State of the art of Energy & Artificial Intelligence and New Challenges

To-date, most of the energy sector’s transition efforts have focused on hardware: new low-carbon infrastructure that will replace legacy carbon-intensive systems. Relatively little effort and investment has focused on another critical tool for the transition: next-generation digital technologies, in particular artificial intelligence (AI). These powerful technologies can be adopted more quickly at larger scales than new hardware solutions, and can become an essential enabler for the energy transition.

AI is already proving its value to the energy transition in multiple domains, driving measurable improvements in renewable energy forecasting, grid operations and optimization, coordination of distributed energy assets and demand-side management, and materials innovation and discovery. AI holds far greater potential to accelerate the global energy transition, but it will only be realized if there is greater AI innovation, adoption and collaboration across the industry.

The principles define the actions that are needed to unlock AI’s potential in the energy sector across three critical domains:

1. Governing the use of AI:

• Standards – implement compatible software standards and interoperable interfaces.
• Risk management – agree upon a common technology and education approach to managing the risks presented by AI.
• Responsibility – ensure that AI ethics and responsible use are at the core of AI development and deployment.

2. Designing AI that’s fit for purpose:

• Automation – design generation equipment and grid operations for automation and increased autonomy of AI.
• Sustainability – adopt the most energy-efficient infrastructure as well as best practices around sustainable computing to limit the carbon footprint of AI.
• Design – focus AI development on usability and interpretability.

3. Enabling the deployment of AI at scale:

• Data – establish data standards, data-sharing mechanisms and platforms to increase the availability and quality of data.
• Education – empower consumers and the energy workforce with a human-centred AI approach and invest in education to match technology and skill development.
• Incentives – create market designs and regulatory frameworks that allow AI use cases to capture the value that they create.

Artificial Intelligence: Concepts, challenges, opportunities and Ethics

If the United States dominates the development and use of artificial intelligence (AI), China intends to challenge this supremacy…Algeria needs to pay attention to and respond to this new AI craze because a country that develops and uses AI will shape its future and significantly improve its economic competitiveness, while a country that falls behind risks losing out its competitiveness in key industries, and even its national sovereignty will be threatened.

Of course, we must not lose sight of the fact that AI arouses both enthusiasm and skepticism, albeit in different measures.

In this plenary session, we recall the concept of Artificial Intelligence and Deep Learning and the importance of Data. We show interest in some key applications in the fields of medicine, telecommunications, intelligent transportation systems, and security.

Ethical issues arise such as surveillance by AI, the role of AI in promoting misinformation and disinformation, the role of AI in politics and international relations, governance of AI, etc.

New technologies are always created in the interest of something good, and AI offers us amazing new capabilities to help people and make the world a better place. But to make the world a better place, we must choose to do so, ethically.

With the concerted effort of many people and organizations, we can hope that AI technology will help us create a better world.