By: Kalin Contois, and Fallon Brook
November 9, 2023
As the integration of Artificial Intelligence (AI) into society increases each day, it may be helpful to summarize this innovative technology. Understanding the history and concepts behind AI can help us understand what it means for society in the future, and how it can be applied to rural settings.
History and Definition
The term and concept “Artificial Intelligence” is becoming a common topic of discussion in society due to the latest technological applications and its availability for public use. For many, the question is, “What is Artificial Intelligence (AI)?” Within the last 50 years, the technology and research behind AI have grown exponentially, so it may have become difficult to define its current applications. We have assimilated numerous sources to attempt to answer this question for those who would like a basic explanation from an observer’s perspective.
The second chapter from Mission AI is a useful resource in summarizing the evolution of AI. Interestingly, humans have recorded the concept of AI since antiquity through myths or cultural tales. Early scholars believed that AI could be defined by a computer’s ability to mimic human intelligence; for example, Alan Turing created the Turing Test, a modification to the imitation game that would reveal if computers could successfully imitate human responses to questions. However, the possibility of simulating human intelligence has only been achievable in the last century due to an improved understanding of electricity, thus allowing scientists to finally make myths come true. 
The exploration of AI began as limited as conceptual ideas because of the technological barriers that prevented applicable research. The development of computer systems, such as the first digital computer Colossus fueled AI research, as in the final half of the 20th century, conceptual and technological breakthroughs in AI development occurred. Early designs of AI can be categorized into two main typologies: symbolic learning and machine learning. The former is a rule-based formula that determines the computing process and is more contained on a theoretical level and less likely to deviate from its programming; the latter is an expansive network of nodes simulating a neural network that can differentiate knowledge on a hierarchical level, allowing more complexity for learning systems and can generate several different answers if needed . Deep learning and natural language processors (NLP) build upon the machine learning model, in which there is Generative AI using data collected from both subsets of machine learning to create new content, e.g., pictures, chatbots, and voice acting. As of 2023, machine learning/deep learning models and natural language processors are fueling the current wave of AI technology; ChatGPT is the most popular example of this machine learning and generative AI.
Sci-Fi and AI
While society is becoming more familiar with the symbolic learning and machine learning models, most of us may have come to understand AI from pop culture representations from books and other media. There are numerous fictional AI representations in sci-fi media, e.g. Cortana from the Halo video games, replicants from the Blade Runner movies, and C-3PO from Star Wars can all be potentially described as machine learning models, albeit more advanced models of what we have in our society today. This is due to their ability to act on their own accord in relation to the environment or a situation they find themselves reacting to, and sometimes they do this without the need to be prompted by a user.These characters from various sci-fi franchises can help visualize the future possibilities of Strong AI and its capabilities, which are intelligent beings able to make autonomous decisions based on environmental and situational factors presented without the need for initial prompts to begin a reaction, i.e., Cortana can hack into physical infrastructure and existing communication networks to aid the protagonist in conflict situations. Replicants are designed to simulate humans by recreating the smallest details of human nature and personality, but they are highly regulated and are akin to slaves. These sci-fi concepts reveal how advanced AI can become when collecting and utilizing information compared to its human creators. It also must be noted that there is the potential for wrongdoing as AI surpasses human intelligence and by adding more characteristics of human nature, like personality, it can become entirely unpredictable, for example fictional universes like the Terminator or Matrix franchises present the worst-case of AI application, in both, AI and humans are engaged in deadly conflict with each other. It is unknown when this can become possible, but these representations can help guide the creation of Strong AI. This can be done by combining existing research and using these fictional concepts as ethical guidelines of development, which can also provide inspiration for potential applications that are yet to be created in our society.
AI has already been present in society for the last decade in the forms of digital assistants like Alexa (2014) or Siri (2011). However, this latest wave of innovation has begun to contribute to many facets of society and the economy, some are noted in the Generative AI Market map . These applications adhere to the machine learning concept, and its subsets (deep learning and NLP). It will be an arduous attempt to list all industries using AI, so some examples will be made. In the health industry, AI models are being trained to help manage the well-being of patients. The art and media industries are currently debating the use of AI, as many workers feel that technology is disrupting their livelihoods or outright replacing them due to Generative AI and how it utilizes existing data to create new content. These markets are rapidly growing as more practical uses for AI are being used by industry experts, and considering the integration into the public, it seems AI is here to stay. While implementing AI has benefits, there are also detractors and thus requires essential oversight to prevent misuse by users and institutions or organizations . Renowned AI experts such as Geoffrey Hinton  and Andrew Ng  understand the need to protect users and sensitive data. As of November 3rd, 2023, this sentiment is shared by world leaders, as the US has released an executive order about AI use and development, and the UK has just hosted an AI safety summit for world leaders.
The Rural-Urban Technological Divide
With rural areas having fewer people to work and fewer resources to complete tasks, turning to automation and AI might make significant changes in rural communities. The technological divide is a key factor impacting the rural struggle for automation and AI. The technological or digital divide is a term used to describe the gap in access to modern communications and information.
It can be spoken about in various contexts. However, here, we will use it to describe the urban/rural technological divide specifically. Some technology has already been implemented to decrease the technological divide for rural folks. Geospatial AI has been working to plot out more efficient places for internet and cell phone towers within rural Georgia as a school district superintendent has noticed the impact of the technological divide in schools . This divide can also be felt outside the school system, impacting everything from agriculture to healthcare and rural businesses.
Rural AI in Action
As internet access becomes more reliable in rural areas, there is growing interest in exploring how AI can positively impact various aspects of rural life, including government, tourism, agriculture, and more. For example, research has begun to explore how blockchain, defined in the Oxford Dictionary as a system that maintains transaction records across a network of computers, could be beneficial in creating a decentralized government in rural spaces. The goal is to reduce the administrative load on municipal staff. However, significant technological barriers exist, and a 2022 study by the National Innovation Centre for Rural Enterprise has determined that implementing these changes will take time and significant investment .
One area where rural areas are currently benefiting from AI is banking . AI has helped rural folks have easier access to banking services by making the banking process more convenient and efficient and increasing financial literacy with chatbots and financial insights on customers’ spending. Chatbots allow folks to troubleshoot basic tasks and may save rural patrons an unnecessary trip into town by providing solutions to common issues encountered. Financial insights may allow rural customers access to financial literacy programs not otherwise available in their area, such as financial advisors.
Progress is Not Without Problems
Using AI in rural areas is great because it can help bridge the technological divide and give people access to its benefits. But some difficulties come with this expansion. Installing the infrastructure required for AI involves setting up high-speed broadband and fiber optic cables, which can harm the environment. This may result in disturbances to the natural habitats of local wildlife. Moreover, AI is super energy-intensive, which makes it a significant contributor to global emissions. Earth Org  estimates that by 2040, around 14% of global emissions will be caused by Information and Communication Technology, with a large portion coming from data centers that are necessary for the functioning of AI.
AI is starting to make a difference in rural areas, and many more opportunities are on the horizon. To get the most out of AI, we need to ensure everyone in rural areas can access the Internet. But we also have to be mindful that AI has a big impact on the environment. That’s why finding sustainable ways to reduce its negative effects is important. Nobody knows for sure what the benefits and risks of AI will be in the long run, but we will have to adapt to whatever changes come our way over the next decade and beyond.
Chapter 2 from Mission AI (2023), this chapter covers the history of AI development since Antiquity to the current day, while providing some explanations of current AI models.
 Lastra, R. 2023. Lifelong Education in the Age of Artificial Intelligence. Online Webinar, September 23, 2023. University of Manitoba, Extended Education: Winnipeg, MB. (Work in progress).
Market Map of AI applications
This article (2020) from Tzu Chi Medical Journal discusses the current applications and ethics of AI integration into society.
Interview with Geoffrey Hinton, the whole interview is insightful but a discussion on ethics and future of AI begins around the 24:00 minute mark and later (someone has timestamped the whole interview in the comments).
Andrew Ng shares his experiences in creating AI and his perspective on ethics in the growing field. (2023)
Here Jim Strizinger (2019) writes about how the placement of cell towers (for internet services) in rural areas (USA) benefits from AI via IBM’s Watson.
2022 study which investigates the feasibility of blockchain in rural development
A look into the international use of AI for rural banking solutions in India
Behind the scenes of AI: gas emissions aggravate climate change.