Najib Saab, February 2024

Governments, businesses, industries and financial institutions, as well as universities and research centers that do not keep pace with developments in artificial intelligence (AI) put themselves out of the competition. This has become an established fact, as demonstrated by the discussions at the latest sessions of the World Economic Forum in Davos and the Riyadh Economic Forum, among others. AI was also a major focus of the World Government Summit (WGS) this week in Dubai, which brought together some of the world's top industry leaders, strategic planners and decision-makers. Resource management and environmental protection to achieve sustainability are not outside this scope, as AI can shift development paths in multiple and opposing directions, from enhancing the balance of natural resources to depleting them.

Artificial intelligence is not an entirely new discovery, but rather a revolutionary development in the functions of the first calculator and the first computer. But while previous tasks were limited to carrying out specific single operations, such as calculating numbers, collecting data, and classifying it according to a specific program, AI takes quick steps to collect, link, compare and analyse data from different sources, with research going on to enable it to simulate the way the human brain works in complex analytics and making decisions. But this remains governed by the availability of accurate and reliable data, as artificial intelligence programs do not create data and information, but rather collect what is openly available.

The mission, however, cannot be achieved by collecting whatever data is available, but should start from generating data in the first place, in the field as well as laboratories and research centers. Examples of the enormous gaps in the generation of reliable data in the domain of environment and nature are many, from measuring the quality of air, soil, water and oceans, and deposits of toxic fertilizers and pesticides in food products and forests, to information related to climate change. The lack of accurate data in most Arab countries in these areas is due to the fact that they have not been generated in the first place, and what little does exist is often subject to restrictions that limit its dissemination. It is interesting to note that access to environment impact reports of major projects is barred in many countries, while they should be made available to the scientific community and the public for scrutiny.

Hence, the outcome of applying artificial intelligence in planning programs for resource management, environmental protection and sustainable development in general, remains dependent on the accuracy of the available data. Only with comprehensive and accurate data can AI properly accelerate tasks. Collecting and analysing satellite images of vast areas, after linking them to data generated on the ground through fixed monitoring stations as well as field and lab work, provides a solid basis for knowing the status of bodies of water, vegetation, oceans, and land uses, including agriculture, industry, housing and transportation networks. Think about things like interpreting geospatial data to figure out what kind of crops are grown, where or whether there is imminent risk of drought or lower harvests or pests. Certain decision-making can benefit a lot from AI because it allows more work to be done more quickly and efficiently, for a huge area. Without advanced satellite imagery technologies and digital analysis systems, it would not have been possible to timely implement ambitious strategies such as "Saudi Green Initiative," which includes converting 30 percent of the country's area into protected reserves by 2030, amounting to 700,000 square kilometers. Needless to say that designing and implementing programs, within a limited time frame, to manage territory more than twice the size of Germany, cannot be accomplished by traditional means.

Artificial intelligence capabilities contribute to studying the potential environmental impacts of any project and proposing alternatives that result in less risk. They also include monitoring and adjusting emissions to control climate change. Managing the production and distribution of energy and water and regulating road traffic are among the most important areas of using artificial intelligence to enhance efficiency and reduce waste and emissions.

Artificial Intelligence and Data Technology was the subject of a report presented by the International Advisory Group (IAG) at the World Government Summit. While the report confirmed that those who lag behind in artificial intelligence will be excluded from the competition, not only in governance, but also in health, education, urban planning, financial markets, energy, water and climate change, among others, it found that the Arab region has achieved remarkable advancements on the path to digital transformation, with a large variation among countries. In this regard, internet users increased from 29 to 70 percent in 10 years between 2012 and 2022, which created a valid basis for introducing AI into the services provided by the public and private sectors. The report showed the ability of artificial intelligence to enhance economic growth in Arab countries by an additional $320 billion by 2030, helping to overcome coronavirus losses at a faster pace.

The report gave Saudi Vision 2030 as an example of the national commitment to modernization and expanding the use of artificial intelligence technologies to promote innovation, development and environmental protection. It also highlighted the establishment of a ministry dedicated to artificial intelligence in the UAE, the Qatar Center for Artificial Intelligence (QCAI) and the AI Academy in Bahrain, as models of transformation in GCC countries. Jordan, Egypt, Morocco, and Tunisia also launched national programs and strategies for artificial intelligence, including education, research, health, and sustainability, in addition to government services.

It remains that success in keeping pace with artificial intelligence depends on the success in building national capabilities and skills that lead this transformation, as well as in supporting scientific research to generate accurate data that will be the basis for the work of artificial intelligence. Otherwise, we turn into consumers of ready-made knowledge and technologies that are controlled by other parties, who are capable of using them to their advantage and interests, especially since a limited number of companies are trying to monopolize this sector. This threatens the formation of a hidden global authority that controls the fate of humanity. Also, excessive reliance on ready-made artificial intelligence systems carries the risk of reducing the urge to be educated, while we need more and better education, learning, research, and innovation to control these systems.

In the absence of scientific foundations and ethical controls for the use of AI, its advantage in collecting, linking, and analysing data at breakneck speed may turn into accelerating the discovery of limited resources by monopolies, to exhaust them fast and reap greater profits, or altering basic data to manipulate the results according to the interests of the programmers. On the other hand, building a solid scientific and human foundation for new technology opens up limitless horizons, such as using satellite imagery and artificial intelligence to accelerate environmental and climate action and sustainability measures, from natural resource management to climate modelling and forecasting.

I was asked at the Summit if it would be better to transfer decision-making powers entirely to artificial intelligence programs, in order to ensure the absence of bias and prevent private interest from prevailing over the decisions of government officials. I answered that this hypothesis remains theoretical, because AI lacks any accountability, and has its limitations based on human-made data, controls, and software. AI does not create knowledge but organizes existing knowledge, as it is not really thinking of new things but rather predicting based on all knowledge it finds on the internet. And because it is a black box, it is very difficult to audit what it predicts and make sure that it didn't make mistakes, or reflect mistakes in the underlying data.

If the use of artificial intelligence is necessary to keep pace with the times, then the responsibility for major decisions in development policies remains with humans, which requires strengthening accountability in public administration not weakening it.