Artificial Intelligence and The Circular Economy: Understanding Effects, Practices & Initiatives

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The capitalistic structure of most societies is designed to prioritize businesses and industries in a way that boosts economic growth while bringing in huge amounts of revenue. Today, as we pedestalize leading industry and business owners for their novel ideas and strategies, we often forget that we are doing it at the cost of heavy climate damage and degradation.

With this article, we will be highlighting an innovative collaboration of two diverse fields: artificial intelligence and circular economy. However, before dwelling on both topics, let us start by understanding the meaning of both terms and how they can come together to pave the way for a cleaner, brighter, and sustainable future.

What is Artificial Intelligence and Circular Economy?

Let’s start with the basic definition of Artificial Intelligence. In simple words, Artificial Intelligence (AI) is a wide and comprehensive branch of science that is related to designing and constructing smart machines. They have the potential of carrying out tasks that usually require extensive human labor and intelligence. Even though the field of Artificial Intelligence is vast, it can broadly be categorized into four types:

  • Theory of Mind
  • Limited Memory
  • Reactive Machines
  • Self-Awareness

The popular perception today is that Artificial Intelligence (AI) is a newly found invention that is still a domain of rigorous research and study. However, AI was actively deployed in various verticals to leverage an array of advantages like zero downtime, operational efficiency, multi-tasking, quick decision making, and more. Now, let’s move on to the definition of a circular economy.

The concept of circular economy was drafted to combat climate change by designing markets that extend a range of advantages and incentives to business owners that reuse products instead of dumping them or scraping them off. In a circular economy, all forms of waste resources like obsolete electronic appliances, scrap metal, used clothes are utilized more efficiently or skillfully returned to the economy. This actively promotes green and sustainable practices at ground level and offers benefits like:

  • Zero wastage
  • Low carbon emissions
  • Boosts the chances of economic growth
  • Reduced use of non-renewable materials and resources
  • Makes room for new opportunities and business strategies
  • Creates demand for leveraging innovative products and services.

4 Primary Effects of Artificial Intelligence on Circular Economy

Initially, for someone who has no knowledge of the technological or financial field, it is difficult to connect the dots between circular economy and artificial intelligence. But as mentioned above, by operating and optimizing the processes of circular economy, artificial intelligence is considered to be the right tool to promote the idea of employing green practices on a domestic level. Below we have mentioned many ways in which artificial intelligence can affect the functioning of a circular economy:

  1. Artificial Intelligence Solves Complex Problems Within a Short Span of Time

    Artificial intelligence is an umbrella term used for a collection of intelligent technologies that deal with a variety of systems and models that perform highly intellectual cognitive functions like learning and reasoning. In addition, AI can also find solutions to intricate problems by using pattern optimization, prediction, recommendation generation, and recognition based on data from audio, images, videos, text, numeric, and more.

  2. Artificial Intelligence Follows a Streamlined Process that is Conducive for the Circular Economy

    When artificial intelligence is integrated with the circular economy, it usually follows a solidified process of data collection, algorithm refinement, algorithm development, and data engineering in generating results that can quickly find solutions to multiple problems. This means that, unlike human practices and efforts, there is minimal chance of errors, intermixing of resources, and delays.

  3. Deploy Artificial Intelligence to Design Products and Materials for the Circular Economy

    In a circular economy, it is imperative to build components, products and materials that can empower and enhance cycles of repair, reuse, refurbishment of technical resources. In addition, economic circularity needs effective materials, components, and products that require features like recycled content, upgradability, or disassembly.
    Therefore, artificial intelligence can enable technicians and designers in manufacturing materials by providing detailed and continuous feedback. This will also lead to the introduction of novel and innovative assets in the market.

  4. AI Ensures Optimized Infrastructure for Material Flows and Circular Products

    It is important to remember that one of the primary features of a circular economy is that products and materials are not scraped and disposed of but are repeatedly used by industries. In order to do this, it is crucial to have a system where nutrients can be extracted from biological waste streams; thus, the need for large-scale infrastructure to conduct the process of collation, separation, performing treatments, and redistribution.
    In recent years, AI has proven to be the ideal choice for enabling optimum valorization of products and materials by rearranging materials of mixed streams through advanced visual recognition methods and techniques.

Strengthening Circular Economy Solutions with Artificial Intelligence

Several industries are comprehending the benefits of investing in artificial intelligence while realizing the ambitions of a circular economy. However, this transition requires an ecosystem and collective efforts of trustworthy partners to achieve a common goal that will eventually benefit every sector of society.

Now, since strong collaborations are the primary requirement to achieve a fully functioning circular economy, people must have in-depth knowledge about the difficulties they face in their industrial chains and what they expect from artificial intelligence. Even the smartest machines cannot resolve problems unless humans find a way to clearly establish the required outputs and inputs.

Therefore, before implementing several features of AI like learning feedbacks and rapid testing, it is best to have a comprehensive understanding of all the areas that need acceleration so that the overall structure of AI is suited to curate efficient solutions for a particular system.

Schneider Electric: Paving the Way with Artificial Intelligence

At Schneider Electric, we envision a sustainable future with zero wastage. To achieve this goal, we go out of our way to invent innovative retrofit solutions, novel products, services that help customers achieve much more while utilizing minimal resources and at the same time protecting the planet in the most efficient way possible.

We are a leading organization in the digital transformation of automation and energy management and are working diligently to advance and upgrade our AI technology. This will further help our customers gather data from value chains which is integral in decarbonization and decision making. In addition, we are also deploying a plethora of AI-driven business models that help unlock new levels of sustainability and efficiency across different verticals.