نوع مقاله : مقاله پژوهشی

نویسنده

• محمد حسینی مقدم

استادیار گروه مطالعات آینده نگر،موسسه مطالعات فرهنگی و اجتماعی ،تهران ،ایران

چکیده

در طول تاریخ ایده پیشرفت یکی از موضوعات اصلی اندیشمندان بوده است. ابتنا به علم و فناوری برای دستیابی به پیشرفت و بهبود مستمر کیفیت زندگی به یکی از اصول جهان شمول تبدیل شده است. بهره‌مندی از هوش مصنوعی به عنوان یکی از پیشرفت‌های فناورانه به منظور توانمندسازی انسان در محاسبه‌گری، پیش‌بینی و شکل‌دهی به آینده مطلوب مورد توجه متخصصان و دانشمندان قرار گرفته است. گسترش بکارگیری هوش مصنوعی در اکتشافات علمی موجب پیداش تحولات هستی‌شناختی و معرفت‌شناختی در علم شده است. هدف این مقاله تبیین چگونگی بهره‌مندی از هوش‌مصنوعی برای ارتقای توان اکتشافات علمی و دانش‌ورزی انسانی در فرایند پیشرفت علم است. پرسش اصلی این مقاله آن است که هوش مصنوعی چگونه امکان گذار از علوم عادی به علوم پساعادی را مهیا ساخته است؟
روش‌های استفاده شده در این مقاله عبارتند از: مطالعات اسنادی و تحلیل روند به منظور بررسی چگونگی نفوذ هوش مصنوعی در پیشرفت علم و فناوری. یافته‌های اصلی این مقاله عبارتند از: پیشرفت علم از حیث ساختار، کارکرد، روش و عاملیت انسان به شیوه‌ای بنیادین توسط هوش مصنوعی دستخوش تحول شده است. این وضعیت باعث شکل‌گیری نوعی استیلا و انقیاد نوین در علم می‌شود که به شکل مستمر شکاف میان بهره‌برداران و محرومان از هوش مصنوعی به دلیل دسترسی‌های نابرابر به فناوری‌های نوین تشدید خواهد شد.

کلیدواژه‌ها

• هوش مصنوعی
• علوم عادی
• علوم پساعادی
• پیشرفت علم

موضوعات

• علم داده، هوشمندی و تحلیل‌های آینده ‌نگر

عنوان مقاله [English]

Artificial Intelligence and The Future of Scientific Progress: From Normal Science to Post Normal Science

نویسنده [English]

• Mohammad Hoseini Moghadam

Assistant professor, Foresight Department, Institute for Social and Cultural Studies,, Tehran, Iran

چکیده [English]

 
The touch of the product plays an important role in the final decision of the customer when purchasing from physical and online retail, and the sensations that come to be enjoyed through touch enable them to experience the product from all angles. Therefore, considering the importance of touch, this research has investigated the lived experience of touching the product from the point of view of customers of physical and online stores. The following article is done with qualitative method and phenomenological paradigm. The research community is made up of electronic and clothing buyers from online and physical stores: Technolife, Adak, Havadar and Happyland in Tehran, and through semi-structured interviews, evidence was collected based on the purposeful sampling method. The interviews continued until reaching the theoretical saturation, and in this research, the interviews reached saturation with 15 people. Based on the extracted results, the main themes include; Product perception is physical touch, virtual touch, touch experiences, need for touch and touch perceptions. According to the results, managers of physical and online stores should provide conditions (such as the use of modern technologies) that touch and contact with the product happen to both groups of online and physical buyers so that they can buy products based on their needs and wants, and also this research can pave the way for the development of touch literature for researchers.

Introduction

Throughout human history, the idea of progress has been a central concern for thinkers and intellectuals, with technological advancements playing a pivotal role in shaping the development of societies (Du Pisani, 2006; Rivers, 2002). Artificial intelligence (AI), as a driving force behind the fourth industrial revolution, has had a profound impact on numerous fields, including scientific research and discovery (Velarde, 2020). AI has revolutionized scientific knowledge to such an extent that distinguishing between the discoveries made by intelligent machines and human experts has become increasingly difficult (Krenn et al, 2022). This article explores the implications of AI for the future of scientific progress and its potential to give rise to post-normal science.
Here is my attempt at rewriting the text as a senior researcher:
The central question examined in this article is: what role does AI play in shaping the future of scientific developments? In exploring this overarching question, several related questions are also considered: How can AI be leveraged to uncover and obtain new scientific knowledge? Can novel computing techniques based on AI not only detect unusual patterns and events in data, but also lay the groundwork for new scientific advances? Might AI furnish new theories and transform our comprehension of science? Can AI-based scientific systems determine which scientific questions are worthwhile, and for whom are they valuable? Looking ahead, what assurances will scientists have about the validity of AI-based analyses in science?
In response to these pressing questions, the core hypothesis presented is that AI has become the foundation for the emergence of a new breed and style of scientific discovery, which can be characterized as post-normal science. To evaluate this hypothesis, the historical background of relevant research is reviewed. AI represents a seismic shift in the practice of science, enabling analyses and discoveries that would be impossible for humans alone. While promising, it also poses troubling philosophical questions about the nature of truth and scientific understanding.

Methodology

A variety of research methods were employed to address the questions raised in this study, including a systematic review of relevant literature to identify the transition from normal to post-normal science, trend analysis to examine the influence and expansion of AI in scientific discoveries, documentary studies to obtain theoretical and conceptual foundations, and modeling to understand and describe the progress of post-normal science under the influence of AI.

Findings

AI has facilitated a new model of scientific discovery, known as data-driven scientific discovery, which derives hypotheses from data rather than relying on preconceived assumptions (Wheeler, 2004). This approach has transformed traditional sciences into data sciences, with scientific patterns extracted from data and an increasing focus on intelligent automation in scientific progress (King & Roberts, 2018). As a result, a new type of epistemology has emerged, characterized by the involvement of machines in scientific discovery and the advancement of the science cycle. This development, referred to as "Science 0.4" or the fourth type of science, has integrated science into society, enabling every citizen to participate as a scientist and fostering a shift towards "open science" (Odman & Govender, 2021).
AI's impact on scientific research has been guided by several key principles, including sustainability, different forms of knowledge, accountability and responsibility, values and interests, collective wisdom and rationality, and non-determinism and non-linearity in the process of scientific discovery. AI has contributed to the realization of post-normal science by facilitating simulation and modeling, improving decision-making, promoting ethics, embracing diversity, fostering interdisciplinary collaboration, expanding stakeholder engagement, and enabling big data analysis.

Conclusion

AI systems have fostered interdisciplinary collaborations and facilitated the integration of knowledge and expertise across various fields, allowing for the identification and resolution of complex, interdisciplinary scientific issues. This collaboration disrupts the linear progression of normal science, promoting a more integrated and cooperative approach to problem-solving. Furthermore, AI has introduced new ethical and social considerations in scientific research, necessitating a departure from conventional forms of normal science. Although it remains uncertain whether AI will replace the human role in scientific discovery, it is clear that scientists and institutions that embrace AI technology will surpass those that do not.

Recommendations

To achieve excellence in the field of AI within scientific institutions, it is crucial to understand the "state of maturity in AI" and to establish a starting point for the governance system of science and its actors. In this process, scientific institutions can be categorized along a spectrum, ranging from those seeking to familiarize themselves with AI-driven changes in scientific discovery to those actively leveraging AI technology to advance scientific knowledge.
Keywords: Artificial Intelligence, Normal Science, Post Normal Science, Science Progress, Scientific Discoveries.
 
 
 

کلیدواژه‌ها [English]

• Artificial intelligence
• normal science
• post-normal science
• scientific progress