The Role of Artificial Intelligence in Future Technology. Introduction With the advancement

The Role of Artificial Intelligence in Future Technology.

Introduction

With the advancement and commercialization of Large Language Models and Generative AI, Artificial Intelligence has gained a substantial spotlight in society. It is expected to grow continuously in the future, with the development of AI research and an increase in computational power. However, before further exploring AI growth and its future role, it is crucial to establish a concrete definition of Artificial Intelligence (AI). In 1988, Simmons and Campbell defined AI as “denoting behaviour of a machine which, if a human behaves in the same way, is considered intelligence” (Simmons and Chappell). We can further elaborate on it as a machine’s ability to learn and perform similar tasks as humans, such as problem-solving, information retrieval, communication, etc. Since its introduction, it has grown and can execute more tasks when given enough task-specific data. This paper posits that AI should continue to grow as a vital tool, integrated into various technologies to improve human productivity and, specifically, serve a significant role in assisting humans in highly specialized, challenging, yet impactful work. The paper will provide a specific example in the highly specialized medical industry. However, there are vital concerns, such as safety and privacy, that AI engineers and users should be aware of to ensure that future AI technology can have a positive role in society.

Historical and Current State of AI

Although the term “Artificial Intelligence” was coined in 1956 by John McCarthy(McCarthy et al.), its significant development took place in the 1990s with more powerful computers and massive growth in the amount of data available(Toosi et al.). In recent years, with this growth in computing power, large datasets as well as the introduction in key AI architecture (e.g. Convolutional Neural Networks, Transformer, Generative Adversarial Networks), AI have been capable of performing various tasks and is integrated into various technologies such as autonomous driving cars and AI-powered chatbots. It has also been implemented in a wide range of industries that substantially benefit humanity. In transportation, AI integration enables the development of Intelligent Transport Systems to monitor and control different city infrastructures to ensure citizens’ efficiency and safety (Bharadiya). In Agriculture, AI has been widely integrated into robotics, surveillance systems and automatic decision systems to improve efficiency and reduce human resources in operating farms while tracking and maintaining crops’ health. In the current state, AI can help industry experts monitor crucial information and speed up the analytical process to assist experts in making more informed decisions. As AI technology advances, we anticipate these technologies to showcase even more profound implications(Wakchaure et al.). In medicine, while there are still limited AI systems used in direct patient diagnosis, they have been a crucial part of medical studies, medical image analysis and patient symptoms (Rajpurkar et al.) (Tekkeşin).This shows that although AI lacks inherent reasoning ability and cannot perform highly technical and accuracy-required tasks, it could provide substantial value in assisting industry experts in monitoring and processing information and helping them make more informed decisions.

Future Role and Outlook

In the future, as researchers further develop robust AI technologies, it could serve a more vital role in a highly technical yet impactful industry. Among them, the most crucial industries are medicine and healthcare. The healthcare industry is driven by high-level expertise, and there is a shortage of experienced medical practitioners (Kumar et al.). AI models in this field have faced challenges such as limited datasets (Rajalakshmi et al.) and poor explainability and interpretability. These challenges limit model performance and medical practitioners’ understanding of model behaviour. However, with improved computational power, more published datasets, and more healthcare researchers, AI could have a more significant role in assisting practitioners. With more datasets and more computing power, researchers can scale up models while developing more efficient models to understand the highly technical medical data. Combining large models in imaging and large language models can assist the model in understanding the medical terminology more inherently and knowledge, thus improving performance. In 2023, Google produced the Med-PaLM2, which is fine-tuned from the PaLM2 large language model with domain-specific Question Answering dataset MultiMedQA(Karen et al.). Enhanced by their growing proficiency in interpreting medical texts and imaging, the large, sophisticated AI models have the potential to support the diagnostic process by analyzing patient symptoms and imaging results with greater efficiency and accuracy, thereby facilitating the delivery of precise diagnoses and tailored medical treatments. Thus, AI will play a vital role in assisting current practitioners in all phases of health care systems, including precise clinical diagnosis, precision medicine, and precision therapeutics (Bajwa et al.). These challenges that only experts in the field can have the expertise to do; with AI assistants, could relieve their workload and be able to be more efficient and accurate in their work.

Risks of AI

Although AI technology has substantial positive outlooks, specific vital issues must be focused on to ensure safety, reliability, and privacy. Due to the large amount of data models required for model training and the “black-box” nature of large language models’ logic, concerns have been raised about whether models are safe and can be trusted. To alleviate such concern, it is crucial for government, researchers and large companies to design standard protocols on model training and inference to promote transparency, which helps safeguard personal privacy and maintain trust from the general public (Meghasai). By addressing these concerns and instituting stringent protocols, we can create a secure and transparent framework that allows AI to flourish and harness its capabilities to benefit humanity.

Conclusion

With the rapid speed at which AI has developed and commercialized in the past few years, it has started to impact various industries in people’s lives. However, I believe that when trust and safety issues are adequately addressed, AI technology will continuously play a major role, especially in assisting industry experts to solve difficult, industry-related tasks. This will produce substantial value in improving society’s efficiency and quality of life.

References

Simmons, A.B., and S.G. Chappell. “Artificial Intelligence-Definition and Practice.” IEEE Journal of Oceanic Engineering, vol. 13, no. 2, Apr. 1988, pp. 14–42, doi:10.1109/48.551.

McCarthy, J., M. L. Minsky, N. Rochester, and C. E. Shannon. “A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955”. AI Magazine, vol. 27, no. 4, Dec. 2006, p. 12, doi:10.1609/aimag.v27i4.1904.

Toosi, Amirhosein, et al. “A Brief History of AI: How to Prevent Another Winter (a Critical Review).” PET Clinics, vol. 16, no. 4, Oct. 2021, pp. 449–469, doi:10.1016/j.cpet.2021.07.001.

Bharadiya, Jasmin. “Artificial Intelligence in Transportation Systems A Critical Review.” American Journal of Computing and Engineering, vol. 6, no. 1, 3 June 2023, pp. 34–45, doi:10.47672/ajce.1487.

Wakchaure, Manas, et al. “Application of AI Techniques and Robotics in Agriculture: A Review.” Artificial Intelligence in the Life Sciences, vol. 3, Dec. 2023, p. 100057, doi:10.1016/j.ailsci.2023.100057.

Rajpurkar, Pranav, et al. “Ai in Health and Medicine.” Nature Medicine, vol. 28, no. 1, Jan. 2022, pp. 31–38, doi:10.1038/s41591-021-01614-0.

Tekkeşin, Ahmet İlker. “Artificial Intelligence in Healthcare: Past, Present and Future.” The Anatolian Journal of Cardiology, 2019, doi:10.14744/anatoljcardiol.2019.28661.

Kumar, Yogesh, et al. “Artificial Intelligence in Disease Diagnosis: A Systematic Literature Review, Synthesizing Framework and Future Research Agenda.” Journal of Ambient Intelligence and Humanized Computing, vol. 14, no. 7, 13 Jan. 2022, pp. 8459–8486, doi:10.1007/s12652-021-03612-z.

Rajalakshmi, Ramachandran, et al. “Automated Diabetic Retinopathy Detection in Smartphone-Based Fundus Photography Using Artificial Intelligence.” Eye, vol. 32, no. 6, 9 Mar. 2018, pp. 1138–1144, doi:10.1038/s41433-018-0064-9.

Karan, Singhal et al. “Towards expert-level medical question answering with Large Language Models”, https://arxiv.org/pdf/2305.09617.pdf

Bajwa, Junaid, et al. “Artificial Intelligence in Healthcare: Transforming the Practice of Medicine.” Future Healthcare Journal, vol. 8, no. 2, July 2021, doi:10.7861/fhj.2021-0095.

Meghasai, Bodimani “Assessing The Impact of Transparent AI Systems in Enhancing User Trust and Privacy” Journal of Science and Technology, vol. 5, no.2, 2024