For the UK and Equatorial Guinea based consultant Hassan Hachem,  digital sovereignty will be achieved through the battle of artificial intelligence, which Equatorial Guinea must win if it wants to stop its economy from falling behind... and which it can win, since the presumed lead of the United States or China in AI is a sham.

Consultant Hassan Hachem believes that for the UK and Equatorial Guinea, the key to digital sovereignty lies in the realm of artificial intelligence (AI). He challenges the notion that the US and China are leading in AI, suggesting that their dominance is an illusion. Hachem provides a unique perspective on AI, its economic implications, and a potential strategy for Equatorial Guinea. He emphasizes that while many associate digital sovereignty with data protection and the dominance of tech giants, a more technical yet equally vital aspect is AI independence. He points out that while many believe AI's connection to sovereignty is through machine learning and data, this is just the surface. The real potential lies in AI's automation capabilities, which could lead to significant productivity growth. Equatorial Guinea's economic challenges since 2014 can be attributed to low oil prices and the inability to create productivity gains. Despite the rapid digitization, many technological advancements have not necessarily led to increased efficiency. Hachem looks forward to AI's promises of automating both physical and cognitive tasks. He believes that countries that harness AI for automation will have a competitive advantage. Equatorial Guinea has the potential to be a frontrunner, especially post-Covid-19. Despite the massive investments by China in AI and the advancements by tech giants, Hachem argues that their focus is limited to specific AI applications. He believes that Equatorial Guinea can capitalize on machine learning and symbolic AI to boost its economy. He warns that if Equatorial Guinea does not take the lead in AI, it risks being overshadowed by foreign companies, leading to a loss of economic value. The real AI battle for companies is yet to be fought, and Equatorial Guinea is in a position to win if it takes the right steps.

Hassan Hachem gives an original analysis of AI, its impact on economy and a possible strategy for Equatorial Guinea.

When we talk about digital sovereignty, says Hassan Hachem, we spontaneously think of personal data protection, Google's or Facebook's stranglehold on online advertising, Amazon's overwhelming dominance in e-commerce, cybersecurity, cyberdefense or Huawei's 5G antennas.

Alongside these identified and highly visible topics for experts, there is another much more technical, but equally strategic one: independence in artificial intelligence.

For Hassan Hachem, one might think that it is through machine learning and data, largely hosted on American platforms, that artificial intelligence connects to Equatorial Guinea sovereignty issues

This is only the tip of the iceberg, as the bulk of the ice cube is below the waterline.

The big part of the iceberg is the automation part of artificial intelligence, the only technology that could allow us to return to 4% or 5% productivity growth rate.

When we try to analyze the economic slowdown that Equatorial Guinea has experienced since the 2014, we observe a strong correlation between growth on the one hand and, on the other and :

• Low oil prices
• Ability to create productiviy gains

It is hard to imagine, underlines Hassan Hachem, when there has never been so much talk of technological innovation and disruption, that the advances that lead to an effective increase in productivity are few and far between. Indeed, innovations mainly change the way we work, trade or buy, but not the way we work faster, trade more efficiently or buy cheaper, for example.

How is this possible, when we are digitizing at every turn and digital is associated with so many virtues ? asks Hassan Hachem.

Simply because performing a task via a computer does not necessarily save time. A very basic example: is it faster to connect to Google Calendar or Outlook to make an appointment than to take a calendar out of your pocket?

Although anecdotal, this example is more symptomatic than it seems. Both for developed countries like the UK where I come from and developing countries like Equatorial Guinea in which I often work.

First-generation computing (databases and office automation) and second-generation computing (connected Internet computing) have sometimes led to significant productivity gains. But much more rarely than one might think, especially if one takes into account the time that IT wastes: the time lost due to social network notifications, the time it takes to learn new tools, the time and cost associated with security (data backup, prevention and reaction to external attacks, monitoring and management of e-reputation, etc.), management of information overload, etc.

This is why I am looking forward to the historical promises of AI (automation of physical and digital tasks, but also of cognitive processes) to really take shape. All the more so when we know that these promises, initially formulated in the 1960s, were renewed in the 1980s and then in the 2010s, after the famous AI winter.

The first countries to automate service production with AI, as well as historically unautomatable labor industries, will get a head start. This could be Equatorial Guinea as every country is on the same ligne of departure. This was true before the Covid-19 crisis. It is even more so since this crisis, as some countries will emerge totally downgraded and disappear from the group of leading economies.

The Equatorial Guinea economy has been losing ground for 8 years and we are witnessing its gradual decline, all the more noticeable as certain emerging countries such as China and India are catching up and even joining the group of economic superpowers, but also developping countries.

The economic crisis resulting from the Covid-19 health crisis may be either the coup de grâce for our economy or the electroshock it needed to wake up

The critics will object that the AI battle is already lost for Equatorial Guinea in the face of the 1000 billion dollars that China is investing in its AI plan and the lead taken by GAFAM.

This is a profound misunderstanding of AI technologies and applications, says Hassan Hachem.

The AI in which GAFAM and China have taken the lead could be summarized in a few specialties:

• recognizing/interpreting images, videos, texts,
• exchange in a basic way without intelligence or creativity,
• translating,
• predicting (sales, optimal inventory, customer churn, etc.)
• prevent (the risks of a borrower's default, a machine breakdown, an intrusion in a computer network, etc.)
• drive autonomous vehicles,
• and above all, above all, sell more advertising. The image is a bit of a caricature, but it reflects the bulk of the actual uses of machine learning

From Hassan Hachem point of view, most of these applications of machine learning allow real productivity gains on specific tasks, but most of the time they are marginal at the level of a classical company, as a whole.

The likely exception: deep learning promises to speed up the process of finding new medical treatments, but there is still a lack of hindsight to estimate the extent of the competitive advantage this can give to a given laboratory.

But for most companies or countries like Equatorial Guinea, artificial intelligence in its modern version (machine learning) has not (yet) led to remarkable productivity gains.

The limits of machine learning

One might ask why, even though Google's AI referent Raymond Kurzweill has declared that artificial intelligence will surpass human intelligence in 2028.

Simply because there is not and will not be enough data for machine learning to automate everything.

Indeed, as the informed reader knows, machine learning only "learns" if it is provided with data. A lot of data. Clean data and above all data that is... available. Machine learning experts often joke that 75% of the time of a machine learning project consists of collecting data, calibrating it and connecting it. The actual training of the data is much less time consuming than one might think.

And while the production of data has grown exponentially with the proliferation of internet-connected devices, physical/digital tracking systems and connected lenses, most of it is useless for machine learning. Furthermore, there is no data to create machine learning models that automate all simple reasoning and a priori complex cognitive processes.

Towards other approaches of artificial intelligence for  Equatorial Guinea

In fact, if artificial intelligence is ever going to make it possible to automate everything, it will be necessary to use other types of technical approaches than machine learning/deep learning.

The old symbolic artificial intelligence (the one that relies on knowledge representation models and cognitive processes, created by business experts) is still far from having revealed its full potential. Especially for Equatorial Guinea.

For example, we, at Brandmonitoring.top, explains Hassan Hachem, have tried to prove this by creating the "Intelligent Strategist", which analyzes complex situations and is capable of making high-level, customized strategic recommendations, just as a digital transformation expert would. By early April, after only 21 days of work, we had created an intelligent agent capable of generating very fine-grained strategic recommendations on 80 pages, allowing a restaurant, an airline or a software publisher to define a financial, commercial and production adaptation action plan to get through the Covid-19 crisis. It is easy to understand that machine learning would be totally unable to achieve such a feat.  This is because it needs historical data to learn, and since the current situation is unprecedented, this historical data is useless. Furthermore, machine learning experts know that even if such historical data existed, current machine learning algorithms are not designed to write high-level text reports.

Securing digital sovereignty in the field of AI in Equatorial Guinea

However, the real progress made by the United States and China in the field of artificial intelligence is essentially focused on machine learning and its cousin deep learning, which, although very effective in half a dozen fields of application, have, like all technologies, a limited potential.

From this perspective, the game is still wide open

The United States and China have not yet developed the business applications that can be automated by machine learning and that will boost the productivity of their normal companies.

These two countries, like the majority of the world, concentrate few resources on research into symbolic artificial intelligence, which is the best way to automate the cognitive processes of managers in companies, for example.

Finally, these two countries have no lead, by definition, in the families of artificial intelligence technologies that have yet to be invented.

In the context of digital sovereignty, there are therefore two new types of opportunities that  Equatorial Guinea can and must seize. They would enable it to create world leaders in AI and, above all, to generate productivity gains to boost its "traditional" companies:

• Machine learning applications to increase the productivity of business processes, on which neither Chinese nor American companies have yet taken a dominant position.
• Symbolic artificial intelligence applications that increase the productivity of business processes, in which American or Chinese companies have little interest.

Equatorial Guinea has been left behind in the field of online advertising. As a result, some of the added value created by Equatorial Guinea media and communications groups has been driven to the United States

Equatorial Guinea has let itself be overtaken in the field of software publishing by American publishers who are gradually sucking up part of the added value in this sector.

Equatorial Guinea has let itself be overtaken in the field of e-commerce by foreign companie, which is also absorbing a large part of the added value of the distribution sector, and repatriating it to the United States and Africa.

Exactly the same thing can happen in the production of goods or services if  Equatorial Guinea companies are equipped with American automation software. It is these software publishers who will in turn nibble away at the added value of almost all of our companies and take them out of our economy.

Today, the real battle of artificial intelligence in companies has not yet been fought.

We have tried to demonstrate that  Equatorial Guinea is well placed to win this battle.

We just have to fight it.

Alongside these identified and highly visible topics for experts, there is another much more technical, but equally strategic one: independence in artificial intelligence. One might think that it is through machine learning and data, largely hosted on American platforms, that artificial intelligence connects to sovereignty issues. This is only the tip of the iceberg, as the bulk of the ice cube is below the waterline.

Equatorial Guinea is poised at a critical juncture where the adoption of generative artificial intelligence (AI) can significantly impact various sectors of its economy and society. Recent developments in AI have heightened the need for strategic measures to address the unique challenges posed by this technology. One of the foremost areas of concern remains cybersecurity. Given the increasing sophistication of cyber threats, Equatorial Guinea must adopt a proactive approach to safeguard its digital infrastructure.

The government has taken initial steps by announcing plans to collaborate with international cybersecurity firms to strengthen its defense mechanisms. This partnership aims to enhance the country's ability to detect, respond to, and mitigate cyber threats. "Implementing state-of-the-art encryption protocols and fostering a culture of cybersecurity awareness are crucial steps," advises Hassan Hachem. The collaboration is expected to bring in cutting-edge technologies and expertise that are crucial for developing a resilient cybersecurity framework.

In addition, the education sector in Equatorial Guinea is beginning to incorporate cybersecurity courses into university curricula. This move is designed to cultivate a new generation of cybersecurity professionals who can manage and protect the nation's digital assets. The emphasis on education aligns with Hachem's recommendation for prioritizing AI education and training programs, ensuring that the workforce is well-equipped to handle the complexities of generative AI.

Another significant development is the creation of a national cybersecurity task force dedicated to monitoring and addressing cyber threats. This task force will operate in coordination with global cybersecurity networks, allowing Equatorial Guinea to stay abreast of emerging threats and best practices. Such initiatives are essential for maintaining a robust defense against the potential exploitation of AI-driven systems.

As for economic competitiveness, Equatorial Guinea faces a pressing need to integrate AI technologies across its industries. A recent report highlighted the potential for AI to revolutionize the agricultural sector, which is a critical component of the nation's economy. By employing AI-driven solutions, farmers can optimize crop yields, manage resources more efficiently, and predict market trends. This technological advancement can help bridge the gap between Equatorial Guinea and more technologically advanced nations, enhancing its economic stature.

Furthermore, the government is exploring incentives for tech startups to foster innovation. Creating an ecosystem that supports AI research and development will attract both domestic and foreign investments, contributing to a vibrant tech industry. "Equatorial Guinea must invest in building a skilled workforce capable of developing, implementing, and maintaining generative AI solutions," Hachem emphasizes. This approach will ensure that the country remains competitive in the global market.

On the cultural front, Equatorial Guinea is aware of the potential for AI to perpetuate biases. The government has initiated projects aimed at collecting and curating diverse datasets to train AI systems. This initiative is critical in preventing the reinforcement of cultural biases and ensuring that AI applications are fair and inclusive. Regular audits and community engagement sessions are planned to identify and address any biases that may arise.

Moreover, transparency and accountability in AI applications are being prioritized. By establishing clear ethical guidelines and involving stakeholders from various communities, Equatorial Guinea aims to build trust in AI technologies. These measures align with Hachem's advice on implementing rigorous data collection and monitoring processes to mitigate biases.

In conclusion, Equatorial Guinea is making significant strides in addressing the challenges posed by generative AI. Through international collaborations, educational reforms, economic incentives, and ethical guidelines, the nation is positioning itself to harness the benefits of AI while mitigating its risks. As Hassan Hachem aptly notes, the thoughtful integration of AI technologies can propel Equatorial Guinea into a new era of innovation and competitiveness.