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Artificial Intelligence and Ethical Challenges
The Tycoon Herald > Innovation > Artificial Intelligence and Ethical Challenges
InnovationTrending

Artificial Intelligence and Ethical Challenges

Tycoon Herald
By Tycoon Herald 14 Min Read
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Author: Carlos Pestana Pereira

Abstract : Artificial Intelligence (AI) has emerged as one of the most impactful technologies of the 21st century, transforming diverse industries and shaping the future in unprecedented ways.

Contents
Author: Carlos Pestana PereiraIntroductionRecent DevelopmentsEthical ChallengesAdvances in Medicinepatient doctor relationshipImproving medical practiceImproving administrative care and primary careImpact on Employment and healthcare jobs:Autonomous Security and Risks:Conclusion:Bibliografia

Health is, perhaps, the sector with the greatest impact and importance of the applicability of AI, with an estimated increase of 18% in efficiency, covering diagnostic techniques, imaging, data evaluation and therapeutic drug administration. The article addresses some advances and advantages of applying AI in healthcare. It has great potential to transform entire industries, with an innovative impact on technology and science. The applications are diverse, from agriculture to medicine, including the financial sector, with great advantages for these sectors, if used correctly. For this, professional skills are needed to operate and ethical principles to regulate the activity, in order to make this challenge a good for society.

This article explores the challenges and opportunities associated with AI, highlighting its role in contemporary society.

Introduction

Artificial Intelligence, as a non-conscious entity, has no ability to express thoughts, feelings or self-awareness. The term “Artificial Intelligence” refers to computer systems that can perform tasks that normally require human intelligence. These systems are built with algorithms and mathematical models, but they do not have self-awareness, self-expression or self-concept. Furthermore, AI does not have emotional intelligence or common sense.

The capacity of an artificial intelligence model is defined by the data it was trained with and the algorithms that compose it. Although AI can perform complex tasks such as pattern recognition, decision making and natural language processing, it does not have an understanding of its own or the ability to reflect on its own existence.

In short, artificial intelligence does not have a perspective on itself, as it is a human construct intended to perform specific tasks based on programmed instructions and provided data, without consciousness or self-knowledge.

Recent Developments

In recent years, we have witnessed significant advances in AI, fuelled by deep learning algorithms and increasing computational power. AI systems are now capable of performing complex tasks such as facial  recognition, machine translation and medical  diagnoses with remarkable accuracy. It can also interpret radiological or endoscopic images providing a report and a possible diagnosis. The interplay between Artificial Intelligence (AI) and Nanoscience represents a remarkable convergence of two innovative areas of research, each  with  the potential to radically transform their respective disciplines. This promising union opens the door to significant advances in several fields, from the design of new materials to the manufacture of nanotechnology devices that can be applied in the field of Medicine. However, the possible connection of Artificial Intelligence with data storage devices and surveillance cameras can provide instant information about people, actions and processes, without guaranteeing any type of control over this information. It thus violates the principle of privacy and places individuals

under constant scrutiny, with the possibility of this data being shared with insurance companies, banks, public institutions and all types of private commercial companies.

Ethical Challenges

With the rapid proliferation of AI come ethical concerns that require careful attention. As AI systems become more complex and integrated into diverse aspects of everyday life, ethical questions emerge, challenging societies to balance technological innovation and fundamental ethical concerns.

Issues related to privacy, algorithmic bias and the impact on employability are increasingly discussed. The need for ethical regulations becomes crucial to ensure the responsible and fair use of technology. The extensive use of AI often involves the massive collection of personal data. This raises questions about individual privacy and data security. Developing robust regulations to protect privacy and ensure data is used ethically is essential to building trust in the widespread adoption of AI. On the other hand, AI’s ability to analyze data on a large scale allows for more informed decision-making across multiple industries. However, it is crucial to address issues related to the transparency and interpretability of algorithms, ensuring that automated decisions are understandable and fair. AI algorithms often learn from historical data, thus reflecting the biases present in that data. This can result in automated decisions that perpetuate existing discriminations, such as gender, racial or socio-economic bias. Ensuring equity in the creation and implementation of algorithms becomes crucial to avoid the expansion of social disparities. Many AI systems are black boxes, meaning their decisions can be difficult to understand. Lack of transparency and interpretability can undermine trust in technology. Requiring developers to make their algorithms more understandable is vital to ensuring responsibility and accountability.

Advances in Medicine

In healthcare, AI has shown significant promise. From analyzing large medical data, images, sets to personalizing treatments, AI is contributing to remarkable advances in diagnosis and the development of innovative therapies. In healthcare, applied nanoscience and robotics can enable more precise diagnoses and treatments on a molecular scale. AI can be used to analyze complex nanometric diagnostic data, identifying subtle patterns and providing valuable insights for personalizing treatments. However, AI is not endowed with emotional intelligence, clinical sense, or the years of experience of the “art” that a healthcare professional might have. Therefore, it is difficult to see how AI would be able to replace doctors or nurses. Ethical problems are posed by humans and are a dimension that is poorly handled by AI. They focus mainly on the availability and privacy of patients’ clinical data. For this reason, all this technology should not enjoy any type of decision-making autonomy, but instead be under the total control of professionals.

As AI is increasingly present in healthcare, this has implications for the interaction between doctors and patients. Here are some ways AI can positively influence the doctor-patient relationship:

patient doctor relationship

  1. Improving Communication: AI helps to better explain medical and nursing procedures to patients.  The  systems  can  provide  detailed  information  about  treatment  options,  helping

patients to better understand their conditions and actively participate in decisions about their health, when present in a hospital or consultation.

  • Improving Efficiency: AI tools can automate administrative tasks, allowing doctors to spend more time with patients. This can result in more meaningful consultations and closer interactions.
  • Optimizing Empathy: with the analysis of emotions and consequent psychological support. AI tools can be used to analyze the tone and content of patient messages, helping healthcare professionals identify signs of emotional distress and offer appropriate support.

Improving medical practice

  1. Aid in Diagnosis: AI systems can  help doctors with diagnosis, with an  improvement of approximately 10%, analyzing medical data, exams and patient history. In the case of Melanoma, a type of skin cancer, Linkoping University reports AI statistics with early diagnosis in more than 85% of cases compared to clinical observation. Something similar, but with lower percentages, happens with breast carcinoma detected early by imaging analysis conducted by AI
  • Treatment Assistance Algorithms can suggest treatment options based on large sets of data. Microsoft and Google Deepmind have AI technology for oncology treatments well succeed.
  • Treatment Personalization: AI can analyze genetic data and other factors to personalize treatments with greater precision, considering the individual characteristics of each patient.
  • Remote Monitoring: Monitoring devices, in the form of applications or  other types of technologies connected to AI, can allow continuous monitoring of patient health, providing real- time data to healthcare professionals. Some applications already monitor sleep, memory and other data to help with early diagnoses

Improving administrative care and primary care

AI-powered Virtual Assistants and Chatbots, in outpatient, consultation or home settings, can be used to answer common questions, provide information about medical conditions and assist patients in improving their health.

Increased team effectiveness with improved joint decision-making: resulting from better and faster knowledge sharing

However, it is important to highlight that the introduction of AI into medical practice also brings ethical, privacy and reliability challenges. Special attention must be paid to the doctor-patient relationship, which will continue to be crucial, even with AI serving as a complementary tool to improve the provision of healthcare.

Impact on Employment and healthcare jobs:

Firstly, we need to demystify the notion that AI will simply replace jobs. More than a substitute, AI is a tool that amplifies human capabilities. However, aI-driven automation raises concerns about the loss of traditional jobs, particularly in healthcare. While AI promises efficiency and innovation, it also raises questions about replacing traditional jobs automatically without any human thought. It is imperative to address the social and economic implications of the changing job market by investing in re-skilling and creating policies that promote a just transition to an AI-driven economy. Retraining the workforce therefore becomes essential to ensure that professionals are prepared for the challenges of the AI-driven job market. Therefore, the focus

should not be on fear of job loss caused by these technologies, but rather on concern about the ability to adapt and learn in the efficient use of these tools.

Autonomous Security and Risks:

The use of autonomous systems, such as autonomous vehicles and drones, raises safety concerns. The same security problem arises in the military sphere. It is necessary to establish rigorous standards to ensure that AI systems are safe and robust, avoiding adverse consequences, especially in critical situations

Nanoscience seeks to understand and manipulate phenomena on atomic and molecular scales that can be controlled and analysed by AI. AI can play a key role in the rational design of materials, accelerating the process of discovering, and optimizing new compounds. Machine learning algorithms can analyze vast sets of experimental and theoretical data to identify patterns, predict material properties, and suggest new candidates for synthesis. But is it safe to let these processes be autonomous?

Conclusion:

AI performs efficiently but it does not presume effectiveness. Collaboration between AI experts and various scientific or technological areas promises to revolutionize the way we perceive and interact with the world. By exploring the intersection of these disciplines, we can not only unlock fundamental new knowledge, but also catalyze practical innovations with the potential to transform industries ranging from electronics to medicine. An ethical and responsible approach is crucial to maximizing the benefits of this convergence and mitigating any associated risks.

As AI continues to shape the future, it is essential to address its ethical implications. Collaboration between researchers, developers, policymakers and society in general is essential to create an ethical and sustainable environment for the evolution of artificial intelligence. The challenge lies in balancing technological progress with fundamental ethical principles, ensuring that AI is a positive force for humanity.

Bibliografia

Coelho, Helder (1994). Inteligência Artificial em 25 Lições. Lisboa: Fundação Calouste Gulbenkian. p. 341. 532 páginas. ISBN 972-31-0679-5

Marr Bernard (2018) How is AI used in Healthcare- 5 powerful Real – world exmples that show the latest advances . Forbes Magazine 27 Jul 2018

Kaplan, Andreas; Haenlein, Michael (1 de outubro de 2019). «Rulers  of the  world,  unite! The challenges and opportunities of artificial intelligence». Business Horizons. Consultado em 6 de novembro de 2019

LOBO, Luiz Carlos. Inteligência Artificial e Medicina. Rev. bras. educ. med. [online]. 2017, vol.41, n.2 [cited 2021-04-14], pp.185-193. Available from:

<http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100- 55022017000200185&lng=en&nrm=iso>. ISSN 1981-5271.

http://dx.doi.org/10.1590/1981-52712015v41n2esp.

Karin Söderlund Leifler 2023 -A Step Towards al-base precision Medicine https://liu.se/en/news-item/a-step-towards-ai-based-precision-medicine

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