اولویت¬گذاری هوشمند فنّاوری به کمک سامانۀ استنتاج فازی (موردکاوی: فنّاوری اطلاعات در ایران)
محورهای موضوعی : تخصصی
امیر خدادادی
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غلامعلی منتظر
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سید سپهر قاضی نوری
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محمد حسینی مقدم
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1 - دانشگاه تربیت مدرس
2 - دانشگاه تربیت مدرس
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4 - پژوهشگاه مطالعات فرهنگی اجتماعی
کلید واژه: اولویت گذاری فنّاوری, معیار جذابیت-توانمندی, سناریونگاری, فنّاوری اطلاعات, سامانۀ استنتاج فازی,
چکیده مقاله :
اولویتگذاری فنّاوری یکی از مهمترین جنبه های سیاستگذاری علم و فنّاوری است. روشها و چارچوبهای موجود برای اولویت گذاری فنّاوری به دلیل نقایص موجود در آنها، در ارائۀ توصیه های سیاستی به سیاستگذاران با محدودیتهایی مواجهند. یکی از این نقیصه ها، غفلت از عدم قطعیتهای آینده و سناریوهایی است که برای توسعۀ فنّاوری ترسیم می شود. نقیصۀ دیگر، بروز ابهام در میان ذینفعان فنّاوری نسبت به پارامترهای ارزیابی فنّاوری ها و معیارهای آنهاست. رفع این نقایص مستلزم تجدیدنظر در چارچوبهای پیشین و معرفی چارچوب جدیدی برای اولویت گذاری است. از سوی دیگر، با توجه به مزایای بهره گیری از سامانه های هوشمند در سیاستگذاری، این سؤال مطرح است که چگونه می توان اولویت گذاری را به ابزارهای هوشمندی مجهّز کرد؟ در این مقاله، با معرفی چارچوب جدیدی برای اولویت گذاری فنّاوری که هر سه ابزار هوشمندی سیاستی (آینده نگاری، ارزیابی، پیش بینی) را در خود جای داده، نحوۀ افزودن هوشمندی محاسباتی به کمک نظریۀ مجموعه های فازی تبیین می شود. بدین منظور برای امتیازدهی به گزینه ها در الگوی جذابیت-توانمندی به جای روش های مرسومِ پیمایش و تصمیم گیری چندمعیاره، از سامانۀ استنتاج فازی استفاده می کنیم که به رفع ابهام از محدودۀ معیارها کمک می کند و درجه ای از هوشمندی را برای اولویت گذاری فراهم می کند. معیارها نیز از میان ابعاد عدم قطعیت سناریونگاری ها انتخاب می شوند تا تأثیر تحوّلات آینده در تحلیل اولویت ها مدنظر قرار گیرد. نتایج حاکی از این است که از بین پنج فنّاوری انقلاب صنعتی چهارم، فنّاوری هوش مصنوعی در کشور با وجود برخورداری از جذابیت بالا، توانمندی پایینی دارد و نیازمند توسعۀ بیشتری از حیث توجه به ارتقای معیارهای توانمندی فنّاورانه است. دستاورد تحقیق حاضر، یک مصنوع است که با برخورداری از درجهای از هوشمندی می تواند برای اولویت گذاری فنّاوری اطلاعات در سطح ملّی به کار رود.
Technology priority-setting is one of the most important aspects of science and technology policy-making. Due to their shortcomings, the existing methods and frameworks for technology priority-setting face limitations in providing policy recommendations to policymakers. One of these shortcomings is neglecting the future's uncertainties and the scenarios drawn for technological development. Another shortcoming is ambiguity among technological stakeholders regarding the parameters of evaluating technologies and their criteria. Fixing these defects requires revising the previous frameworks and introducing a new framework for priority-setting. On the other hand, considering the benefits of using intelligent systems in policymaking, the question is how to equip priority-setting with intelligence tools. In this article, by introducing a new framework for technology priority-setting that includes all three policy intelligence tools (forecasting, evaluation, foresight), the method of adding computational intelligence is explained with the help of fuzzy set theory. For this purpose, instead of conventional methods such as survey and multi-criteria decision-making, we use a fuzzy inference system to score the alternatives in the capability-attractiveness model, which helps to resolve the ambiguity of the range of criteria and provides a degree of intelligence for priority-setting. The criteria are also selected from among the dimensions of the uncertainty of the scenarios to consider the impact of future developments in the analysis of priorities. The achievement of the present research is an artifact that, with a degree of intelligence, can be used for information technology priority-setting at the national level.
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