The present view on the AI system is based on the book “Artificial Intelligence: A Modern Approach“, which defines AI as “the designing and building of intelligent agents that receive precepts from the environment and take actions that affect that environment”. The system gathers raw data and inputs from the environment, analyses and interprets the data in an automated manner or manually (AI Model) by providing predictions, recommendations or decisions, and takes actions to influence the state of the environment.  

Although current AI applications have narrow forms and are limited to their singular specialty, AI has been developed and deployed on a massive scale ranging from modern web search engines (e.g., Google Search) and recommendation systems (used by YouTube, Amazon) to self-driving car and generative tools (e.g.ChatGPT).

With access to large amounts of data and enough computing power to process it, Big Tech is at the forefront of AI. Tech Giants are going all in on AI. Companies are investing unprecedented capital into research and development ($223bn in 2022). Microsoft is a leader in venture capital and private equity investments in AI-related companies (Fig. 2). It extends its partnership with an AI research and deployment company OpenAI and invested 10 billion dollars into ChatGPT. Meanwhile, Facebook’s CEO recently said AI was his firm’s largest share of investments and Alphabet (Google) plans to disclose the size of its AI investment for the first time. Moreover, the number of job postings by Google, Meta and Microsoft requesting AI skills also keeps growing. Meanwhile, the dominance of Big Tech companies in the AI field indicates that the progress and advancements of AI technologies within the companies will have a significant influence on their market position and revenue streams.

A tonne of uncertainty around AI raises questions around the responsible development and deployment of AI technologies. Some of the biggest names in tech signed an open letter calling for a temporary halt on any further AI development.  The signatories petitioned to pause for at least 6 months the training of AI systems more powerful than GPT-4 as the systems can pose profound risks and dangers to society. However, the letter sparked controversy over its claims. Critics commented that the claims are unclear and they ignore more immediate concerns about AI. The Future of Life Institute, a non-profit organisation that coordinated the effort, was accused by some experts of focusing on fictional apocalyptic scenarios over current challenges about AI.

AI has the potential to automate many tasks that were previously performed by humans. For example, chatbots can be used to provide customer service and support, while AI algorithms can be used to automate data analysis, financial modelling, and even programming. This increased automation has the potential to reduce costs for big tech companies, increase efficiency, and allow employees to focus on higher-level tasks.

However, as AI systems are now becoming human-competitive at general tasks, there is concern that AI could lead to job displacement. According to OpenAI research, approximately 19% of jobs have at least 50% of their tasks affected by the introduction of large language models.

AI holds tremendous promise to improve our educational systems, with intelligent features being incorporated into virtual and distance learning, predictive analytic systems, and management and administration of teaching and learning. As an assistant to students, AI can be used for building personalised learning systems. Adaptive learning platforms can analyse student data, assess their strengths and weaknesses, and provide targeted content and feedback.  For example, Teach to One is an AI-powered personalised learning program that individualises maths instruction for middle school students. The system uses daily assessments, student preferences, and learning objectives to create personalised schedules and tailored lessons for each student. In addition, AI technologies can enhance accessibility for students with disabilities and additional learning and support needs through the adaptation of learning materials (e.g. speech recognition, text-to-speech conversion).

AI can be an effective tool for supporting teachers. AI can streamline administrative tasks, such as grading and scheduling, allowing educators to focus more on teaching. For instance, Gradescope employs AI to automate the grading of assignments, saving time for teachers and providing faster feedback to students. Nevertheless, it is important to evaluate applications of AI in education, including considerations of potential biases, privacy and data transparency.

Healthcare is one of the most promising AI applications. In the industry, AI enables making medical services universal, high-quality, and affordable. AI-based solutions currently help to improve the diagnostic process for cancer and neurologic disorders. At the same time, digital technologies reduce costs through avoiding losses from low productivity and sick days and a better understanding of risk factors and selecting appropriate interventions.

The use of AI has the potential to address the most important health issues in low- and middle-income countries such as HIV/AIDS, psychiatric pathologies and maternal and child health thereby reducing global health inequalities. However, as AI systems rely on vast amounts of personal data, the potential for AI algorithms to extract sensitive information from personal data or make inferences about individuals’ private lives needs to be addressed.

Proponents of AI development highlight its potential to expedite the achievement of the sustainable development goals. For example, AI technologies can make the food system more sustainable through the automation food production processes, including transport, logistics and supply chain. It also can be used in environmental conservation. For instance, an automated alert system in a park helps to track wildlife poachers and prevent illegal practices threatening species worldwide. Moreover, AI can have a significant impact on fighting climate change.  Deep learning algorithms can help to improve existing forecasting and prediction systems and better understand extreme weather events. At the same time, the introduction of AI into the climate area imposes several social and ethical challenges already associated with AI more generally.

Tech leaders address environmental challenges with AI by forming partnerships with organisations and individuals working to advance sustainability. Through the Social Good program, Google supports various projects that tackle social and environmental challenges such as the minimisation of crop damage in India and waste management in Indonesia to improving air quality in Uganda and adapting to extreme heat. While Microsoft’s AI for Earth is a 5-year $50 million initiative launched in 2017, supported by over 950 projects, organisations and researchers using AI to power sustainability applications.