Dr Abdelrahman AlMahmoud is the principal cloud and big data researcher at Technology Innovation Institute, a UAE-based scientific research centre
January 03, 2022
I was optimistic a year ago that AI would aid us considerably in putting an end to the pandemic. As an international community, however, we are still struggling to stem the spread of Covid-19 with all of its evolving variants, the latest named Omicron.
When the pandemic started, hundreds of AI projects were announced around the world; from infection-tracking systems to technologies that claimed to reverse engineer the code of the virus, to means that accelerated the speed of vaccine discovery, to processes that quickly diagnosed Covid-19 from medical images.
Medical staff prepare a patient in need of an ECMO (extracorporeal membrane oxygenation) life support unit for a CT examination, at the coronavirus disease (COVID-19) Intensive Care Unit in Darmstadt, Germany, December 11. Reuters
I often get asked where all the promise of AI went. In some people’s minds, the hype around AI remains unfulfilled or exaggerated. In fact, according to some estimates, around 85 per cent of AI projects will fail. However, it is unfair to gauge the success of AI based on a single project’s failure or success. On the contrary, we should measure success based on how big of an impact AI had or will have on certain domains and on a positive global effect on the pandemic.
I recall seeing hundreds of face mask detection projects when the pandemic started. While some have tried to spinoff startups from the technology, these startups tried to capitalise on the need for mask enforcement during the pandemic. None of them are in use right now. It turned out that this wasn't as big of a deal as many imagined and policies and law handled it much more effectively.
Another popular application was diagnosing Covid-19 from medical images.
Initially, many thought that medical staff would not be able to cope with the huge number of tests requested by people, considering we had millions of infections worldwide. Enter deep learning tools that could detect positive cases in seconds from x-rays and MRIs.
In theory, these were the perfect solution. However, it turned out that taking imaging devices like MRI machines into the field was impractical. Setting up a mobile lab to collect swabs made much more sense.
A health worker in a mobile lab takes a sample for a Covid-19 test in New Delhi, India. AP
Furthermore, these imaging systems could not be used in hospitals. They needed further clinical studies and scrutiny by regulatory authorities to ensure they were safe for medical use – tests that not many ended up passing. Thus, only a select few of these diagnostic tools are actually still in use.
AI is tied to available data. Unfortunately, the ability to access relevant, real-time data is extremely privileged. Only the top tech company superpowers and governments have access to granulated data. While the tech companies have a good handle on the data framework – due to heavily monetising it – governments still struggle to build such a framework. In fact, several governments around the world have struggled to collect useful data because of the extremely high level of expertise needed. Add to that the privacy issues, and there is a definite challenge on your hands.
If we want effective AI solutions, then we must define a framework for researchers, governments and the private sector
The existing data monopoly often strangles smaller companies and startups and pushes them to work on less pressing problems, such as face mask detection. The solution to this is very complex, due to data sharing frameworks and the nature of personal data.
One popular approach has been to share small datasets with researchers to test and develop their systems. While that can get the ball rolling, it is extremely difficult to do it in a meaningful way. In most cases, such efforts only end up being useful for student course projects or to test a hypothesis. The reality is that building effective AI tools requires constant development, monitoring and on flowing data which can only be achieved with tight integration. Static datasets just do not suffice in the real world.
Let us also look at the example of Tesla, one of the leaders in autonomous driving – the concept of driver-less cars has gripped many imaginations over the years. In pursuit of making this goal a reality, Tesla is effectively crowdsourcing data from its enormous fleet of cars to its cloud and data centres. The amount of engineering work, expertise and massive infrastructure developed to cope with incoming data is an example of the huge effort needed to solve these challenges.
A new Tesla owner demonstrates on a closed course in Portland, Oregon, how he can play video games while driving, on December 8, 2021. The US has opened an investigation into a report that Tesla vehicles allow people to play video games on a centre touch screen while behind the wheel. AP
To put a dent in a global healthcare challenge like Covid-19 requires much more effort than a quick-win mentality. The time, effort and resources needed is not something that a single entity – even tech giants – can handle. What is needed is government support, funding and the integrated effort of a top scientists and their teams.
If we want effective AI solutions, then we must define a framework for researchers, governments and the private sector to get access to relevant data when needed. The first steps towards addressing these challenges are already under way in the form of analysis systems that preserve privacy and are secure, but much remains to be done still to make them practical.
Finally, isolation is the biggest impediment to AI success, by which I mean the disconnect between academic institutions and governments. If you have attended any meeting where researchers and officials are trying to engage with one another, you will immediately see that these teams tend to speak different languages. They simply do not understand one another.
Or in many cases, their interests, the way they perceive the challenges, and their thoughts on how to proceed don't align.
While they can both do just fine in their own bubbles, neither will be able to enjoy any significant impact or transformation. It is time to re-engage all parties to drive this worthwhile effort in a more organised and consistent way.
Mercer, the investment consulting arm of US services company Marsh & McLennan, expects its wealth division to at least double its assets under management (AUM) in the Middle East as wealth in the region continues to grow despite economic headwinds, a company official said.
Mercer Wealth, which globally has $160 billion in AUM, plans to boost its AUM in the region to $2-$3bn in the next 2-3 years from the present $1bn, said Yasir AbuShaban, a Dubai-based principal with Mercer Wealth.
“Within the next two to three years, we are looking at reaching $2 to $3 billion as a conservative estimate and we do see an opportunity to do so,” said Mr AbuShaban.
Mercer does not directly make investments, but allocates clients’ money they have discretion to, to professional asset managers. They also provide advice to clients.
“We have buying power. We can negotiate on their (client’s) behalf with asset managers to provide them lower fees than they otherwise would have to get on their own,” he added.
Mercer Wealth’s clients include sovereign wealth funds, family offices, and insurance companies among others.
From its office in Dubai, Mercer also looks after Africa, India and Turkey, where they also see opportunity for growth.
Wealth creation in Middle East and Africa (MEA) grew 8.5 per cent to $8.1 trillion last year from $7.5tn in 2015, higher than last year’s global average of 6 per cent and the second-highest growth in a region after Asia-Pacific which grew 9.9 per cent, according to consultancy Boston Consulting Group (BCG). In the region, where wealth grew just 1.9 per cent in 2015 compared with 2014, a pickup in oil prices has helped in wealth generation.
BCG is forecasting MEA wealth will rise to $12tn by 2021, growing at an annual average of 8 per cent.
Drivers of wealth generation in the region will be split evenly between new wealth creation and growth of performance of existing assets, according to BCG.
Another general trend in the region is clients’ looking for a comprehensive approach to investing, according to Mr AbuShaban.
“Institutional investors or some of the families are seeing a slowdown in the available capital they have to invest and in that sense they are looking at optimizing the way they manage their portfolios and making sure they are not investing haphazardly and different parts of their investment are working together,” said Mr AbuShaban.
Some clients also have a higher appetite for risk, given the low interest-rate environment that does not provide enough yield for some institutional investors. These clients are keen to invest in illiquid assets, such as private equity and infrastructure.
“What we have seen is a desire for higher returns in what has been a low-return environment specifically in various fixed income or bonds,” he said.
“In this environment, we have seen a de facto increase in the risk that clients are taking in things like illiquid investments, private equity investments, infrastructure and private debt, those kind of investments were higher illiquidity results in incrementally higher returns.”
The Abu Dhabi Investment Authority, one of the largest sovereign wealth funds, said in its 2016 report that has gradually increased its exposure in direct private equity and private credit transactions, mainly in Asian markets and especially in China and India. The authority’s private equity department focused on structured equities owing to “their defensive characteristics.”
What are NFTs?
Are non-fungible tokens a currency, asset, or a licensing instrument? Arnab Das, global market strategist EMEA at Invesco, says they are mix of all of three.
You can buy, hold and use NFTs just like US dollars and Bitcoins. “They can appreciate in value and even produce cash flows.”
However, while money is fungible, NFTs are not. “One Bitcoin, dollar, euro or dirham is largely indistinguishable from the next. Nothing ties a dollar bill to a particular owner, for example. Nor does it tie you to to any goods, services or assets you bought with that currency. In contrast, NFTs confer specific ownership,” Mr Das says.
This makes NFTs closer to a piece of intellectual property such as a work of art or licence, as you can claim royalties or profit by exchanging it at a higher value later, Mr Das says. “They could provide a sustainable income stream.”
This income will depend on future demand and use, which makes NFTs difficult to value. “However, there is a credible use case for many forms of intellectual property, notably art, songs, videos,” Mr Das says.
First Test
November 23-27 (The Gabba, Brisbane) Second Test
December 2-6 (Adelaide Oval, Adelaide) Third Test
December 14-18 (Waca Ground, Perth) Fourth Test
December 26-30 (Melbourne Cricket Ground, Melbourne) Fifth Test
January 4-8, 2018 (Sydney Cricket Ground, Sydney)
'My Son'
Director: Christian Carion
Starring: James McAvoy, Claire Foy, Tom Cullen, Gary Lewis
What is Financial Fair Play?
Introduced in 2011 by Uefa, European football’s governing body, it demands that clubs live within their means. Chiefly, spend within their income and not make substantial losses.
What the rules dictate?
The second phase of its implementation limits losses to €30 million (Dh136m) over three seasons. Extra expenditure is permitted for investment in sustainable areas (youth academies, stadium development, etc). Money provided by owners is not viewed as income. Revenue from “related parties” to those owners is assessed by Uefa's “financial control body” to be sure it is a fair value, or in line with market prices.
What are the penalties?
There are a number of punishments, including fines, a loss of prize money or having to reduce squad size for European competition – as happened to PSG in 2014. There is even the threat of a competition ban, which could in theory lead to PSG’s suspension from the Uefa Champions League.
