and machine vision, Uber’s gig-economy lobbying and disregard for labour law, Facebook’s unchecked extraction of unprecedented amounts of user data - are driving a public backlash that may contain the seeds of a neo-Luddite movement.
As Gavin Mueller writes in his new book on Luddism, our goal in taking up the Luddite banner should be “to study and learn from the history of past struggles, to recover the voices from past movements so that they might inform current ones”.
What would Luddism look like today? It won’t necessarily (or only) be a movement that takes up hammers against smart fridges, data servers and e-commerce warehouses. Instead, it would treat technology as a political and economic phenomenon that deserves to be critically scrutinised and democratically governed, rather than a grab bag of neat apps and gadgets.
In a recent article in Nature, my colleagues and I argued that data must be reclaimed from corporate gatekeepers and managed as a collective good by public institutions. This kind of argument is deeply informed by the Luddite ethos, calling for the hammer of antitrust to break up the tech oligopoly that currently controls how data is created, accessed, and used.
A neo-Luddite movement would understand no technology is sacred in itself, but is only worthwhile insofar as it benefits society. It would confront the harms done by digital capitalism and seek to address them by giving people more power over the technological systems that structure their lives.
This is what it means to be a Luddite today. Two centuries ago, Luddism was a rallying call used by the working class to build solidarity in the battle for their livelihoods and autonomy.
And so too should neo-Luddism be a banner that brings workers together in today’s fight for those same rights. Join me in reclaiming the name of Ludd!